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A review of the global climate change impacts, adaptation, and sustainable mitigation measures

• Review Article
• Published: 04 April 2022
• Volume 29 , pages 42539–42559, ( 2022 )

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• Kashif Abbass 1 ,
• Muhammad Zeeshan Qasim 2 ,
• Huaming Song 1 ,
• Muntasir Murshed   ORCID: orcid.org/0000-0001-9872-8742 3 , 4 ,
• Haider Mahmood   ORCID: orcid.org/0000-0002-6474-4338 5 &
• Ijaz Younis 1  

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Climate change is a long-lasting change in the weather arrays across tropics to polls. It is a global threat that has embarked on to put stress on various sectors. This study is aimed to conceptually engineer how climate variability is deteriorating the sustainability of diverse sectors worldwide. Specifically, the agricultural sector’s vulnerability is a globally concerning scenario, as sufficient production and food supplies are threatened due to irreversible weather fluctuations. In turn, it is challenging the global feeding patterns, particularly in countries with agriculture as an integral part of their economy and total productivity. Climate change has also put the integrity and survival of many species at stake due to shifts in optimum temperature ranges, thereby accelerating biodiversity loss by progressively changing the ecosystem structures. Climate variations increase the likelihood of particular food and waterborne and vector-borne diseases, and a recent example is a coronavirus pandemic. Climate change also accelerates the enigma of antimicrobial resistance, another threat to human health due to the increasing incidence of resistant pathogenic infections. Besides, the global tourism industry is devastated as climate change impacts unfavorable tourism spots. The methodology investigates hypothetical scenarios of climate variability and attempts to describe the quality of evidence to facilitate readers’ careful, critical engagement. Secondary data is used to identify sustainability issues such as environmental, social, and economic viability. To better understand the problem, gathered the information in this report from various media outlets, research agencies, policy papers, newspapers, and other sources. This review is a sectorial assessment of climate change mitigation and adaptation approaches worldwide in the aforementioned sectors and the associated economic costs. According to the findings, government involvement is necessary for the country’s long-term development through strict accountability of resources and regulations implemented in the past to generate cutting-edge climate policy. Therefore, mitigating the impacts of climate change must be of the utmost importance, and hence, this global threat requires global commitment to address its dreadful implications to ensure global sustenance.

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Introduction

Worldwide observed and anticipated climatic changes for the twenty-first century and global warming are significant global changes that have been encountered during the past 65 years. Climate change (CC) is an inter-governmental complex challenge globally with its influence over various components of the ecological, environmental, socio-political, and socio-economic disciplines (Adger et al.  2005 ; Leal Filho et al.  2021 ; Feliciano et al.  2022 ). Climate change involves heightened temperatures across numerous worlds (Battisti and Naylor  2009 ; Schuurmans  2021 ; Weisheimer and Palmer  2005 ; Yadav et al.  2015 ). With the onset of the industrial revolution, the problem of earth climate was amplified manifold (Leppänen et al.  2014 ). It is reported that the immediate attention and due steps might increase the probability of overcoming its devastating impacts. It is not plausible to interpret the exact consequences of climate change (CC) on a sectoral basis (Izaguirre et al.  2021 ; Jurgilevich et al.  2017 ), which is evident by the emerging level of recognition plus the inclusion of climatic uncertainties at both local and national level of policymaking (Ayers et al.  2014 ).

Climate change is characterized based on the comprehensive long-haul temperature and precipitation trends and other components such as pressure and humidity level in the surrounding environment. Besides, the irregular weather patterns, retreating of global ice sheets, and the corresponding elevated sea level rise are among the most renowned international and domestic effects of climate change (Lipczynska-Kochany  2018 ; Michel et al.  2021 ; Murshed and Dao 2020 ). Before the industrial revolution, natural sources, including volcanoes, forest fires, and seismic activities, were regarded as the distinct sources of greenhouse gases (GHGs) such as CO 2 , CH 4 , N 2 O, and H 2 O into the atmosphere (Murshed et al. 2020 ; Hussain et al.  2020 ; Sovacool et al.  2021 ; Usman and Balsalobre-Lorente 2022 ; Murshed 2022 ). United Nations Framework Convention on Climate Change (UNFCCC) struck a major agreement to tackle climate change and accelerate and intensify the actions and investments required for a sustainable low-carbon future at Conference of the Parties (COP-21) in Paris on December 12, 2015. The Paris Agreement expands on the Convention by bringing all nations together for the first time in a single cause to undertake ambitious measures to prevent climate change and adapt to its impacts, with increased funding to assist developing countries in doing so. As so, it marks a turning point in the global climate fight. The core goal of the Paris Agreement is to improve the global response to the threat of climate change by keeping the global temperature rise this century well below 2 °C over pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5° C (Sharma et al. 2020 ; Sharif et al. 2020 ; Chien et al. 2021 .

Furthermore, the agreement aspires to strengthen nations’ ability to deal with the effects of climate change and align financing flows with low GHG emissions and climate-resilient paths (Shahbaz et al. 2019 ; Anwar et al. 2021 ; Usman et al. 2022a ). To achieve these lofty goals, adequate financial resources must be mobilized and provided, as well as a new technology framework and expanded capacity building, allowing developing countries and the most vulnerable countries to act under their respective national objectives. The agreement also establishes a more transparent action and support mechanism. All Parties are required by the Paris Agreement to do their best through “nationally determined contributions” (NDCs) and to strengthen these efforts in the coming years (Balsalobre-Lorente et al. 2020 ). It includes obligations that all Parties regularly report on their emissions and implementation activities. A global stock-take will be conducted every five years to review collective progress toward the agreement’s goal and inform the Parties’ future individual actions. The Paris Agreement became available for signature on April 22, 2016, Earth Day, at the United Nations Headquarters in New York. On November 4, 2016, it went into effect 30 days after the so-called double threshold was met (ratification by 55 nations accounting for at least 55% of world emissions). More countries have ratified and continue to ratify the agreement since then, bringing 125 Parties in early 2017. To fully operationalize the Paris Agreement, a work program was initiated in Paris to define mechanisms, processes, and recommendations on a wide range of concerns (Murshed et al. 2021 ). Since 2016, Parties have collaborated in subsidiary bodies (APA, SBSTA, and SBI) and numerous formed entities. The Conference of the Parties functioning as the meeting of the Parties to the Paris Agreement (CMA) convened for the first time in November 2016 in Marrakesh in conjunction with COP22 and made its first two resolutions. The work plan is scheduled to be finished by 2018. Some mitigation and adaptation strategies to reduce the emission in the prospective of Paris agreement are following firstly, a long-term goal of keeping the increase in global average temperature to well below 2 °C above pre-industrial levels, secondly, to aim to limit the rise to 1.5 °C, since this would significantly reduce risks and the impacts of climate change, thirdly, on the need for global emissions to peak as soon as possible, recognizing that this will take longer for developing countries, lastly, to undertake rapid reductions after that under the best available science, to achieve a balance between emissions and removals in the second half of the century. On the other side, some adaptation strategies are; strengthening societies’ ability to deal with the effects of climate change and to continue & expand international assistance for developing nations’ adaptation.

However, anthropogenic activities are currently regarded as most accountable for CC (Murshed et al. 2022 ). Apart from the industrial revolution, other anthropogenic activities include excessive agricultural operations, which further involve the high use of fuel-based mechanization, burning of agricultural residues, burning fossil fuels, deforestation, national and domestic transportation sectors, etc. (Huang et al.  2016 ). Consequently, these anthropogenic activities lead to climatic catastrophes, damaging local and global infrastructure, human health, and total productivity. Energy consumption has mounted GHGs levels concerning warming temperatures as most of the energy production in developing countries comes from fossil fuels (Balsalobre-Lorente et al. 2022 ; Usman et al. 2022b ; Abbass et al. 2021a ; Ishikawa-Ishiwata and Furuya  2022 ).

This review aims to highlight the effects of climate change in a socio-scientific aspect by analyzing the existing literature on various sectorial pieces of evidence globally that influence the environment. Although this review provides a thorough examination of climate change and its severe affected sectors that pose a grave danger for global agriculture, biodiversity, health, economy, forestry, and tourism, and to purpose some practical prophylactic measures and mitigation strategies to be adapted as sound substitutes to survive from climate change (CC) impacts. The societal implications of irregular weather patterns and other effects of climate changes are discussed in detail. Some numerous sustainable mitigation measures and adaptation practices and techniques at the global level are discussed in this review with an in-depth focus on its economic, social, and environmental aspects. Methods of data collection section are included in the supplementary information.

Review methodology

Related study and its objectives.

Today, we live an ordinary life in the beautiful digital, globalized world where climate change has a decisive role. What happens in one country has a massive influence on geographically far apart countries, which points to the current crisis known as COVID-19 (Sarkar et al.  2021 ). The most dangerous disease like COVID-19 has affected the world’s climate changes and economic conditions (Abbass et al. 2022 ; Pirasteh-Anosheh et al.  2021 ). The purpose of the present study is to review the status of research on the subject, which is based on “Global Climate Change Impacts, adaptation, and sustainable mitigation measures” by systematically reviewing past published and unpublished research work. Furthermore, the current study seeks to comment on research on the same topic and suggest future research on the same topic. Specifically, the present study aims: The first one is, organize publications to make them easy and quick to find. Secondly, to explore issues in this area, propose an outline of research for future work. The third aim of the study is to synthesize the previous literature on climate change, various sectors, and their mitigation measurement. Lastly , classify the articles according to the different methods and procedures that have been adopted.

Review methodology for reviewers

This review-based article followed systematic literature review techniques that have proved the literature review as a rigorous framework (Benita  2021 ; Tranfield et al.  2003 ). Moreover, we illustrate in Fig.  1 the search method that we have started for this research. First, finalized the research theme to search literature (Cooper et al.  2018 ). Second, used numerous research databases to search related articles and download from the database (Web of Science, Google Scholar, Scopus Index Journals, Emerald, Elsevier Science Direct, Springer, and Sciverse). We focused on various articles, with research articles, feedback pieces, short notes, debates, and review articles published in scholarly journals. Reports used to search for multiple keywords such as “Climate Change,” “Mitigation and Adaptation,” “Department of Agriculture and Human Health,” “Department of Biodiversity and Forestry,” etc.; in summary, keyword list and full text have been made. Initially, the search for keywords yielded a large amount of literature.

Source : constructed by authors

Methodology search for finalized articles for investigations.

Since 2020, it has been impossible to review all the articles found; some restrictions have been set for the literature exhibition. The study searched 95 articles on a different database mentioned above based on the nature of the study. It excluded 40 irrelevant papers due to copied from a previous search after readings tiles, abstract and full pieces. The criteria for inclusion were: (i) articles focused on “Global Climate Change Impacts, adaptation, and sustainable mitigation measures,” and (ii) the search key terms related to study requirements. The complete procedure yielded 55 articles for our study. We repeat our search on the “Web of Science and Google Scholars” database to enhance the search results and check the referenced articles.

In this study, 55 articles are reviewed systematically and analyzed for research topics and other aspects, such as the methods, contexts, and theories used in these studies. Furthermore, this study analyzes closely related areas to provide unique research opportunities in the future. The study also discussed future direction opportunities and research questions by understanding the research findings climate changes and other affected sectors. The reviewed paper framework analysis process is outlined in Fig.  2 .

Framework of the analysis Process.

Natural disasters and climate change’s socio-economic consequences

Natural and environmental disasters can be highly variable from year to year; some years pass with very few deaths before a significant disaster event claims many lives (Symanski et al.  2021 ). Approximately 60,000 people globally died from natural disasters each year on average over the past decade (Ritchie and Roser  2014 ; Wiranata and Simbolon  2021 ). So, according to the report, around 0.1% of global deaths. Annual variability in the number and share of deaths from natural disasters in recent decades are shown in Fig.  3 . The number of fatalities can be meager—sometimes less than 10,000, and as few as 0.01% of all deaths. But shock events have a devastating impact: the 1983–1985 famine and drought in Ethiopia; the 2004 Indian Ocean earthquake and tsunami; Cyclone Nargis, which struck Myanmar in 2008; and the 2010 Port-au-Prince earthquake in Haiti and now recent example is COVID-19 pandemic (Erman et al.  2021 ). These events pushed global disaster deaths to over 200,000—more than 0.4% of deaths in these years. Low-frequency, high-impact events such as earthquakes and tsunamis are not preventable, but such high losses of human life are. Historical evidence shows that earlier disaster detection, more robust infrastructure, emergency preparedness, and response programmers have substantially reduced disaster deaths worldwide. Low-income is also the most vulnerable to disasters; improving living conditions, facilities, and response services in these areas would be critical in reducing natural disaster deaths in the coming decades.

Source EMDAT ( 2020 )

Global deaths from natural disasters, 1978 to 2020.

The interior regions of the continent are likely to be impacted by rising temperatures (Dimri et al.  2018 ; Goes et al.  2020 ; Mannig et al.  2018 ; Schuurmans  2021 ). Weather patterns change due to the shortage of natural resources (water), increase in glacier melting, and rising mercury are likely to cause extinction to many planted species (Gampe et al.  2016 ; Mihiretu et al.  2021 ; Shaffril et al.  2018 ).On the other hand, the coastal ecosystem is on the verge of devastation (Perera et al.  2018 ; Phillips  2018 ). The temperature rises, insect disease outbreaks, health-related problems, and seasonal and lifestyle changes are persistent, with a strong probability of these patterns continuing in the future (Abbass et al. 2021c ; Hussain et al.  2018 ). At the global level, a shortage of good infrastructure and insufficient adaptive capacity are hammering the most (IPCC  2013 ). In addition to the above concerns, a lack of environmental education and knowledge, outdated consumer behavior, a scarcity of incentives, a lack of legislation, and the government’s lack of commitment to climate change contribute to the general public’s concerns. By 2050, a 2 to 3% rise in mercury and a drastic shift in rainfall patterns may have serious consequences (Huang et al. 2022 ; Gorst et al.  2018 ). Natural and environmental calamities caused huge losses globally, such as decreased agriculture outputs, rehabilitation of the system, and rebuilding necessary technologies (Ali and Erenstein  2017 ; Ramankutty et al.  2018 ; Yu et al.  2021 ) (Table 1 ). Furthermore, in the last 3 or 4 years, the world has been plagued by smog-related eye and skin diseases, as well as a rise in road accidents due to poor visibility.

Climate change and agriculture

Global agriculture is the ultimate sector responsible for 30–40% of all greenhouse emissions, which makes it a leading industry predominantly contributing to climate warming and significantly impacted by it (Grieg; Mishra et al.  2021 ; Ortiz et al.  2021 ; Thornton and Lipper  2014 ). Numerous agro-environmental and climatic factors that have a dominant influence on agriculture productivity (Pautasso et al.  2012 ) are significantly impacted in response to precipitation extremes including floods, forest fires, and droughts (Huang  2004 ). Besides, the immense dependency on exhaustible resources also fuels the fire and leads global agriculture to become prone to devastation. Godfray et al. ( 2010 ) mentioned that decline in agriculture challenges the farmer’s quality of life and thus a significant factor to poverty as the food and water supplies are critically impacted by CC (Ortiz et al.  2021 ; Rosenzweig et al.  2014 ). As an essential part of the economic systems, especially in developing countries, agricultural systems affect the overall economy and potentially the well-being of households (Schlenker and Roberts  2009 ). According to the report published by the Intergovernmental Panel on Climate Change (IPCC), atmospheric concentrations of greenhouse gases, i.e., CH 4, CO 2 , and N 2 O, are increased in the air to extraordinary levels over the last few centuries (Usman and Makhdum 2021 ; Stocker et al.  2013 ). Climate change is the composite outcome of two different factors. The first is the natural causes, and the second is the anthropogenic actions (Karami 2012 ). It is also forecasted that the world may experience a typical rise in temperature stretching from 1 to 3.7 °C at the end of this century (Pachauri et al. 2014 ). The world’s crop production is also highly vulnerable to these global temperature-changing trends as raised temperatures will pose severe negative impacts on crop growth (Reidsma et al. 2009 ). Some of the recent modeling about the fate of global agriculture is briefly described below.

Decline in cereal productivity

Crop productivity will also be affected dramatically in the next few decades due to variations in integral abiotic factors such as temperature, solar radiation, precipitation, and CO 2 . These all factors are included in various regulatory instruments like progress and growth, weather-tempted changes, pest invasions (Cammell and Knight 1992 ), accompanying disease snags (Fand et al. 2012 ), water supplies (Panda et al. 2003 ), high prices of agro-products in world’s agriculture industry, and preeminent quantity of fertilizer consumption. Lobell and field ( 2007 ) claimed that from 1962 to 2002, wheat crop output had condensed significantly due to rising temperatures. Therefore, during 1980–2011, the common wheat productivity trends endorsed extreme temperature events confirmed by Gourdji et al. ( 2013 ) around South Asia, South America, and Central Asia. Various other studies (Asseng, Cao, Zhang, and Ludwig 2009 ; Asseng et al. 2013 ; García et al. 2015 ; Ortiz et al. 2021 ) also proved that wheat output is negatively affected by the rising temperatures and also caused adverse effects on biomass productivity (Calderini et al. 1999 ; Sadras and Slafer 2012 ). Hereafter, the rice crop is also influenced by the high temperatures at night. These difficulties will worsen because the temperature will be rising further in the future owing to CC (Tebaldi et al. 2006 ). Another research conducted in China revealed that a 4.6% of rice production per 1 °C has happened connected with the advancement in night temperatures (Tao et al. 2006 ). Moreover, the average night temperature growth also affected rice indicia cultivar’s output pragmatically during 25 years in the Philippines (Peng et al. 2004 ). It is anticipated that the increase in world average temperature will also cause a substantial reduction in yield (Hatfield et al. 2011 ; Lobell and Gourdji 2012 ). In the southern hemisphere, Parry et al. ( 2007 ) noted a rise of 1–4 °C in average daily temperatures at the end of spring season unti the middle of summers, and this raised temperature reduced crop output by cutting down the time length for phenophases eventually reduce the yield (Hatfield and Prueger 2015 ; R. Ortiz 2008 ). Also, world climate models have recommended that humid and subtropical regions expect to be plentiful prey to the upcoming heat strokes (Battisti and Naylor 2009 ). Grain production is the amalgamation of two constituents: the average weight and the grain output/m 2 , however, in crop production. Crop output is mainly accredited to the grain quantity (Araus et al. 2008 ; Gambín and Borrás 2010 ). In the times of grain set, yield resources are mainly strewn between hitherto defined components, i.e., grain usual weight and grain output, which presents a trade-off between them (Gambín and Borrás 2010 ) beside disparities in per grain integration (B. L. Gambín et al. 2006 ). In addition to this, the maize crop is also susceptible to raised temperatures, principally in the flowering stage (Edreira and Otegui 2013 ). In reality, the lower grain number is associated with insufficient acclimatization due to intense photosynthesis and higher respiration and the high-temperature effect on the reproduction phenomena (Edreira and Otegui 2013 ). During the flowering phase, maize visible to heat (30–36 °C) seemed less anthesis-silking intermissions (Edreira et al. 2011 ). Another research by Dupuis and Dumas ( 1990 ) proved that a drop in spikelet when directly visible to high temperatures above 35 °C in vitro pollination. Abnormalities in kernel number claimed by Vega et al. ( 2001 ) is related to conceded plant development during a flowering phase that is linked with the active ear growth phase and categorized as a critical phase for approximation of kernel number during silking (Otegui and Bonhomme 1998 ).

The retort of rice output to high temperature presents disparities in flowering patterns, and seed set lessens and lessens grain weight (Qasim et al. 2020 ; Qasim, Hammad, Maqsood, Tariq, & Chawla). During the daytime, heat directly impacts flowers which lessens the thesis period and quickens the earlier peak flowering (Tao et al. 2006 ). Antagonistic effect of higher daytime temperature d on pollen sprouting proposed seed set decay, whereas, seed set was lengthily reduced than could be explicated by pollen growing at high temperatures 40◦C (Matsui et al. 2001 ).

The decline in wheat output is linked with higher temperatures, confirmed in numerous studies (Semenov 2009 ; Stone and Nicolas 1994 ). High temperatures fast-track the arrangements of plant expansion (Blum et al. 2001 ), diminution photosynthetic process (Salvucci and Crafts‐Brandner 2004 ), and also considerably affect the reproductive operations (Farooq et al. 2011 ).

The destructive impacts of CC induced weather extremes to deteriorate the integrity of crops (Chaudhary et al. 2011 ), e.g., Spartan cold and extreme fog cause falling and discoloration of betel leaves (Rosenzweig et al. 2001 ), giving them a somehow reddish appearance, squeezing of lemon leaves (Pautasso et al. 2012 ), as well as root rot of pineapple, have reported (Vedwan and Rhoades 2001 ). Henceforth, in tackling the disruptive effects of CC, several short-term and long-term management approaches are the crucial need of time (Fig.  4 ). Moreover, various studies (Chaudhary et al. 2011 ; Patz et al. 2005 ; Pautasso et al. 2012 ) have demonstrated adapting trends such as ameliorating crop diversity can yield better adaptability towards CC.

Schematic description of potential impacts of climate change on the agriculture sector and the appropriate mitigation and adaptation measures to overcome its impact.

Climate change impacts on biodiversity

Global biodiversity is among the severe victims of CC because it is the fastest emerging cause of species loss. Studies demonstrated that the massive scale species dynamics are considerably associated with diverse climatic events (Abraham and Chain 1988 ; Manes et al. 2021 ; A. M. D. Ortiz et al. 2021 ). Both the pace and magnitude of CC are altering the compatible habitat ranges for living entities of marine, freshwater, and terrestrial regions. Alterations in general climate regimes influence the integrity of ecosystems in numerous ways, such as variation in the relative abundance of species, range shifts, changes in activity timing, and microhabitat use (Bates et al. 2014 ). The geographic distribution of any species often depends upon its ability to tolerate environmental stresses, biological interactions, and dispersal constraints. Hence, instead of the CC, the local species must only accept, adapt, move, or face extinction (Berg et al. 2010 ). So, the best performer species have a better survival capacity for adjusting to new ecosystems or a decreased perseverance to survive where they are already situated (Bates et al. 2014 ). An important aspect here is the inadequate habitat connectivity and access to microclimates, also crucial in raising the exposure to climate warming and extreme heatwave episodes. For example, the carbon sequestration rates are undergoing fluctuations due to climate-driven expansion in the range of global mangroves (Cavanaugh et al. 2014 ).

Similarly, the loss of kelp-forest ecosystems in various regions and its occupancy by the seaweed turfs has set the track for elevated herbivory by the high influx of tropical fish populations. Not only this, the increased water temperatures have exacerbated the conditions far away from the physiological tolerance level of the kelp communities (Vergés et al. 2016 ; Wernberg et al. 2016 ). Another pertinent danger is the devastation of keystone species, which even has more pervasive effects on the entire communities in that habitat (Zarnetske et al. 2012 ). It is particularly important as CC does not specify specific populations or communities. Eventually, this CC-induced redistribution of species may deteriorate carbon storage and the net ecosystem productivity (Weed et al. 2013 ). Among the typical disruptions, the prominent ones include impacts on marine and terrestrial productivity, marine community assembly, and the extended invasion of toxic cyanobacteria bloom (Fossheim et al. 2015 ).

The CC-impacted species extinction is widely reported in the literature (Beesley et al. 2019 ; Urban 2015 ), and the predictions of demise until the twenty-first century are dreadful (Abbass et al. 2019 ; Pereira et al. 2013 ). In a few cases, northward shifting of species may not be formidable as it allows mountain-dwelling species to find optimum climates. However, the migrant species may be trapped in isolated and incompatible habitats due to losing topography and range (Dullinger et al. 2012 ). For example, a study indicated that the American pika has been extirpated or intensely diminished in some regions, primarily attributed to the CC-impacted extinction or at least local extirpation (Stewart et al. 2015 ). Besides, the anticipation of persistent responses to the impacts of CC often requires data records of several decades to rigorously analyze the critical pre and post CC patterns at species and ecosystem levels (Manes et al. 2021 ; Testa et al. 2018 ).

Nonetheless, the availability of such long-term data records is rare; hence, attempts are needed to focus on these profound aspects. Biodiversity is also vulnerable to the other associated impacts of CC, such as rising temperatures, droughts, and certain invasive pest species. For instance, a study revealed the changes in the composition of plankton communities attributed to rising temperatures. Henceforth, alterations in such aquatic producer communities, i.e., diatoms and calcareous plants, can ultimately lead to variation in the recycling of biological carbon. Moreover, such changes are characterized as a potential contributor to CO 2 differences between the Pleistocene glacial and interglacial periods (Kohfeld et al. 2005 ).

Climate change implications on human health

It is an understood corporality that human health is a significant victim of CC (Costello et al. 2009 ). According to the WHO, CC might be responsible for 250,000 additional deaths per year during 2030–2050 (Watts et al. 2015 ). These deaths are attributed to extreme weather-induced mortality and morbidity and the global expansion of vector-borne diseases (Lemery et al. 2021; Yang and Usman 2021 ; Meierrieks 2021 ; UNEP 2017 ). Here, some of the emerging health issues pertinent to this global problem are briefly described.

Climate change and antimicrobial resistance with corresponding economic costs

Antimicrobial resistance (AMR) is an up-surging complex global health challenge (Garner et al. 2019 ; Lemery et al. 2021 ). Health professionals across the globe are extremely worried due to this phenomenon that has critical potential to reverse almost all the progress that has been achieved so far in the health discipline (Gosling and Arnell 2016 ). A massive amount of antibiotics is produced by many pharmaceutical industries worldwide, and the pathogenic microorganisms are gradually developing resistance to them, which can be comprehended how strongly this aspect can shake the foundations of national and global economies (UNEP 2017 ). This statement is supported by the fact that AMR is not developing in a particular region or country. Instead, it is flourishing in every continent of the world (WHO 2018 ). This plague is heavily pushing humanity to the post-antibiotic era, in which currently antibiotic-susceptible pathogens will once again lead to certain endemics and pandemics after being resistant(WHO 2018 ). Undesirably, if this statement would become a factuality, there might emerge certain risks in undertaking sophisticated interventions such as chemotherapy, joint replacement cases, and organ transplantation (Su et al. 2018 ). Presently, the amplification of drug resistance cases has made common illnesses like pneumonia, post-surgical infections, HIV/AIDS, tuberculosis, malaria, etc., too difficult and costly to be treated or cure well (WHO 2018 ). From a simple example, it can be assumed how easily antibiotic-resistant strains can be transmitted from one person to another and ultimately travel across the boundaries (Berendonk et al. 2015 ). Talking about the second- and third-generation classes of antibiotics, e.g., most renowned generations of cephalosporin antibiotics that are more expensive, broad-spectrum, more toxic, and usually require more extended periods whenever prescribed to patients (Lemery et al. 2021 ; Pärnänen et al. 2019 ). This scenario has also revealed that the abundance of resistant strains of pathogens was also higher in the Southern part (WHO 2018 ). As southern parts are generally warmer than their counterparts, it is evident from this example how CC-induced global warming can augment the spread of antibiotic-resistant strains within the biosphere, eventually putting additional economic burden in the face of developing new and costlier antibiotics. The ARG exchange to susceptible bacteria through one of the potential mechanisms, transformation, transduction, and conjugation; Selection pressure can be caused by certain antibiotics, metals or pesticides, etc., as shown in Fig.  5 .

Source: Elsayed et al. ( 2021 ); Karkman et al. ( 2018 )

A typical interaction between the susceptible and resistant strains.

Certain studies highlighted that conventional urban wastewater treatment plants are typical hotspots where most bacterial strains exchange genetic material through horizontal gene transfer (Fig.  5 ). Although at present, the extent of risks associated with the antibiotic resistance found in wastewater is complicated; environmental scientists and engineers have particular concerns about the potential impacts of these antibiotic resistance genes on human health (Ashbolt 2015 ). At most undesirable and worst case, these antibiotic-resistant genes containing bacteria can make their way to enter into the environment (Pruden et al. 2013 ), irrigation water used for crops and public water supplies and ultimately become a part of food chains and food webs (Ma et al. 2019 ; D. Wu et al. 2019 ). This problem has been reported manifold in several countries (Hendriksen et al. 2019 ), where wastewater as a means of irrigated water is quite common.

Climate change and vector borne-diseases

Temperature is a fundamental factor for the sustenance of living entities regardless of an ecosystem. So, a specific living being, especially a pathogen, requires a sophisticated temperature range to exist on earth. The second essential component of CC is precipitation, which also impacts numerous infectious agents’ transport and dissemination patterns. Global rising temperature is a significant cause of many species extinction. On the one hand, this changing environmental temperature may be causing species extinction, and on the other, this warming temperature might favor the thriving of some new organisms. Here, it was evident that some pathogens may also upraise once non-evident or reported (Patz et al. 2000 ). This concept can be exemplified through certain pathogenic strains of microorganisms that how the likelihood of various diseases increases in response to climate warming-induced environmental changes (Table 2 ).

A recent example is an outburst of coronavirus (COVID-19) in the Republic of China, causing pneumonia and severe acute respiratory complications (Cui et al. 2021 ; Song et al. 2021 ). The large family of viruses is harbored in numerous animals, bats, and snakes in particular (livescience.com) with the subsequent transfer into human beings. Hence, it is worth noting that the thriving of numerous vectors involved in spreading various diseases is influenced by Climate change (Ogden 2018 ; Santos et al. 2021 ).

Psychological impacts of climate change

Climate change (CC) is responsible for the rapid dissemination and exaggeration of certain epidemics and pandemics. In addition to the vast apparent impacts of climate change on health, forestry, agriculture, etc., it may also have psychological implications on vulnerable societies. It can be exemplified through the recent outburst of (COVID-19) in various countries around the world (Pal 2021 ). Besides, the victims of this viral infection have made healthy beings scarier and terrified. In the wake of such epidemics, people with common colds or fever are also frightened and must pass specific regulatory protocols. Living in such situations continuously terrifies the public and makes the stress familiar, which eventually makes them psychologically weak (npr.org).

CC boosts the extent of anxiety, distress, and other issues in public, pushing them to develop various mental-related problems. Besides, frequent exposure to extreme climatic catastrophes such as geological disasters also imprints post-traumatic disorder, and their ubiquitous occurrence paves the way to developing chronic psychological dysfunction. Moreover, repetitive listening from media also causes an increase in the person’s stress level (Association 2020 ). Similarly, communities living in flood-prone areas constantly live in extreme fear of drowning and die by floods. In addition to human lives, the flood-induced destruction of physical infrastructure is a specific reason for putting pressure on these communities (Ogden 2018 ). For instance, Ogden ( 2018 ) comprehensively denoted that Katrina’s Hurricane augmented the mental health issues in the victim communities.

Climate change impacts on the forestry sector

Forests are the global regulators of the world’s climate (FAO 2018 ) and have an indispensable role in regulating global carbon and nitrogen cycles (Rehman et al. 2021 ; Reichstein and Carvalhais 2019 ). Hence, disturbances in forest ecology affect the micro and macro-climates (Ellison et al. 2017 ). Climate warming, in return, has profound impacts on the growth and productivity of transboundary forests by influencing the temperature and precipitation patterns, etc. As CC induces specific changes in the typical structure and functions of ecosystems (Zhang et al. 2017 ) as well impacts forest health, climate change also has several devastating consequences such as forest fires, droughts, pest outbreaks (EPA 2018 ), and last but not the least is the livelihoods of forest-dependent communities. The rising frequency and intensity of another CC product, i.e., droughts, pose plenty of challenges to the well-being of global forests (Diffenbaugh et al. 2017 ), which is further projected to increase soon (Hartmann et al. 2018 ; Lehner et al. 2017 ; Rehman et al. 2021 ). Hence, CC induces storms, with more significant impacts also put extra pressure on the survival of the global forests (Martínez-Alvarado et al. 2018 ), significantly since their influences are augmented during higher winter precipitations with corresponding wetter soils causing weak root anchorage of trees (Brázdil et al. 2018 ). Surging temperature regimes causes alterations in usual precipitation patterns, which is a significant hurdle for the survival of temperate forests (Allen et al. 2010 ; Flannigan et al. 2013 ), letting them encounter severe stress and disturbances which adversely affects the local tree species (Hubbart et al. 2016 ; Millar and Stephenson 2015 ; Rehman et al. 2021 ).

Climate change impacts on forest-dependent communities

Forests are the fundamental livelihood resource for about 1.6 billion people worldwide; out of them, 350 million are distinguished with relatively higher reliance (Bank 2008 ). Agro-forestry-dependent communities comprise 1.2 billion, and 60 million indigenous people solely rely on forests and their products to sustain their lives (Sunderlin et al. 2005 ). For example, in the entire African continent, more than 2/3rd of inhabitants depend on forest resources and woodlands for their alimonies, e.g., food, fuelwood and grazing (Wasiq and Ahmad 2004 ). The livings of these people are more intensely affected by the climatic disruptions making their lives harder (Brown et al. 2014 ). On the one hand, forest communities are incredibly vulnerable to CC due to their livelihoods, cultural and spiritual ties as well as socio-ecological connections, and on the other, they are not familiar with the term “climate change.” (Rahman and Alam 2016 ). Among the destructive impacts of temperature and rainfall, disruption of the agroforestry crops with resultant downscale growth and yield (Macchi et al. 2008 ). Cruz ( 2015 ) ascribed that forest-dependent smallholder farmers in the Philippines face the enigma of delayed fruiting, more severe damages by insect and pest incidences due to unfavorable temperature regimes, and changed rainfall patterns.

Among these series of challenges to forest communities, their well-being is also distinctly vulnerable to CC. Though the detailed climate change impacts on human health have been comprehensively mentioned in the previous section, some studies have listed a few more devastating effects on the prosperity of forest-dependent communities. For instance, the Himalayan people have been experiencing frequent skin-borne diseases such as malaria and other skin diseases due to increasing mosquitoes, wild boar as well, and new wasps species, particularly in higher altitudes that were almost non-existent before last 5–10 years (Xu et al. 2008 ). Similarly, people living at high altitudes in Bangladesh have experienced frequent mosquito-borne calamities (Fardous; Sharma 2012 ). In addition, the pace of other waterborne diseases such as infectious diarrhea, cholera, pathogenic induced abdominal complications and dengue has also been boosted in other distinguished regions of Bangladesh (Cell 2009 ; Gunter et al. 2008 ).

Pest outbreak

Upscaling hotter climate may positively affect the mobile organisms with shorter generation times because they can scurry from harsh conditions than the immobile species (Fettig et al. 2013 ; Schoene and Bernier 2012 ) and are also relatively more capable of adapting to new environments (Jactel et al. 2019 ). It reveals that insects adapt quickly to global warming due to their mobility advantages. Due to past outbreaks, the trees (forests) are relatively more susceptible victims (Kurz et al. 2008 ). Before CC, the influence of factors mentioned earlier, i.e., droughts and storms, was existent and made the forests susceptible to insect pest interventions; however, the global forests remain steadfast, assiduous, and green (Jactel et al. 2019 ). The typical reasons could be the insect herbivores were regulated by several tree defenses and pressures of predation (Wilkinson and Sherratt 2016 ). As climate greatly influences these phenomena, the global forests cannot be so sedulous against such challenges (Jactel et al. 2019 ). Table 3 demonstrates some of the particular considerations with practical examples that are essential while mitigating the impacts of CC in the forestry sector.

Climate change impacts on tourism

Tourism is a commercial activity that has roots in multi-dimensions and an efficient tool with adequate job generation potential, revenue creation, earning of spectacular foreign exchange, enhancement in cross-cultural promulgation and cooperation, a business tool for entrepreneurs and eventually for the country’s national development (Arshad et al. 2018 ; Scott 2021 ). Among a plethora of other disciplines, the tourism industry is also a distinct victim of climate warming (Gössling et al. 2012 ; Hall et al. 2015 ) as the climate is among the essential resources that enable tourism in particular regions as most preferred locations. Different places at different times of the year attract tourists both within and across the countries depending upon the feasibility and compatibility of particular weather patterns. Hence, the massive variations in these weather patterns resulting from CC will eventually lead to monumental challenges to the local economy in that specific area’s particular and national economy (Bujosa et al. 2015 ). For instance, the Intergovernmental Panel on Climate Change (IPCC) report demonstrated that the global tourism industry had faced a considerable decline in the duration of ski season, including the loss of some ski areas and the dramatic shifts in tourist destinations’ climate warming.

Furthermore, different studies (Neuvonen et al. 2015 ; Scott et al. 2004 ) indicated that various currently perfect tourist spots, e.g., coastal areas, splendid islands, and ski resorts, will suffer consequences of CC. It is also worth noting that the quality and potential of administrative management potential to cope with the influence of CC on the tourism industry is of crucial significance, which renders specific strengths of resiliency to numerous destinations to withstand against it (Füssel and Hildén 2014 ). Similarly, in the partial or complete absence of adequate socio-economic and socio-political capital, the high-demanding tourist sites scurry towards the verge of vulnerability. The susceptibility of tourism is based on different components such as the extent of exposure, sensitivity, life-supporting sectors, and capacity assessment factors (Füssel and Hildén 2014 ). It is obvious corporality that sectors such as health, food, ecosystems, human habitat, infrastructure, water availability, and the accessibility of a particular region are prone to CC. Henceforth, the sensitivity of these critical sectors to CC and, in return, the adaptive measures are a hallmark in determining the composite vulnerability of climate warming (Ionescu et al. 2009 ).

Moreover, the dependence on imported food items, poor hygienic conditions, and inadequate health professionals are dominant aspects affecting the local terrestrial and aquatic biodiversity. Meanwhile, the greater dependency on ecosystem services and its products also makes a destination more fragile to become a prey of CC (Rizvi et al. 2015 ). Some significant non-climatic factors are important indicators of a particular ecosystem’s typical health and functioning, e.g., resource richness and abundance portray the picture of ecosystem stability. Similarly, the species abundance is also a productive tool that ensures that the ecosystem has a higher buffering capacity, which is terrific in terms of resiliency (Roscher et al. 2013 ).

Climate change impacts on the economic sector

Climate plays a significant role in overall productivity and economic growth. Due to its increasingly global existence and its effect on economic growth, CC has become one of the major concerns of both local and international environmental policymakers (Ferreira et al. 2020 ; Gleditsch 2021 ; Abbass et al. 2021b ; Lamperti et al. 2021 ). The adverse effects of CC on the overall productivity factor of the agricultural sector are therefore significant for understanding the creation of local adaptation policies and the composition of productive climate policy contracts. Previous studies on CC in the world have already forecasted its effects on the agricultural sector. Researchers have found that global CC will impact the agricultural sector in different world regions. The study of the impacts of CC on various agrarian activities in other demographic areas and the development of relative strategies to respond to effects has become a focal point for researchers (Chandioet al. 2020 ; Gleditsch 2021 ; Mosavi et al. 2020 ).

With the rapid growth of global warming since the 1980s, the temperature has started increasing globally, which resulted in the incredible transformation of rain and evaporation in the countries. The agricultural development of many countries has been reliant, delicate, and susceptible to CC for a long time, and it is on the development of agriculture total factor productivity (ATFP) influence different crops and yields of farmers (Alhassan 2021 ; Wu  2020 ).

Food security and natural disasters are increasing rapidly in the world. Several major climatic/natural disasters have impacted local crop production in the countries concerned. The effects of these natural disasters have been poorly controlled by the development of the economies and populations and may affect human life as well. One example is China, which is among the world’s most affected countries, vulnerable to natural disasters due to its large population, harsh environmental conditions, rapid CC, low environmental stability, and disaster power. According to the January 2016 statistical survey, China experienced an economic loss of 298.3 billion Yuan, and about 137 million Chinese people were severely affected by various natural disasters (Xie et al. 2018 ).

Mitigation and adaptation strategies of climate changes

Adaptation and mitigation are the crucial factors to address the response to CC (Jahanzad et al. 2020 ). Researchers define mitigation on climate changes, and on the other hand, adaptation directly impacts climate changes like floods. To some extent, mitigation reduces or moderates greenhouse gas emission, and it becomes a critical issue both economically and environmentally (Botzen et al. 2021 ; Jahanzad et al. 2020 ; Kongsager 2018 ; Smit et al. 2000 ; Vale et al. 2021 ; Usman et al. 2021 ; Verheyen 2005 ).

Researchers have deep concern about the adaptation and mitigation methodologies in sectoral and geographical contexts. Agriculture, industry, forestry, transport, and land use are the main sectors to adapt and mitigate policies(Kärkkäinen et al. 2020 ; Waheed et al. 2021 ). Adaptation and mitigation require particular concern both at the national and international levels. The world has faced a significant problem of climate change in the last decades, and adaptation to these effects is compulsory for economic and social development. To adapt and mitigate against CC, one should develop policies and strategies at the international level (Hussain et al. 2020 ). Figure  6 depicts the list of current studies on sectoral impacts of CC with adaptation and mitigation measures globally.

Sectoral impacts of climate change with adaptation and mitigation measures.

Conclusion and future perspectives

Specific socio-agricultural, socio-economic, and physical systems are the cornerstone of psychological well-being, and the alteration in these systems by CC will have disastrous impacts. Climate variability, alongside other anthropogenic and natural stressors, influences human and environmental health sustainability. Food security is another concerning scenario that may lead to compromised food quality, higher food prices, and inadequate food distribution systems. Global forests are challenged by different climatic factors such as storms, droughts, flash floods, and intense precipitation. On the other hand, their anthropogenic wiping is aggrandizing their existence. Undoubtedly, the vulnerability scale of the world’s regions differs; however, appropriate mitigation and adaptation measures can aid the decision-making bodies in developing effective policies to tackle its impacts. Presently, modern life on earth has tailored to consistent climatic patterns, and accordingly, adapting to such considerable variations is of paramount importance. Because the faster changes in climate will make it harder to survive and adjust, this globally-raising enigma calls for immediate attention at every scale ranging from elementary community level to international level. Still, much effort, research, and dedication are required, which is the most critical time. Some policy implications can help us to mitigate the consequences of climate change, especially the most affected sectors like the agriculture sector;

Seasonal variations and cultivation practices

Warming might lengthen the season in frost-prone growing regions (temperate and arctic zones), allowing for longer-maturing seasonal cultivars with better yields (Pfadenhauer 2020 ; Bonacci 2019 ). Extending the planting season may allow additional crops each year; when warming leads to frequent warmer months highs over critical thresholds, a split season with a brief summer fallow may be conceivable for short-period crops such as wheat barley, cereals, and many other vegetable crops. The capacity to prolong the planting season in tropical and subtropical places where the harvest season is constrained by precipitation or agriculture farming occurs after the year may be more limited and dependent on how precipitation patterns vary (Wu et al. 2017 ).

New varieties of crops

The genetic component is comprehensive for many yields, but it is restricted like kiwi fruit for a few. Ali et al. ( 2017 ) investigated how new crops will react to climatic changes (also stated in Mall et al. 2017 ). Hot temperature, drought, insect resistance; salt tolerance; and overall crop production and product quality increases would all be advantageous (Akkari 2016 ). Genetic mapping and engineering can introduce a greater spectrum of features. The adoption of genetically altered cultivars has been slowed, particularly in the early forecasts owing to the complexity in ensuring features are expediently expressed throughout the entire plant, customer concerns, economic profitability, and regulatory impediments (Wirehn 2018 ; Davidson et al. 2016 ).

Changes in management and other input factors

To get the full benefit of the CO 2 would certainly require additional nitrogen and other fertilizers. Nitrogen not consumed by the plants may be excreted into groundwater, discharged into water surface, or emitted from the land, soil nitrous oxide when large doses of fertilizer are sprayed. Increased nitrogen levels in groundwater sources have been related to human chronic illnesses and impact marine ecosystems. Cultivation, grain drying, and other field activities have all been examined in depth in the studies (Barua et al. 2018 ).

The technological and socio-economic adaptation

The policy consequence of the causative conclusion is that as a source of alternative energy, biofuel production is one of the routes that explain oil price volatility separate from international macroeconomic factors. Even though biofuel production has just begun in a few sample nations, there is still a tremendous worldwide need for feedstock to satisfy industrial expansion in China and the USA, which explains the food price relationship to the global oil price. Essentially, oil-exporting countries may create incentives in their economies to increase food production. It may accomplish by giving farmers financing, seedlings, fertilizers, and farming equipment. Because of the declining global oil price and, as a result, their earnings from oil export, oil-producing nations may be unable to subsidize food imports even in the near term. As a result, these countries can boost the agricultural value chain for export. It may be accomplished through R&D and adding value to their food products to increase income by correcting exchange rate misalignment and adverse trade terms. These nations may also diversify their economies away from oil, as dependence on oil exports alone is no longer economically viable given the extreme volatility of global oil prices. Finally, resource-rich and oil-exporting countries can convert to non-food renewable energy sources such as solar, hydro, coal, wind, wave, and tidal energy. By doing so, both world food and oil supplies would be maintained rather than harmed.

IRENA’s modeling work shows that, if a comprehensive policy framework is in place, efforts toward decarbonizing the energy future will benefit economic activity, jobs (outweighing losses in the fossil fuel industry), and welfare. Countries with weak domestic supply chains and a large reliance on fossil fuel income, in particular, must undertake structural reforms to capitalize on the opportunities inherent in the energy transition. Governments continue to give major policy assistance to extract fossil fuels, including tax incentives, financing, direct infrastructure expenditures, exemptions from environmental regulations, and other measures. The majority of major oil and gas producing countries intend to increase output. Some countries intend to cut coal output, while others plan to maintain or expand it. While some nations are beginning to explore and execute policies aimed at a just and equitable transition away from fossil fuel production, these efforts have yet to impact major producing countries’ plans and goals. Verifiable and comparable data on fossil fuel output and assistance from governments and industries are critical to closing the production gap. Governments could increase openness by declaring their production intentions in their climate obligations under the Paris Agreement.

It is firmly believed that achieving the Paris Agreement commitments is doubtlful without undergoing renewable energy transition across the globe (Murshed 2020 ; Zhao et al. 2022 ). Policy instruments play the most important role in determining the degree of investment in renewable energy technology. This study examines the efficacy of various policy strategies in the renewable energy industry of multiple nations. Although its impact is more visible in established renewable energy markets, a renewable portfolio standard is also a useful policy instrument. The cost of producing renewable energy is still greater than other traditional energy sources. Furthermore, government incentives in the R&D sector can foster innovation in this field, resulting in cost reductions in the renewable energy industry. These nations may export their technologies and share their policy experiences by forming networks among their renewable energy-focused organizations. All policy measures aim to reduce production costs while increasing the proportion of renewables to a country’s energy system. Meanwhile, long-term contracts with renewable energy providers, government commitment and control, and the establishment of long-term goals can assist developing nations in deploying renewable energy technology in their energy sector.

Availability of data and material

Data sources and relevant links are provided in the paper to access data.

Abbass K, Begum H, Alam ASA, Awang AH, Abdelsalam MK, Egdair IMM, Wahid R (2022) Fresh Insight through a Keynesian Theory Approach to Investigate the Economic Impact of the COVID-19 Pandemic in Pakistan. Sustain 14(3):1054

Abbass K, Niazi AAK, Qazi TF, Basit A, Song H (2021a) The aftermath of COVID-19 pandemic period: barriers in implementation of social distancing at workplace. Library Hi Tech

Abbass K, Song H, Khan F, Begum H, Asif M (2021b) Fresh insight through the VAR approach to investigate the effects of fiscal policy on environmental pollution in Pakistan. Environ Scie Poll Res 1–14

Abbass K, Song H, Shah SM, Aziz B (2019) Determinants of Stock Return for Non-Financial Sector: Evidence from Energy Sector of Pakistan. J Bus Fin Aff 8(370):2167–0234

Google Scholar  

Abbass K, Tanveer A, Huaming S, Khatiya AA (2021c) Impact of financial resources utilization on firm performance: a case of SMEs working in Pakistan

Abraham E, Chain E (1988) An enzyme from bacteria able to destroy penicillin. 1940. Rev Infect Dis 10(4):677

CAS   Google Scholar  

Adger WN, Arnell NW, Tompkins EL (2005) Successful adaptation to climate change across scales. Glob Environ Chang 15(2):77–86

Article   Google Scholar  

Akkari C, Bryant CR (2016) The co-construction approach as approach to developing adaptation strategies in the face of climate change and variability: A conceptual framework. Agricultural Research 5(2):162–173

Alhassan H (2021) The effect of agricultural total factor productivity on environmental degradation in sub-Saharan Africa. Sci Afr 12:e00740

Ali A, Erenstein O (2017) Assessing farmer use of climate change adaptation practices and impacts on food security and poverty in Pakistan. Clim Risk Manag 16:183–194

Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Hogg ET (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag 259(4):660–684

Anwar A, Sinha A, Sharif A, Siddique M, Irshad S, Anwar W, Malik S (2021) The nexus between urbanization, renewable energy consumption, financial development, and CO2 emissions: evidence from selected Asian countries. Environ Dev Sust. https://doi.org/10.1007/s10668-021-01716-2

Araus JL, Slafer GA, Royo C, Serret MD (2008) Breeding for yield potential and stress adaptation in cereals. Crit Rev Plant Sci 27(6):377–412

Aron JL, Patz J (2001) Ecosystem change and public health: a global perspective: JHU Press

Arshad MI, Iqbal MA, Shahbaz M (2018) Pakistan tourism industry and challenges: a review. Asia Pacific Journal of Tourism Research 23(2):121–132

Ashbolt NJ (2015) Microbial contamination of drinking water and human health from community water systems. Current Environmental Health Reports 2(1):95–106

Article   CAS   Google Scholar  

Asseng S, Cao W, Zhang W, Ludwig F (2009) Crop physiology, modelling and climate change: impact and adaptation strategies. Crop Physiol 511–543

Asseng S, Ewert F, Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Cammarano D (2013) Uncertainty in simulating wheat yields under climate change. Nat Clim Chang 3(9):827–832

Association A (2020) Climate change is threatening mental health, American Psychological Association, “Kirsten Weir, . from < https://www.apa.org/monitor/2016/07-08/climate-change >, Accessed on 26 Jan 2020.

Ayers J, Huq S, Wright H, Faisal A, Hussain S (2014) Mainstreaming climate change adaptation into development in Bangladesh. Clim Dev 6:293–305

Balsalobre-Lorente D, Driha OM, Bekun FV, Sinha A, Adedoyin FF (2020) Consequences of COVID-19 on the social isolation of the Chinese economy: accounting for the role of reduction in carbon emissions. Air Qual Atmos Health 13(12):1439–1451

Balsalobre-Lorente D, Ibáñez-Luzón L, Usman M, Shahbaz M (2022) The environmental Kuznets curve, based on the economic complexity, and the pollution haven hypothesis in PIIGS countries. Renew Energy 185:1441–1455

Bank W (2008) Forests sourcebook: practical guidance for sustaining forests in development cooperation: World Bank

Barua S, Valenzuela E (2018) Climate change impacts on global agricultural trade patterns: evidence from the past 50 years. In Proceedings of the Sixth International Conference on Sustainable Development (pp. 26–28)

Bates AE, Pecl GT, Frusher S, Hobday AJ, Wernberg T, Smale DA, Colwell RK (2014) Defining and observing stages of climate-mediated range shifts in marine systems. Glob Environ Chang 26:27–38

Battisti DS, Naylor RL (2009) Historical warnings of future food insecurity with unprecedented seasonal heat. Science 323(5911):240–244

Beesley L, Close PG, Gwinn DC, Long M, Moroz M, Koster WM, Storer T (2019) Flow-mediated movement of freshwater catfish, Tandanus bostocki, in a regulated semi-urban river, to inform environmental water releases. Ecol Freshw Fish 28(3):434–445

Benita F (2021) Human mobility behavior in COVID-19: A systematic literature review and bibliometric analysis. Sustain Cities Soc 70:102916

Berendonk TU, Manaia CM, Merlin C, Fatta-Kassinos D, Cytryn E, Walsh F, Pons M-N (2015) Tackling antibiotic resistance: the environmental framework. Nat Rev Microbiol 13(5):310–317

Berg MP, Kiers ET, Driessen G, Van DerHEIJDEN M, Kooi BW, Kuenen F, Ellers J (2010) Adapt or disperse: understanding species persistence in a changing world. Glob Change Biol 16(2):587–598

Blum A, Klueva N, Nguyen H (2001) Wheat cellular thermotolerance is related to yield under heat stress. Euphytica 117(2):117–123

Bonacci O (2019) Air temperature and precipitation analyses on a small Mediterranean island: the case of the remote island of Lastovo (Adriatic Sea, Croatia). Acta Hydrotechnica 32(57):135–150

Botzen W, Duijndam S, van Beukering P (2021) Lessons for climate policy from behavioral biases towards COVID-19 and climate change risks. World Dev 137:105214

Brázdil R, Stucki P, Szabó P, Řezníčková L, Dolák L, Dobrovolný P, Suchánková S (2018) Windstorms and forest disturbances in the Czech Lands: 1801–2015. Agric for Meteorol 250:47–63

Brown HCP, Smit B, Somorin OA, Sonwa DJ, Nkem JN (2014) Climate change and forest communities: prospects for building institutional adaptive capacity in the Congo Basin forests. Ambio 43(6):759–769

Bujosa A, Riera A, Torres CM (2015) Valuing tourism demand attributes to guide climate change adaptation measures efficiently: the case of the Spanish domestic travel market. Tour Manage 47:233–239

Calderini D, Abeledo L, Savin R, Slafer GA (1999) Effect of temperature and carpel size during pre-anthesis on potential grain weight in wheat. J Agric Sci 132(4):453–459

Cammell M, Knight J (1992) Effects of climatic change on the population dynamics of crop pests. Adv Ecol Res 22:117–162

Cavanaugh KC, Kellner JR, Forde AJ, Gruner DS, Parker JD, Rodriguez W, Feller IC (2014) Poleward expansion of mangroves is a threshold response to decreased frequency of extreme cold events. Proc Natl Acad Sci 111(2):723–727

Cell CC (2009) Climate change and health impacts in Bangladesh. Clima Chang Cell DoE MoEF

Chandio AA, Jiang Y, Rehman A, Rauf A (2020) Short and long-run impacts of climate change on agriculture: an empirical evidence from China. Int J Clim Chang Strat Manag

Chaudhary P, Rai S, Wangdi S, Mao A, Rehman N, Chettri S, Bawa KS (2011) Consistency of local perceptions of climate change in the Kangchenjunga Himalaya landscape. Curr Sci 504–513

Chien F, Anwar A, Hsu CC, Sharif A, Razzaq A, Sinha A (2021) The role of information and communication technology in encountering environmental degradation: proposing an SDG framework for the BRICS countries. Technol Soc 65:101587

Cooper C, Booth A, Varley-Campbell J, Britten N, Garside R (2018) Defining the process to literature searching in systematic reviews: a literature review of guidance and supporting studies. BMC Med Res Methodol 18(1):1–14

Costello A, Abbas M, Allen A, Ball S, Bell S, Bellamy R, Kett M (2009) Managing the health effects of climate change: lancet and University College London Institute for Global Health Commission. The Lancet 373(9676):1693–1733

Cruz DLA (2015) Mother Figured. University of Chicago Press. Retrieved from, https://doi.org/10.7208/9780226315072

Cui W, Ouyang T, Qiu Y, Cui D (2021) Literature Review of the Implications of Exercise Rehabilitation Strategies for SARS Patients on the Recovery of COVID-19 Patients. Paper presented at the Healthcare

Davidson D (2016) Gaps in agricultural climate adaptation research. Nat Clim Chang 6(5):433–435

Diffenbaugh NS, Singh D, Mankin JS, Horton DE, Swain DL, Touma D, Tsiang M (2017) Quantifying the influence of global warming on unprecedented extreme climate events. Proc Natl Acad Sci 114(19):4881–4886

Dimri A, Kumar D, Choudhary A, Maharana P (2018) Future changes over the Himalayas: mean temperature. Global Planet Change 162:235–251

Dullinger S, Gattringer A, Thuiller W, Moser D, Zimmermann N, Guisan A (2012) Extinction debt of high-mountain plants under twenty-first-century climate change. Nature Publishing Group, Nat Clim Chang

Book   Google Scholar  

Dupuis I, Dumas C (1990) Influence of temperature stress on in vitro fertilization and heat shock protein synthesis in maize (Zea mays L.) reproductive tissues. Plant Physiol 94(2):665–670

Edreira JR, Otegui ME (2013) Heat stress in temperate and tropical maize hybrids: a novel approach for assessing sources of kernel loss in field conditions. Field Crop Res 142:58–67

Edreira JR, Carpici EB, Sammarro D, Otegui M (2011) Heat stress effects around flowering on kernel set of temperate and tropical maize hybrids. Field Crop Res 123(2):62–73

Ellison D, Morris CE, Locatelli B, Sheil D, Cohen J, Murdiyarso D, Pokorny J (2017) Trees, forests and water: Cool insights for a hot world. Glob Environ Chang 43:51–61

Elsayed ZM, Eldehna WM, Abdel-Aziz MM, El Hassab MA, Elkaeed EB, Al-Warhi T, Mohammed ER (2021) Development of novel isatin–nicotinohydrazide hybrids with potent activity against susceptible/resistant Mycobacterium tuberculosis and bronchitis causing–bacteria. J Enzyme Inhib Med Chem 36(1):384–393

EM-DAT (2020) EMDAT: OFDA/CRED International Disaster Database, Université catholique de Louvain – Brussels – Belgium. from http://www.emdat.be

EPA U (2018) United States Environmental Protection Agency, EPA Year in Review

Erman A, De Vries Robbe SA, Thies SF, Kabir K, Maruo M (2021) Gender Dimensions of Disaster Risk and Resilience

Fand BB, Kamble AL, Kumar M (2012) Will climate change pose serious threat to crop pest management: a critical review. Int J Sci Res Publ 2(11):1–14

FAO (2018).The State of the World’s Forests 2018 - Forest Pathways to Sustainable Development.

Fardous S Perception of climate change in Kaptai National Park. Rural Livelihoods and Protected Landscape: Co-Management in the Wetlands and Forests of Bangladesh, 186–204

Farooq M, Bramley H, Palta JA, Siddique KH (2011) Heat stress in wheat during reproductive and grain-filling phases. Crit Rev Plant Sci 30(6):491–507

Feliciano D, Recha J, Ambaw G, MacSween K, Solomon D, Wollenberg E (2022) Assessment of agricultural emissions, climate change mitigation and adaptation practices in Ethiopia. Clim Policy 1–18

Ferreira JJ, Fernandes CI, Ferreira FA (2020) Technology transfer, climate change mitigation, and environmental patent impact on sustainability and economic growth: a comparison of European countries. Technol Forecast Soc Change 150:119770

Fettig CJ, Reid ML, Bentz BJ, Sevanto S, Spittlehouse DL, Wang T (2013) Changing climates, changing forests: a western North American perspective. J Forest 111(3):214–228

Fischer AP (2019) Characterizing behavioral adaptation to climate change in temperate forests. Landsc Urban Plan 188:72–79

Flannigan M, Cantin AS, De Groot WJ, Wotton M, Newbery A, Gowman LM (2013) Global wildland fire season severity in the 21st century. For Ecol Manage 294:54–61

Fossheim M, Primicerio R, Johannesen E, Ingvaldsen RB, Aschan MM, Dolgov AV (2015) Recent warming leads to a rapid borealization of fish communities in the Arctic. Nat Clim Chang 5(7):673–677

Füssel HM, Hildén M (2014) How is uncertainty addressed in the knowledge base for national adaptation planning? Adapting to an Uncertain Climate (pp. 41–66): Springer

Gambín BL, Borrás L, Otegui ME (2006) Source–sink relations and kernel weight differences in maize temperate hybrids. Field Crop Res 95(2–3):316–326

Gambín B, Borrás L (2010) Resource distribution and the trade-off between seed number and seed weight: a comparison across crop species. Annals of Applied Biology 156(1):91–102

Gampe D, Nikulin G, Ludwig R (2016) Using an ensemble of regional climate models to assess climate change impacts on water scarcity in European river basins. Sci Total Environ 573:1503–1518

García GA, Dreccer MF, Miralles DJ, Serrago RA (2015) High night temperatures during grain number determination reduce wheat and barley grain yield: a field study. Glob Change Biol 21(11):4153–4164

Garner E, Inyang M, Garvey E, Parks J, Glover C, Grimaldi A, Edwards MA (2019) Impact of blending for direct potable reuse on premise plumbing microbial ecology and regrowth of opportunistic pathogens and antibiotic resistant bacteria. Water Res 151:75–86

Gleditsch NP (2021) This time is different! Or is it? NeoMalthusians and environmental optimists in the age of climate change. J Peace Res 0022343320969785

Godfray HCJ, Beddington JR, Crute IR, Haddad L, Lawrence D, Muir JF, Toulmin C (2010) Food security: the challenge of feeding 9 billion people. Science 327(5967):812–818

Goes S, Hasterok D, Schutt DL, Klöcking M (2020) Continental lithospheric temperatures: A review. Phys Earth Planet Inter 106509

Gorst A, Dehlavi A, Groom B (2018) Crop productivity and adaptation to climate change in Pakistan. Environ Dev Econ 23(6):679–701

Gosling SN, Arnell NW (2016) A global assessment of the impact of climate change on water scarcity. Clim Change 134(3):371–385

Gössling S, Scott D, Hall CM, Ceron J-P, Dubois G (2012) Consumer behaviour and demand response of tourists to climate change. Ann Tour Res 39(1):36–58

Gourdji SM, Sibley AM, Lobell DB (2013) Global crop exposure to critical high temperatures in the reproductive period: historical trends and future projections. Environ Res Lett 8(2):024041

Grieg E Responsible Consumption and Production

Gunter BG, Rahman A, Rahman A (2008) How Vulnerable are Bangladesh’s Indigenous People to Climate Change? Bangladesh Development Research Center (BDRC)

Hall CM, Amelung B, Cohen S, Eijgelaar E, Gössling S, Higham J, Scott D (2015) On climate change skepticism and denial in tourism. J Sustain Tour 23(1):4–25

Hartmann H, Moura CF, Anderegg WR, Ruehr NK, Salmon Y, Allen CD, Galbraith D (2018) Research frontiers for improving our understanding of drought-induced tree and forest mortality. New Phytol 218(1):15–28

Hatfield JL, Prueger JH (2015) Temperature extremes: Effect on plant growth and development. Weather and Climate Extremes 10:4–10

Hatfield JL, Boote KJ, Kimball B, Ziska L, Izaurralde RC, Ort D, Wolfe D (2011) Climate impacts on agriculture: implications for crop production. Agron J 103(2):351–370

Hendriksen RS, Munk P, Njage P, Van Bunnik B, McNally L, Lukjancenko O, Kjeldgaard J (2019) Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage. Nat Commun 10(1):1124

Huang S (2004) Global trade patterns in fruits and vegetables. USDA-ERS Agriculture and Trade Report No. WRS-04–06

Huang W, Gao Q-X, Cao G-L, Ma Z-Y, Zhang W-D, Chao Q-C (2016) Effect of urban symbiosis development in China on GHG emissions reduction. Adv Clim Chang Res 7(4):247–252

Huang Y, Haseeb M, Usman M, Ozturk I (2022) Dynamic association between ICT, renewable energy, economic complexity and ecological footprint: Is there any difference between E-7 (developing) and G-7 (developed) countries? Tech Soc 68:101853

Hubbart JA, Guyette R, Muzika R-M (2016) More than drought: precipitation variance, excessive wetness, pathogens and the future of the western edge of the eastern deciduous forest. Sci Total Environ 566:463–467

Hussain M, Butt AR, Uzma F, Ahmed R, Irshad S, Rehman A, Yousaf B (2020) A comprehensive review of climate change impacts, adaptation, and mitigation on environmental and natural calamities in Pakistan. Environ Monit Assess 192(1):48

Hussain M, Liu G, Yousaf B, Ahmed R, Uzma F, Ali MU, Butt AR (2018) Regional and sectoral assessment on climate-change in Pakistan: social norms and indigenous perceptions on climate-change adaptation and mitigation in relation to global context. J Clean Prod 200:791–808

Intergov. Panel Clim Chang 33 from  https://doi.org/10.1017/CBO9781107415324

Ionescu C, Klein RJ, Hinkel J, Kumar KK, Klein R (2009) Towards a formal framework of vulnerability to climate change. Environ Model Assess 14(1):1–16

IPCC (2013) Summary for policymakers. Clim Chang Phys Sci Basis Contrib Work Gr I Fifth Assess Rep

Ishikawa-Ishiwata Y, Furuya J (2022) Economic evaluation and climate change adaptation measures for rice production in vietnam using a supply and demand model: special emphasis on the Mekong River Delta region in Vietnam. In Interlocal Adaptations to Climate Change in East and Southeast Asia (pp. 45–53). Springer, Cham

Izaguirre C, Losada I, Camus P, Vigh J, Stenek V (2021) Climate change risk to global port operations. Nat Clim Chang 11(1):14–20

Jactel H, Koricheva J, Castagneyrol B (2019) Responses of forest insect pests to climate change: not so simple. Current opinion in insect science

Jahanzad E, Holtz BA, Zuber CA, Doll D, Brewer KM, Hogan S, Gaudin AC (2020) Orchard recycling improves climate change adaptation and mitigation potential of almond production systems. PLoS ONE 15(3):e0229588

Jurgilevich A, Räsänen A, Groundstroem F, Juhola S (2017) A systematic review of dynamics in climate risk and vulnerability assessments. Environ Res Lett 12(1):013002

Karami E (2012) Climate change, resilience and poverty in the developing world. Paper presented at the Culture, Politics and Climate change conference

Kärkkäinen L, Lehtonen H, Helin J, Lintunen J, Peltonen-Sainio P, Regina K, . . . Packalen T (2020) Evaluation of policy instruments for supporting greenhouse gas mitigation efforts in agricultural and urban land use. Land Use Policy 99:104991

Karkman A, Do TT, Walsh F, Virta MP (2018) Antibiotic-resistance genes in waste water. Trends Microbiol 26(3):220–228

Kohfeld KE, Le Quéré C, Harrison SP, Anderson RF (2005) Role of marine biology in glacial-interglacial CO2 cycles. Science 308(5718):74–78

Kongsager R (2018) Linking climate change adaptation and mitigation: a review with evidence from the land-use sectors. Land 7(4):158

Kurz WA, Dymond C, Stinson G, Rampley G, Neilson E, Carroll A, Safranyik L (2008) Mountain pine beetle and forest carbon feedback to climate change. Nature 452(7190):987

Lamperti F, Bosetti V, Roventini A, Tavoni M, Treibich T (2021) Three green financial policies to address climate risks. J Financial Stab 54:100875

Leal Filho W, Azeiteiro UM, Balogun AL, Setti AFF, Mucova SA, Ayal D, . . . Oguge NO (2021) The influence of ecosystems services depletion to climate change adaptation efforts in Africa. Sci Total Environ 146414

Lehner F, Coats S, Stocker TF, Pendergrass AG, Sanderson BM, Raible CC, Smerdon JE (2017) Projected drought risk in 1.5 C and 2 C warmer climates. Geophys Res Lett 44(14):7419–7428

Lemery J, Knowlton K, Sorensen C (2021) Global climate change and human health: from science to practice: John Wiley & Sons

Leppänen S, Saikkonen L, Ollikainen M (2014) Impact of Climate Change on cereal grain production in Russia: Mimeo

Lipczynska-Kochany E (2018) Effect of climate change on humic substances and associated impacts on the quality of surface water and groundwater: a review. Sci Total Environ 640:1548–1565

livescience.com. New coronavirus may have ‘jumped’ to humans from snakes, study finds, live science,. from < https://www.livescience.com/new-coronavirus-origin-snakes.html > accessed on Jan 2020

Lobell DB, Field CB (2007) Global scale climate–crop yield relationships and the impacts of recent warming. Environ Res Lett 2(1):014002

Lobell DB, Gourdji SM (2012) The influence of climate change on global crop productivity. Plant Physiol 160(4):1686–1697

Ma L, Li B, Zhang T (2019) New insights into antibiotic resistome in drinking water and management perspectives: a metagenomic based study of small-sized microbes. Water Res 152:191–201

Macchi M, Oviedo G, Gotheil S, Cross K, Boedhihartono A, Wolfangel C, Howell M (2008) Indigenous and traditional peoples and climate change. International Union for the Conservation of Nature, Gland, Suiza

Mall RK, Gupta A, Sonkar G (2017) Effect of climate change on agricultural crops. In Current developments in biotechnology and bioengineering (pp. 23–46). Elsevier

Manes S, Costello MJ, Beckett H, Debnath A, Devenish-Nelson E, Grey KA, . . . Krause C (2021) Endemism increases species’ climate change risk in areas of global biodiversity importance. Biol Conserv 257:109070

Mannig B, Pollinger F, Gafurov A, Vorogushyn S, Unger-Shayesteh K (2018) Impacts of climate change in Central Asia Encyclopedia of the Anthropocene (pp. 195–203): Elsevier

Martínez-Alvarado O, Gray SL, Hart NC, Clark PA, Hodges K, Roberts MJ (2018) Increased wind risk from sting-jet windstorms with climate change. Environ Res Lett 13(4):044002

Matsui T, Omasa K, Horie T (2001) The difference in sterility due to high temperatures during the flowering period among japonica-rice varieties. Plant Production Science 4(2):90–93

Meierrieks D (2021) Weather shocks, climate change and human health. World Dev 138:105228

Michel D, Eriksson M, Klimes M (2021) Climate change and (in) security in transboundary river basins Handbook of Security and the Environment: Edward Elgar Publishing

Mihiretu A, Okoyo EN, Lemma T (2021) Awareness of climate change and its associated risks jointly explain context-specific adaptation in the Arid-tropics. Northeast Ethiopia SN Social Sciences 1(2):1–18

Millar CI, Stephenson NL (2015) Temperate forest health in an era of emerging megadisturbance. Science 349(6250):823–826

Mishra A, Bruno E, Zilberman D (2021) Compound natural and human disasters: Managing drought and COVID-19 to sustain global agriculture and food sectors. Sci Total Environ 754:142210

Mosavi SH, Soltani S, Khalilian S (2020) Coping with climate change in agriculture: Evidence from Hamadan-Bahar plain in Iran. Agric Water Manag 241:106332

Murshed M (2020) An empirical analysis of the non-linear impacts of ICT-trade openness on renewable energy transition, energy efficiency, clean cooking fuel access and environmental sustainability in South Asia. Environ Sci Pollut Res 27(29):36254–36281. https://doi.org/10.1007/s11356-020-09497-3

Murshed M (2022) Pathways to clean cooking fuel transition in low and middle income Sub-Saharan African countries: the relevance of improving energy use efficiency. Sustainable Production and Consumption 30:396–412. https://doi.org/10.1016/j.spc.2021.12.016

Murshed M, Dao NTT (2020) Revisiting the CO2 emission-induced EKC hypothesis in South Asia: the role of Export Quality Improvement. GeoJournal. https://doi.org/10.1007/s10708-020-10270-9

Murshed M, Abbass K, Rashid S (2021) Modelling renewable energy adoption across south Asian economies: Empirical evidence from Bangladesh, India, Pakistan and Sri Lanka. Int J Finan Eco 26(4):5425–5450

Murshed M, Nurmakhanova M, Elheddad M, Ahmed R (2020) Value addition in the services sector and its heterogeneous impacts on CO2 emissions: revisiting the EKC hypothesis for the OPEC using panel spatial estimation techniques. Environ Sci Pollut Res 27(31):38951–38973. https://doi.org/10.1007/s11356-020-09593-4

Murshed M, Nurmakhanova M, Al-Tal R, Mahmood H, Elheddad M, Ahmed R (2022) Can intra-regional trade, renewable energy use, foreign direct investments, and economic growth reduce ecological footprints in South Asia? Energy Sources, Part B: Economics, Planning, and Policy. https://doi.org/10.1080/15567249.2022.2038730

Neuvonen M, Sievänen T, Fronzek S, Lahtinen I, Veijalainen N, Carter TR (2015) Vulnerability of cross-country skiing to climate change in Finland–an interactive mapping tool. J Outdoor Recreat Tour 11:64–79

npr.org. Please Help Me.’ What people in China are saying about the outbreak on social media, npr.org, . from < https://www.npr.org/sections/goatsandsoda/2020/01/24/799000379/please-help-me-what-people-in-china-are-saying-about-the-outbreak-on-social-medi >, Accessed on 26 Jan 2020.

Ogden LE (2018) Climate change, pathogens, and people: the challenges of monitoring a moving target. Bioscience 68(10):733–739

Ortiz AMD, Outhwaite CL, Dalin C, Newbold T (2021) A review of the interactions between biodiversity, agriculture, climate change, and international trade: research and policy priorities. One Earth 4(1):88–101

Ortiz R (2008) Crop genetic engineering under global climate change. Ann Arid Zone 47(3):343

Otegui MAE, Bonhomme R (1998) Grain yield components in maize: I. Ear growth and kernel set. Field Crop Res 56(3):247–256

Pachauri RK, Allen MR, Barros VR, Broome J, Cramer W, Christ R, . . . Dasgupta P (2014) Climate change 2014: synthesis report. Contribution of Working Groups I, II and III to the fifth assessment report of the Intergovernmental Panel on Climate Change: Ipcc

Pal JK (2021) Visualizing the knowledge outburst in global research on COVID-19. Scientometrics 126(5):4173–4193

Panda R, Behera S, Kashyap P (2003) Effective management of irrigation water for wheat under stressed conditions. Agric Water Manag 63(1):37–56

Pärnänen KM, Narciso-da-Rocha C, Kneis D, Berendonk TU, Cacace D, Do TT, Jaeger T (2019) Antibiotic resistance in European wastewater treatment plants mirrors the pattern of clinical antibiotic resistance prevalence. Sci Adv 5(3):eaau9124

Parry M, Parry ML, Canziani O, Palutikof J, Van der Linden P, Hanson C (2007) Climate change 2007-impacts, adaptation and vulnerability: Working group II contribution to the fourth assessment report of the IPCC (Vol. 4): Cambridge University Press

Patz JA, Campbell-Lendrum D, Holloway T, Foley JA (2005) Impact of regional climate change on human health. Nature 438(7066):310–317

Patz JA, Graczyk TK, Geller N, Vittor AY (2000) Effects of environmental change on emerging parasitic diseases. Int J Parasitol 30(12–13):1395–1405

Pautasso M, Döring TF, Garbelotto M, Pellis L, Jeger MJ (2012) Impacts of climate change on plant diseases—opinions and trends. Eur J Plant Pathol 133(1):295–313

Peng S, Huang J, Sheehy JE, Laza RC, Visperas RM, Zhong X, Cassman KG (2004) Rice yields decline with higher night temperature from global warming. Proc Natl Acad Sci 101(27):9971–9975

Pereira HM, Ferrier S, Walters M, Geller GN, Jongman R, Scholes RJ, Cardoso A (2013) Essential biodiversity variables. Science 339(6117):277–278

Perera K, De Silva K, Amarasinghe M (2018) Potential impact of predicted sea level rise on carbon sink function of mangrove ecosystems with special reference to Negombo estuary, Sri Lanka. Global Planet Change 161:162–171

Pfadenhauer JS, Klötzli FA (2020) Zonal Vegetation of the Subtropical (Warm–Temperate) Zone with Winter Rain. In Global Vegetation (pp. 455–514). Springer, Cham

Phillips JD (2018) Environmental gradients and complexity in coastal landscape response to sea level rise. CATENA 169:107–118

Pirasteh-Anosheh H, Parnian A, Spasiano D, Race M, Ashraf M (2021) Haloculture: A system to mitigate the negative impacts of pandemics on the environment, society and economy, emphasizing COVID-19. Environ Res 111228

Pruden A, Larsson DJ, Amézquita A, Collignon P, Brandt KK, Graham DW, Snape JR (2013) Management options for reducing the release of antibiotics and antibiotic resistance genes to the environment. Environ Health Perspect 121(8):878–885

Qasim MZ, Hammad HM, Abbas F, Saeed S, Bakhat HF, Nasim W, Fahad S (2020) The potential applications of picotechnology in biomedical and environmental sciences. Environ Sci Pollut Res 27(1):133–142

Qasim MZ, Hammad HM, Maqsood F, Tariq T, Chawla MS Climate Change Implication on Cereal Crop Productivity

Rahman M, Alam K (2016) Forest dependent indigenous communities’ perception and adaptation to climate change through local knowledge in the protected area—a Bangladesh case study. Climate 4(1):12

Ramankutty N, Mehrabi Z, Waha K, Jarvis L, Kremen C, Herrero M, Rieseberg LH (2018) Trends in global agricultural land use: implications for environmental health and food security. Annu Rev Plant Biol 69:789–815

Rehman A, Ma H, Ahmad M, Irfan M, Traore O, Chandio AA (2021) Towards environmental Sustainability: devolving the influence of carbon dioxide emission to population growth, climate change, Forestry, livestock and crops production in Pakistan. Ecol Indic 125:107460

Reichstein M, Carvalhais N (2019) Aspects of forest biomass in the Earth system: its role and major unknowns. Surv Geophys 40(4):693–707

Reidsma P, Ewert F, Boogaard H, van Diepen K (2009) Regional crop modelling in Europe: the impact of climatic conditions and farm characteristics on maize yields. Agric Syst 100(1–3):51–60

Ritchie H, Roser M (2014) Natural disasters. Our World in Data

Rizvi AR, Baig S, Verdone M (2015) Ecosystems based adaptation: knowledge gaps in making an economic case for investing in nature based solutions for climate change. IUCN, Gland, Switzerland, p 48

Roscher C, Fergus AJ, Petermann JS, Buchmann N, Schmid B, Schulze E-D (2013) What happens to the sown species if a biodiversity experiment is not weeded? Basic Appl Ecol 14(3):187–198

Rosenzweig C, Elliott J, Deryng D, Ruane AC, Müller C, Arneth A, Khabarov N (2014) Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc Natl Acad Sci 111(9):3268–3273

Rosenzweig C, Iglesius A, Yang XB, Epstein PR, Chivian E (2001) Climate change and extreme weather events-implications for food production, plant diseases, and pests

Sadras VO, Slafer GA (2012) Environmental modulation of yield components in cereals: heritabilities reveal a hierarchy of phenotypic plasticities. Field Crop Res 127:215–224

Salvucci ME, Crafts-Brandner SJ (2004) Inhibition of photosynthesis by heat stress: the activation state of Rubisco as a limiting factor in photosynthesis. Physiol Plant 120(2):179–186

Santos WS, Gurgel-Gonçalves R, Garcez LM, Abad-Franch F (2021) Deforestation effects on Attalea palms and their resident Rhodnius, vectors of Chagas disease, in eastern Amazonia. PLoS ONE 16(5):e0252071

Sarkar P, Debnath N, Reang D (2021) Coupled human-environment system amid COVID-19 crisis: a conceptual model to understand the nexus. Sci Total Environ 753:141757

Schlenker W, Roberts MJ (2009) Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc Natl Acad Sci 106(37):15594–15598

Schoene DH, Bernier PY (2012) Adapting forestry and forests to climate change: a challenge to change the paradigm. Forest Policy Econ 24:12–19

Schuurmans C (2021) The world heat budget: expected changes Climate Change (pp. 1–15): CRC Press

Scott D (2021) Sustainable Tourism and the Grand Challenge of Climate Change. Sustainability 13(4):1966

Scott D, McBoyle G, Schwartzentruber M (2004) Climate change and the distribution of climatic resources for tourism in North America. Climate Res 27(2):105–117

Semenov MA (2009) Impacts of climate change on wheat in England and Wales. J R Soc Interface 6(33):343–350

Shaffril HAM, Krauss SE, Samsuddin SF (2018) A systematic review on Asian’s farmers’ adaptation practices towards climate change. Sci Total Environ 644:683–695

Shahbaz M, Balsalobre-Lorente D, Sinha A (2019) Foreign direct Investment–CO2 emissions nexus in Middle East and North African countries: Importance of biomass energy consumption. J Clean Product 217:603–614

Sharif A, Mishra S, Sinha A, Jiao Z, Shahbaz M, Afshan S (2020) The renewable energy consumption-environmental degradation nexus in Top-10 polluted countries: Fresh insights from quantile-on-quantile regression approach. Renew Energy 150:670–690

Sharma R (2012) Impacts on human health of climate and land use change in the Hindu Kush-Himalayan region. Mt Res Dev 32(4):480–486

Sharma R, Sinha A, Kautish P (2020) Examining the impacts of economic and demographic aspects on the ecological footprint in South and Southeast Asian countries. Environ Sci Pollut Res 27(29):36970–36982

Smit B, Burton I, Klein RJ, Wandel J (2000) An anatomy of adaptation to climate change and variability Societal adaptation to climate variability and change (pp. 223–251): Springer

Song Y, Fan H, Tang X, Luo Y, Liu P, Chen Y (2021) The effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on ischemic stroke and the possible underlying mechanisms. Int J Neurosci 1–20

Sovacool BK, Griffiths S, Kim J, Bazilian M (2021) Climate change and industrial F-gases: a critical and systematic review of developments, sociotechnical systems and policy options for reducing synthetic greenhouse gas emissions. Renew Sustain Energy Rev 141:110759

Stewart JA, Perrine JD, Nichols LB, Thorne JH, Millar CI, Goehring KE, Wright DH (2015) Revisiting the past to foretell the future: summer temperature and habitat area predict pika extirpations in California. J Biogeogr 42(5):880–890

Stocker T, Qin D, Plattner G, Tignor M, Allen S, Boschung J, . . . Midgley P (2013) Climate change 2013: The physical science basis. Working group I contribution to the IPCC Fifth assessment report: Cambridge: Cambridge University Press. 1535p

Stone P, Nicolas M (1994) Wheat cultivars vary widely in their responses of grain yield and quality to short periods of post-anthesis heat stress. Funct Plant Biol 21(6):887–900

Su H-C, Liu Y-S, Pan C-G, Chen J, He L-Y, Ying G-G (2018) Persistence of antibiotic resistance genes and bacterial community changes in drinking water treatment system: from drinking water source to tap water. Sci Total Environ 616:453–461

Sunderlin WD, Angelsen A, Belcher B, Burgers P, Nasi R, Santoso L, Wunder S (2005) Livelihoods, forests, and conservation in developing countries: an overview. World Dev 33(9):1383–1402

Symanski E, Han HA, Han I, McDaniel M, Whitworth KW, McCurdy S, . . . Delclos GL (2021) Responding to natural and industrial disasters: partnerships and lessons learned. Disaster medicine and public health preparedness 1–4

Tao F, Yokozawa M, Xu Y, Hayashi Y, Zhang Z (2006) Climate changes and trends in phenology and yields of field crops in China, 1981–2000. Agric for Meteorol 138(1–4):82–92

Tebaldi C, Hayhoe K, Arblaster JM, Meehl GA (2006) Going to the extremes. Clim Change 79(3–4):185–211

Testa G, Koon E, Johannesson L, McKenna G, Anthony T, Klintmalm G, Gunby R (2018) This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Thornton PK, Lipper L (2014) How does climate change alter agricultural strategies to support food security? (Vol. 1340): Intl Food Policy Res Inst

Tranfield D, Denyer D, Smart P (2003) Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag 14(3):207–222

UNEP (2017) United nations environment programme: frontiers 2017. from https://www.unenvironment.org/news-and-stories/press-release/antimicrobial-resistance - environmental-pollution-among-biggest

Usman M, Balsalobre-Lorente D (2022) Environmental concern in the era of industrialization: Can financial development, renewable energy and natural resources alleviate some load? Ene Policy 162:112780

Usman M, Makhdum MSA (2021) What abates ecological footprint in BRICS-T region? Exploring the influence of renewable energy, non-renewable energy, agriculture, forest area and financial development. Renew Energy 179:12–28

Usman M, Balsalobre-Lorente D, Jahanger A, Ahmad P (2022b) Pollution concern during globalization mode in financially resource-rich countries: Do financial development, natural resources, and renewable energy consumption matter? Rene. Energy 183:90–102

Usman M, Jahanger A, Makhdum MSA, Balsalobre-Lorente D, Bashir A (2022a) How do financial development, energy consumption, natural resources, and globalization affect Arctic countries’ economic growth and environmental quality? An advanced panel data simulation. Energy 241:122515

Usman M, Khalid K, Mehdi MA (2021) What determines environmental deficit in Asia? Embossing the role of renewable and non-renewable energy utilization. Renew Energy 168:1165–1176

Urban MC (2015) Accelerating extinction risk from climate change. Science 348(6234):571–573

Vale MM, Arias PA, Ortega G, Cardoso M, Oliveira BF, Loyola R, Scarano FR (2021) Climate change and biodiversity in the Atlantic Forest: best climatic models, predicted changes and impacts, and adaptation options The Atlantic Forest (pp. 253–267): Springer

Vedwan N, Rhoades RE (2001) Climate change in the Western Himalayas of India: a study of local perception and response. Climate Res 19(2):109–117

Vega CR, Andrade FH, Sadras VO, Uhart SA, Valentinuz OR (2001) Seed number as a function of growth. A comparative study in soybean, sunflower, and maize. Crop Sci 41(3):748–754

Vergés A, Doropoulos C, Malcolm HA, Skye M, Garcia-Pizá M, Marzinelli EM, Vila-Concejo A (2016) Long-term empirical evidence of ocean warming leading to tropicalization of fish communities, increased herbivory, and loss of kelp. Proc Natl Acad Sci 113(48):13791–13796

Verheyen R (2005) Climate change damage and international law: prevention duties and state responsibility (Vol. 54): Martinus Nijhoff Publishers

Waheed A, Fischer TB, Khan MI (2021) Climate Change Policy Coherence across Policies, Plans, and Strategies in Pakistan—implications for the China-Pakistan Economic Corridor Plan. Environ Manage 67(5):793–810

Wasiq M, Ahmad M (2004) Sustaining forests: a development strategy: The World Bank

Watts N, Adger WN, Agnolucci P, Blackstock J, Byass P, Cai W, Cooper A (2015) Health and climate change: policy responses to protect public health. The Lancet 386(10006):1861–1914

Weed AS, Ayres MP, Hicke JA (2013) Consequences of climate change for biotic disturbances in North American forests. Ecol Monogr 83(4):441–470

Weisheimer A, Palmer T (2005) Changing frequency of occurrence of extreme seasonal temperatures under global warming. Geophys Res Lett 32(20)

Wernberg T, Bennett S, Babcock RC, De Bettignies T, Cure K, Depczynski M, Hovey RK (2016) Climate-driven regime shift of a temperate marine ecosystem. Science 353(6295):169–172

WHO (2018) WHO, 2018. Antimicrobial resistance

Wilkinson DM, Sherratt TN (2016) Why is the world green? The interactions of top–down and bottom–up processes in terrestrial vegetation ecology. Plant Ecolog Divers 9(2):127–140

Wiranata IJ, Simbolon K (2021) Increasing awareness capacity of disaster potential as a support to achieve sustainable development goal (sdg) 13 in lampung province. Jurnal Pir: Power in International Relations 5(2):129–146

Wiréhn L (2018) Nordic agriculture under climate change: a systematic review of challenges, opportunities and adaptation strategies for crop production. Land Use Policy 77:63–74

Wu D, Su Y, Xi H, Chen X, Xie B (2019) Urban and agriculturally influenced water contribute differently to the spread of antibiotic resistance genes in a mega-city river network. Water Res 158:11–21

Wu HX (2020) Losing Steam?—An industry origin analysis of China’s productivity slowdown Measuring Economic Growth and Productivity (pp. 137–167): Elsevier

Wu H, Qian H, Chen J, Huo C (2017) Assessment of agricultural drought vulnerability in the Guanzhong Plain. China Water Resources Management 31(5):1557–1574

Xie W, Huang J, Wang J, Cui Q, Robertson R, Chen K (2018) Climate change impacts on China’s agriculture: the responses from market and trade. China Econ Rev

Xu J, Sharma R, Fang J, Xu Y (2008) Critical linkages between land-use transition and human health in the Himalayan region. Environ Int 34(2):239–247

Yadav MK, Singh R, Singh K, Mall R, Patel C, Yadav S, Singh M (2015) Assessment of climate change impact on productivity of different cereal crops in Varanasi. India J Agrometeorol 17(2):179–184

Yang B, Usman M (2021) Do industrialization, economic growth and globalization processes influence the ecological footprint and healthcare expenditures? Fresh insights based on the STIRPAT model for countries with the highest healthcare expenditures. Sust Prod Cons 28:893–910

Yu Z, Razzaq A, Rehman A, Shah A, Jameel K, Mor RS (2021) Disruption in global supply chain and socio-economic shocks: a lesson from COVID-19 for sustainable production and consumption. Oper Manag Res 1–16

Zarnetske PL, Skelly DK, Urban MC (2012) Biotic multipliers of climate change. Science 336(6088):1516–1518

Zhang M, Liu N, Harper R, Li Q, Liu K, Wei X, Liu S (2017) A global review on hydrological responses to forest change across multiple spatial scales: importance of scale, climate, forest type and hydrological regime. J Hydrol 546:44–59

Zhao J, Sinha A, Inuwa N, Wang Y, Murshed M, Abbasi KR (2022) Does Structural Transformation in Economy Impact Inequality in Renewable Energy Productivity? Implications for Sustainable Development. Renew Energy 189:853–864. https://doi.org/10.1016/j.renene.2022.03.050

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Abbass, K., Qasim, M.Z., Song, H. et al. A review of the global climate change impacts, adaptation, and sustainable mitigation measures. Environ Sci Pollut Res 29 , 42539–42559 (2022). https://doi.org/10.1007/s11356-022-19718-6

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Climate change widespread, rapid, and intensifying – ipcc.

GENEVA, Aug 9 – Scientists are observing changes in the Earth’s climate in every region and across the whole climate system, according to the latest Intergovernmental Panel on Climate Change (IPCC) Report, released today. Many of the changes observed in the climate are unprecedented in thousands, if not hundreds of thousands of years, and some of the changes already set in motion—such as continued sea level rise—are irreversible over hundreds to thousands of years.

However, strong and sustained reductions in emissions of carbon dioxide (CO 2 ) and other greenhouse gases would limit climate change. While benefits for air quality would come quickly, it could take 20-30 years to see global temperatures stabilize, according to the IPCC Working Group I report, Climate Change 2021: the Physical Science Basis , approved on Friday by 195 member governments of the IPCC, through a virtual approval session that was held over two weeks starting on July 26.

The Working Group I report is the first instalment of the IPCC’s Sixth Assessment Report (AR6), which will be completed in 2022.

“This report reflects extraordinary efforts under exceptional circumstances,” said Hoesung Lee, Chair of the IPCC. “The innovations in this report, and advances in climate science that it reflects, provide an invaluable input into climate negotiations and decision-making.”

Faster warming

The report provides new estimates of the chances of crossing the global warming level of 1.5°C in the next decades, and finds that unless there are immediate, rapid and large-scale reductions in greenhouse gas emissions, limiting warming to close to 1.5°C or even 2°C will be beyond reach.

The report shows that emissions of greenhouse gases from human activities are responsible for approximately 1.1°C of warming since 1850-1900, and finds that averaged over the next 20 years, global temperature is expected to reach or exceed 1.5°C of warming. This assessment is based on improved observational datasets to assess historical warming, as well progress in scientific understanding of the response of the climate system to human-caused greenhouse gas emissions.

“This report is a reality check,” said IPCC Working Group I Co-Chair Valérie Masson-Delmotte. “We now have a much clearer picture of the past, present and future climate, which is essential for understanding where we are headed, what can be done, and how we can prepare.”

Every region facing increasing changes

Many characteristics of climate change directly depend on the level of global warming, but what people experience is often very different to the global average. For example, warming over land is larger than the global average, and it is more than twice as high in the Arctic.

“Climate change is already affecting every region on Earth, in multiple ways. The changes we experience will increase with additional warming,” said IPCC Working Group I Co-Chair Panmao Zhai.

The report projects that in the coming decades climate changes will increase in all regions. For 1.5°C of global warming, there will be increasing heat waves, longer warm seasons and shorter cold seasons. At 2°C of global warming, heat extremes would more often reach critical tolerance thresholds for agriculture and health, the report shows.

But it is not just about temperature. Climate change is bringing multiple different changes in different regions – which will all increase with further warming. These include changes to wetness and dryness, to winds, snow and ice, coastal areas and oceans. For example:

• Climate change is intensifying the water cycle. This brings more intense rainfall and associated flooding, as well as more intense drought in many regions.
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• Coastal areas will see continued sea level rise throughout the 21st century, contributing to more frequent and severe coastal flooding in low-lying areas and coastal erosion. Extreme sea level events that previously occurred once in 100 years could happen every year by the end of this century.
• Further warming will amplify permafrost thawing, and the loss of seasonal snow cover, melting of glaciers and ice sheets, and loss of summer Arctic sea ice.
• Changes to the ocean, including warming, more frequent marine heatwaves, ocean acidification, and reduced oxygen levels have been clearly linked to human influence. These changes affect both ocean ecosystems and the people that rely on them, and they will continue throughout at least the rest of this century.
• For cities, some aspects of climate change may be amplified, including heat (since urban areas are usually warmer than their surroundings), flooding from heavy precipitation events and sea level rise in coastal cities.

For the first time, the Sixth Assessment Report provides a more detailed regional assessment of climate change, including a focus on useful information that can inform risk assessment, adaptation, and other decision-making, and a new framework that helps translate physical changes in the climate – heat, cold, rain, drought, snow, wind, coastal flooding and more – into what they mean for society and ecosystems.

This regional information can be explored in detail in the newly developed Interactive Atlas interactive-atlas.ipcc.ch as well as regional fact sheets, the technical summary, and underlying report.

Human influence on the past and future climate

“It has been clear for decades that the Earth’s climate is changing, and the role of human influence on the climate system is undisputed,” said Masson-Delmotte. Yet the new report also reflects major advances in the science of attribution – understanding the role of climate change in intensifying specific weather and climate events such as extreme heat waves and heavy rainfall events.

The report also shows that human actions still have the potential to determine the future course of climate. The evidence is clear that carbon dioxide (CO 2 ) is the main driver of climate change, even as other greenhouse gases and air pollutants also affect the climate.

“Stabilizing the climate will require strong, rapid, and sustained reductions in greenhouse gas emissions, and reaching net zero CO 2 emissions. Limiting other greenhouse gases and air pollutants, especially methane, could have benefits both for health and the climate,” said Zhai.

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Katherine Leitzell [email protected]

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Notes for Editors

Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change

The Working Group I report addresses the most updated physical understanding of the climate system and climate change, bringing together the latest advances in climate science, and combining multiple lines of evidence from paleoclimate, observations, process understanding, global and regional climate simulations. It shows how and why climate has changed to date, and the improved understanding of human influence on a wider range of climate characteristics, including extreme events. There will be a greater focus on regional information that can be used for climate risk assessments.

The Summary for Policymakers of the Working Group I contribution to the Sixth Assessment Report (AR6) as well as additional materials and information are available at https://www.ipcc.ch/report/ar6/wg1/

Note : Originally scheduled for release in April 2021, the report was delayed for several months by the COVID-19 pandemic, as work in the scientific community including the IPCC shifted online. This is first time that the IPCC has conducted a virtual approval session for one of its reports.

AR6 Working Group I in numbers

234 authors from 66 countries

• 31 – coordinating authors
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• 517 – contributing authors

Over 14,000 cited references

A total of 78,007 expert and government review comments

(First Order Draft 23,462; Second Order Draft 51,387; Final Government Distribution: 3,158)

More information about the Sixth Assessment Report can be found here .

About the IPCC

The Intergovernmental Panel on Climate Change (IPCC) is the UN body for assessing the science related to climate change. It was established by the United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO) in 1988 to provide political leaders with periodic scientific assessments concerning climate change, its implications and risks, as well as to put forward adaptation and mitigation strategies. In the same year the UN General Assembly endorsed the action by the WMO and UNEP in jointly establishing the IPCC. It has 195 member states.

Thousands of people from all over the world contribute to the work of the IPCC. For the assessment reports, IPCC scientists volunteer their time to assess the thousands of scientific papers published each year to provide a comprehensive summary of what is known about the drivers of climate change, its impacts and future risks, and how adaptation and mitigation can reduce those risks.

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At its 41st Session in February 2015, the IPCC decided to produce a Sixth Assessment Report (AR6). At its 42nd Session in October 2015 it elected a new Bureau that would oversee the work on this report and the Special Reports to be produced in the assessment cycle.

Global Warming of 1.5°C , an IPCC special report on the impacts of global warming of 1.5 degrees Celsius above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty was launched in October 2018.

Climate Change and Land , an IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems was launched in August 2019, and the Special Report on the Ocean and Cryosphere in a Changing Climate was released in September 2019.

In May 2019 the IPCC released the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories , an update to the methodology used by governments to estimate their greenhouse gas emissions and removals.

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Article Contents

Background information and structure of paper, climate sensitivity (ecs and ess), climate response time, cenozoic era, perspective on policy implications, acknowledgements, supplementary data, conflict of interest, data availability, authors’ contributions.

• < Previous

Global warming in the pipeline

• Article contents
• Figures & tables
• Supplementary Data

James E Hansen, Makiko Sato, Leon Simons, Larissa S Nazarenko, Isabelle Sangha, Pushker Kharecha, James C Zachos, Karina von Schuckmann, Norman G Loeb, Matthew B Osman, Qinjian Jin, George Tselioudis, Eunbi Jeong, Andrew Lacis, Reto Ruedy, Gary Russell, Junji Cao, Jing Li, Global warming in the pipeline, Oxford Open Climate Change , Volume 3, Issue 1, 2023, kgad008, https://doi.org/10.1093/oxfclm/kgad008

• Permissions Icon Permissions

Improved knowledge of glacial-to-interglacial global temperature change yields Charney (fast-feedback) equilibrium climate sensitivity 1.2 ± 0.3°C (2σ) per W/m 2 , which is 4.8°C ± 1.2°C for doubled CO 2 . Consistent analysis of temperature over the full Cenozoic era—including ‘slow’ feedbacks by ice sheets and trace gases—supports this sensitivity and implies that CO 2 was 300–350 ppm in the Pliocene and about 450 ppm at transition to a nearly ice-free planet, exposing unrealistic lethargy of ice sheet models. Equilibrium global warming for today’s GHG amount is 10°C, which is reduced to 8°C by today’s human-made aerosols. Equilibrium warming is not ‘committed’ warming; rapid phaseout of GHG emissions would prevent most equilibrium warming from occurring. However, decline of aerosol emissions since 2010 should increase the 1970–2010 global warming rate of 0.18°C per decade to a post-2010 rate of at least 0.27°C per decade. Thus, under the present geopolitical approach to GHG emissions, global warming will exceed 1.5°C in the 2020s and 2°C before 2050. Impacts on people and nature will accelerate as global warming increases hydrologic (weather) extremes. The enormity of consequences demands a return to Holocene-level global temperature. Required actions include: (1) a global increasing price on GHG emissions accompanied by development of abundant, affordable, dispatchable clean energy, (2) East-West cooperation in a way that accommodates developing world needs, and (3) intervention with Earth’s radiation imbalance to phase down today’s massive human-made ‘geo-transformation’ of Earth’s climate. Current political crises present an opportunity for reset, especially if young people can grasp their situation.

It has been known since the 1800s that infrared-absorbing (greenhouse) gases (GHGs) warm Earth’s surface and that the abundance of GHGs changes naturally as well as from human actions [ 1 , 2 ]. 1 Roger Revelle wrote in 1965 that we are conducting a ‘vast geophysical experiment’ by burning fossil fuels that accumulated in Earth’s crust over hundreds of millions of years [ 3 ] Carbon dioxide (CO 2 ) in the air is now increasing and already has reached levels that have not existed for millions of years, with consequences that have yet to be determined. Jule Charney led a study in 1979 by the United States National Academy of Sciences that concluded that doubling of atmospheric CO 2 was likely to cause global warming of 3 ± 1.5°C [ 4 ]. Charney added: ‘However, we believe it is quite possible that the capacity of the intermediate waters of the ocean to absorb heat could delay the estimated warming by several decades.’

After U.S. President Jimmy Carter signed the 1980 Energy Security Act, which included a focus on unconventional fossil fuels such as coal gasification and rock fracturing (‘fracking’) to extract shale oil and tight gas, the U.S. Congress asked the National Academy of Sciences again to assess potential climate effects. Their massive Changing Climate report had a measured tone on energy policy—amounting to a call for research [ 5 ]. Was not enough known to caution lawmakers against taxpayer subsidy of the most carbon-intensive fossil fuels? Perhaps the equanimity was due in part to a major error: the report assumed that the delay of global warming caused by the ocean’s thermal inertia is 15 years, independent of climate sensitivity. With that assumption, they concluded that climate sensitivity for 2 × CO 2 is near or below the low end of Charney’s 1.5–4.5°C range. If climate sensitivity was low and the lag between emissions and climate response was only 15 years, climate change would not be nearly the threat that it is.

Simultaneous with preparation of Changing Climate , climate sensitivity was addressed at the 1982 Ewing Symposium at the Lamont Doherty Geophysical Observatory of Columbia University on 25–27 October, with papers published in January 1984 as a monograph of the American Geophysical Union [ 6 ]. Paleoclimate data and global climate modeling together led to an inference that climate sensitivity is in the range 2.5–5°C for 2 × CO 2 and that climate response time to a forcing is of the order of a century, not 15 years [ 7 ]. Thus, the concept that a large amount of additional human-made warming is already ‘in the pipeline’ was introduced. E.E. David, Jr, President of Exxon Research and Engineering, in his keynote talk at the symposium insightfully noted [ 8 ]: ‘The critical problem is that the environmental impacts of the CO 2 buildup may be so long delayed. A look at the theory of feedback systems shows that where there is such a long delay, the system breaks down, unless there is anticipation built into the loop.’

Thus, the danger caused by climate’s delayed response and the need for anticipatory action to alter the course of fossil fuel development was apparent to scientists and the fossil fuel industry 40 years ago. 2 Yet industry chose to long deny the need to change energy course [ 9 ], and now, while governments and financial interests connive, most industry adopts a ‘greenwash’ approach that threatens to lock in perilous consequences for humanity. Scientists will share responsibility if we allow governments to rely on goals for future global GHG levels, as if targets had meaning in the absence of policies required to achieve them.

The Intergovernmental Panel on Climate Change (IPCC) was established in 1988 to provide scientific assessments on the state of knowledge about climate change [ 10 ] and almost all nations agreed to the 1992 United Nations Framework Convention on Climate Change [ 11 ] with the objective to avert ‘dangerous anthropogenic interference with the climate system’. The current IPCC Working Group 1 report [ 12 ] provides a best estimate of 3°C for equilibrium global climate sensitivity to 2 × CO 2 and describes shutdown of the overturning ocean circulations and large sea level rise on the century time scale as ‘high impact, low probability’ even under extreme GHG growth scenarios. This contrasts with ‘high impact, high probability’ assessments reached in a paper [ 13 ]—hereafter abbreviated Ice Melt—that several of us published in 2016. Recently, our paper’s first author (JEH) described a long-time effort to understand the effect of ocean mixing and aerosols on observed and projected climate change, which led to a conclusion that most climate models are unrealistically insensitive to freshwater injected by melting ice and that ice sheet models are unrealistically lethargic in the face of rapid, large climate change [ 14 ].

Eelco Rohling, editor of Oxford Open Climate Change, invited a perspective article on these issues. Our principal motivation in this paper is concern that IPCC has underestimated climate sensitivity and understated the threat of large sea level rise and shutdown of ocean overturning circulations, but these issues, because of their complexity, must be addressed in two steps. Our present paper addresses climate sensitivity and warming in the pipeline, concluding that these exceed IPCC’s best estimates. Response of ocean circulation and ice sheet dynamics to global warming—already outlined in the Ice Melt paper—will be addressed further in a later paper.

The structure of our present paper is as follows. Climate sensitivity section makes a fresh evaluation of Charney’s equilibrium climate sensitivity (ECS) based on improved paleoclimate data and introduces Earth system sensitivity (ESS), which includes the feedbacks that Charney held fixed. Climate response time section explores the fast-feedback response time of Earth’s temperature and energy imbalance to an imposed forcing, concluding that cloud feedbacks buffer heat uptake by the ocean, thus increasing the delay in surface warming and making Earth’s energy imbalance an underestimate of the forcing reduction required to stabilize climate. Cenozoic era section analyzes temperature change of the past 66 million years and infers the Cenozoic history of CO 2 , thus providing insights about climate change. Aerosols section addresses the absence of aerosol forcing data via inferences from paleo data and modern global temperature change, and we point out potential information in ‘the great inadvertent aerosol experiment’ provided by recent restrictions on fuels in international shipping. Summary section discusses policy implications of high climate sensitivity and the delayed response of the climate system. Warming in the pipeline need not appear. We can take actions that slow and reverse global warming; indeed, we suggest that such actions are needed to avoid disastrous consequences for humanity and nature. Reduction of greenhouse gas emissions as rapidly as practical has highest priority, but that policy alone is now inadequate and must be complemented by additional actions to affect Earth’s energy balance. The world is still early in this ‘vast geophysical experiment’—as far as consequences are concerned—but time has run short for the ‘anticipation’ that E.E. David recommended.

This section gives a brief overview of the history of ECS estimates since the Charney report and uses glacial-to-interglacial climate change to infer an improved estimate of ECS. We discuss how ECS and the more general Earth system sensitivity (ESS) depend on the climate state.

Charney defined ECS as the eventual global temperature change caused by doubled CO 2 if ice sheets, vegetation and long-lived GHGs are fixed (except the specified CO 2 doubling). Other quantities affecting Earth’s energy balance—clouds, aerosols, water vapor, snow cover and sea ice—change rapidly in response to climate change. Thus, Charney’s ECS is also called the ‘fast-feedback’ climate sensitivity. Feedbacks interact in many ways, so their changes are calculated in global climate models (GCMs) that simulate such interactions. Charney implicitly assumed that change of the ice sheets on Greenland and Antarctica—which we categorize as a ‘slow feedback’—was not important on time scales of most public interest.

ECS defined by Charney is a gedanken concept that helps us study the effect of human-made and natural climate forcings. If knowledge of ECS were based only on models, it would be difficult to narrow the range of estimated climate sensitivity—or have confidence in any range—because we do not know how well feedbacks are modeled or if the models include all significant real-world feedbacks. Cloud and aerosol interactions are complex, e.g. and even small cloud changes can have a large effect. Thus, data on Earth’s paleoclimate history are essential, allowing us to compare different climate states, knowing that all feedbacks operated.

Climate sensitivity estimated at the 1982 Ewing Symposium

We evaluated contributions of individual feedback processes to g by inserting changes of water vapor, clouds, and surface albedo (reflectivity, literally whiteness, due to sea ice and snow changes) from the 2 × CO 2 GCM simulation one-by-one into a one-dimensional radiative-convective model [ 16 ], finding g wv = 0.4, g cl = 0.2, g sa = 0.1, where g wv , g cl , and g sa are the water vapor, cloud and surface albedo gains. The 0.2 cloud gain was about equally from a small increase in cloud top height and a small decrease in cloud cover. These feedbacks all seemed reasonable, but how could we verify their magnitudes or the net ECS due to all feedbacks?

We recognized the potential of emerging paleoclimate data. Early data from polar ice cores revealed that atmospheric CO 2 was much less during glacial periods and the CLIMAP project [ 17 ] used proxy data to reconstruct global surface conditions during the Last Glacial Maximum (LGM), which peaked about 20 000 years ago. A powerful constraint was the fact that Earth had to be in energy balance averaged over the several millennia of the LGM. However, when we employed CLIMAP boundary conditions including sea surface temperatures (SSTs), Earth was out of energy balance, radiating 2.1 W/m 2 to space, i.e. Earth was trying to cool off with an enormous energy imbalance, equivalent to half of 2 × CO 2 forcing.

Something was wrong with either assumed LGM conditions or our climate model. We tried CLIMAP’s maximal land ice—this only reduced the energy imbalance from 2.1 to 1.6 W/m 2 . Moreover, we had taken LGM CO 2 as 200 ppm and did not know that CH 4 and N 2 O were less in the LGM than in the present interglacial period; accurate GHGs and CLIMAP SSTs produce a planetary energy imbalance close to 3 W/m 2 . Most feedbacks in our model were set by CLIMAP. Sea ice is set by CLIMAP. Water vapor depends on surface temperature, which is set by CLIMAP SSTs. Cloud feedback is uncertain, but ECS smaller than 2.4°C for 2 × CO 2 would require a negative cloud gain. g cl ∼ 0.2 from our GCM increases ECS from 2.4°C to 4°C ( Equation 1 ) and accounts for almost the entire difference of sensitivities of our model (4°C for 2 × CO 2 ) and the Manabe and Stouffer model [ 18 ] (2°C for 2 × CO 2 ) that had fixed cloud cover and cloud height. Manabe suggested [ 19 ] that our higher ECS was due to a too-large sea ice and snow feedback, but we noted [ 7 ] that sea ice in our control run was less than observed, so we likely understated sea ice feedback. Amplifying feedback due to high clouds increasing in height with warming is expected and is found in observations, large-eddy simulations and GCMs [ 20 ] Sherwood et al . [ 21 ] conclude that negative low-cloud feedback is ‘neither credibly suggested by any model, nor by physical principles, nor by observations.’ Despite a wide spread among models, GCMs today show an amplifying cloud feedback due to increases in cloud height and decreases in cloud amount, despite increases in cloud albedo [ 22 ]. These cloud changes are found in all observed cloud regimes and locations, implying robust thermodynamic control [ 23 ].

CLIMAP SSTs were a more likely cause of the planetary energy imbalance. Co-author D. Peteet used pollen data to infer LGM tropical and subtropical cooling 2–3°C greater than in a GCM forced by CLIMAP SSTs. D. Rind and Peteet found that montane LGM snowlines in the tropics descended 1 km in the LGM, inconsistent with climate constrained by CLIMAP SSTs. CLIMAP assumed that tiny shelled marine species migrate to stay in a temperature zone they inhabit today. But what if, instead, these species partly adapt over millennia to changing temperature? Based on the work of Rind and Peteet, later published [ 24 ], we suspected but could not prove that CLIMAP SSTs were too warm.

Based on GCM simulations for 2 × CO 2 , on our feedback analysis for the LGM, and on observed global warming in the past century, we concluded that ECS was in the range 2.5–5°C for 2 × CO 2 . If CLIMAP SSTs were accurate, ECS was near the low end of that range. In contrast, our analysis implied that ECS for 2 × CO 2 was in the upper half of the 2.5–5°C range, but our analysis depended in part on our GCM, which had sensitivity 4°C for 2 × CO 2 . To resolve the matter, a paleo thermometer independent of biologic adaptation was needed. Several decades later, such a paleo thermometer and advanced analysis techniques exist. We will use recent studies to infer our present best estimates for ECS and ESS. First, however, we will comment on other estimates of climate sensitivity and clarify the definition of climate forcings that we employ.

IPCC and independent climate sensitivity estimates

Reviews of climate sensitivity are available, e.g. Rohling et al . [ 25 ], which focuses on the physics of the climate system, and Sherwood et al . [ 26 ], which adds emphasis on probabilistic combination of multiple uncertainties. Progress in narrowing the uncertainty in climate sensitivity was slow in the first five IPCC assessment reports. The fifth assessment report [ 26 ] (AR5) in 2014 concluded only—with 66% probability—that ECS was in the range 1.5–4.5°C, the same as Charney’s report 35 years earlier. The broad spectrum of information on climate change—especially constraints imposed by paleoclimate data—at last affected AR6 [ 12 ], which concluded with 66% probability that ECS is 2.5–4°C, with 3°C as their best estimate ( Supplementary Fig. TS.6 ).

Sherwood et al . [ 21 ] combine three lines of evidence: climate feedback studies, historical climate change, and paleoclimate data, inferring S = 2.6–3.9°C with 66% probability for 2 × CO 2 , where S is an ‘effective sensitivity’ relevant to a 150-year time scale. They find ECS only slightly larger: 2.6–4.1°C with 66% probability. Climate feedback studies, inherently, cannot yield a sharp definition of ECS, as we showed in the cloud feedback discussion above. Earth’s climate system includes amplifying feedbacks that push the gain, g, closer to unity than zero, thus making ECS sensitive to uncertainty in any feedback; the resulting sensitivity of ECS to g prohibits precise evaluation from feedback analysis. Similarly, historical climate change cannot define ECS well because the aerosol climate forcing is unmeasured. Also, forced and unforced ocean dynamics give rise to a pattern effect: [ 27 ] the geographic pattern of transient and equilibrium temperature changes differ, which affects ECS inferred from transient climate change. These difficulties help explain how Sherwood et al . [ 21 ] could estimate ECS as only 6% larger than S , an implausible result in view of the ocean’s great thermal inertia. An intercomparison of GCMs run for millennial time scales, LongRunMIP [ 28 ], includes 14 simulations of 9 GCMs with runs of 5000 years (or close enough for extrapolation to 5000 years). Their global warmings at 5000 years range from 30% to 80% larger than their 150-year responses.

Our approach is to compare glacial and interglacial equilibrium climate states. The change of atmospheric and surface forcings can be defined accurately, thus leading to a sharp evaluation of ECS for cases in which equilibrium response is assured. With this knowledge in hand, additional information can be extracted from historical and paleo climate changes.

Climate forcing definitions

Attention to climate forcing definitions is essential for quantitative analysis of climate change. However, readers uninterested in radiative forcings may skip this section with little penalty. We describe our climate forcing definition and compare our forcings with those of IPCC. Our total GHG forcing matches that of IPCC within a few percent, but this close fit hides larger differences in individual forcings that deserve attention.

A further refinement of climate forcing is suggested in Efficacy : effective forcing (F e ) defined by a long GCM run with calculated ocean temperature. The resulting global surface temperature change, relative to that for equal CO 2 forcing, defines the forcing’s efficacy. Effective forcings, F e , were found to be within a few percent of F s for most forcing agents, i.e. the results confirm that F s is a robust forcing. This support is for F s , not for F o = ERF, which is systematically smaller than F s . The Goddard Institute for Space Studies (GISS) GCM [ 32 , 33 ] used for CMIP6 [ 34 ] studies, which we label the GISS (2020) model, 3 has higher resolution (2° × 2.5° and 40 atmospheric layers) and other changes that yield a moister upper troposphere and lower stratosphere, relative to the GISS model used in Efficacy . GHG forcings reported for the GISS (2020) model [ 32 , 33 ] are smaller than in prior GISS models, a change attributed [ 33 ] to blanketing by high level water vapor. However, part of the change is from comparison of F o in GISS (2020) to F S in earlier models. The 2 × CO 2 fixed SST simulation with the GISS (2020) model yields F o = 3.59 W/m 2 , δTo = 0.27°C and λ = 0.9°C per W/m 2 . Thus F S = 3.59 + 0.30 = 3.89 W/m 2 , which is only 5.4% smaller than the F S = 4.11 W/m 2 for the GISS model used in Efficacy .

Greenhouse gas radiative forcings

c, CO 2 (ppm); m, CH 4 (ppb); n, N 2 O (ppb); x/y, CFC-11/12 (ppb).

The CH 4 coefficient (1.45) includes the effect of CH 4 on O 3 and stratospheric H 2 O, as well as the efficacy (1.10) of CH 4 per se . We assume that CH 4 is responsible for 45% of the O 3 change [ 37 ]. Forcing caused by the remaining 55% of the O 3 change is based on IPCC AR6 O 3 forcing (Fa = 0.47 W/m 2 in 2019); we multiply this AR6 O 3 forcing by 0.55 × 0.82 = 0.45, where 0.82 is the efficacy of O 3 forcing from Table 1 of Efficacy . Thus, the non-CH 4 portion of the O 3 forcing is 0.21 W/m 2 in 2019. MPTGs and OTGs are Montreal Protocol Trace Gases and Other Trace Gases [ 38 ]. A list of these gases and a table of annual forcings since 1992 are available as well as the earlier data [ 39 ].

The climate forcing from our formulae is slightly larger than IPCC AR6 forcings ( Fig. 1 ). In 2019, the final year of AR6 data, our GHG forcing is 4.00 W/m 2 ; the AR6 forcing is 3.84 W/m 2 . Our forcing should be larger, because IPCC forcings are F o for all gases except O 3 , for which they provide F a (AR6 section 7.3.2.5). Table 1 in Efficacy allows accurate comparison: δT o for 2 × CO 2 for the GISS model used in Efficacy is 0.22°C, λ is 0.67°C per W/m 2 , so δT o /λ = 0.33 W/m 2 . Thus, the conversion factor from F o to F e (or F s ) is 4.11/(4.11−0.33). The non-O 3 portion of AR6 2019 forcing (3.84−0.47 = 3.37) W/m 2 increases to 3.664 W/m 2 . The O 3 portion of the AR6 2019 forcing (0.47 W/m 2 ) decreases to 0.385 W/m 2 because the efficacy of F a (O 3 ) is 0.82. The AR6 GHG forcing in 2019 is thus ∼4.05 W/m 2 , expressed as Fe ∼ Fs, which is ∼1% larger than follows from our formulae. This precise agreement is not indicative of the true uncertainty in the GHG forcing, which IPCC AR6 estimates as 10%, thus about 0.4 W/m 2 . We concur with their error estimate and employ it in our ECS uncertainty analysis (Equilibrium climate sensitivity section).

IPCC AR6 Annex III greenhouse gas forcing [ 12 ], which employs F a for O 3 and F o for other GHGs, compared with the effective forcing, F e , from Equation (4) . See discussion in text.

We conclude that the GHG increase since 1750 already produces a climate forcing equivalent to that of 2 × CO 2 (our formulae yield F e ∼ F s = 4.08 W/m 2 for 2021 and 4.13 W/m 2 for 2022; IPCC AR6 has F s = 4.14 W/m 2 for 2021). The human-made 2 × CO 2 climate forcing imagined by Charney, Tyndall and other greenhouse giants is no longer imaginary. Humanity is now taking its first steps into the period of consequences. Earth’s paleoclimate history helps us assess the potential outcomes.

Glacial-to-interglacial climate oscillations

In this section we describe how ice core data help us assess ECS for climate states from glacial conditions to interglacial periods such as the Holocene, the interglacial period of the past 12 000 years. We discuss climate sensitivity in warmer climates in Cenozoic era section.

Air bubbles in Antarctic ice cores—trapped as snow piled up and compressed into ice—preserve a record of long-lived GHGs for at least 800 000 years. Isotopic composition of the ice provides a measure of temperature in and near Antarctica [ 40 ]. Changes of temperature and CO 2 are highly correlated ( Fig. 2 ). This does not mean that CO 2 is the primal cause of the climate oscillations. Hays et al . [ 42 ] showed that small changes of Earth’s orbit and the tilt of Earth’s spin axis are pacemakers of the ice ages. Orbital changes alter the seasonal and geographical distribution of insolation, which affects ice sheet size and GHG amount. Long-term climate is sensitive because ice sheets and GHGs act as amplifying feedbacks: [ 43 ] as Earth warms, ice sheets shrink, expose a darker surface, and absorb more sunlight; also, as Earth warms, the ocean and continents release GHGs to the air. These amplifying feedbacks work in the opposite sense as Earth cools. Orbital forcings oscillate slowly over tens and hundreds of thousands of years [ 44 ]. The picture of how Earth orbital changes drive millennial climate change was painted in the 1920s by Milutin Milankovitch, who built on 19th century hypotheses of James Croll and Joseph Adhémar. Paleoclimate changes of ice sheets and GHGs are sometimes described as slow feedbacks [ 45 ], but their slow change is paced by the Earth orbital forcing; their slow change does not mean that these feedbacks cannot operate more rapidly in response to a rapid climate forcing.

Antarctic Dome C temperature for past 800 ky from Jouzel et al . [ 40 ] relative to the mean of the last 10 ky and Dome C CO 2 amount from Luthi et al . [ 41 ] (kyBP is kiloyears before present).

We evaluate ECS by comparing stable climate states before and after a glacial-to-interglacial climate transition. GHG amounts are known from ice cores and ice sheet sizes are known from geologic data. This empirical ECS applies to the range of global temperature covered by ice cores, which we will conclude is about –7°C to + 1°C relative to the Holocene. The Holocene is an unusual interglacial. Maximum melt rate was at 13.2 kyBP, as expected [ 45 ] and GHG amounts began to decline after peaking early in the Holocene, as in most interglacials. However, several ky later, CO 2 and CH 4 increased, raising a question of whether humans were affecting GHGs. Ruddiman [ 46 ] suggests that deforestation began to affect CO 2 6500 years ago and rice irrigation began to affect CH 4 5000 years ago. Those possibilities complicate use of LGM-Holocene warming to estimate ECS. However, sea level, and thus the size of the ice sheets, had stabilized by 7000 years ago (Evidence of aerosol forcing in the Holocene section). Thus, the millennium centered on 7 kyBP provides a good period to compare with the LGM. Comparison of the Eemian interglacial ( Fig. 2 ) with the prior glacial maximum (PGM) has potential for independent assessment.

LGM-Holocene and PGM-Eemian evaluation of ECS

In this section we evaluate ECS by comparing neighboring glacial and interglacial periods when Earth was in energy balance within less than 0.1 W/m 2 averaged over a millennium. Larger imbalance would cause temperature or sea level change that did not occur [ 48 ]. 4 Thus, we can assess ECS from knowledge of atmospheric and surface forcings that maintained these climates.

Recent advanced analysis techniques allow improved estimate of paleo temperatures. Tierney et al . [ 49 ] exclude microbiology fossils whose potential to adapt makes them dubious thermometers. Instead, they use a large collection of geochemical (isotope) proxies for SST in an analysis constrained by climate change patterns defined by GCMs. They find cooling of 6.1°C (95% confidence: 5.7–6.5°C) for the interval 23–19 kyBP. A similarly constrained global analysis by Osman et al . [ 50 ] finds LGM cooling at 21–18 kyBP of 7.0 ± 1°C (95% confidence). Tierney (priv. comm.) attributes the difference between the two studies to the broader time interval of the former study, and concludes that peak LGM cooling was near 7°C.

Seltzer et al . [ 51 ] use the temperature-dependent solubility of dissolved noble gases in ancient groundwater to show that land areas between 45°S and 35°N cooled 5.8 ± 0.6°C in the LGM. This cooling is consistent with 1 km lowering of alpine snowlines found by Rind and Peteet [ 24 ]. Land response to a forcing exceeds ocean response, but polar amplification makes the global response as large as the low latitude land response in GCM simulations with fixed ice sheets ( Supplementary Material Fig. S3 ). When ice sheet growth is added, cooling amplification at mid and high latitudes is greater [ 7 ], making 5.8°C cooling of low latitude land consistent with global cooling of ∼7°C.

LGM CO 2 , CH 4 and N 2 O amounts are known accurately with the exception of N 2 O in the PGM when N 2 O reactions with dust in the ice core corrupt the data. We take PGM N 2 O as the mean of the smallest reported PGM amount and the LGM amount; potential error in the N 2 O forcing is ∼0.01 W/m 2 . We calculate CO 2 , CH 4 , and N 2 O forcings using Equation (4) and formulae for each gas in Supplementary Material for the periods shown by green bars in Fig. 3 . The Eemian period avoids early CO 2 and temperature spikes, assuring that Earth was in energy balance. Between the LGM (19–21 kyBP) and Holocene (6.5–7.5 kyBP), GHG forcing increased 2.25 W/m 2 with 77% from CO 2 . Between the PGM and Eemian, GHG forcing increased 2.30 W/m 2 with 79% from CO 2 .

Dome C temperature (Jouzel et al . [ 40 ]) and multi-ice core GHG amounts (Schilt et al . [ 47 ]). Green bars (1–5, 6.5–7.5, 18–21, 120–126, 137–144 kyBP) are periods of calculations.

Glacial-interglacial aerosol changes are not included as a forcing. Natural aerosol changes, like clouds, are fast feedbacks. Indeed, aerosols and clouds form a continuum and distinction is arbitrary as humidity approaches 100%. There are many aerosol types, including VOCs (volatile organic compounds) produced by trees, sea salt produced by wind and waves, black and organic carbon produced by forest and grass fires, dust produced by wind and drought, and marine biologic dimethyl sulfide and its secondary aerosol products, all varying geographically and in response to climate change. We do not know, or need to know, natural aerosol properties in prior eras because their changes are feedbacks included in the climate response. However, human-made aerosols are a climate forcing (an imposed perturbation of Earth’s energy balance). Humans may have begun to affect gases and aerosols in the latter Holocene (Aerosols section), but we minimize that issue by using the 6.5–7.5 kyBP window to evaluate climate sensitivity.

Earth’s surface change is the other forcing needed to evaluate ECS: (1) change of surface albedo (reflectivity) and topography by ice sheets, (2) vegetation change, e.g. boreal forests replaced by brighter tundra, and (3) continental shelves exposed by lower sea level. Forcing by all three can be evaluated at once with a GCM. Accuracy requires realistic clouds, which shield the surface. Clouds are the most uncertain feedback [ 52 ]. Evaluation is ideal for CMIP [ 53 ] (Coupled Model Intercomparison Project) collaboration with PMIP [ 54 ] (Paleoclimate Modelling Intercomparison Project); a study of LGM surface forcing could aid GCM development and assessment of climate sensitivity. Sherwood et al . [ 21 ] review studies of LGM ice sheet forcing and settle on 3.2 ± 0.7 W/m 2 , the same as IPCC AR4 [ 55 ]. However, some GCMs yield efficacies as low as ∼0.75 [ 56 ] or even ∼0.5 [ 57 ], likely due to cloud shielding. We found [ 7 ] a forcing of −0.9 W/m 2 for LGM vegetation by using the Koppen [ 58 ] scheme to relate vegetation to local climate, but we thought the model effect was exaggerated as real-world forests tends to shake off snow albedo effects. Kohler et al . [ 59 ] estimate a continental shelf forcing of −0.67 W/m 2 . Based on an earlier study [ 60 ] (hereafter Target CO 2 ), our estimate of LGM-Holocene surface forcing is 3.5 ± 1 W/m 2 . Thus, LGM (18–21 kyBP) cooling of 7°C relative to mid-Holocene (7 kyBP), GHG forcing of 2.25 W/m 2 , and surface forcing of 3.5 W/m 2 yield an initial ECS estimate 7/(2.25 + 3.5) = 1.22°C per W/m 2 . We discuss uncertainties in Equilibrium climate sensitivity section.

PGM-Eemian global warming provides a second assessment of ECS, one that avoids concern about human influence. PGM-Eemian GHG forcing is 2.3 W/m 2 . We estimate surface albedo forcing as 0.3 W/m 2 less than in the LGM because sea level was about 10 m higher during the PGM [ 61 ]. North American and Eurasian ice sheet sizes differed between the LGM and PGM [ 62 ], but division of mass between them has little effect on the net forcing ( Supplementary Fig. S4 [ 60 ]). Thus, our central estimate of PGM-Eemian forcing is 5.5 W/m 2 . Eemian temperature reached about +1°C warmer than the Holocene [ 63 ], based on Eemian SSTs of +0.5 ± 0.3°C relative to 1870–1889 [ 64 ], or +0.65 ± 0.3°C SST and +1°C global (land plus ocean) relative to 1880–1920. However, the PGM was probably warmer than the LGM; it was warmer at Dome C ( Fig. 2 ), but cooler at Dronning Maud Land [ 65 ]. Based on deep ocean temperatures (Cenozoic Era section), we estimate PGM-Eemian warming as 0.5°C greater than LGM-Holocene warming, that is 7.5°C. The resulting ECS is 7.5/5.5 = 1.36°C per W/m 2 . Although PGM temperature lacks quantification comparable to that of Seltzer et al . [ 51 ] and Tierney et al . [ 49 ] for the LGM, the PGM-Eemian warming provides support for the high ECS inferred from LGM-Holocene warming.

We conclude that ECS for climate in the Holocene-LGM range is 1.2°C ± 0.3°C per W/m 2 , where the uncertainty is the 95% confidence range. The uncertainty estimate is inherently subjective, as it depends mainly on the ice age surface albedo forcing. The GHG forcing and glacial-interglacial temperature change are well-defined, but the efficacy of ice age surface forcing varies among GCMs. This variability is likely related to cloud shielding of surface albedo, which reaffirms the need for a focus on precise cloud observations and modeling.

State dependence of climate sensitivity

ECS based on glacial-interglacial climate is an average for global temperatures −7°C to +1°C relative to the Holocene and in general differs for other climate states because water vapor, aerosol-cloud and sea ice feedbacks depend on the initial climate. However, ECS is rather flat between today’s climate and warmer climate, based on a study [ 66 ] covering a range of 15 CO 2 doublings using an efficient GCM developed by Gary Russell [ 67 ]. Toward colder climate, ice-snow albedo feedback increases nonlinearly, reaching snowball Earth conditions—with snow and ice on land reaching sea level in the tropics—when CO 2 declines to a quarter to an eighth of its 1950 abundance ( Fig. 7 of the study) [ 66 ]. Snowball Earth occurred several times in Earth’s history, most recently about 600 million years ago [ 68 ] when the Sun was 6% dimmer [ 69 ] than today, a forcing of about –12 W/m 2 . Toward warmer climate, the water vapor feedback increases as the tropopause rises [ 70 ], the tropopause cold trap disappearing at 32 × CO 2 ( Fig. 7 ) [ 66 ]. However, for the range of ECS of practical interest—say from half preindustrial CO 2 to 4 × CO 2 —state dependence of ECS is small compared to state dependence of ESS.

Earth system sensitivity (ESS) includes amplifying feedbacks of GHGs and ice sheets [ 71 ]. When we consider CO 2 change as a known forcing, other GHGs provide a feedback that is smaller than the ice sheet feedback, but not negligible. Ice core data on GHG amounts show that non-CO 2 GHGs—including O 3 and stratospheric H 2 O produced by changing CH 4 —provide about 20% of the total GHG forcing, not only on average for the full glacial-interglacial change, but as a function of global temperature right up to +1°C global temperature relative to the Holocene ( Supplementary Fig. S5 ). Atmospheric chemistry modeling suggests that non-CO 2 GHG amplification of CO 2 forcing by about a quarter continues into warmer climate states [ 72 ]. Thus, for climate change in the Cenozoic era, we approximate non-CO 2 GHG forcing by increasing the CO 2 forcing by one-quarter.

Ice sheet feedback, in contrast to non-CO 2 GHG feedback, is highly nonlinear. Preindustrial climate was at most a few halvings of CO 2 from runaway snowball Earth and LGM climate was even closer to that climate state. The ice sheet feedback is reduced as Earth heads toward warmer climate today because already two-thirds of LGM ice has been lost. Yet remaining ice on Antarctica and Greenland constitutes a powerful feedback, which humanity is about to bring into play. We can illuminate that feedback and the climate path Earth is now on by examining data on the Cenozoic era—which includes CO 2 levels comparable to today’s amount—but first we must consider climate response time.

In this section we define response functions for global temperature and Earth’s energy imbalance that help reveal the physics of climate change. Cloud feedbacks amplify climate sensitivity and thus increase eventual heat uptake by the ocean, but cloud feedbacks also have the potential to buffer the rate at which the ocean takes up heat, thus increasing climate response time.

Climate response time was surprisingly long in our climate simulations [ 7 ] for the 1982 Ewing Symposium. The e-folding time—the time for surface temperature to reach 63% of its equilibrium response—was about a century. The only published atmosphere-ocean GCM—that of Bryan and Manabe [ 73 ]—had a response time of 25 years, while several simplified climate models referenced in our Ewing paper had even faster responses. The longer response time of our climate model was largely a result of high climate sensitivity—our model had an ECS of 4°C for 2 × CO 2 while the Bryan and Manabe model had an ECS of 2°C.

The physics is straightforward. If the delay were a result of a fixed source of thermal inertia, say the ocean’s well-mixed upper layer, response time would increase linearly with ECS because most climate feedbacks come into play in response to temperature change driven by the adjusted forcing, not in direct response to the forcing. Thus, a model with ECS of 4°C takes twice as long to reach full response as a model with ECS of 2°C, if the mixed layer provides the only heat capacity. However, while the mixed layer is warming, there is exchange of water with the deeper ocean, which slows the mixed layer warming. The longer response time with high ECS allows more of the ocean to come into play. If mixing into the deeper ocean is approximated as diffusive, surface temperature response time is proportional to the square of climate sensitivity [ 74 ].

Slow climate response accentuates need for the ‘anticipation’ that E.E. David, Jr spoke about. If ECS is 4.8°C (1.2°C per W/m 2 ), more warming is in the pipeline than widely assumed. GHG forcing today already exceeds 4 W/m 2 . Aerosols reduce the net forcing to about 3 W/m 2 , based on IPCC estimates (Aerosols section), but warming still in the pipeline for 3 W/m 2 forcing is 2.4°C, exceeding warming realized to date (1.2°C). Slow feedbacks increase the equilibrium response even further (Summary section). Large warmings can be avoided via a reasoned policy response, but definition of effective policies will be aided by an understanding of climate response time.

Temperature response function

T G is the Green’s function estimate of global temperature at time t, λ (°C per W/m 2 ) the model’s equilibrium sensitivity, R the dimensionless temperature response function (% of equilibrium response), and dF e the forcing change per unit time, dt. Integration over time begins when Earth is in near energy balance, e.g. in preindustrial time. The response function yields an accurate estimate of global temperature change for a forcing that does not cause reorganization of ocean circulation. Accuracy of this approximation for temperature for one climate model is shown in Chart 15 in the Bjerknes presentation and wider applicability has been demonstrated [ 76 ].

We study ocean mixing effects by comparing two GCMs: GISS (2014) [ 77 ] and GISS (2020) [ 33 ], both models 6 described by Kelley et al . [ 32 ].Ocean mixing is improved in GISS (2020) by use of a high-order advection scheme [ 78 ], finer upper-ocean vertical resolution (40 layers), updated mesoscale eddy parameterization, and correction of errors in the ocean modeling code [ 32 ]. The GISS (2020) model has improved variability, including the Madden-Julian Oscillation (MJO), El Nino Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO), but the spectrum of ENSO-like variability is unrealistic and its amplitude is excessive, as shown by the magnitude of oscillations in Fig. 4a . Ocean mixing in GISS (2020) may still be excessive in the North Atlantic, where the model’s simulated penetration of CFCs is greater than observed [ 79 ].

( a ) Global mean surface temperature response to instant CO 2 doubling and ( b ) normalized response function (percent of final change). Thick lines in Figs 4 and 5 are smoothed (yr1 no smoothing; yr2 3-yr mean; yr3–12 5-yr mean, yr13–300 25-yr mean; yr301–5000 101-yr mean).

Despite reduced ocean mixing, the GISS (2020) model surface temperature response is no faster than in the GISS (2014) model ( Fig. 4b ): it takes 100 years to reach within 1/e of the equilibrium response. Slow response is partly explained by the larger ECS of the GISS (2020) model, which is 3.5°C versus 2.7°C for the GISS (2014) model, but something more is going on in the newer model, as exposed by the response function of Earth’s energy imbalance.

Earth’s energy imbalance (EEI)

When a forcing perturbs Earth’s energy balance, the imbalance drives warming or cooling to restore balance. Observed EEI is now of order +1 W/m 2 (more energy coming in than going out) [ 80 ]. High accuracy of EEI is obtained by tracking ocean warming—the main repository for excess energy—and adding heat stored in warming continents and heat used in net ice melt [ 80 ]. Heat storage in air adds a small amount. Radiation balance measured from Earth-orbiting satellites cannot by itself define the absolute imbalance, but, when anchored to an in situ EEI value for a sufficient interval (e.g. 10 years), satellite Earth radiation budget observations [ 81 ] provide invaluable EEI data on finer temporal and spatial scales than the in situ data.

After a step-function forcing is imposed, EEI and global surface temperature must each approach a new equilibrium, but EEI does so more rapidly, especially for the GISS (2020) model ( Fig. 5 ). EEI in GISS (2020) needs only a decade to reach within 1/e of full response ( Fig. 5b ), but global surface temperature requires a century ( Fig. 4b ). Rapid decline of EEI—to half the forcing in 5 years ( Fig. 5a )—has practical implications. First, EEI defines the rate heat is pumped into the ocean, so if EEI is reduced, ocean warming is slowed. Second, rapid EEI decline implies that it is wrong to assume that global warming can be stopped by a reduction of climate forcing by the amount of EEI. Instead, the required reduction of forcing is larger than EEI. The difficulty in finding additional reduction in climate forcing of even a few tenths of a W/m 2 is substantial [ 63 ]. Calculations that help quantify this matter are discussed in Supplementary Material section SM8 .

( a ) Earth’s energy imbalance (EEI) for 2 × CO 2 , and ( b ) EEI normalized response function.

What is the physics behind the fast response of EEI? The 2 × CO 2 forcing and initial EEI are both nominally 4 W/m 2 . In the GISS (2014) model, the decline of EEI averaged over the first year is 0.5 W/m 2 ( Fig. 5a ), a moderate decline that might be largely caused by warming continents and thus increased heat radiation to space. In contrast, EEI declines 1.3 W/m 2 in the GISS (2020) model ( Fig. 5a ). Such a huge, immediate decline of EEI implies existence of an ultrafast climate feedback. Climate feedbacks are the heart of climate change and warrant discussion.

Slow, fast and ultrafast feedbacks

Charney et al . [ 4 ] described climate feedbacks without discussing time scales. At the 1982 Ewing Symposium, water vapor, clouds and sea ice were described as ‘fast’ feedbacks [ 7 ] presumed to change promptly in response to global temperature change, as opposed to ‘slow’ feedbacks or specified boundary conditions such as ice sheet size, vegetation cover, and atmospheric CO 2 amount, although it was noted that some specified boundary conditions, e.g. vegetation, in reality may be capable of relatively rapid change [ 7 ].

The immediate EEI response ( Fig. 5a ) implies a third feedback time scale: ultrafast. Ultrafast feedbacks are not a new concept. When CO 2 is doubled, the added infrared opacity causes the stratosphere to cool. Instant EEI upon CO 2 doubling is only F i = +2.5 W/m 2 , but stratospheric cooling quickly increases EEI to +4 W/m 2 [ 82 ]. All models calculate a similar radiative effect, so it is useful to define an adjusted forcing, F a , which is superior to F i as a measure of climate forcing. In contrast, if cloud change—the likely cause of the present ultrafast change—is lumped into the adjusted forcing, each climate model has its own forcing, losing the merit of a common forcing.

Kamae et al . [ 83 ] review rapid cloud adjustment distinct from surface temperature-mediated change. Clouds respond to radiative forcing, e.g. via effects on cloud particle phase, cloud cover, cloud albedo and precipitation [ 84 ]. The GISS (2020) model alters glaciation in stratiform mixed-phase clouds, which increases supercooled water in stratus clouds, especially over the Southern Ocean [ Fig. 1 in the GCM description [ 32 ]]. The portion of supercooled cloud water drops goes from too little in GISS (2014) to too much in GISS (2020). Neither model simulates well stratocumulus clouds, yet the models help expose real-world physics that affects climate sensitivity and climate response time. Several models in CMIP6 comparisons find high ECS [ 84 ]. For the sake of revealing the physics, it would be useful if the models defined their temperature and EEI response functions. Model runs of even a decade can define the important part of Figs 4a and 5a . Many short (e.g. 2-year) 2 × CO 2 climate simulations with each run beginning at a different point in the model’s control run, can define cloud changes to an arbitrary accuracy.

In this section, we use ocean sediment core data to explore climate change in the past 66 million years. This allows us to study warmer climates that are relevant to human-made climate forcing.

High equilibrium climate sensitivity that we have inferred, ECS = 1.2°C ± 0.3°C per W/m 2 , may affect interpretation of warmer climates. GCMs have difficulty in producing Pliocene warmth [ 85 ], especially in the Arctic, without large—probably unrealistic—CO 2 amounts. In addition, a coupled GCM/ice sheet model needs 700–840 ppm CO 2 for transition between glaciated and unglaciated Antarctica [ 86 ]. Understanding of these climate states is hampered by uncertainty in the forcings that maintained the climate, as proxy measures of CO 2 have large uncertainty.

Theory informs us that CO 2 is the principal control knob on global temperature [ 87 ]. Climate of the past 800 000 years demonstrates ( Fig. 2 ) the tight control. Our aim here is to extract Cenozoic surface temperature history from the deep ocean oxygen isotope δ 18 O and infer Cenozoic CO 2 history. Oxygen isotope data has high temporal resolution for the entire Cenozoic, which aids understanding of Cenozoic climate change and resulting implications for future climate. Our CO 2 analysis is a complement to proxy CO 2 measurements. Despite progress in estimating CO 2 via carbon isotopes in alkenones and boron isotopes in planktic foraminifera [ 88 ], there is wide scatter among results and fossil plant stomata suggest smaller CO 2 amounts [ 89 ].

Deep ocean temperature and sea level from δ 18 O

Global deep ocean δ 18 O. Black line: Westerhold et al . [ 90 ] data in 5 kyr bins until 34 MyBP and subsequently 2 kyr bins. Green line: Zachos et al . [ 44 ] data at 1 Myr resolution. Lower left: velocity [ 91 ] of Indian tectonic plate. PETM = Paleocene Eocene Thermal Maximum; EECO = Early Eocene Climatic Optimum; Oi-1 marks the transition to glaciated Antarctica; MCO = Miocene Climatic Optimum; NAIP = North Atlantic Igneous Province.

This equation is used for the early Cenozoic, up to the large-scale glaciation of Antarctica at ∼34 MyBP (Oi-1in Fig. 6 ). At larger δ 18 O (colder climate), lighter 16 O evaporates preferentially from the ocean and accumulates in ice sheets. In Zachos data, δ 18 O increases by 3 between Oi-1 and the LGM. Half of this δ 18 O change is due to the 6°C change of deep ocean temperature between Oi-1 (5°C) and the LGM (–1°C) [ 92 ]. The other 1.5 of δ 18 O change is presumed to be due to the ∼180 m sea level (SL) change between ice-free Earth and the LGM, with ∼60 m from Antarctic ice and 120 m from Northern Hemisphere ice. Thus, as an approximation to extract both SL and T do from δ 18 O, Hansen et al . [ 66 ] assumed that SL rose linearly by 60 m as δ 18 O increased from 1.75 to 3.25 and linearly by 120 m as δ 18 O increased from 3.25 to 4.75.

Zachos and Westerhold δ 18 O, SL and T do for the full Cenozoic, Pleistocene, and the past 800 000 years are graphed in Supplementary Material and sea level is compared to data of Rohling et al . [ 94 ]. We focus on the finer resolution W data. Differences between the W and Z data and interpretation of those differences are discussed in Paleocene Eocene Thermal Maximum section.

Cenozoic T S

In this section we combine the rich detail in T do provided by benthic δ 18 O with constraints on the range of Cenozoic T S from surface proxies to produce an estimated history of Cenozoic T S .

We expect T do change, which derives from sea surface temperature (SST) at high latitudes where deepwater forms, to approximate T S change when T do is not near the freezing point. Global SST change understates global T S (land plus ocean) change because land temperature response to a forcing exceeds SST response [ 95 ], e.g. the equilibrium global SST response of the GISS (2020) GCM to 2 × CO 2 is 70.6% of the global (land plus ocean) response. However, polar amplification of the SST response tends to compensate for SST undershoot of global T S change. Compensation is nearly exact at latitudes of North Atlantic deepwater formation for 2 × CO 2 climate change in the GISS (2020) climate model ( Fig. 7a ), but Southern Hemisphere polar amplification does not fully cover the 60–75°S latitudes where Antarctic bottom water forms.

( a ) Ratio of ΔSST (latitude) to global T S change for all ocean and the Atlantic Ocean, based on equilibrium response (years 4001–4500) in 2 × CO 2 simulations of GISS (2020) model. ( b ) ΔT, the amount by which T S change exceeds T do change, based on an exponential fit to the two data points provided by the Holocene and LGM (see text).

Cenozoic temperature based on linear ( Equations 15 and 16 ) and nonlinear ( Equation 17 ) analyses. Antarctic Dome C data [ 40 ] (red) relative to last 1000 years are multiplied by 0.6 to account for polar amplification and 14°C is added for absolute scale.

The result is a consistent analysis of global T S for the entire Cenozoic ( Fig. 8b ). Oxygen isotope δ 18 O of deep ocean foraminifera reproduces glacial-interglacial temperature change well; more detailed agreement is not expected as Antarctic ice core data are for a location that moves, especially in altitude. Our interest is in warmer global climate and its relevance to upcoming human-caused climate change. For that purpose, we want to know the forcing that drove Cenozoic climate change. With the assumption that non-CO 2 GHG forcings provide 20% of the total GHG forcing, it is not difficult to infer the CO 2 abundance required to cause the Cenozoic temperature history in Fig. 8b . Considering the large disagreement among proxy CO 2 measures, this indirect measure of CO 2 via global T S may provide the most accurate Cenozoic CO 2 history.

Cenozoic CO 2

All quantities are known except ΔF CO2 (t), which is thus defined. Cenozoic CO 2 (t) for specified ECS is obtained from T S (t) using the CO 2 radiative forcing equation ( Table 1 , Supplementary Material ). Resulting CO 2 ( Fig. 9 ) is about 1,200 ppm at the EECO, 450 ppm at Oi-1, and 325 ppm in the Pliocene for ECS = 1.2°C per W/m 2 . For ECS = 1°C—about as low as we believe plausible—Pliocene CO 2 is near 350 ppm, rising only to ∼500 ppm at Oi-1 and ∼1500 ppm at EECO.

Cenozoic CO 2 estimated from δ 18 O of Westerhold et al . (see text). Black lines are for ECS = 1.2°C per W/m 2 ; red and green curves (ECS = 1.0 and 1.4°C per W/m 2 ) are 1 My smoothed. Blue curves (last 800 000 years) are Antarctica ice core data [ 41 ].

Assumed Holocene CO 2 amount is also a minor factor. We tested two cases: 260 and 278 ppm ( Fig. 9 ). These were implemented as the CO 2 values at 7 kyBP, but Holocene-mean values are similar—a few ppm less than CO 2 at 7 kyBP. Holocene = 278 ppm increases CO 2 about 20 ppm between today and Oi-1, and about 50 ppm at the EECO. However, Holocene CO 2 278 ppm causes the amplitude of inferred glacial-interglacial CO 2 oscillations to be less than reality ( Fig. 9b ), providing support for the Holocene 260 ppm level and for the interpretation that high late-Holocene CO 2 was due to human influence. Proxy measures of Cenozoic CO 2 yield a notoriously large range. A recent review [ 88 ] constructs a CO 2 history with Loess-smoothed CO 2 ∼700–1100 ppm at Oi-1. That high Oi-1 CO 2 amount is not plausible without overthrowing the concept that global temperature is a response to climate forcings. More generally, we conclude that actual CO 2 during the Cenozoic was near the low end of the range of proxy measurements.

Interpretation of Cenozoic T S and CO 2

In this section we consider Cenozoic T S and CO 2 histories, which are rich in insights about climate change with implications for future climate.

In Target CO 2 [ 60 ] and elsewhere [ 98 ] we argue that the broad sweep of Cenozoic temperature is a result of plate tectonic (popularly ‘continental drift’) effects on CO 2 . Solid Earth sources and sinks of CO 2 are not balanced at any given time. CO 2 is removed from surface reservoirs by: (1) chemical weathering of rocks with deposition of carbonates on the ocean floor, and (2) burial of organic matter [ 99 , 100 ]. CO 2 returns via metamorphism and volcanic outgassing at locations where oceanic crust is subducted beneath moving continental plates. The interpretation in Target CO 2 was that the main Cenozoic source of CO 2 was associated with the Indian plate ( Fig. 10 ), which separated from Pangea in the Cretaceous [ 101 , 102 ] and moved through the Tethys (now Indian) Ocean at a rate exceeding 10 cm/year until collision with the Eurasian plate at circa 50 MyBP. Associated CO 2 emissions include those from formation of the Deccan Traps 7 in western India (a large igneous province, LIP, formed by repeated deposition of large-scale flood basalts), the smaller Rajahmundry Traps [ 103 ] in eastern India, and metamorphism and vulcanism associated with the moving Indian plate. The Indian plate slowed circa 60 Mya (inset, Fig. 6 ) before resuming high speed [ 91 ], leaving an indelible signature in the Cenozoic δ 18 O history ( Fig. 6 ) that supports our interpretation of the CO 2 source. Since the continental collision, subduction and CO 2 emissions continue at a diminishing rate as the India plate underthrusts the Asian continent and pushes up the Himalayan mountains [ 104 ]. We interpret the decline of CO 2 over the past 50 million years as, at least in part, a decline of the metamorphic source from continued subduction of the Indian plate, but burial of organic matter and increased weathering due to exposure of fresh rock by Himalayan uplift [ 105 ] may contribute to CO 2 drawdown. Quantitative understanding of these processes is limited [ 106 ], e.g. weathering is both a source and sink of CO 2 [ 107 ].

Continental configuration 56 MyBP [ 97 ]. Continental shelves (light blue) were underwater as little water was locked in ice. The Indian plate was moving north at about 15 cm per year.

This picture for the broad sweep of Cenozoic CO 2 is consistent with current understanding of the long-term carbon cycle [ 108 ], but relative contributions of metamorphism [ 106 ] and volcanism [ 109 ] are uncertain. Also, emissions from rift-induced Large Igneous Provinces (LIPs) [ 110 , 111 ] contribute to long-term change of atmospheric CO 2 , with two cases prominent in Fig. 6 . The Columbia River Flood Basalt at ca. 17–15 MyBP was a principal cause of the Miocene Climatic Optimum [ 112 ], but the processes are poorly understood [ 113 ]. A more dramatic event occurred as Greenland separated from Europe, causing a rift in the sea floor; flood basalt covered more than a million square kilometers with magma volume 6–7 million cubic kilometers [ 111 ]—the North Atlantic Igneous Province (NAIP). Flood basalt volcanism occurred during 60.5–54.5 MyBP, but at 56.1 ± 0.5 MyBP melt production increased by more than a factor of 10, continued at a high level for about a million years, and then subsided ( Fig. 5 of Storey et al . [ 114 ]). The striking Paleocene-Eocene Thermal Maximum (PETM) δ 18 O spike ( Fig. 6 ) occurs early in this million-year bump-up of δ 18 O. Svensen et al . [ 115 ] proposed that the PETM was initiated by the massive flood basalt into carbon-rich sedimentary strata. Gutjahr et al . [ 116 ] developed an isotope analysis, concluding that most of PETM carbon emissions were volcanic, with climate-driven carbon feedbacks playing a lesser role. Yet other evidence [ 117 ], while consistent with volcanism as a trigger for the PETM, suggests that climate feedback—perhaps methane hydrate and peat CO 2 release—may have caused more than half of the PETM warming. Berndt et al . [ 118 ] describe extensive shallow-water vents that likely released CH 4 as well as CO 2 during the NAIP activity. We discuss PETM warming and CO 2 levels below, but first we must quantify the mechanisms that drove Cenozoic climate change and consider where Earth’s climate was headed before humanity intervened.

The sum of climate forcings (CO 2 and solar) and slow feedbacks (ice sheets and non-CO 2 GHGs) that maintained EECO warmth was 12.5 W/m 2 ( Fig. 11 ). CO 2 forcing of 9.1 W/m 2 combined with solar forcing of—1.2 W/m 2 to yield a total forcing 8 8 W/m 2 . Slow feedbacks were 4.5 W/m 2 forcing (ice albedo = 2 W/m 2 and non-CO 2 GHGs = 2.5 W/m 2 ). With today’s solar irradiance, human-made GHG forcing required for Earth to return to EECO warmth is 8 W/m 2 . Present human-made GHG forcing is 4.6 W/m 2 relative to 7 kyBP. 9 Equilibrium response to this forcing includes the 2 W/m 2 ice sheet feedback and 25% amplification (of 6.6 W/m 2 ) by non-CO 2 GHGs, yielding a total forcing plus slow feedbacks of 8.25 W/m 2 . Thus, equilibrium global warming for today’s GHGs is 10°C. 10 If human-made aerosol forcing is −1.5 W/m 2 and remains at that level indefinitely, equilibrium warming for today’s atmosphere is reduced to 8°C. Either 10°C or 8°C dwarfs observed global warming of 1.2°C to date. Most of the equilibrium warming for today’s atmosphere has not yet occurred and need not occur (Earth’s energy imbalance section).

Climate forcings and slow feedbacks relative to 7 kyBP from terms in Equations (21–23) .

Prospects for another snowball Earth

We would be remiss if we did not comment on the precipitous decline of Earth’s temperature over the last several million years. Was Earth falling off the table into another Snowball Earth?

Global temperature plummeted in the past 50 million years, with growing, violent, oscillations ( Figs 6 and 7 ). Glacial-interglacial average CO 2 declined from about 325 ppm to 225 ppm in the past five million years in an accelerating decline ( Fig. 9a ). As CO 2 fell to 180 ppm during recent glacial maxima, an ice sheet covered most of Canada and reached midlatitudes in the U.S. Continents in the current supercontinent cycle [ 101 ] are now dispersed, with movement slowing to 2–3 cm/year. Emissions from the last high-speed high-impact tectonic event—collision of the Indian plate with Eurasia—are fizzling out. The most recent large igneous province (LIP) event—the Columbia River Flood Basalt about 15 million years ago ( Fig. 6 )—is no longer a factor, and there is no evidence of another impending LIP. Snowball conditions are possible, even though the Sun’s brightness is increasing and is now almost 6% greater [ 69 ] than it was at the last snowball Earth, almost 600 million years ago [ 68 ]. Runaway snowball likely requires only 1–2 halvings [ 66 ] of CO 2 from the LGM 180 ppm level, i.e. to 45–90 ppm. Although the weathering rate declines in colder climate [ 119 ], weathering and burial of organic matter continue, so decrease of atmospheric CO 2 could have continued over millions of years, if the source of CO 2 from metamorphism and vulcanism continued to decline.

Another factor that may have contributed to cooling in the Pliocene is uplift and poleward movement of Greenland that accelerated about 5 MyBP [ 120 ], which likely enhanced glaciation of Greenland and should be accounted for in simulations of Pliocene climate change. We conclude that, in the absence of human activity, Earth may have been headed for snowball Earth conditions within the next 10 or 20 million years, but the chance of future snowball Earth is now academic. Human-made GHG emissions remove that possibility on any time scale of practical interest. Instead, GHG emissions are now driving Earth toward much warmer climate.

Paleocene eocene thermal maximum (PETM)

The PETM event provides a benchmark for assessing the potential impact of the human-made climate forcing and the time scale for natural recovery of the climate system.

Westerhold [ 90 ] data have 10°C deep ocean warming at the PETM ( Figs 8 and 12a ), which exceeds proxy-derived surface warming. Low latitude SST data have 3–4°C PETM warming [ 121 ]. Tierney et al . [ 122 ] obtain PETM global surface warming 5.6°C (5.4–59°C, 95% confidence) via analysis of proxy surface temperature data that accounts for patterns of temperature change. Zachos [ 44 ] data have a deep ocean warming similar to the proxy-based surface warming. These warming estimates can be reconciled, but first let’s note the practical importance of the PETM.

Pre-PETM (56–56.4 MyBP) CO 2 is 910 ppm in our analysis for the most likely ECS (1.2°C per W/m 2 ). Peak PETM CO 2 required to yield the 5.6°C global surface warming estimate of Tierney et al . [ 122 ] is then 1630 ppm if CO 2 provides 80% of the GHG forcing, thus less than a doubling of CO 2 . (In the unlikely case that CO 2 caused 100% of the GHG forcing, required CO 2 is 1780, not quite a doubling.) CO 2 amounts for ECS = 1.0 and 1.4°C per W/m 2 are 1165 and 760 ppm in the pre-PETM and 2260 and 1270 ppm at peak PETM, respectively. In all these ECS cases, the CO 2 forcing of the PETM is less than or about a CO 2 doubling. Our assumed 20% contribution by non-CO 2 GHGs (amplification factor 1.25, Climate sensitivity (ECS and ESS) section), is nominal; Hopcroft et al ., e.g. estimate a 30% contribution from non-CO 2 GHGs [ 123 ], thus an amplification factor 1.43.

Thus, today’s human-made GHG forcing (4.6 W/m 2 , growing 0.5 W/m 2 per decade) is already at least comparable to the PETM forcing, although the net human-made forcing including aerosols has probably not reached the PETM forcing. However, there are two big differences between the PETM and today. First, there were no large ice sheets on Earth in the PETM era. Ice sheets on Antarctica and Greenland today make Earth system sensitivity (ESS) greater than it was during the PETM. Equilibrium response to today’s GHG climate forcing would include deglaciation of Antarctica and Greenland, sea level rise of 60 m (200 feet), and surface albedo forcing (slow feedback) of 2 W/m 2 . The second difference between the PETM and today is the rate of change of the climate forcing. Most of today’s climate forcing was introduced in a century, which is 10 times or more faster than the PETM forcing growth. Although a bolide impact [ 124 ] has been proposed as a trigger for the PETM, the issue is the time scale on which the climate forcing—increased GHGs—occurred. Despite uncertainty in the carbon source(s), data and modeling point to duration of a millennium or more for PETM emissions [ 121 , 125 ].

Better understanding of the PETM could inform us on climate feedbacks. Gutjahr et al . [ 116 ] argue persuasively that PETM emissions were mostly volcanic, yet we know of no other large igneous province that produced such great, temporally-isolated, emissions. Further, Cenozoic orbitally-driven hyperthermal events [ 126 ] testify to large CO 2 feedbacks. Northern peatlands today contain more than 1000 Gt carbon [ 127 ], much of which can be mobilized at PETM warming levels [ 128 ]. The double peak in deep ocean δ 18 O (thus in temperature, cf. Fig. 12 , where each square is a binning interval of 5000 years) is also found in terrestrial data [ 129 ]. Perhaps the sea floor rift occurred in two bursts, or the rift was followed tens of thousands of years later by methane hydrate release as a feedback to the ocean warming; much of today’s methane hydrate is in stratigraphic deposits hundreds of meters below the sea floor, where millennia may pass before a thermal wave from the surface reaches the deposits [ 130 ]. Feedback emissions, especially from permafrost, seem to be more chronic than catastrophic, but stabilization of climate may require cooling that terminates growth of those feedbacks (Summary section). The PETM provides perhaps the best empirical check on understanding of the atmospheric lifetime of fossil fuel CO 2 [ 131 ], but for that purpose we must untangle as well as possible the time dependence of the PETM CO 2 source and feedbacks. If continuing magma flow or a slow-release feedback is a substantial portion of PETM CO 2 , the CO 2 lifetime inferred from post-PETM CO 2 recovery may be an exaggeration.

Temperature and CO 2 implied by Westerhold et al . [ 90 ] δ 18 O, if surface warming equaled deep ocean warming. In reality, the unique PETM event had surface warming ∼5.6°C, which implies a peak PETM CO 2 of about 1630 ppm (see text).

The PETM draws attention to differences between the Westerhold (W) and Zachos (Z) δ 18 O data. Zachos attributes the larger PETM response in W data to the shallow (less than 1 km) depth of the Walvis Ridge core in the Southeast Atlantic that anchors the PETM period in the W data (see Supplementary Material SM9 ). Given that the PETM was triggered by a rift in the floor of the North Atlantic and massive lava injection, it is not surprising that ocean temperature was elevated and circulation disrupted during the PETM. Nunes and Norris [ 132 ] conclude that ocean circulation changed at the start of the PETM with a shift in location of deep-water formation that delivered warmer waters to the deep sea, a circulation change that persisted at least 40 000 years. With regard to differences in the early Cenozoic, Zachos notes ( Supplementary Material SM9 ) a likely bias in the Z data with a heavy weighting of data from Southern Ocean sites (Kerguelen Plateau and Maud Rise), which were intended for study of climate of Antarctica and the Southern Ocean.

Differences between the W and Z data sets have limited effect on our paper, as we apply separate scaling ( Equations 7–14 ) to W and Z data to match observations at the LGM, mid-Holocene, and Oi-1 points. This approach addresses, e.g. the cumulative effect in combining data splices noted by Zachos in SM9. Further, we set the EECO global temperature relative to the Holocene and the PETM temperature relative to pre-PETM based on proxy-constrained, full-field, GCM analyses of Tierney et al . [ 122 ] and Zhu et al . [ 96 ] Nevertheless, there is much to learn from more precise study of the Cenozoic in general and the PETM in particular.

Policy implications require first an understanding of the role of aerosols in climate change.

The role of aerosols in climate change is uncertain because aerosol properties are not measured well enough to define their climate forcing. In this section we estimate aerosol climate forcing via aerosol effects on Earth’s temperature and Earth’s energy imbalance.

Aerosol impact is suggested by the gap between observed global warming and expected warming due to GHGs based on ECS inferred from paleoclimate ( Fig. 13 ). Expected warming is from Eq. 5 with the normalized response function of the GISS (2020) model. Our best estimate for ECS, 1.2°C per W/m 2 , yields a gap of 1.5°C between expected and actual warming in 2022. Aerosols are the likely cooling source. The other negative forcing discussed by IPCC—surface albedo change—is estimated by IPCC (Chapter 7, Table 7.8) to be –0.12 ± 0.1 W/m 2 , an order of magnitude smaller than aerosol forcing [ 12 ]. Thus, for clarity, we focus on GHGs and aerosols.

Observed global surface temperature (black line) and expected GHG warming with two choices for ECS. The blue area is the estimated aerosol cooling effect. The temperature peak in the World War II era is in part an artifact of inhomogeneous ocean data in that period [ 63 ].

Absence of global warming over the period 1850–1920 ( Supplementary Fig. S1 of IPCC AR6 WG1 report [ 12 ]) is a clue about aerosol forcing. GHG forcing increased 0.54 W/m 2 in 1850–1920, which causes expected warming 0.3–0.4°C by 1920 for ECS = 1.2°C per W/m 2 ( Equation 5 ). Natural forcings—solar irradiance and volcanoes—may contribute to lack of warming, but a persuasive case for the required forcing has not been made. Human-made aerosols are the likely offset of GHG warming. Such aerosol cooling is a Faustian bargain [ 98 ] because payment in enhanced global warming will come due once we can no longer tolerate the air pollution. Ambient air pollution causes millions of deaths per year, with particulates most responsible [ 133 , 134 ].

Evidence of aerosol forcing in the Holocene

In this section we infer evidence of human-made aerosols in the last half of the Holocene from the absence of global warming. Some proxy-based analyses [ 135 ] report cooling in the last half of the Holocene, but a recent analysis [ 50 ] that uses GCMs to overcome spatial and temporal biases in proxy data finds rising global temperature in the first half of the Holocene followed by nearly constant temperature in the last 6000 years until the last few centuries ( Fig. 14 ). Antarctic, deep ocean, and tropical sea surface data all show stable temperature in the last 6000 years ( Supplementary Fig. S6 of reference [ 60 ]). GHG forcing increased 0.5 W/m 2 during those 6000 years ( Fig. 15 ), yet Earth did not warm. Fast feedbacks alone should yield at least +0.5°C warming and 6000 years is long enough for slow feedbacks to also contribute. How can we interpret the absence of warming?

Global mean surface temperature change over the past 24 ky, reproduced from Fig. 2 of Osman et al . [ 50 ] including Last Millennium reanalysis of Tardif et al . [ 136 ].

GHG climate forcing in past 20 ky with vertical scale expanded for the past 10 ky on the right. GHG amounts are from Schilt et al . [ 47 ]. Formulae for forcing are in Supplementary Material .

Humanity’s growing footprint deserves scrutiny. Ruddiman’s suggestion that deforestation and agriculture began to affect CO 2 6500 year ago and rice agriculture began to affect CH 4 5000 years ago has been criticized [ 46 ] mainly because of the size of proposed sources. Ruddiman sought sources sufficient to offset declines of CO 2 and CH 4 in prior interglacial periods, but such large sources are not needed to account for Holocene GHG levels. Paleoclimate GHG decreases are slow feedbacks that occur in concert with global cooling. However, if global cooling did not occur in the past 6000 years, feedbacks did not occur. Earth orbital parameters 6000 years ago kept the Southern Ocean warm, as needed to maintain strong overturning ocean circulation [ 137 ] and minimize carbon sequestration in the deep ocean. Maximum insolation at 60°S was in late-spring (mid-November); since then, maximum insolation at 60°S slowly advanced through the year, recently reaching mid-summer (mid-January, Fig. 26b of Ice Melt [ 13 ]). Maximum insolation from late-spring through mid-summer is optimum to warm the Southern Ocean and promote early warm-season ice melt, which reduces surface albedo and magnifies regional warming [ 45 ].

GHG forcing of –0.2 W/m 2 in 10–6 kyBP ( Fig. 15 ) was exceeded by forcing of +1 W/m 2 due to ice sheet shrinkage ( Supplementary Material in Target CO 2 [ 60 ]) for a 40 m sea level rise ( Fig. 16 ). Net 0.8 W/m 2 forcing produced expected 1°C global warming ( Fig. 14 ). The mystery is the absence of warming in the past 6000 years. Hansen et al . [ 45 ] suggested that aerosol cooling offset GHG warming. Growing population, agriculture and land clearance produced aerosols and CO 2 ; wood was the main fuel for cooking and heating. Nonlinear aerosol forcing is largest in a pristine atmosphere, so it is unsurprising that aerosols tended to offset CO 2 warming as civilization developed. Hemispheric differences could provide a check. GHG forcing is global, while aerosol forcing is mainly in the Northern Hemisphere. Global offset implies a net negative Northern Hemisphere forcing and positive Southern Hemisphere forcing. Thus, data and modeling studies (including orbital effects) of regional response are warranted but beyond the scope of this paper.

Sea level since the last glacial period relative to present. Credit: Robert Rohde [ 138 ].

Industrial era aerosols

Scientific advances often face early resistance from other scientists [ 139 ]. Examples are the snowball Earth hypothesis [ 140 ] and the role of an asteroid impact in extinction of non-avian dinosaurs [ 141 ], which initially were highly controversial but are now more widely accepted. Ruddiman’s hypothesis, right or wrong, is still controversial. Thus, we minimize this issue by showing aerosol effects with and without preindustrial human-made aerosols.

Global aerosols are not monitored with detail needed to define aerosol climate forcing [ 142 , 143 ]. IPCC12 estimates forcing ( Fig. 17a ) from assumed precursor emissions, a herculean task due to many aerosol types and complex cloud effects. Aerosol forcing uncertainty is comparable to its estimated value ( Fig. 17a ), which is constrained more by observed global temperature change than by aerosol measurements [ 144 ]. IPCC’s best estimate of aerosol forcing ( Fig. 17 ) and GHG history define the percent of GHG forcing offset by aerosol cooling—the dark blue area in Fig. 17b . However, if human-made aerosol forcing was −0.5 W/m 2 by 1750, offsetting +0.5 W/m 2 GHG forcing, this forcing should be included. Such aerosol forcing—largely via effects of land use and biomass fuels on clouds—continues today. Thirty million people in the United States use wood for heating [ 145 ]. Such fuels are also common in Europe [ 146 , 147 ] and much of the world.

( a ) Estimated greenhouse gas and aerosol forcings relative to 1750 values. ( b ) Aerosol forcing as percent of GHG forcing. Forcings for dark blue area are relative to 1750. Light blue area adds 0.5 W/m 2 forcing estimated for human-caused aerosols from fires, biofuels and land use.

Figure 17b encapsulates two alternative views of aerosol history. IPCC aerosol forcing slowly becomes important relative to GHG forcing. In our view, civilization always produced aerosols as well as GHGs. As sea level stabilized, organized societies and population grew as coastal biologic productivity increased [ 148 ] and agriculture developed. Wood was the main fuel. Aerosols travel great distances, as shown by Asian aerosols in North America [ 149 ]. Humans contributed to both rising GHG and aerosol climate forcings in the past 6000 years. One result is that human-caused aerosol climate forcing is at least 0.5 W/m 2 more than usually assumed. Thus, the Faustian payment that will eventually come due is also larger, as discussed in Summary section.

Ambiguity in aerosol climate forcing

In this section we discuss uncertainty in the aerosol forcing. We discuss why global warming in the past century—often used to infer climate sensitivity—is ill-suited for that purpose.

Recent global warming does not yield a unique ECS because warming depends on three major unknowns with only two basic constraints. Unknowns are ECS, net climate forcing (aerosol forcing is unmeasured), and ocean mixing (many ocean models are too diffusive). Constraints are observed global temperature change and Earth’s energy imbalance (EEI) [ 80 ]. Knutti [ 150 ] and Hansen [ 75 ] suggest that many climate models compensate for excessive ocean mixing (which reduces surface warming) by using aerosol forcing less negative than the real world, thus achieving realistic surface warming. This issue is unresolved and complicated by the finding that cloud feedbacks can buffer ocean heat uptake (Climate response time section), affecting interpretation of EEI.

IPCC AR6 WG1 best estimate of aerosol forcing (Table AIII.3) [ 12 ] is near maximum (negative) value by 1975, then nearly constant until rising in the 21st century to –1.09 W/m 2 in 2019 ( Fig. 18 ). We use this IPCC aerosol forcing in climate simulations here. We also use an alternative aerosol scenario [ 151 ] that reaches –1.63 W/m 2 in 2010 relative to 1880 and –1.8 W/m 2 relative to 1850 ( Fig. 18 ) based on modeling of Koch [ 152 ] that included changing technology factors defined by Novakov [ 153 ]. This alternative scenario 11 is comparable to the forcing in some current aerosol models ( Fig. 18 ). Human-made aerosol forcing relative to several millennia ago may be even more negative, by about –0.5 W/m 2 as discussed above, but the additional forcing was offset by increasing GHGs and thus those additional forcings are neglected, with climate assumed to be in approximate equilibrium in 1850.

Aerosol forcing relative to 1850 from IPCC AR6, an alternative aerosol scenario [ 151 ] two aerosol model scenarios of Bauer et al . [ 154 ].

Many combinations of climate sensitivity and aerosol forcing can fit observed global warming. The GISS (2014) model (ECS = 2.6°C) with IPCC AR6 aerosol forcing can match observed warming ( Fig. 19 ) in the last half century (when human-made climate forcing overwhelmed natural forcings, unforced climate variability, and flaws in observations). However, agreement also can be achieved by climate models with high ECS. The GISS (2020) model (with ECS = 3.5°C) yields greater warming than observed if IPCC aerosol forcing is used, but less than observed for the alternative aerosol scenario ( Fig. 19 ). This latter aerosol scenario achieves agreement with observed warming if ECS ∼4°C (green curve in Fig. 19 ). 12 Agreement can be achieved with even higher ECS by use of a still more negative aerosol forcing.

Global temperature change T G due to aerosols + GHGs calculated with Green’s function Equation (5) using GISS (2014) and GISS (2020) response functions ( Fig. 4 ). Observed temperature is the NASA GISS analysis [ 155 , 156 ]. Base period: 1951–1980 for observations and model.

The issue we raise is the magnitude of the aerosol forcing, with implications for future warming when particulate air pollution is likely to be reduced. We suggest that IPCC reports may have gravitated toward climate sensitivity near 3°C for 2 × CO 2 in part because of difficulty that models have in realistically simulating amplifying cloud feedbacks and a climate model tendency for excessive mixing of heat into the deep ocean. Our finding from paleoclimate analysis that ECS is 1.2°C ± 0.3°C per W/m 2 (4.8°C ± 1.2°C for 2 × CO 2 ) implies that the (unmeasured) aerosol forcing must be more negative than IPCC’s best estimate. In turn—because aerosol-cloud interactions are the main source of uncertainty in aerosol forcing—this finding emphasizes the need to measure both global aerosol and cloud particle properties.

The case for monitoring global aerosol climate forcing will grow as recognition of the need to slow and reverse climate change emerges. Aerosol and cloud particle microphysics must be measured with precision adequate to define the forcing [ 142 , 158 ]. In the absence of such Keeling-like global monitoring, progress can be made via more limited satellite measurements of aerosol and cloud properties, field studies, and aerosol and cloud modeling. As described next, a great opportunity to study aerosol and cloud physics is provided by a recent change in the IMO (International Maritime Organization) regulations on ship emissions.

The great inadvertent aerosol experiment

Sulfate aerosols are cloud condensation nuclei (CCN), so sulfate emissions by ships result in a larger number of smaller cloud particles, thus affecting cloud albedo and cloud lifetime [ 144 ]. Ships provide a large percentage of sulfates in the North Pacific and North Atlantic regions ( Fig. 20 ). It has been suggested that cooling by these clouds is overestimated because of cloud liquid water adjustments [ 159 ], but Manshausen et al . [ 160 ] present evidence that liquid water path (LWP) effects are substantial even in regions without visible ship-tracks; they estimate a LWP forcing −0.76 ± 0.27 W/m 2 , in stark contrast with the IPCC estimate of +0.2 ± 0.2 W/m 2 . Wall et al . [ 161 ] use satellite observations to quantify relationships between sulfates and low-level clouds; they estimate a sulfate indirect aerosol forcing of −1.11 ± 0.43 W/m 2 over the global ocean. The range of aerosol forcings used in CMIP6 and AR6 GCMs (small blue bar in Fig. 18 ) is not a measure of aerosol forcing uncertainty. The larger bar, from Chapter 7 [ 162 ] of AR6, has negative forcing as great as –2 W/m 2 , but even that does not measure the full uncertainty.

Total sulfate (parts per trillion by volume) and percentage of total sulfate provided by shipping in simulations of Jin et al . [ 157 ] prior to IMO regulations on sulfur content of fuels.

Changes of IMO emission regulations provide a great opportunity for insight into aerosol climate forcing. Sulfur content of fuels was limited to 1% in 2010 near the coasts of North America and in the North Sea, Baltic Sea and English Channel, and further restricted there to 0.1% in 2015 [ 163 ]. In 2020 a limit of 0.5% was imposed worldwide. The 1% limit did not have a noticeable effect on ship-tracks, but a striking reduction of ship-tracks was found after the 2015 IMO regulations, especially in the regions near land where emissions were specifically limited [ 164 ]. Following the additional 2020 regulations [ 165 ], global ship-tracks were reduced more than 50% [ 166 ].

Earth’s albedo (reflectivity) measured by CERES (Clouds and Earth’s Radiant Energy System) satellite-borne instruments [ 81 ] over the 22-years March 2000 to March 2022 reveal a decrease of albedo and thus an increase of absorbed solar energy coinciding with the 2015 change of IMO emission regulations. Global absorbed solar energy is + 1.05 W/m 2 in the period January 2015 through December 2022 relative to the mean for the first 10 years of data ( Fig. 21 ). This increase is 5 times greater than the standard deviation (0.21 W/m 2 ) of annual absorbed solar energy in the first 10 years of data and 4.5 times greater than the standard deviation (0.23 W/m 2 ) of CERES data through December 2014. The increase of absorbed solar energy is notably larger than estimated potential CERES instrument drift, which is <0.085 W/m 2 per decade [ 81 ]. Increased solar energy absorption occurred despite 2015–2020 being the declining phase of the ∼11-year solar irradiance cycle [ 167 ]. Nor can increased absorption be attributed to correlation of Earth’s albedo (and absorbed solar energy) with the Pacific Decadal Oscillation (PDO): the PDO did shift to the positive phase in 2014–2017, but it returned to the negative phase in 2017–2022 [ 168 ].

Global absorbed solar radiation (W/m 2 ) relative to mean of the first 120 months of CERES data. CERES data are available at http://ceres.larc.nasa.gov/order_data.php .

Given the large increase of absorbed solar energy, cloud changes are likely the main cause. Quantitative analysis [ 168 ] of contributions to the 20-year trend of absorbed solar energy show that clouds provide most of the change. Surface albedo decrease due to sea ice decline contributes to the 20-year trend in the Northern Hemisphere, but that sea ice decline occurred especially in 2007, with minimum sea ice cover reached in 2012; over the past decade as global and hemispheric albedos declined, sea ice had little trend [ 169 ]. Potential causes of the cloud changes include: (1) reduced aerosol forcing, (2) cloud feedbacks to global warming, (3) natural variability [ 170 ]. Absorbed solar energy was 0.77 W/m 2 greater in Jan2015-Dec2022 than in the first decade of CERES data at latitudes 20–60°S ( Fig. 22 ), a region of relatively little ship traffic. This change is an order of magnitude larger than the estimate of potential detector degradation [ 81 ].

Absorbed solar radiation for indicated regions relative to first 120 months of CERES data. Southern Hemisphere 20–60°S is 89% ocean. North Atlantic is (20–60°N, 0–60°W) and North Pacific is (20–60°N, 120–220°W). Data source: http://ceres.larc.nasa.gov/order_data.php .

Climate models predict a reduction of cloud albedo in this region as a feedback effect driven by global warming [ 12 ] (Sec. 7.4.2.4). Continued monitoring of absorbed energy can confirm the reality of the change, but without global monitoring of detailed physical properties of aerosols and clouds [ 142 ], it will be difficult to apportion observed change among candidate causes.

North Pacific and North Atlantic regions of heavy ship traffic are ripe for detailed study of cloud changes and their causes, although unforced cloud variability is large in such sub-global regions. Both regions have increased absorption of solar radiation after 2015 ( Fig. 22 ). The 2014–2017 maximum absorption in the North Pacific is likely enhanced by reduced cloud cover during the positive PDO, but the more recent high absorption is during the negative PDO phase. In the North Atlantic, persistence of increased absorption for several years exceeds prior variability, but longer records plus aerosol and cloud microphysical data are needed for interpretation.

Climate change is characterized by delayed response and amplifying feedbacks. Delayed response makes human-made climate forcing a threat to today’s public and future generations because of the practical difficulty of reversing the forcing once consequences become apparent. Feedbacks determine climate sensitivity to any applied forcing. We find that Earth’s climate is very sensitive—more sensitive than the best estimate of the Intergovernmental Panel on Climate Change (IPCC)—which implies that there is a great amount of climate change ‘in the pipeline.’ Extraordinary actions are needed to reduce the net human-made climate forcing, as is required to reduce global warming and avoid highly undesirable consequences for humanity and nature.

Equilibrium climate sensitivity (ECS)

The 1979 Charney study [ 4 ] considered an idealized climate sensitivity in which ice sheets and non-CO 2 GHGs are fixed. The Charney group estimated that the equilibrium response to 2 × CO 2 , a forcing of 4 W/m 2 , was 3°C, thus an ECS of 0.75°C per W/m 2 , with one standard deviation uncertainty σ = 0.375°C. Charney’s estimate stood as the canonical ECS for more than 40 years. The current IPCC report [ 12 ] concludes that 3°C for 2 × CO 2 is their best estimate for ECS.

We compare recent glacial and interglacial climates to infer ECS with a precision not possible with climate models alone. Uncertainty about Last Glacial Maximum (LGM) temperature has been resolved independently with consistent results by Tierney et al . [ 49 ] and Seltzer et al . [ 51 ]. The Tierney approach, using a collection of geochemical temperature indicators in a global analysis constrained by climate change patterns defined by a global climate model, is used by Osman et al . [ 50 ] to find peak LGM cooling 7.0 ± 1°C (2σ, 95% confidence) at 21–18 kyBP. We show that, accounting for polar amplification, these analyses are consistent with the 5.8 ± 0.6°C LGM cooling of land areas between 45°S and 35°N found by Seltzer et al . using the temperature-dependent solubility of dissolved noble gases in ancient groundwater. The forcing that maintained the 7°C LGM cooling was the sum of 2.25 ± 0.45 W/m 2 (2σ) from GHGs and 3.5 ± 1.0 W/m 2 (2σ) from the LGM surface albedo, thus 5.75 ± 1.1 W/m 2 (2σ). ECS implied by the LGM is thus 1.22 ± 0.29°C (2σ) per W/m 2 , which, at this final step, we round to 1.2 ± 0.3°C per W/m 2 . For transparency, we have combined uncertainties via simple RMS (root-mean-square). ECS as low as 3°C for 2 × CO 2 is excluded at the 3σ level, i.e. with 99.7% confidence.

More sophisticated mathematical analysis, which has merits but introduces opportunity for prior bias and obfuscation, is not essential; error assessment ultimately involves expert judgment. Instead, focus is needed on the largest source of error: LGM surface albedo change, which is uncertain because of the effect of cloud shielding on the efficacy of the forcing. As cloud modeling is advancing rapidly, this topic is ripe for collaboration of CMIP [ 53 ] (Coupled Model Intercomparison Project) with PMIP [ 54 ] (Paleoclimate Modelling Intercomparison Project). Simulations should include at the same time change of surface albedo and topography of ice sheets, vegetation change, and exposure of continental shelves due to lower sea level.

Knowledge of climate sensitivity can be advanced further via analysis of the wide climate range in the Cenozoic era (Earth system sensitivity section). However, interpretation of data and models, and especially projections of climate change, depend on understanding of climate response time.

We expected climate response time—the time for climate to approach a new equilibrium after imposition of a forcing—to become faster as mixing of heat in ocean models improved [ 75 ]. That expectation was not met when we compared two generations of the GISS GCM (global climate model). The GISS (2020) GCM is improved [ 32 , 33 ] in its ocean simulation over the GISS (2014) GCM as a result of higher vertical and horizontal resolution, more realistic parameterization of sub-grid scale motions, and correction of errors in the ocean computer program [ 32 ]. Yet the time for the model to achieve 63% of its equilibrium response remained about 100 years. There are two reasons for this: one that is obvious and one that is more interesting and informative.

The surface in the newer model warms as fast as in the older model, but it must achieve greater warming to reach 63% of equilibrium because its ECS is higher, which is one reason that the response time remains long. The other reason is that Earth’s energy imbalance (EEI) in the newer model decreases rapidly. EEI defines the rate that heat is pumped into the ocean, so a smaller EEI implies a longer time for the ocean to reach its new equilibrium temperature. Quick drop of EEI—in the first year after introduction of the forcing—implies existence of ultrafast feedback in the GISS (2020) model. For want of an alternative with such a large effect on Earth’s energy budget, we infer a rapid cloud feedback and we suggest (Slow, fast and ultrafast feedbacks section) a set of brief GCM runs that define cloud changes and other diagnostic quantities to an arbitrary accuracy.

The Charney report [ 4 ] recognized that clouds were a main cause of a wide range in ECS estimates. Today, clouds still cast uncertainty on climate predictions. Several CMIP6 [ 34 ] GCMs have ECS of ∼4–6°C for 2×CO 2 [ 171 , 172 ] with the high sensitivity caused by cloud feedbacks [ 84 ]. As cloud modeling progresses, it will aid understanding if climate models report their 2 × CO 2 response functions for both temperature and EEI (Earth’s energy imbalance).

Fast EEI response—faster than global temperature response—has a practical effect: observed EEI understates the reduction of climate forcing required to stabilize climate. Although the magnitude of this effect is uncertain (see Supplementary Material SM6 ), it makes the task of restoring a hospitable climate and saving coastal cities more challenging. On the other hand, long climate response time implies the potential for educated policies to affect the climate outcome before the most undesirable consequences occur.

The time required for climate to reach a new equilibrium is relevant to policy (Perspective on policy implications section), but there is another response time of practical importance. With climate in a state of disequilibrium, how much time do we have before we pass the point of no return, the point where major climate impacts are locked in, beyond our ability to control? That’s a complex matter; it requires understanding of ‘slow’ feedbacks, especially ice sheets. It also depends on how far climate is out of equilibrium. Thus, we first consider the full Earth system sensitivity.

Earth system sensitivity (ESS)

The Cenozoic era—the past 66 million years—provides an opportunity to study Earth system sensitivity via a consistent analysis for climate ranging from hothouse conditions with Earth 15°C warmer and sea level 60 m higher than preindustrial climate to glacial conditions with Earth 7°C cooler and sea level 120 m lower than preindustrial. Atmospheric CO 2 amount in the past 800 000 years ( Fig. 2 ), confirms expectation that CO 2 is the main control knob [ 87 ] on global temperature. We can assume this control existed when CO 2 amount varied due to CO 2 emissions caused by plate tectonics (continental drift). The two-step [ 91 ] that the Indian plate executed as it moved through the Tethys (now Indian) ocean left a signature in atmospheric CO 2 and global temperature. CO 2 emissions from subduction of ocean crust were greatest when the Indian plate was moving fastest (inset, Fig. 6 ) and peaked at its hard collision with the Eurasian plate at 50 MyBP. Diminishing metamorphic CO 2 emissions continue as the Indian plate is subducted beneath the Eurasian plate, pushing up the Himalayan Mountains, but carbon drawdown from weathering and burial of organic carbon exceeds emissions. Motion of the Indian Plate thus dominates the broad sweep of Cenozoic CO 2 , but igneous provinces play a role. The North Atlantic Igneous Province (caused by a rift in the sea floor as Greenland pulled away from Europe) that triggered the Paleocene-Eocene Thermal Maximum (PETM) event about 56 MyBP and the Columbia River Flood Basalt about 15 MyBP ( Fig. 6 ) are most notable.

We infer the Cenozoic history of sea surface temperature (SST) at sites of deepwater formation from the oxygen isotope δ 18 O in shells of deep-ocean-dwelling foraminifera preserved in ocean sediments [ 44 , 90 ]. High latitude SST change—including a correction term as SST approaches the freezing point—provides an accurate estimate of global surface temperature change. This Cenozoic temperature history and climate sensitivity inferred from the LGM cooling yield an estimate of Cenozoic CO 2 history. We suggest that this whole-Cenozoic approach may define the CO 2 history ( Fig. 9a ) more accurately than CO 2 proxy measurements. We find CO 2 about 325 ppm in the early Pliocene and 450 ppm at transition to glaciated Antarctica. Global climate models (GCMs) that isolate on the Pliocene tend to use CO 2 levels of order 400 ppm in attempts to match actual Pliocene warmth and ice sheet models use CO 2 of order 700 ppm or greater to achieve ice sheet disintegration on Antarctica, which suggests that the models are not realistically capturing amplifying feedback processes (see Cenozoic CO 2 section).

The Cenozoic provides a perspective on present greenhouse gas (GHG) levels. The dashed line in Fig. 23 is the ‘we are here’ level of GHG climate forcing. Today’s GHG forcing of 4.6 W/m 2 is relative to mid-Holocene CO 2 of 260 ppm; we present evidence in Cenozoic CO 2 section that 260 ppm is the natural Holocene CO 2 level. Human-caused GHG forcing today is already above the level needed to deglaciate Antarctica, if such forcing is left in place long enough. We do not predict full deglaciation of Antarctica on a time scale people care about—rather we draw attention to how far today’s climate is out of equilibrium with today’s GHG level. This is one measure of how strongly humanity is pushing the climate system. Stabilizing climate requires removing the disequilibrium by reducing human-made climate forcing. A danger is that it will become difficult or implausible to prevent large sea level rise, if deglaciation is allowed to get well underway.

Forcing required to yield Cenozoic temperature for today’s solar irradiance, compared with human-made GHG forcing in 2022.

GHGs are not the only large human-made climate forcing. Understanding of ongoing climate change requires that we also include the effect of aerosols (fine airborne particles).

Aerosol climate forcing is larger than the IPCC AR6 estimate and has likely been significant for millennia. We know of no other persuasive explanation for absence of global warming in the last half of the Holocene ( Fig. 14 ) as GHG forcing increased 0.5 W/m 2 ( Fig. 15 ). Climate models without a growing negative aerosol forcing yield notable warming in that period [ 173 ], a warming that, in fact, did not occur. Negative aerosol forcing, increasing as civilization developed and population grew, is expected. As humans burned fuels at a growing rate—wood and other biomass for millennia and fossil fuels in the industrial era—aerosols as well as GHGs were an abundant, growing, biproduct. The aerosol source from wood-burning has continued in modern times [ 146 ]. GHGs are long-lived and accumulate, so their forcing dominates eventually, unless aerosol emissions grow higher and higher—the Faustian bargain [ 98 ].

Multiple lines of evidence show that aerosol forcing peaked early this century [ 174 ]. Emissions from the largest sources, China and India, were increasing in 2000, but by 2010 when the first limits on ship emissions were imposed, China’s emissions were declining. We estimate peak (negative) aerosol forcing as at least 1.5–2 W/m 2 , with turning point at 2010, consistent with Fig. 3 of Bauer et al . [ 175 ] GHG plus aerosol forcing grew +0.3 W/m 2 per decade (GHGs: +0.45, aerosols: –0.15) during 1970–2010, which produced warming of 0.18°C per decade. With current policies, we expect climate forcing for a few decades post-2010 to increase 0.5–06 W/m 2 per decade and produce global warming of at least +0.27°C per decade. In that case, global warming will reach 1.5°C in the 2020s and 2°C before 2050 ( Fig. 24 ). Such acceleration is dangerous in a climate system that is already far out of equilibrium and dominated by multiple amplifying feedbacks.

Global temperature relative to 1880–1920. Edges of the predicted post-2010 accelerated warming rate (see text) are 0.36 and 0.27°C per decade.

The sharp change of ship emissions in 2020 (The great inadvertent aerosol experiment section) provides an indirect measure of aerosol effects. Diamond [ 176 ] finds a cloud brightness decrease of order 1 W/m 2 in a shipping corridor. We find a larger effect, increased absorption of about 3 W/m 2 in regions of heavy ship traffic in the North Atlantic and North Pacific ( Fig. 22 ), but a longer record is needed to define significance. However, the single best sentinel for global climate change is Earth’s energy imbalance.

Earth’s energy imbalance

Earth’s energy imbalance (EEI) is the net gain (or loss) of energy by the planet, the difference between absorbed solar energy and emitted thermal (heat) radiation. As long as EEI is positive, Earth will continue to get hotter. EEI is hard to measure, a small difference between two large quantities (Earth absorbs and emits about 240 W/m 2 averaged over the entire planetary surface), but change of EEI can be well-measured from space [ 81 ]. Absolute calibration is from the change of heat in the heat reservoirs, mainly the global ocean, over a period of at least a decade, as needed to reduce error due to the finite number of places that the ocean is sampled [ 80 ]. EEI varies year-to-year ( Fig. 25 ), largely because global cloud amount varies with weather and ocean dynamics, but averaged over several years EEI helps inform us about what is needed to stabilize climate.

12-month running-mean of Earth’s energy imbalance from CERES satellite data [ 81 ] normalized to 0.71 W/m 2 mean for July 2005–June 2015 (blue bar) from in situ data [ 80 ].

The data indicate that EEI has doubled since the first decade of this century ( Fig. 25 ). This increase is one basis for our prediction of post-2010 acceleration of the global warming rate. The EEI increase may be partly due to restrictions on maritime aerosol precursor emissions imposed in 2015 and 2020 (The great inadvertent aerosol experiment section), but the growth rate of GHG climate forcing also increased in 2015 and since has remained at the higher level (Equilibrium warming versus committed warming section).

Reduction of climate forcing needed to reduce EEI to zero is greater than EEI because of ultrafast cloud feedback (Slow, fast and ultrafast feedbacks section), but the magnitude of this effect is uncertain (SM6). Cloud feedbacks are only beginning to be simulated well, but climate sensitivity near 1.2°C per W/m 2 implies that the net cloud feedback is large and deserves greater attention. Precise monitoring of EEI is essential as a sentinel for future climate change and to assess efforts to stabilize climate and avoid undesirable consequences. Global satellite monitoring of geographical and temporal changes of EEI and ocean in situ monitoring (especially in polar regions of rapid change) are both needed for the sake of understanding ongoing climate change.

Equilibrium warming versus committed warming

Equilibrium warming for today’s climate forcing is the warming required to restore Earth’s energy balance if atmospheric composition is fixed at today’s conditions. Equilibrium warming is a benchmark that can be evaluated from atmospheric composition and paleoclimate data, with little involvement of climate models. It is the standard benchmark used in definition of the Charney ECS (equilibrium climate sensitivity excluding slow feedbacks) [ 4 ] and ESS (Earth system sensitivity, which includes slow feedbacks such as ice sheet size) [ 71 ]. GHG climate forcing now is 4.6 W/m 2 relative to the mid-Holocene (7 kyBP) or 4.1 W/m 2 relative to 1750. There is little merit in debating whether GHG forcing is 4.6 or 4.1 W/m 2 because it is still increasing 0.5 W/m 2 per decade (Perspective on policy implications section). ECS response to 4.6 W/m 2 forcing for climate sensitivity 1.2°C per W/m 2 is 5.5°C. The eventual Earth system response (ESS) to sustained 4.6 W/m 2 forcing is about 10°C (Earth system sensitivity section), because that forcing is large enough to deglaciate Antarctica ( Fig. 23 ). Net human-made forcing today is probably near 3 W/m 2 due to negative aerosol forcing. Even 3 W/m 2 may be sufficient to largely deglaciate Antarctica, if the forcing is left in place permanently ( Fig. 23 ).

‘Committed warming’ is less precisely defined; even in the current IPCC report [ 12 ] (p. 2222) it has multiple definitions. One concept is the warming that occurs if human-made GHG emissions cease today, but that definition is ill-posed as well as unrealistic. Do aerosol emissions also cease? That would cause a sudden leap in Earth’s energy imbalance, a ‘termination shock,’ as the cooling effect of human-made aerosols disappears. A more useful definition is the warming that will occur with plausibly rapid phasedown of GHG emissions, including comparison with ongoing reality. However, the required ‘integrated assessment models,’ while useful, are complex and contain questionable assumptions that can mislead policy (see Perspective on policy implications section).

Nature’s capacity for restoration provides hope that future warming can be limited, if humanity moves promptly toward sustainable energy and climate policies. Earth’s ability to remove human-made CO 2 emissions from the atmosphere is revealed by Fig. 26 . Fossil fuel emissions now total more than 10 GtC/year, which is almost 5 ppm of CO 2 , yet CO 2 in the air is only increasing 2.5 ppm/year. The other half is being taken up by the ocean, solid land, and biosphere. Indeed, Earth is taking up even more because deforestation, fires, and poor agricultural and forestry practices are additional human-made CO 2 sources. If human emissions ceased, atmospheric CO 2 would initially decline a few ppm per year, but uptake would soon slow—it would take millennia for CO 2 to reach preindustrial levels [ 131 ]. This underscores the difficulty of restoring Earth’s energy balance via emission reductions alone. Furthermore, fossil fuels have raised living standards in most of the world and still provide 80% of the world’s energy, which contributes to a policy inertia. As the reality of climate change emerges, the delayed response of climate and amplifying feedbacks assure that the world has already set sail onto even more turbulent climate seas. Scientists must do their best to help the public understand policy options that may preserve and restore a propitious climate for future generations.

Fossil fuel emissions divided into portions appearing in the annual increase of airborne CO 2 and the remainder, which is taken up by the ocean and land (1 ppm CO 2  ∼ 2.12 GtC).

This section is the first author’s perspective based on more than 20 years of experience on policy issues that began with a paper [ 179 ] and two workshops [ 180 ] that he organized at the East-West Center in Hawaii, followed by meetings and workshops with utility experts and trips to more than a dozen nations for discussions with government officials, energy experts, and environmentalists. The aim was to find a realistic scenario with a bright energy and climate future, with emphasis on cooperation between the West and nations with emerging or underdeveloped economies.

Energy, CO 2 and the climate threat

The world’s energy and climate path has good reason: fossil fuels powered the industrial revolution and raised living standards. Fossil fuels still provide most of the world’s energy ( Fig. 27a ) and produce most CO 2 emissions ( Fig. 27b ). Much of the world is still in early or middle stages of economic development. Energy is needed and fossil fuels are a convenient, affordable source of energy. One gallon (3.8 l) of gasoline (petrol) provides the work equivalent of more than 400 h labor by a healthy adult. These benefits are the basic reason for continued high emissions. The Covid pandemic dented emissions in 2020, but 2022 global emissions were a record high level. Fossil fuel emissions from mature economies are beginning to fall due to increasing energy efficiency, introduction of carbon-free energies, and export of manufacturing from mature economies to emerging economies. However, at least so far, those reductions have been more than offset by increasing emissions in developing nations ( Fig. 28 ).

Global energy consumption and CO 2 emissions (Hefner at al . [ 177 ] and Energy Institute [ 178 ]).

Fossil fuel CO 2 emissions from mature and emerging economies. China is counted as an emerging economy. Data sources as in Fig. 27 .

The potential for rising CO 2 to be a serious threat to humanity was the reason for the 1979 Charney report, which confirmed that climate was likely sensitive to expected CO 2 levels in the 21st century. In the 1980s it emerged that high climate sensitivity implied a long delay between changing atmospheric composition and the full climate response. Ice core data revealed the importance of amplifying climate feedbacks. A climate characterized by delayed response and amplifying feedbacks is especially dangerous because the public and policymakers are unlikely to make fundamental changes in world energy systems until they see visible evidence of the threat. Thus, it is incumbent on scientists to make this situation clear to the public as soon as possible. That task is complicated by the phenomenon of scientific reticence.

Scientific reticence

Bernard Barber decried the absence of attention to scientific reticence, a tendency of scientists to resist scientific discovery or new ideas [ 139 ]. Richard Feynman needled fellow physicists about their reticence to challenge authority [ 181 ], specifically to correct the electron charge that Millikan derived in his famous oil drop experiment. Later researchers moved Millikan’s result bit by bit—experimental uncertainties allow judgment—reaching an accurate result only after years. Their reticence embarrassed the physics community but caused no harm to society. A factor that may contribute to reticence among climate scientists is ‘delay discounting:’ preference for immediate over delayed rewards [ 182 ]. The penalty for ‘crying wolf’ is immediate, while the danger of being blamed for ‘fiddling while Rome was burning’ is distant. One of us has noted [ 183 ] that larding of papers and proposals with caveats and uncertainties increases chances of obtaining research support. ‘Gradualism’ that results from reticence is comfortable and well-suited for maintaining long-term support. Gradualism is apparent in IPCC’s history in evaluating climate sensitivity as summarized in our present paper. Barber identifies professional specialization—which causes ‘outsiders’ to be ignored by ‘insiders’—as one cause of reticence; specialization is relevant to ocean and ice sheet dynamics, matters upon which the future of young people hangs.

Discussion [ 184 ] with field glaciologists 13 20 years ago revealed frustration with IPCC’s ice sheet assessment. One glaciologist said—about a photo [ 185 ] of a moulin (a vertical shaft that carries meltwater to the base of the Greenland ice sheet)—‘the whole ice sheet is going down that damned hole!’ Concern was based on observed ice sheet changes and paleoclimate evidence of sea level rise by several meters in a century, implying that ice sheet collapse is an exponential process. Thus, as an alternative to ice sheet models, we carried out a study described in Ice Melt [ 13 ]. In a GCM simulation, we added a growing freshwater flux to the ocean surface mixed layer around Greenland and Antarctica, with the flux in the early 21st century based on estimates from in situ glaciological studies [ 186 ] and satellite data on sea level trends near Antarctica [ 187 ]. Doubling times of 10 and 20 years were used for the growth of freshwater flux. One merit of our GCM was reduced, more realistic, small-scale ocean mixing, with a result that Antarctic Bottom Water formed close to the Antarctic coast [ 13 ], as in the real world. Growth of meltwater and GHG emissions led to shutdown of the North Atlantic and Southern Ocean overturning circulations, amplified warming at the foot of the ice shelves that buttress the ice sheets, and other feedbacks consistent with ‘nonlinearly growing sea level rise, reaching several meters in 50–150 years’ [ 13 ]. Shutdown of ocean overturning circulation occurs this century, as early as midcentury. The 50–150-year time scale for multimeter sea level rise is consistent with the 10–20-year range for ice melt doubling time. Real-world ice melt will not follow a smooth curve, but its growth rate is likely to accelerate in coming years due to increasing heat flux into the ocean ( Fig. 25 ).

We submitted Ice Melt to a journal that makes reviews publicly available [ 188 ]. One reviewer, an IPCC lead author, seemed intent on blocking publication, while the other reviewer described the paper as a ‘masterwork of scholarly synthesis, modeling virtuosity, and insight, with profound implications’. Thus, the editor obtained additional reviewers, who recommended publication. Promptly, an indictment was published [ 189 ] of our conclusion that continued high GHG emissions would cause shutdown of the AMOC (Atlantic Meridional Overturning Circulation) this century. The 15 authors, representing leading GCM groups, used 21 climate projections from eight ‘…state-of-the-science, IPCC class…’ GCMs to conclude that ‘…the probability of an AMOC collapse is negligible. This is contrary to a recent modeling study [ Hansen et al . , 2016 ] that used a much larger, and in our assessment unrealistic, Northern Hemisphere freshwater forcing… According to our probabilistic assessment, the likelihood of an AMOC collapse remains very small (<1% probability) if global warming is below ∼ 5K…’[ 189 ]. They treated the ensemble of their model results as if it were the probability distribution for the real world.

In contrast, we used paleoclimate evidence, global modeling, and ongoing climate observations. Paleoclimate data [ 190 ] showed that AMOC shutdown is not unusual and occurred in the Eemian (when global temperature was similar to today), and also that sea level in the Eemian rose a few meters within a century [ 191 ] with the likely source being collapse of the West Antarctic ice sheet. Although we would not assert that our model corrected all excessive ocean mixing, the higher vertical resolution and improved mixing increased the sensitivity to freshwater flux, as confirmed in later tests [ 192 ]. Modern observations showed and continue to add evidence that the overturning Southern Ocean [ 193 , 194 ] and North Atlantic [ 195 ] are already slowing. Growth of meltwater injection onto the Southern [ 196 ] and North Atlantic Oceans [ 197 ] is consistent with a doubling time of 10–20 years. High climate sensitivity inferred in our present paper also implies there will be a greater increase of precipitation on polar oceans than that in most climate models.

The indictment of Ice Melt by Bakker et al . [ 189 ] was accepted by the research community. Papers on the same topics ignored our paper or referred to it parenthetically with a note that we used unrealistic melt rates, even though these were based on observations. Ice Melt was blackballed in IPCC’s AR6 report, which is a form of censorship [ 14 ]. Science usually acknowledges alternative views and grants ultimate authority to nature. In the opinion of our first author, IPCC does not want its authority challenged and is comfortable with gradualism. Caution has merits, but the delayed response and amplifying feedbacks of climate make excessive reticence a danger. Our present paper—via revelation that the equilibrium response to current atmospheric composition is a nearly ice-free Antarctica—amplifies concern about locking in nonlinearly growing sea level rise. Also, our conclusion that CO 2 was about 450 ppm at Antarctic glaciation disparages ice sheet models. Portions of the ice sheets may be recalcitrant to rapid change, but enough ice is in contact with the ocean to provide of the order of 25 m (80 feet) of sea level rise. Thus, if we allow a few meters of sea level rise, we may lock in much larger sea level rise.

Climate change responsibilities

The industrial revolution began in the U.K., which was the largest source of fossil fuel emissions in the 19th century ( Fig. 29a ), but development soon moved to Germany, the rest of Europe, and the U.S. Nearly half of global emissions were from the U.S. in the early 20th century, and the U.S. is presently the largest source of cumulative emissions ( Fig. 29b ) that drive climate change [ 198 , 199 ]. Mature economies, mainly in the West, are responsible for most cumulative emissions, especially on a per capita basis ( Fig. 30 ). Growth of emissions is now occurring in emerging economies ( Figs 28 and 29a ). China’s cumulative emissions will eventually pass those of the U.S. in the absence of a successful effort to replace coal with carbon-free energy.

Fossil fuel CO 2 emissions by nation or region as a fraction of global emissions. Data sources as in Fig. 27 .

Cumulative per capita national fossil fuel emissions [ 200 ].

Greenhouse gas emissions situation

The United Nations uses a target for maximum global warming to cajole progress in limiting climate change. The 2015 Paris Agreement [ 201 ] aimed to hold ‘the increase in the global average temperature to well below 2°C above the pre-industrial levels and pursue efforts to limit the temperature increase to 1.5°C above the pre-industrial levels.’ The IPCC AR5 report added a climate forcing scenario, RCP2.6, with a rapid decrease of GHG climate forcings, as needed to prevent global warming from exceeding 2°C. Since then, a gap between that scenario and reality opened and is growing ( Fig. 31 ). The 0.03 W/m 2 gap in 2022 could be closed by extracting CO 2 from the air. However, required negative emissions (CO 2 extracted from the air and stored permanently) must be larger than the desired atmospheric CO 2 reduction by a factor of about 1.7 [ 63 ]. Thus, the required CO 2 extraction is 2.1 ppm, which is 7.6 GtC. Based on a pilot direct-air carbon capture plant, Keith [ 202 ] estimates an extraction cost of $450–920 per tC, as clarified elsewhere [ 203 ]. Keith’s cost range yields an extraction cost of $3.4–7.0 trillion. That covers excess emissions in 2022 only; it is an annual cost. Given the difficulty the UN faced in raising $0.1 trillion for climate purposes and the growing emissions gap ( Fig. 31 ), this example shows the need to reduce emissions as rapidly as practical and shows that carbon capture cannot be viewed as the solution, although it may play a role in a portfolio of policies, if its cost is driven down.

Annual growth of climate forcing by GHGs [ 38 ] including part of O 3 forcing not included in CH 4 forcing ( Supplementary Material ). MPTG and OTG are Montreal Protocol and Other Trace Gases.

IPCC (Intergovernmental Panel on Climate Change), the scientific body advising the world on climate, has not bluntly informed the world that the present precatory policy approach will not keep warming below 1.5°C or even 2°C. The ‘tragedy of the commons’ [ 204 ] is that, as long as fossil fuel pollution can be dumped in the air free of charge, agreements such as the Kyoto Protocol [ 205 ] and Paris Agreement have limited effect on global emissions. Political leaders profess ambitions for dubious net-zero emissions while fossil fuel extraction expands. IPCC scenarios that phase down human-made climate change amount to ‘a miracle will occur’. The IPCC scenario that moves rapidly to negative global emissions (RCP2.6) has vast biomass-burning powerplants that capture and sequester CO 2 , a nature-ravaging, food-security-threatening [ 206 ], proposition without scientific and engineering credibility and without a realistic chance of being deployed at scale and on time to address the climate threat.

Climate and energy policy

Climate science reveals the threat of being too late. ‘Being too late’ refers not only to warning of the climate threat, but also to technical advice on policy implications. Are we scientists not complicit if we allow reticence and comfort to obfuscate our description of the climate situation? Does our training, years of graduate study and decades of experience, not make us well-equipped to advise the public on the climate situation and its policy implications? As professionals with deep understanding of planetary change and as guardians of young people and their future, do we not have an obligation, analogous to the code of ethics of medical professionals, to render to the public our full and unencumbered diagnosis? That is our objective.

The basis for the following opinions of the first author, to the extent not covered in this paper, will be described in a book in preparation [ 2 ]. We are in the early phase of a climate emergency. The present huge planetary energy imbalance assures that climate will become less tolerable to humanity, with greater climate extremes, before it is feasible to reverse the trend. Reversing the trend is essential—we must cool the planet—for the sake of preserving shorelines and saving the world’s coastal cities. Cooling will also address other major problems caused by global warming. We should aim to return to a climate like that in which civilization developed, in which the nature that we know and love thrived. As far as is known, it is still feasible to do that without passing through irreversible disasters such as many-meter sea level rise.

Abundant, affordable, carbon-free energy is essential to achieve a world with propitious climate, while recognizing the rights and aspirations of all people. The staggering magnitude of the task is implied by global and national carbon intensities: carbon emissions per unit energy use ( Fig. 32 ). Global carbon intensity must decline to near zero over the next several decades. This chart—not vaporous promises of net zero future carbon emissions inserted in integrated assessment models—should guide realistic assessment of progress toward clean energy. Policy must include apolitical targeting of support for development of low-cost carbon-free energy. All nations would do well to study strategic decisions of Sweden, which led past decarbonization efforts ( Fig. 32 ) and is likely to lead in the quest for zero or negative carbon intensity that will be needed to achieve a bright future for today’s young people and future generations.

Carbon intensity (carbon emissions per unit energy use) of several nations and the world. Mtoe = megatons of oil equivalent. Data sources as in Fig. 27 .

Given the global situation that we have allowed to develop, three actions are now essential.

First, underlying economic incentives must be installed globally to promote clean energy and discourage CO 2 emissions. Thus, a rising price on GHG emissions is needed, enforced by border duties on products from nations without a carbon fee. Public buy-in and maximum efficacy require the funds to be distributed to the public, which will also address wealth disparity. Economists in the U.S. support carbon fee-and-dividend [ 207 ]; college and high school students join in advocacy [ 208 ]. A rising carbon price creates a level playing field for energy efficiency, renewable energy, nuclear power, and innovations; it would spur the thousands of ‘miracles’ needed for energy transition. However, instead, fossil fuels and renewable energy are now subsidized. Thus, nuclear energy has been disadvantaged and excluded as a ‘clean development mechanism’ under the Kyoto Protocol, based on myths about nuclear energy unsupported by scientific fact [ 209 ]. A rising carbon price is crucial for decarbonization, but not enough. Long-term planning is needed. Sweden provides an example: 50 years ago, its government decided to replace fossil fuel power stations with nuclear energy, which led to its extraordinary and rapid decarbonization ( Fig. 32 ).

Second, global cooperation is needed. De facto cooperation between the West and China drove down the price of renewable energy. Without greater cooperation, developing nations will be the main source of future GHG emissions ( Fig. 28 ). Carbon-free, dispatchable electricity is a crucial need. Nations with emerging economies are eager to have modern nuclear power because of its small environmental footprint. China-U.S. cooperation to develop low-cost nuclear power was proposed, but stymied by U.S. prohibition of technology transfer [ 210 ]. Competition is normal, but it can be managed if there is a will, reaping benefits of cooperation over confrontation [ 211 ]. Of late, priority has been given instead to economic and military hegemony, despite recognition of the climate threat, and without consultation with young people or seeming consideration of their aspirations. Scientists can support an ecumenical perspective of our shared future by expanding international cooperation. Awareness of the gathering climate storm will grow this decade, so we must increase scientific understanding worldwide as needed for climate restoration.

Third, we must take action to reduce and reverse Earth’s energy imbalance. Highest priority is to phase down emissions, but it is no longer feasible to rapidly restore energy balance via only GHG emission reductions. Additional action is almost surely needed to prevent grievous escalation of climate impacts including lock-in of sea level rise that could destroy coastal cities world-wide. At least several years will be needed to define and gain acceptance of an approach for climate restoration. This effort should not deter action on mitigation of emissions; on the contrary, the concept of human intervention in climate is distasteful to many people, so support for GHG emission reductions will likely increase. Temporary solar radiation management (SRM) will probably be needed, e.g. via purposeful injection of atmospheric aerosols. Risks of such intervention must be defined, as well as risks of no intervention; thus, the U.S. National Academy of Sciences recommends research on SRM [ 212 ]. The Mt. Pinatubo eruption of 1991 is a natural experiment [ 213 , 214 ] with a forcing that reached [ 30 ] –3 W/m 2 . Pinatubo deserves a coordinated study with current models. The most innocuous aerosols may be fine salty droplets extracted from the ocean and sprayed into the air by autonomous sailboats [ 215 ]. This approach has been discussed for potential use on a global scale [ 216 ], but it needs research into potential unintended effects [ 217 ]. This decade may be our last chance to develop the knowledge, technical capability, and political will for actions needed to save global coastal regions from long-term inundation.

Politics and climate change

Actions needed to drive carbon intensity to zero—most important a rising carbon fee—are feasible, but not happening. The first author gained perspective on the reasons why during trips to Washington, DC, and to other nations at the invitation of governments, environmentalists, and, in one case, oil executives in London. Politicians from right (conservative) and left (progressive) parties are affected by fossil fuel interests. The right denies that fossil fuels cause climate change or says that the effect is exaggerated. The left takes up the climate cause but proposes actions with only modest effect, such as cap-and-trade with offsets, including giveaways to the fossil fuel industry. The left also points to work of Amory Lovins as showing that energy efficiency plus renewables (mainly wind and solar energy) are sufficient to phase out fossil fuels. Lovins says that nuclear power is not needed. It is no wonder that the President of Shell Oil would write a foreword with praise for Lovins’ book, Reinventing Fire [ 218 ], and that the oil executives in London did not see Lovins’ work as a threat to their business.

Opportunities for progress often occur in conjunction with crises. Today, the world faces a crisis—political polarization, especially in the United States—that threatens effective governance. Yet the crisis offers an opportunity for young people to help shape the future of the nation and the planet. Ideals professed by the United States at the end of World War II were consummated in formation of the United Nations, the World Bank, the Marshall Plan, and the Universal Declaration of Human Rights. Progress toward equal rights continued, albeit slowly. The ‘American dream’ of economic opportunity was real, as most people willing to work hard could afford college. Immigration policy welcomed the brightest; NASA in the 1960s invited scientists from European countries, Japan, China, India, Canada, and those wanting to stay found immigration to be straightforward. But the power of special interests in Washington grew, government became insular and inefficient, and Congress refused to police itself. Their first priority became reelection and maintenance of elite status, supported by special interests. Thousands of pages of giveaways to special interests lard every funding bill, including the climate bill titled ‘Inflation Reduction Act’—Orwellian double-speak—as the funding is borrowed from young people via deficit spending. The public is fed up with the Washington swamp but hamstrung by rigid two-party elections focused on a polarized cultural war.

A political party that takes no money from special interests is essential to address political polarization, which is necessary if the West is to be capable of helping preserve the planet and a bright future for coming generations. Young people showed their ability to drive an election—via their support of Barack Obama in 2008 and Bernie Sanders in 2016—without any funding from special interests. Groundwork is being laid to allow third party candidates in 2026 and 2028 elections in the U.S. Ranked voting is being advocated in every state to avoid the ‘spoiler’ effect of a third party. It is asking a lot to expect young people to grasp the situation that they have been handed—but a lot is at stake. As they realize that they are being handed a planet in decline, the first reaction may be to stamp their feet and demand that governments do better, but that has little effect. Nor is it sufficient to parrot big environmental organizations, which are now part of the problem, as they are partly supported by the fossil fuel industry and wealthy donors who are comfortable with the status quo. Instead, young people have the opportunity to provide the drive for a revolutionary third party that restores democratic ideals while developing the technical knowledge that is needed to navigate the stormy sea that their world is setting out upon.

We thank Eelco Rohling for inviting JEH to describe our perspective on global climate response to human-made forcing. JEH began to write a review of past work, but a paper on the LGM by Jessica Tierney et al . [ 49 ] and data on changing ship emissions provided by Leon Simons led to the need for new analyses and division of the paper into two parts. We thank Jessica also for helpful advice on other related research papers, Jim Zachos and Thomas Westerhold for explanations of their data and interpretations, Ed Dlugokencky of the NOAA Earth System Research Laboratory for continually updated GHG data, and David Arthur for pointing out the paper by Steinberger et al . JEH designed the study and carried out the research with help of Makiko Sato and Isabelle Sangha; Larissa Nazarenko provided data from GISS models and helped with analysis; Leon Simons provided ship emission information and aided interpretations; Pushker Kharecha provided critical review of the paper; James Zachos provided critical interpretation of ocean core data needed for interpretation of Cenozoic climate; Norman Loeb and Karina von Schuckmann provided EEI data and insight about implications; Matthew Osman provided paleoclimate data and an insightful review of an early draft paper; Qinjian Jin provided simulations of atmospheric sulfate and interpretations; Eunbi Jeong reviewed multiple drafts and advised on presentation; all authors contributed to our research summarized in the paper and reviewed and commented on the manuscript. Climate Science, Awareness and Solutions, which is directed by JEH and supports MS and PK is a 501(C3) nonprofit supported 100% by public donations. Principal supporters in the past few years have been the Grantham Foundation, Frank Batten, Eric Lemelson, James and Krisann Miller, Carl Page, Peter Joseph, Ian Cumming, Gary and Claire Russell, Donald and Jeanne Keith Ferris, Aleksandar Totic, Chris Arndt, Jeffrey Miller, Morris Bradley and about 150 more contributors to annual appeals.

Supplementary data are available at Oxford Open Climate Change online.

The authors declare that they have no conflict of interest.

The data used to create the Figs in this paper are available in the Zenodo repository, at https://zenodo.org/record/8419583 .

James Hansen (Conceptualization [lead], Data curation [equal], Formal analysis [lead], Funding acquisition [lead], Investigation [lead], Methodology [lead], Project administration [lead], Resources [lead], Software [equal], Supervision [lead], Validation [lead], Visualization [equal], Writing—original draft [lead], Writing—review and editing [lead]), Makiko Sato (Data curation [equal], Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Project administration [supporting], Resources [supporting], Software [equal], Supervision [supporting], Validation [supporting], Visualization [equal], Writing—original draft [supporting], Writing—review and editing [supporting]), Leon Simons (Data curation [supporting], Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Visualization [supporting], Writing—review and editing [supporting]), Larissa S. Nazarenko (Data curation [supporting], Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Visualization [supporting], Writing—review and editing [supporting]), Isabelle Sangha (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), Pushker Kharecha (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), James Zachos (Data curation [supporting], Resources [supporting], Writing—review and editing [supporting]), Karina von Schuckmann (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), Norman G. Loeb (Data curation [supporting], Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Visualization [supporting], Writing—review and editing [supporting]), Matthew B. Osman (Data curation [supporting], Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Visualization [supporting], Writing—review and editing [supporting)], Qinjian Jin (Data curation [supporting], Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Visualization [supporting], Writing—review and editing [supporting]), George Tselioudis (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Writing—review and editing [supporting]), Eunbi Jeong (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), Andrew Lacis (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), Reto Ruedy (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), Gary Russell (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), Junji Cao (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]), Jing Li (Formal analysis [supporting], Investigation [supporting], Methodology [supporting], Resources [supporting], Software [supporting], Supervision [supporting], Validation [supporting], Writing—review and editing [supporting]).

Drafts of the chapters of Sophie’s Planet relevant to climate sensitivity are available here ; criticisms are welcome.

David EE, Jr later became a global warming denier.

GISS (2020) model is described as GISS-E2.1-G-NINT in published papers; NINT (noninteractive) signifies that the models use specified GHG and aerosol amounts.

An imbalance of 1 W/m 2 for a millennium is enough energy to melt ice raising sea level 110 m or to raise the temperature of the ocean’s upper kilometer by 11°C.

Tom Delworth (NOAA Geophysical Fluid Dynamics Laboratory), Gokhan Danabasoglu (National Center for Atmospheric Research), and Jonathan Gregory (UK Hadley Centre) kindly provided long 2 × CO 2 runs of GCMs of these leading modeling groups. All three models had response time as slow or slower than the GISS GCM.

The GISS (2014) model is labeled as GISS-E2-R-NINT and GISS (2020) as GISS-E2.1-G-NINT in published papers, where NINT (noninteractive) signifies that the models use specified GHG and aerosol amounts.

In Swedish, trapps are stairs. Basalt formations are commonly in layers from multiple extrusions.

Small apparent discrepancy is roundoff. CO 2 forcing is 9.13 W/m 2 and solar forcing is −1.16 W/m 2 at 50 MyBP.

Forcing = 4.6 W/m 2 assumes that the increase of non-CO 2 GHGs is human-made. This is true for CFCs and most trace gases, but a small part of CH 4 and N 2 O growth could be a slow feedback, slightly reducing the GHG forcing.

9.9°C for ECS = 1.2°C per W/m 2 ; 10.1°C for ECS = 1.22°C per W/m 2 (the precise ECS for 7°C LGM cooling).

Two significant flaws in the derivation of this ‘alternative aerosol scenario’ were largely offsetting: (1) the intermediate climate response function employed was too ‘fast’, but (2) this was compensated by use of a low climate sensitivity of 3°C for 2 × CO 2 .

In the absence of a response function from a GCM with ECS = 4°C, we use the normalized response function of the GISS (2020) model and put λ = 1°C per W/m 2 in Equation (5) .

Jay Zwally, Eric Rignot, Konrad Steffen, and Roger Braithwaite.

Tyndall J. On the absorption and radiation of heat by gases and vapours . Phil Mag 1861 ; 22 : 169 – 194 , 273 – 285 .

Google Scholar

Hansen J. Greenhouse Giants, Chapter 15 in Sophie’s Planet . New York : Bloomsbury , 2024 .

Google Preview

Revelle R , Broecker W , Craig H et al.  Appendix Y4 atmospheric carbon dioxide. In: Hornig J, York HF, Branscomb LM et al. (eds,) President’s Science Advisory Committee. Restoring the Quality of Our Environment . Washington : The White House , 1965 , 111 – 33 .

Charney J , Arakawa A , Baker D et al.  Carbon Dioxide and Climate: A Scientific Assessment . Washington : National Academy of Sciences Press , 1979 .

Nierenberg WA. Changing Climate: Report of the Carbon Dioxide Assessment Committee . Washington : National Academies Press , 1983 .

Hansen JE , Takahashi T (eds). AGU Geophysical Monograph 29 Climate Processes and Climate Sensitivity . Washington : American Geophysical Union , 1984 .

Hansen J , Lacis A , Rind D et al.  Climate sensitivity: analysis of feedback mechanisms. In: Hansen JE, Takahashi T (eds), AGU Geophysical Monograph 29 Climate Processes and Climate Sensitivity . Washington : American Geophysical Union , 1984 , 130 – 63 .

David EE Jr . Inventing the future: energy and the CO 2 “Greenhouse Effect”. In: Hansen JE, Takahashi T (eds). AGU Geophysical Monograph 29 Climate Processes and Climate Sensitivity . Washington : American Geophysical Union , 1984 , 1 – 5 .

Oreskes N , Conway E. Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming . London : Bloomsbury , 2010 .

Intergovernmental Panel on Climate Change . History of the IPCC . https://www.ipcc.ch/about/history (date last accessed 7 March 2023).

United Nations Framework Convention on Climate Change . What is the United Nations Framework Convention on Climate Change? https://unfccc.int/process-and-meetings/what-is-the-united-nations-framework-convention-on-climate-change ) (date last accessed 30 November 2022 ).

IPCC . Climate Change 2021: The Physical Science Basis . [Masson-Delmotte V, Zhai P, Pirani A et al.  (eds)], Cambridge and New York : Cambridge University Press , 2021 .

Hansen J , Sato M , Hearty P et al.  Ice melt, sea level rise and superstorms: evidence from paleoclimate data, climate modeling, and modern observations that 2 C global warming could be dangerous . Atmos Chem Phys 2016 ; 16 : 3761 – 812 .

Hansen J. Foreword: uncensored science is crucial for global conservation. In: DellaSala DA (ed), Conservation Science and Advocacy for a Planet in Peril . Amsterdam : Elsevier , 2021 , 451 .

Bode HW. Network Analysis and Feedback Amplifier Design . New York : Van Nostrand , 1945 .

Lacis A , Hansen J , Lee P et al.  Greenhouse effect of trace gases, 1970-1980 . Geophys Res Lett 1981 ; 8 : 1035 – 8 .

CLIMAP Project Members . Seasonal reconstruction of the Earth’s surface at the last glacial maximum. Geol Soc Amer, Map and Chart Series , No. 36, Geological Society of America 1981 .

Manabe S , Stouffer RJ. Sensitivity of a global climate model to an increase of CO 2 concentration in the atmosphere . J Geophys Res 1980 ; 85 : 5529 – 54 .

Manabe S. Carbon dioxide and climate change . Adv Geophys 1983 ; 25 : 39 – 82 .

Klein SA , Hall A , Norris JR et al.  Low-cloud feedbacks from cloud-controlling factors: a review . Surv Geophys 2017 ; 38 : 1307 – 29 .

Sherwood SC , Webb MJ , Annan JD et al.  An assessment of Earth’s climate sensitivity using multiple lines of evidence . Rev Geophys 2020 ; 58 : e2019RG000678 .

Zelinka MD , Zhou C , Klein SA. Insights from a refined decomposition of cloud feedbacks . Geophys Res Lett 2016 ; 43 : 9259 – 69 .

Zelinka M , Tan I , Oreopoulos L et al.  Detailing cloud property feedbacks with a regime-based decomposition . Clim Dyn 2023 ; 60 : 2983 – 3003 .

Rind D , Peteet D. Terrestrial conditions at the last glacial maximum and CLIMAP sea-surface temperature estimates: Are they consistent? Quat Res 1985 ; 24 : 1 – 22 .

Rohling EJ , Marino G , Foster GL et al.  Comparing climate sensitivity, past and present . Ann Rev Mar Sci 2018 ; 10 : 261 – 88 .

IPCC . Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. [ Core Writing Team , Pachauri RK, Meyer LA (eds)]. Geneva : IPCC , 2014 .

Andrews T , Gregory JM , Paynter D et al.  Accounting for changing temperature patterns increases historical estimates of climate sensitivity . Geophys Res Lett 2018 ; 45 : 8490 – 9 .

Rugenstein M , Bloch-Johnson J , Abe-Ouchi A et al.  LongRunMIP: motivation and design for a large collection of millennial-length AOGCM simulations . Bull Amer Meteorol Soc 2019 ; 100 : 2551 – 70 .

Myhre G , Shindell D , Bréon F-M et al.  Anthropogenic and natural radiative forcing. In: Stocker TF, Qin D, Plattner G-K et al.  (eds), Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change . Cambridge and New York : Cambridge University Press , 2013 .

Hansen J , Sato M , Ruedy R et al.  Efficacy of climate forcings . J Geophys Res 2005 ; 110 : D18104 .

Lohmann U , Rotstayn L , Storelvmo T et al.  Total aerosol effect: radiative forcing or radiative flux perturbation? Atmos Chem Phys 2010 ; 10 : 3235 – 46 .

Kelley M , Schmidt GA , Nazarenko L et al.  GISS-E2.1: configurations and climatology . J Adv Model Earth Syst 2020 ; 12 : e2019MS002025 .

Miller RL , Schmidt GA , Nazarenko L et al.  CMIP6 historical simulations (1850-2014) with GISS-E2.1 . J Adv Model Earth Syst 2021 ; 13 : e2019MS002034 .

Eyring V , Bony S , Meehl GA et al.  Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization . Geosci Model Dev 2016 ; 9 : 1937 – 58 .

Lacis AA , Oinas V. A description of the correlated k distributed method for modeling nongray gaseous absorption, thermal emission, and multiple scattering in vertically inhomogeneous atmospheres . J Geophys Res 1991 ; 96 : 9027 – 63 .

Rothman L , Rinsland C , Goldman A et al.  The HITRAN molecular spectroscopic database and HAWKS (HITRAN Atmospheric Workshation) 1996 edition . J Quan Spec Rad Trans 1998 ; 60 : 665 – 710 .

Prather M , Ehhalt D. Chapter 4: Atmospheric chemistry and greenhouse gases. In: Houghton JT (ed), Climate Change 2001: The Scientific Basis . New York : Cambridge University , 2001 , 239 – 87 .

Hansen J , Sato M. Greenhouse gas growth rates . Proc Natl Acad Sci U S A 2004 ; 101 : 16109 – 14 .

Columbia University . MPTG and OTG data : www.columbia.edu/~mhs119/GHGs/TG_F.1900-1990.txt and http://www.columbia.edu/~mhs119/GHGs/TG_F.1992-2021.txt (date last accessed 9 August 2023).

Jouzel J , Masson-Delmotte V , Cattani O et al.  Orbital and millennial Antarctic climate variability over the past 800,000 years . Science 2007 ; 317 : 793 – 6 .

Luthi D , Le Floch M , Bereiter B et al.  High-resolution carbon dioxide concentration record 650,000-800,000 years before present . Nature 2008 ; 453 : 379 – 82 .

Hays JD , Imbrie J , Shackleton NJ. Variation in the Earth’s orbit: pacemaker of the ice ages . Science 1976 ; 194 : 1121 – 32 .

Lorius C , Jouzel J , Raynaud D et al.  The ice-core record: climate sensitivity and future greenhouse warming . Nature 1990 ; 347 : 139 – 45 .

Zachos J , Pagani M , Sloan L et al.  Trends, rhythms, and aberrations in global climate 65 Ma to present . Science 2001 ; 292 : 686 – 93 .

Hansen J , Sato M , Kharecha P et al.  Climate change and trace gases . Philos Trans A Math Phys Eng Sci 2007 ; 365 : 1925 – 54 .

Ruddiman WF , Fuller DQ , Kutzbach JE et al.  Late Holocene climate: natural or anthropogenic? Rev Geophys 2016 ; 54 : 93 – 118 .

Schilt A , Baumgartner M , Schwander J et al.  Atmospheric nitrous oxide during the last 140,000 years . Earth Planet Sci Lett 2010 ; 300 : 33 – 43 .

Hansen J , Nazarenko L , Ruedy R et al.  Earth's energy imbalance: Confirmation and implications . Science 2005 ; 308 : 1431 – 5 .

Tierney JE , Zhu J , King J et al.  Glacial cooling and climate sensitivity revisited . Nature 2020 ; 584 : 569 – 73 .

Osman MB , Tierney JE , Zhu J et al.  Globally resolved surface temperatures since the Last Glacial Maximum . Nature 2021 ; 599 : 239 – 44 .

Seltzer AM , Ng J , Aeschbach W et al.  Widespread six degrees Celsius cooling on land during the Last Glacial Maximum . Nature 2021 ; 593 : 228 – 32 .

Schneider T , Teixeira J , Bretherton CS et al.  Climate goals and computing the future of clouds . Nature Clim Change 2017 ; 7 : 3 – 5 .

Pincus R , Forster PM , Stevens B. The radiative forcing model intercomparison project (RFMIP): experimental protocol for CMIP6 . Geosci Model Dev 2016 ; 9 : 3447 – 60 .

Kageyama M , Braconnot P , Harrison SP et al.  The PMIP4 contribution to CMIP6 – Part 1: overview and over-arching analysis plan . Geosci Model Dev 2018 ; 11 : 1033 – 57 .

Hegerl GC , Zwiers FW , Braconnot P et al.  Chapter 9: Understanding and attributing climate change. In: Solomon SD (ed), Climate Change 2007: The Physical Science Basis . New York : Cambridge University , 2007 , 663 – 745

Yoshimori M , Yokohata T , Abe-Ouchi A. A comparison of climate feedback strength between CO 2 doubling and LGM experiments . J Clim 2009 ; 22 : 3374 – 95 .

Stap LB , Kohler P , Lohmann G. Including the efficacy of land ice changes in deriving climate sensitivity from paleodata . Earth Syst Dynam 2019 ; 10 : 333 – 45 .

Koppen W. Das geographische system der climate. In: Koppen W, Geiger G (eds), Handbuch Der Klimatologie 1(C). Berlin : Boentraeger , 1936 .

Kohler P , Bintanja R , Fischer H et al.  What caused Earth’s temperature variations during the last 800,000 years? Data-based evidence on radiative forcing and constraints on climate sensitivity . Quat Sci Rev 2010 ; 29 : 129 – 45 .

Hansen J , Sato M , Kharecha P et al.  Target atmospheric CO 2 : where should humanity aim? Open Atmos Sci J 2008 ; 2 : 217 – 31 .

Rabineau M , Berné S , Olivet J-L et al.  Paleo sea levels reconsidered from direct observation of paleoshoreline position during Glacial Maxima (for the last 500,000 yr) . Earth Planet Sci Lett 2006 ; 252 : 119 – 37 .

Rohling EJ , Hibbert FD , Williams FH et al.  Differences between the last two glacial maxima and implications for ice-sheet, ō18O, and sea-level reconstructions . Quat Sci Rev 2017 ; 176 : 1 – 28 .

Hansen J , Sato M , Kharecha P et al.  Young people’s burden: requirement of negative CO2 emissions . Earth Syst Dynam 2017 ; 8 : 577 – 616 .

Hoffman JS , Clark PU , Parnell AC et al.  Regional and global sea-surface temperatures during the last interglaciation . Science 2017 ; 355 : 276 – 9 .

Ruth U , Barnola JM , Beer J et al.  EDML1: a chronology for the EPICA deep ice core from Dronning Maud Land, Antarctica, over the last 150 000 years . Clim Past 2007 ; 3 : 475 – 84 .

Hansen J , Sato M , Russell G et al.  Climate sensitivity, sea level, and atmospheric carbon dioxide . Philos Trans A Math Phys Eng Sci 2013 ; 371 : 20120294 .

Russell GL , Miller JR , Rind D. A coupled atmosphere-ocean model for transient climate change studies . Atmos Ocean 1995 ; 33 : 683 – 730 .

Hoffman PF , Schrag DP. The snowball Earth hypothesis: testing the limits of global change . Terra Nova 2002 ; 14 : 129 – 55 .

Sackmann J , Boothroyd AI , Kraemer KE. Our Sun. III. Present and future . Astrophys J 1993 ; 418 : 457 – 68 .

Meraner K , Mauritsen T , Voigt A. Robust increase in equilibrium climate sensitivity under global warming . Geophys Res Lett 2013 ; 40 : 5944 – 8 .

Lunt DJ , Haywood AM , Schmidt GA et al.  Earth system sensitivity inferred from Pliocene modelling and data . Nature Geosci 2010 ; 3 : 60 – 4 .

Beerling DJ , Fox A , Stevenson DS et al.  Enhanced chemistry-climate feedbacks in past greenhouse worlds . Proc Natl Acad Sci U S A 2011 ; 108 : 9770 – 5 .

Bryan K , Komro FG , Manabe S et al.  Transient climate response to increasing atmospheric carbon dioxide . Science 1982 ; 215 : 56 – 8 .

Hansen J , Russell G , Lacis A et al.  Climate response times: dependence on climate sensitivity and ocean mixing . Science 1985 ; 229 : 857 – 9 .

Hansen J. Climate Threat to the Planet, American Geophysical Union , San Francisco, California, 17 December 2008 . http://www.columbia.edu/~jeh1/2008/AGUBjerknes20081217.pdf . (date last accessed 3 December 2022).

Good P , Gregory JM , Lowe JA. A step-response simple climate model to reconstruct and interpret AOGCM projections . Geophys Res Lett 2011 ; 38 : e2010GL0452008 .

Schmidt GA , Kelley M , Nazarenko L et al.  Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive . J Adv Model Earth Syst 2014 ; 6 : 141 – 84 .

Prather MJ. Numerical advection by conservation of second order moments . J Geophys Res 1986 ; 91 : 6671 – 81 .

Romanou A , Marshall J , Kelley M et al.  Role of the ocean’s AMOC in setting the uptake efficiency of transient tracers . Geophys Res Lett 2017 ; 44 : 5590 – 8 .

von Schuckmann K , Cheng L , Palmer MD et al.  Heat stored in the Earth system: where does the energy go? Earth Syst Sci Data 2020 ; 12 : 2013 – 41 .

Loeb NG , Johnson GC , Thorsen TJ et al.  Satellite and ocean data reveal marked increase in Earth’s heating rate . Geophys Res Lett 2021 ; 48 : e2021GL093047 .

Hansen J , Johnson D , Lacis A et al.  Climate impact of increasing atmospheric carbon dioxide . Science 1981 ; 213 : 957 – 66 .

Kamae Y , Watanabe M , Ogura T et al.  Rapid adjustments of cloud and hydrological cycle to increasing CO 2 : a review . Curr Clim Change Rep 2015 ; 1 : 103 – 13 .

Zelinka MD , Myers TA , McCoy DT et al.  Causes of higher climate sensitivity in CMIP6 models . Geophys Res Lett 2020 ; 47 : e2019GL085782 .

Crowley TJ. Pliocene climates: the nature of the problem . Marine Micropaleontol 1996 ; 27 : 3 – 12 .

DeConto RM , Pollard D. Rapid Cenozoic glaciation of Antarctica induced by declining atmospheric CO 2 . Nature 2003 ; 421 : 245 – 9 .

Lacis AA , Schmidt GA , Rind D et al.  Atmospheric CO 2 : principal control knob governing Earth’s temperature . Science 2010 ; 330 : 356 – 9 .

Rae JWB , Zhang YG , Liu X et al.  Atmospheric CO 2 over the past 66 million years from marine archives . Annu Rev Earth Planet Sci 2021 ; 49 : 609 – 41 .

Steinthorsdottir M , Vajda V , Pole M et al.  Moderate levels of Eocene pCO 2 indicated by Southern Hemisphere fossil plant stomata . Geology 2019 ; 47 : 914 – 8 .

Westerhold T , Marwan N , Drury AJ et al.  An astronomically dated record of Earth’s climate and its predictability over the last 66 million years . Science 2020 ; 369 : 1383 – 7 .

Yatheesh V , Dyment J , Bhattacharya GC et al.  Detailed structure and plate reconstructions of the central Indian Ocean between 83.0 and 42.5 Ma (chrons 34 and 20) . J Geophys Res: Solid Earth 2019 ; 124 : 4305 – 22 .

Cutler KB , Edwards RL , Taylor FW et al.  Rapid sea-level fall and deep-ocean temperature change since the last interglacial period . Earth Planet Sci Lett 2003 ; 206 : 253 – 71 .

Siddall M , Honisch B , Waelbroeck C et al.  Changes in deep Pacific temperature during the mid-Pleistocene transition and Quaternary . Quatern Sci Rev 2010 ; 29 : 170 – 81 .

Rohling EJ , Grant K , Bolshaw M et al.  Antarctic temperature and global sea level closely coupled over the past five glacial cycles . Nature Geosci 2009 ; 2 : 500 – 4 .

Seltzer AM , Blard P-H , Sherwood SC et al.  Terrestrial amplification of past, present, and future climate change . Sci Adv 2023 ; 9 : eadf8119 .

Zhu J , Poulsen CJ , Tierney JE. Simulation of Eocene extreme warmth and high climate sensitivity through cloud feedbacks . Sci Adv 2019 ; 5 : eaax1874 .

Scotese C. PALEOMAP PaleoAtlas for GPlates , 2016. https://www.earthbyte.org/paleomap-paleoatlas-for-gplates/ (March 2023, date last accessed).

Hansen J. Storms of My Grandchildren . New York : Bloomsbury , 2009 .

Berner RA. The Phanerozoic Carbon Cycle: CO2 and O2 . New York : Oxford University Press , 2004 .

Rohling EJ. The Climate Question: natural Cycles, Human Impact, Future Outlook . New York: Oxford University Press , 2019 .

Merdith AS , Williams SE , Brune S et al.  Rift and plate boundary evolution across two supercontinent cycles . Global Plan Chan 2019 ; 173 : 1 – 14 .

Peace AL , Phethean JJJ , Franke D et al.  A review of Pangea dispersal and large igneous provinces – in search of a causative mechanism . Earth-Science Rev 2020 ; 206 : 102902 .

Baksi AK. Comment on “40Ar/39Ar dating of the Rajahmundry Traps, eastern India and their relationship to the Deccan Traps” by Knight et al. [Earth Planet Sci. Lett. 208 (2003) 85-99] . Earth Planet Sci Lett 2005 ; 239 : 368 – 73 .

Guo Z , Wilson M , Dingwell D et al.  India-Asia collision as a driver of atmospheric CO 2 in the Cenozoic . Nature Comm 2021 ; 12 : 3891 .

Raymo ME , Ruddiman WF. Tectonic forcing of late Cenozoic climate . Nature 1992 ; 359 : 117 – 22 .

Ramos EJ , Lackey JS , Barnes JD et al.  Remnants and rates of metamorphic decarbonation in continental arcs . Gsat 2020 ; 30 : 4 – 10 .

Bufe A , Hovius N , Emberson R et al.  Co-variation of silicate, carbonate and sulfide weathering drives CO 2 release with erosion . Nat Geosci 2021 ; 14 : 211 – 6 .

Lee CTA , Shen B , Slotnick BS et al.  Continental arc-island arc fluctuations, growth of crustal carbonates, and long-term climate change . Geosphere 2013 ; 9 : 21 – 36 .

McKenzie NR , Horton BK , Loomis SE et al.  Continental arc volcanism as the principal driver of icehouse-greenhouse variability . Science 2016 ; 352 : 444 – 7 .

Petersen KD , Schiffer C , Nagel T. LIP formation and protracted lower mantle upwelling induced by rifling and delamination . Scientific Rep 2018 ; 8 : 16578 .

Eldholm E , Grue K. North Atlantic volcanic margins: dimensions and production rates . J Geophys Res 1994 ; 99 : 2955 – 68 .

Ji S , Nie J , Lechler A et al.  A symmetrical CO 2 peak and asymmetrical climate change during the middle Miocene . Earth Plan Sci Lett 2018 ; 499 : 134 – 44 .

Babila TL , Foster GL. The Monterey Event and the Paleocene-Eocene Thermal Maximum: two contrasting oceanic carbonate system responses to LIP emplacement and eruption. In: Dickson A, Bekker A (eds), AGU Geographical Monograph 255, Washington: American Geophysical Union, 2021, 403 – 416 .

Storey M , Duncan RA , Tegner C. Timing and duration of volcanism in the North Atlantic Igneous Province: implications for geodynamics and links to the Iceland hotspot . Chem Geol 2007 ; 241 : 264 – 81 .

Svensen H , Planke S , Malthe-Sorenssen A et al.  Release of methane from a volcanic basin as a mechanism for initial Eocene global warming . Nature 2004 ; 429 : 542 – 5 .

Gutjahr M , Ridgwell A , Sexton PF et al.  Very large release of mostly volcanic carbon during the Palaeocene Thermal Maximum . Nature 2017 ; 548 : 573 – 7 .

Frieling J , Peterse F , Lunt DJ et al.  Widespread warming before and elevated barium burial during the Paleocene-Eocene thermal maximum: evidence for methane hydrate release? Paleoceanogr Paleoclimatol 2019 ; 34 : 546 – 66 .

Berndt C , Planke S , Alvarez Zarikian CA et al.  Shallow-water hydrothermal venting linked to the Palaeocene-Eocene Thermal Maximum . Nature Geosci 2023 ; 16 : 803 – 9 .

Walker JCG , Hays PB , Kasting JF. A negative feedback mechanism for the long-term stabilization of Earth’s surface temperature . J Geophys Res 1981 ; 86 : 9776 – 82 .

Steinberger B , Spakman W , Japsen P et al.  The key role of global solid-Earth processes in preconditioning Greenland’s glaciation since the Pliocene . Terra Nova 2015 ; 27 : 1 – 8 .

Foster GL , Hull P , Lunt DJ et al.  Placing our current ‘hyperthermal’ in the context of rapid climate change in our geological past . Phil Trans Roy Soc A 2018 ; 376 : 200170086 .

Tierney JE , Zhu J , Li M. Spatial patterns of climate change across the Paleocene-Eocene thermal maximum . Proc Natl Acad Sci 2022 ; 119 : e2205326119 .

Hopcroft PO , Ramstein G , Pugh TAM et al.  Polar amplification of Pliocene climate by elevated trace gas radiative forcing . Proc Natl Acad Sci U S A 2020 ; 117 : 23401 – 7 .

Schaller MF , Fung MK. The extraterrestrial impact evidence at the Palaeocene-Eocene boundary and sequence of environmental change on the continental shelf . Phil Trans R Soc A 2018 ; 376 : 20170081 .

Turner SK. Constraints on the onset duration of the Paleocene-Eocene Thermal Maximum . Phil Trans R Soc A 2018 ; 376 : 20170082 .

Zachos JC , McCarren H , Murphy B et al.  Tempo and scale of late Paleocene and early Eocene carbon isotope cycles: implications for the origin of hyperthermals . Earth Plan Sci Lett 2010 ; 299 : 242 – 9 .

Nichols JE , Peteet DM. Rapid expansion of northern peatlands and doubled estimate of carbon storage . Nat Geosci 2019 ; 12 : 917 – 21 .

Hanson PJ , Griffiths NA , Iverson CM et al.  Rapid net carbon loss from a whole-ecosystem warmed peatland . AGU Advan 2020 ; 1 : e2020AV000163 .

Bowen GJ , Maibauer BJ , Kraus MJ et al.  Two massive, rapid releases of carbon during the onset of the Palaeocene-Eocene thermal maximum . Nature Geosci 2015 ; 8 : 44 – 7 .

Archer D , Buffett B , Brovkin V. Ocean methane hydrates as a slow tipping point in the global carbon cycle . Proc Natl Acad Sci U S A 2009 ; 106 : 20596 – 601 .

Archer D , Eby M , Brovkin V et al.  Atmospheric lifetime of fossil fuel carbon dioxide . Annu Rev Earth Planet Sci 2009 ; 37 : 117 – 34 .

Nunes F , Norris RD. Abrupt reversal in ocean overturning during the Palaeocene/Eocene warm period . Nature 2006 ; 439 : 60 – 3 .

World Health Organization . Ambient (Outdoor) Air Pollution . https://www.who.int/en/news-room/fact-sheets/detail/ambient-(outdoor)-air-quality-and-health (date last accessed 23 June 2022).

Vohra K , Vodonos A , Schwartz J et al.  Global mortality from outdoor fine particle pollution generated by fossil fuel combustion: results from GEOS-Chem . Environ Res 2021 ; 195 : 110754 .

Marcott SA , Shakun JD , Clark PU et al.  A reconstruction of regional and global temperature for the last 11,300 . Science 2013 ; 339 : 1198 – 201 .

Tardif R , Hakim GJ , Perkins WA et al.  Last Millenium Reanalysis with an expanded proxy database and seasonal proxy modeling . Clim Past 2019 ; 15 : 1251 – 73 .

Watson AJ , Garabato ACN. The role of Southern Ocean mixing and upwelling in glacial-interglacial atmospheric CO 2 change . Tellus 2006 ; 58 : 73 – 87 .

Wikipedia . File:Post-Glacial Sea Level.png. https://commons.wikimedia.org/wiki/File:Post-Glacial_Sea_Level.png (date last accessed 3 December 2022).

Barber B. Resistance by scientists to scientific discovery . Science 1961 ; 134 : 596 – 602 .

Hoffman PF , Kaufman AJ , Halverson GP et al.  A Neoproterozoic Snowball Earth . Science 1998 ; 281 : 1342 – 6 .

Alvarez L , Alvarez W , Asaro F et al.  Extraterrestrial Cause for the Cretaceous-Tertiary Extinction . Science 1980 ; 208 : 1095 – 108 .

Mishchenko MI , Cairns B , Kopp G et al.  Accurate monitoring of terrestrial aerosols and total solar irradiance: Introducing the Glory mission . Bull Amer Meteorol Soc 2007 ; 88 : 677 – 92 .

Hansen J , Rossow W , Fung I. Long-Term Monitoring of Global Climate Forcings and Feedbacks . Washington : NASA Conference Publication 3234 , 1993 .

Bellouin N , Quaas J , Gryspeerdt E et al.  Bounding global aerosol radiative forcing of climate change . Rev Geophys 2020 ; 58 : e2019RG000660 .

Kruzman D. Wood-burning stoves raise new health concerns. Undark Magazine 2022 , 2 March (6 February 2023, date last accessed).

Glojek K , Mocnik G , Alas HDC et al.  The impact of temperature inversions on black carbon and particle mass concentrations in a mountainous area . Atmos Chem Phys 2022 ; 22 : 5577 – 601 .

Rutgard O. Why is Britain Taking the Axe to Wood-Burning Stoves? Bloomberg Green , 4 February 2023 .

Day JW , Gunn JD , Folan WJ et al.  Emergence of complex societies after sea level stabilized . EOS Transactions 2007 ; 88 : 169 – 70 .

VanCuren RA. Asian aerosols in North America: extracting the chemical composition and mass concentration of the Asian continental aerosol plume from long-term aerosol records in the western United States . J Geophs Res Atmos 2003 ; 108 : D20, 4623 .

Knutti R. Why are climate models reproducing the observed global surface warming so well? Geophys Res Lett 2008 ; 35 : L18704 .

Hansen J , Sato M , Kharecha P et al.  Earth's energy imbalance and implications . Atmos Chem Phys 2011 ; 11 : 13421 – 49 .

Koch D , Bauer SE , Del Genio A et al.  Coupled aerosol-chemistry-climate twentieth-century model investigation: trends in short-lived species and climate responses . J Clim 2011 ; 24 : 2693 – 714 .

Novakov T , Ramanathan V , Hansen JE et al.  Large historical changes of fossil-fuel black carbon aerosols . Geophys Res Lett 2003 ; 30 : 1324 .

Bauer SE , Tsigaridis K , Faluvegi G et al.  Historical (1850-2014) aerosol evolution and role on climate forcing using the GISS ModelE2.1 contribution to CMIP6 . J Adv Model Earth Syst 2020 ; 12 : e2019MS001978 .

Hansen J , Ruedy R , Sato M et al.  Global surface temperature change . Rev Geophys 2010 ; 48 : RG4004 .

Lenssen NJL , Schmidt GA , Hansen JE et al.  Improvements in the GISTEMP uncertainty model . JGR Atmospheres 2019 ; 124 : 6307 – 26 .

Jin Q , Grandey BS , Rothenberg D et al.  Impacts on cloud radiative effects induced by coexisting aerosols converted from international shipping and maritime DMS emissions . Atmos Chem Phys 2018 ; 18 : 16793 – 808 .

Hansen J , Rossow W , Carlson B et al.  Low-cost long-term monitoring of global climate forcings and feedbacks . Clim Chan 1995 ; 31 : 247 – 71 .

Glassmeier F , Hoffmann F , Johnson JS et al.  Aerosol-cloud-climate cooling overestimated by ship-track data . Science 2021 ; 371 : 485 – 9 .

Manshausen P , Watson-Parris D , Christensen MW et al.  Invisible ship tracks show large cloud sensitivity to aerosol . Nature 2022 ; 610 : 101 – 6 .

Wall CJ , Norris JR , Possner A et al.  Assessing effective radiative forcing from aerosol-cloud interactions over the global ocean . Proc Natl Acad Sci U S A 2022 ; 119 : e2210481119 .

Forster P , Storelvmo T , Armour K et al.  The Earth’s energy budget, climate feedbacks, and climate sensitivity. In: Masson-Delmotte V (ed), Climate Change 2021: The Physical Science Basis . New York, Cambridge : Cambridge University Press , 2021 , 923 – 1054 .

International Maritime Organization (IMO), MEPC.176(58) . Amendments to the annex of the protocol of 1997 to amend the international convention for the prevention of pollution from ships, 1973, as modified by the protocol of 1978 relating thereto (Revised MARPOL, Annex VI), 2008 . https://wwwcdn.imo.org/localresources/en/OurWork/Environment/Documents/176(58).pdf (February 2013, date last accessed).

Gryspeerdt E , Smith TWP , O'Keeffe E et al.  The impact of ship emission controls recorded by cloud properties . Geophys Res Lett 2019 ; 46 : 547 – 55 .

International Maritime Organization . IMO 2020–Cutting Sulphur Oxide Emissions, Lowers Limit on Sulfur Content of Marine Fuels from 3.5% to 0.5%. https://www.imo.org/en/MediaCentre/HotTopics/Pages/Sulphur-2020.aspx (date last accessed 5 December 2022).

Yuan T , Song H , Wood R et al.  Global reduction in ship-tracks from sulfur regulations for shipping fuel . Sci Adv 2022 ; 8 : eabn7988 .

Columbia University. Data sources, graphs . http://www.columbia.edu/~mhs119/Solar/ (date last accessed 23 October 2022).

Loeb NG , Thorsen TJ , Rose FG et al.  Recent variations in EEI, SST & clouds. ERB Workshop, Hamburg, Germany, 12–14 October, 2022 (date last accessed 3 December 2022).

Sato M. Sea ice area. Columbia University webpage (date last accessed 5 November 2022 ).

McCoy DT , Burrows SM , Wood R et al.  Natural aerosols explain seasonal and spatial patterns of Southern Ocean cloud albedo . Sci Adv 2015 ; 1 : e1500157 .

Dunne JP , Winton M , Bacmeister J et al.  Comparison of equilibrium climate sensitivity estimates from slab ocean, 150‐year, and longer simulations . Geo Res Lett 2020 ; 47 : e2020GL088852 .

Forster PM , Maycock AC , McKenna CM et al.  Latest climate models confirm need for urgent mitigation . Nat Clim Chang 2020 ; 10 : 7 – 10 .

Liu Z , Zhu J , Rosenthal Y et al.  The Holocene temperature conundrum . Proc Natl Acad Sci U S A 2014 ; 111 : E3501 – E3505 .

Quaas J , Jia H , Smith C et al.  Robust evidence for reversal of the trend in aerosol effective climate forcing . Atmos Chem Phys 2022 ; 22 : 12221 – 39 .

Bauer SE , Tsigaridis K , Faluvegi G et al.  The turning point of the aerosol era . J Adv Mod Earth Syst 2022 ; 14 : e2022MS003070 .

Diamond MS. Detection of large-scale cloud microphysical changes and evidence for decreasing cloud brightness within a major shipping corridor after implementation of the International Maritime Organization 2020 fuel sulfur regulations . Atmos Chem Phys 2023 ; 23 : 8259 – 69 .

Hefner M , Marland G , Boden T et al.  Global, Regional, and National Fossil-Fuel CO 2 Emissions . Research Institute for Environment, Energy, and Economics, Appalachian State University, Boone, NC, USA. https://energy.appstate.edu/cdiac-appstate/data-products (date last accessed 20 August 2023).

Energy Institute . 2023 Statistical Review of World Energy (date last accessed 20 August 2023 ).

Hansen J , Sato M , Ruedy R et al.  Global warming in the twenty-first century: an alternative scenario . Proc Natl Acad Sci U S A 2000 ; 97 : 9875 – 80 .

Hansen JE (ed.). Air Pollution as a Climate Forcing: A Workshop . NASA Goddard Institute for Space Studies , 2002 .

Feynman RP. Surely You’re Joking, Mr. Feynman! . New York : WW Norton , 1985 .

Hariri AR , Brown SM , Williamson DE et al.  Preference for immediate over delayed rewards is associated with magnitude of ventral striatal activity . J Neurosci 2006 ; 26 : 13213 – 7 .

Hansen JE. Scientific reticence and sea level rise . Environ Res Lett 2007 ; 2 : 024002 . er1246875

Hansen JE. A slippery slope: how much global warming constitutes “dangerous anthropogenic interference?” . Clim Change 2005 ; 68 : 269 – 79 .

Braithewaite RJ. Cover photo for Science 2002;297(5579). Reprinted in Hansen, J. Defusing the global warming time bomb . Sci Amer 2004 ; 290 : 68 – 77 .

Rignot E , Jacobs S , Mouginot J et al.  Ice shelf melting around Antarctica . Science 2013 ; 341 : 266 – 70 .

Rye CD , Naveira Garabato AC , Holland PR et al.  Rapid sea-level rise along the Antarctic margins in response to increased glacial discharge . Nature Geosci 2014 ; 7 : 732 – 5 .

Hansen J Sato M Hearty P et al. Ice Melt, Sea Level Rise and Superstorms: Evidence from Paleoclimate Data, Climate Modeling, and Modern Observations that 2 C Global Warming is Highly Dangerous. Atmospheric Chemistry and Physics Discussions. 2015.

Bakker P , Schmittner A , Lenaerts JTM et al.  Fate of the Atlantic Meridional Overturning Circulation: strong decline under continued warming and Greenland melting . Geophy Res Lett 2016 ; 43 : 12252 – 60 .

Irvali N , Ninnemann US , Galaasen EV et al.  Rapid switches in subpolar hydrography and climate during the Last Interglacial (MIS 5e) . Paleoceanography 2012 ; 27 :PA2207.

Blanchon P , Eisenhauer A , Fietzke J et al.  Rapid sea-level rise and reef back-stepping at the close of the last interglacial highstand . Nature 2009 ; 458 : 881 – 4 .

Rye C , Marshall J , Kelley M et al.  Antarctic glacial melt as a driver of recent Southern Ocean climate trends . Geophys Res Lett 2020 ; 47 :e2019GL086892.

Silvano A , Rintoul SR , Pena-Molino B et al.  Freshening by glacial meltwater enhances melting of ice shelves and reduces formation of Antarctic bottom water . Sci Adv 2018 ; 4 : eaap9467 .

Gunn KL , Rintoul SR , England MH et al.  Recent reduced abyssal overturning and ventilation in the Australian Antarctic Basin . Nat Clim Chang 2023 ; 13 : 537 – 44 .

Ditlevsen P , Ditlevsen S. Warning of a forthcoming collapse of the Atlantic meridional overturning circulation . Nature Comm 2023 ; 14 : 4254 .

Rignot E , Mouginot J , Scheuchl B et al.  Four decades of Antarctic ice shelf mass balance from 1979-2017 . Proc Natl Acad Sci U S A 2018 ; 116 : 1096 – 103 .

Otosaka IN , Shepherd A , Ivins ER et al.  Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020 . Earth Syst Sci Data 2023 ; 15 : 1597 – 616 .

Hansen J , Sato M , Ruedy R et al.  Dangerous human-made interference with climate: A GISS modelE study . Atmos Chem Phys 2007 ; 7 : 2287 – 312 .

Matthews HD , Gillett NP , Stott PA et al.  The proportionality of global warming to cumulative carbon emissions . Nature 2009 ; 459 : 829 – 32 .

Hansen J , Sato M. Regional Climate Change and National Responsibilities . Environ Res Lett 2016 ; 11 : 034009 .

Paris Agreement 2015 . UNFCCC Secretariat, 2015 . https://www.google.com/aclk?sa=l&ai=DChcSEwjrgqiAkf2BAxUz2EwCHfzPDPcYABABGgJ0bQ&gclid=Cj0KCQjw4bipBhCyARIsAFsieCzU7epQQG4ouyspwn7TPYa7IWh2W0OqZJVXr0qbGhLzshwOnCk1YEkaAvzLEALw_wcB&sig=AOD64_3vxA5GilCwgEGMqI4OhPZk0EBbbQ&q&adurl&ved=2ahUKEwja_52Akf2BAxVWsFYBHcL6CYcQ0Qx6BAgJEAE (date last accessed 20 August 2023).

Keith DW , Holmes G , Angelo D et al.  A process for capturing CO 2 from the atmosphere . Joule 2018 ; 2 : 1573 – 94 .

Hansen J , Kharecha P. Cost of carbon capture: can young people bear the burden? Joule 2018 ; 2 : 1405 – 7 .

Hardin G. The tragedy of the commons . Science 1968 ; 162 : 1243 – 8 .

Prins G , Rayner S. Time to ditch Kyoto . Nature 2007 ; 449 : 973 – 5 .

Creutzig F , Erb KH , Haberl H et al.  Considering sustainability thresholds for BECCS in IPCC and biodiversity assessments . GCB Bioemergy 2021 ; 13 : 510 – 5 .

Economists’ Statement on Carbon Dividends . https://www.historyismade.org/ (date last accessed 28 November 2022).

Hansen J. Can Young People Save Democracy and the Planet? https://www.columbia.edu/~jeh1/mailings/2021/20211008_YoungPeople.2021.pdf (date last accessed 28 November 2022)

Hayes RB. Nuclear energy myths versus facts support it’s expanded use – a review . Cleaner Ener Sys 2022 ; 2 : 100009 .

Cao J , Cohen A , Hansen J et al.  China-U.S. cooperation to advance nuclear power . Science 2016 ; 353 : 547 – 8 .

Ying F. Cooperative competition is possible between China and the U.S. New York Times , 24 November.

National Academies of Sciences, Engineering, and Medicine . Reflecting Sunlight: Recommendations for Solar Geoengineering Research and Research Governance. https://doi.org/10.17226/25762 (date last accessed 4 December 2022).

Robock A. Volcanic eruptions and climate . Rev Geophys 2000 ; 38 : 191 – 219 .

Hansen J , Sato M , Ruedy R et al.  A Pinatubo climate Modeling investigation . NATO ASI 1996 ; I42 : 234 – 72 .

Tollefson J. Can artificially altered clouds save the Great Barrier Reef? Nature 2021 ; 596 : 476 – 8 .

Latham J , Rasch P , Chen CC et al.  Global temperature stabilization via controlled albedo enhancement of low-level maritime clouds . Philos Trans A Math Phys Eng Sci 2008 ; 366 : 3969 – 87 .

Patrick SM. Reflecting sunlight to reduce climate risk: priorities for research and international cooperation. Council on Foreign Relations . Special Report No. 93, April 2022 (date last accessed 4 December 2022).

Lovins AB. Reinventing Fire . White River Junction, Vermont : Chelsea Green Publishing , 334 p.

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The Macroeconomic Impact of Climate Change: Global vs. Local Temperature

This paper estimates that the macroeconomic damages from climate change are six times larger than previously thought. Exploiting natural global temperature variability, we find that 1°C warming reduces world GDP by 12%. Global temperature correlates strongly with extreme climatic events unlike country-level temperature used in previous work, explaining our larger estimate. We use this evidence to estimate damage functions in a neoclassical growth model. Business-as-usual warming implies a 29% present welfare loss and a Social Cost of Carbon of $1,065 per ton. These impacts suggest that unilateral decarbonization policy is cost-effective for large countries such as the United States.

We thank Marios Angeletos, Marshall Burke, Gabriel Chodorow-Reich, Simon Dietz, Stephane Hallegatte, Jim Hamilton, Xavier Jaravel, Ben Jones, Eben Lazarus, Pooya Molavi, Ishan Nath, Ben Olken, Esteban Rossi-Hansberg, Jon Steinsson, Jeffrey Shrader, Jim Stock and Chris Wolf for helpful comments and suggestions. We thank Ramya Raghavan, Lilian Hartmann and Cathy Wang for outstanding research assistance. Adrien Bilal gratefully acknowledges support from the Chae Family Economics Research Fund at Harvard University. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Assessing climate change projections through high-resolution modelling: a comparative study of three european cities.

1. Introduction

2. data and methods, 2.1. study areas, 2.2. the modelling setup and evaluation, 2.3. climate change indices, 3. results and discussion, 3.1. model evaluation for recent past, 3.2. daily mean, maximum and minimum temperature, 3.3. climate change indices, 4. nature-based solutions potential, 5. summary and conclusions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

• Pörtner, D.C.; Roberts, M.; Tignor, E.S.; Poloczanska, K.; Mintenbeck, A.; Alegría, M.; Craig, S.; Langsdorf, S.; Löschke, V.; Möller, A.; et al. (Eds.) IPCC Climate Change 2022: Impacts, Adaptation, and Vulnerability: Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change ; Cambridge University Press: Cambridge, UK, 2022; ISBN 978-92-9169-159-3. [ Google Scholar ]
• WMO-No. 1320: State of the Climate in Europe 2022 ; World Meteorological Organization: Geneva, Switzerland, 2023. [ Google Scholar ]
• IPCC Sixth Assessment Report. Available online: https://www.ipcc.ch/assessment-report/ar6/ (accessed on 2 August 2024).
• Mbow, C.; Rosenzweig, C.; Barioni, L.G.; Benton, T.G.; Herrero, M.; Krishnapillai, M.; Liwenga, E.; Pradhan, P.; Rivera-Ferre, M.G.; Sapkota, T.; et al. Climate Change and Land: An IPCC Special Report on Climate Change, Desertification, Land Degradation, Sustainable Land Management, Food Security, and Greenhouse Gas Fluxes in Terrestrial Ecosystems ; Shukla, P.R., Skea, J., Calvo Buendia, E., Masson-Delmotte, V., Pörtner, H.-O., Roberts, D.C., Zhai, P., Slade, R., Connors, S., van Diemen, R., et al., Eds.; Cambridge University Press: Cambridge, UK, 2019. [ Google Scholar ]
• Dugord, P.A.; Lauf, S.; Schuster, C.; Kleinschmit, B. Land Use Patterns, Temperature Distribution, and Potential Heat Stress Risk—The Case Study Berlin, Germany. Comput. Environ. Urban Syst. 2014 , 48 , 86–98. [ Google Scholar ] [ CrossRef ]
• Gill, S.E.; Handley, J.F.; Ennos, A.R.; Pauleit, S. Adapting Cities for Climate Change: The Role of the Green Infrastructure. Built Environ. Environ. 2007 , 33 , 115–133. [ Google Scholar ] [ CrossRef ]
• Kim, S.; Ryu, Y. Describing the Spatial Patterns of Heat Vulnerability from Urban Design Perspectives. Int. J. Sustain. Dev. World Ecol. 2015 , 22 , 189–200. [ Google Scholar ] [ CrossRef ]
• Barros, V.R.; Field, C.B.; Dokken, D.J.; Mastrandrea, M.D.; Mach, K.J.; Bilir, T.E.; Chatterjee, M.; Yuka, K.L.E.; Estrada, O.; Genova, R.C. (Eds.) IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability Part A: Global and Sectoral Aspects Working Group II Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change ; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2014; 1132p, ISBN 978107641655. [ Google Scholar ]
• Rafael, S.; Augusto, B.; Ascenso, A.; Borrego, C.; Miranda, A.I. Re-Naturing Cities: Evaluating the Effects on Future Air Quality in the City of Porto. Atmos. Environ. 2020 , 222 , 117123. [ Google Scholar ] [ CrossRef ]
• Hobbie, S.E.; Grimm, N.B. Nature-Based Approaches to Managing Climate Change Impacts in Cities. Philos. Trans. R. Soc. B 2020 , 375 , 1794. [ Google Scholar ] [ CrossRef ]
• Jacob, D.; Petersen, J.; Eggert, B.; Alias, A.; Christensen, O.B.; Bouwer, L.M.; Braun, A.; Colette, A.; Déqué, M.; Georgievski, G.; et al. EURO-CORDEX: New High-Resolution Climate Change Projections for European Impact Research. Reg. Environ. Change 2014 , 14 , 563–578. [ Google Scholar ] [ CrossRef ]
• Van Vuuren, D.P.; Edmonds, J.; Kainuma, M.; Riahi, K.; Thomson, A.; Hibbard, K.; Hurtt, G.C.; Kram, T.; Krey, V.; Lamarque, J.-F.; et al. The Representative Concentration Pathways: An Overview. Clim. Change 2011 , 109 , 5–31. [ Google Scholar ] [ CrossRef ]
• Schär, C.; Fuhrer, O.; Arteaga, A.; Ban, N.; Charpilloz, C.; Di Girolamo, S.; Hentgen, L.; Hoefler, T.; Lapillonne, X.; Leutwyler, D.; et al. Kilometer-Scale Climate Models: Prospects and Challenges. Bull. Am. Meteorol. Soc. 2020 , 101 , E567–E587. [ Google Scholar ] [ CrossRef ]
• Tölle, M.H.; Schefczyk, L.; Gutjahr, O. Scale Dependency of Regional Climate Modeling of Current and Future Climate Extremes in Germany. Theor. Appl. Climatol. 2018 , 134 , 829–848. [ Google Scholar ] [ CrossRef ]
• Keppas, S.C.; Papadogiannaki, S.; Parliari, D.; Kontos, S.; Poupkou, A.; Tzoumaka, P.; Kelessis, A.; Zanis, P.; Casasanta, G.; de’Donato, F.; et al. Future Climate Change Impact on Urban Heat Island in Two Mediterranean Cities Based on High-Resolution Regional Climate Simulations. Atmosphere 2021 , 12 , 884. [ Google Scholar ] [ CrossRef ]
• Qiu, L.; Im, E.-S.; Hur, J.; Shim, K.-M. Added Value of Very High Resolution Climate Simulations over South Korea Using WRF Modeling System. Clim. Dyn. 2020 , 54 , 173–189. [ Google Scholar ] [ CrossRef ]
• Coelho, S.; Rafael, S.; Lopes, D.; Miranda, A.I.; Ferreira, J. How Changing Climate May Influence Air Pollution Control Strategies for 2030? Sci. Total Environ. 2021 , 758 , 143911. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Thomson, A.M.; Calvin, K.V.; Smith, S.J.; Kyle, G.P.; Volke, A.; Patel, P.; Delgado-Arias, S.; Bond-Lamberty, B.; Wise, M.A.; Clarke, L.E.; et al. RCP4.5: A Pathway for Stabilization of Radiative Forcing by 2100. Clim. Change 2011 , 109 , 77–94. [ Google Scholar ] [ CrossRef ]
• Ascenso, A.; Gama, C.; Roebeling, P.; Miranda, A.I. How Effective Are Nature-Based Solutions in Different Environments? Proceedings of the WIT Transactions on Ecology and the Environment. Online, 26–28 October 2021; WIT Press: Billerica MA, USA, 2021; Volume 252, pp. 3–14. [ Google Scholar ] [ CrossRef ]
• Chausson, A.; Turner, B.; Seddon, D.; Chabaneix, N.; Girardin, C.A.J.; Kapos, V.; Key, I.; Roe, D.; Smith, A.; Woroniecki, S.; et al. Mapping the Effectiveness of Nature-Based Solutions for Climate Change Adaptation. Glob. Change Biol. 2020 , 26 , 6134–6155. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Seddon, N.; Smith, A.; Smith, P.; Key, I.; Chausson, A.; Girardin, C.; House, J.; Srivastava, S.; Turner, B. Getting the Message Right on Nature-Based Solutions to Climate Change. Glob. Change Biol. 2021 , 27 , 1518–1546. [ Google Scholar ] [ CrossRef ]
• Pereira, P.; Yin, C.; Hua, T. Nature-Based Solutions, Ecosystem Services, Disservices, and Impacts on Well-Being in Urban Environments. Curr. Opin. Environ. Sci. Health 2023 , 33 , 100465. [ Google Scholar ] [ CrossRef ]
• Coelho, S.; Rafael, S.; Coutinho, M.; Monteiro, A.; Medina, J.; Figueiredo, S.; Cunha, S.; Lopes, M.; Miranda, A.I.; Borrego, C. Climate-Change Adaptation Framework for Multiple Urban Areas in Northern Portugal. Environ. Manag. 2020 , 66 , 395–406. [ Google Scholar ] [ CrossRef ]
• Municipality of Eindhoven Eindhoven | Population & Governance. Available online: https://onderzoek.eindhoven.nl/basisinfo/bevolking-bestuur (accessed on 2 August 2022).
• KNMI Climatology, Daily Data of the Weather in the Netherlands—Download. Available online: http://projects.knmi.nl/klimatologie/daggegevens/selectie.cgi (accessed on 2 August 2022).
• Ascenso, A.; Augusto, B.; Silveira, C.; Rafael, S.; Coelho, S.; Monteiro, A.; Ferreira, J.; Menezes, I.; Roebeling, P.; Miranda, A.I. Impacts of Nature-Based Solutions on the Urban Atmospheric Environment: A Case Study for Eindhoven, The Netherlands. Urban For. Urban Green. 2021 , 57 , 126870. [ Google Scholar ] [ CrossRef ]
• Augusto, B.; Roebeling, P.; Rafael, S.; Ferreira, J.; Ascenso, A.; Bodilis, C. Short and Medium- to Long-Term Impacts of Nature-Based Solutions on Urban Heat. Sustain. Cities Soc. 2020 , 57 , 102122. [ Google Scholar ] [ CrossRef ]
• Costa, S.; Peters, R.; Martins, R.; Postmes, L.; Keizer, J.J.; Roebeling, P. Effectiveness of Nature-Based Solutions on Pluvial Flood Hazard Mitigation: The Case Study of the City of Eindhoven (The Netherlands). Resources 2021 , 10 , 24. [ Google Scholar ] [ CrossRef ]
• Roebeling, P.; Saraiva, M.; Gneco, I.; Palla, A.; Alves, H.; Rocha, J.; Martins, F. Sustainable Urbanizing Landscape Development (SULD) Decision Support Tool: Report on Other Aqua Cases ; Aqua-Add Project, Aqua-Add Technical Report No.04.; Open Repository of the University of Porto: Porto, Portugal, 2014; Volume 33. [ Google Scholar ]
• Saraiva, M.; Roebeling, P.; Sousa, S.; Teotónio, C.; Palla, A.; Gnecco, I. Dimensions of Shrinkage: Evaluating the Socio-Economic Consequences of Population Decline in Two Medium-Sized Cities in Europe, Using the SULD Decision Support Tool. Environ. Plan. B Urban Anal. City Sci. 2017 , 44 , 1122–1144. [ Google Scholar ] [ CrossRef ]
• Istat—Istituto Nazionale di Statistica Resident Population on 1st January. Available online: http://dati.istat.it/?lang=en (accessed on 2 August 2022).
• Acquaotta, F.; Faccini, F.; Fratianni, S.; Paliaga, G.; Sacchini, A.; Vilímek, V. Increased Flash Flooding in Genoa Metropolitan Area: A Combination of Climate Changes and Soil Consumption? Meteorol. Atmos. Phys. 2019 , 131 , 1099–1110. [ Google Scholar ] [ CrossRef ]
• Weatherbase Genoa, Italy Koppen Climate Classification. Available online: https://www.weatherbase.com/weather/weather-summary.php3?s=2161&cityname=Genoa,+Italy,%202021 (accessed on 20 June 2022).
• Rodrigues, V.; Gama, C.; Ascenso, A.; Oliveira, K.; Coelho, S.; Monteiro, A.; Hayes, E.; Lopes, M. Assessing Air Pollution in European Cities to Support a Citizen Centered Approach to Air Quality Management. Sci. Total Environ. 2021 , 799 , 149311. [ Google Scholar ] [ CrossRef ]
• Laikari, A.; Dubovik, M.; Rinta-Hiiro, V.; Wendling, L.; Postmes, L.; Van Dinter, M.; Den Hollander, M.; Van Der Putten, P.; Särkilahti, M.; Leppänen, S.; et al. NBS Demonstration Site Start-Up Report ; Urban Natures Lab: Brussels, Belgium, 2021. [ Google Scholar ]
• Acquaotta, F.; Faccini, F.; Fratianni, S.; Paliaga, G.; Sacchini, A. Rainfall Intensity in the Genoa Metropolitan Area: Secular Variations and Consequences. Weather 2018 , 73 , 356–362. [ Google Scholar ] [ CrossRef ]
• Statistics Finland Key Figures on Population by Area, Information and Year. Available online: https://pxweb2.stat.fi/PxWeb/pxweb/en/StatFin/StatFin__vaerak/statfin_vaerak_pxt_11ra.px/ (accessed on 2 August 2022).
• Tampere City Board. Carbon Neutral Tampere 2030 Roadmap . 2020. Available online: https://www.tampere.fi/sites/default/files/2022-06/Carbon_Neutral_Tampere_2030_Roadmap.pdf (accessed on 2 August 2024).
• Skamarock, C.; Klemp, B.; Dudhia, J.; Gill, O.; Barker, D.; Duda, G.; Huang, X.; Wang, W.; Powers, G. A Description of the Advanced Research WRF Version 3 ; No. NCAR/TN-475+STR; University Corporation for Atmospheric Research: Boulder, CO, USA, 2008. [ Google Scholar ] [ CrossRef ]
• Fita, L.; Fernández, J.; García-Díez, M. CLWRF: WRF Modifications for Regional Climate Simulation under Future Scenarios. In Proceedings of the 11th WRF Users’ Workshop, Boulder, CO, USA, 22–24 June 2010. [ Google Scholar ]
• Fita, L.; Fernández, J.; García-Díez, M. CORINE Land Cover Technical Guide—Addendum 2000 ; European Environment Agency: Copenhagen, Denmark, 2000.
• Pineda, N.; Jorba, O.; Jorge, J.; Baldasano, J.M. Using NOAA AVHRR and SPOT VGT Data to Estimate Surface Parameters: Application to a Mesoscale Meteorological Model. Int. J. Remote Sens. 2004 , 25 , 129–143. [ Google Scholar ] [ CrossRef ]
• Regione Liguria Consultazione Dati Meteoclimatici. Available online: https://ambientepub.regione.liguria.it/SiraQualMeteo/script/PubAccessoDatiMeteo.asp (accessed on 2 August 2022).
• Finnish Meteorological Institute Weather and Sea—Download Observations. Available online: https://en.ilmatieteenlaitos.fi/download-observations (accessed on 3 August 2022).
• Borrego, C.; Monteiro, A.; Ferreira, J.; Miranda, A.I.; Costa, A.M.; Carvalho, A.C.; Lopes, M. Procedures for Estimation of Modelling Uncertainty in Air Quality Assessment. Environ. Int. 2008 , 34 , 613–620. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Schlünzen, K.H.; Sokhi, R.S. Overview of Tools and Methods for Meteorological and Air Pollution Mesoscale Model Evaluation and User Training ; WMO/TD; WMO: Geneva, Switzerland, 2008; Volume 41, ISBN 978-1-905313-59-4. [ Google Scholar ]
• Hong, S.Y.; Lim, J.O.J. The WRF Single Moment 6 Class Microphysics Scheme (WSM6). J. Korean Meteorol. Soc. 2006 , 42 , 129–151. [ Google Scholar ]
• Dudhia, J. Numerical Study of Convection Observed during the Winter Monsoon Experiment Using a Mesoscale Two-Dimensional Model. J. Atmos. Sci. 1989 , 46 , 3077–3107. [ Google Scholar ] [ CrossRef ]
• Mlawer, E.J.; Taubman, S.J.; Brown, P.D.; Iacono, M.J.; Clough, S.A. Radiative Transfer for Inhomogeneous Atmospheres: RRTM, a Validated Correlated-k Model for the Longwave. J. Geophys. Res. D Atmos. 1997 , 102 , 16663–16682. [ Google Scholar ] [ CrossRef ]
• Zhang, D.; Anthes, R.A. A High-Resolution Model of the Planetary Boundary Layer—Sensitivity Tests and Comparisons with SESAME-79 Data. J. Appl. Meteorol. 1982 , 21 , 1594–1609. [ Google Scholar ] [ CrossRef ]
• Tewari, M.; Chen, F.; Wang, W.; Dudhia, J.; LeMone, M.A.; Mitchell, K.; Ek, M.; Gayno, G.; Wegiel, J.; Cuenca, R.H. Implementation and Verification of the Unified Noah Land Surface Model in the WRF Model. In Proceedings of the 20th Conference on Weather Analysis and Forecasting/16th Conference on Numerical Weather Prediction, Seattle, WA, USA, 12–16 January 2004. [ Google Scholar ]
• Hong, S.Y.; Noh, Y.; Dudhia, J. A New Vertical Diffusion Package with an Explicit Treatment of Entrainment Processes. Mon. Weather Rev. 2006 , 134 , 2318–2341. [ Google Scholar ] [ CrossRef ]
• Grell, G.A.; Freitas, S.R. A Scale and Aerosol Aware Stochastic Convective Parameterization for Weather and Air Quality Modeling. Atmos. Chem. Phys. 2014 , 14 , 5233–5250. [ Google Scholar ] [ CrossRef ]
• Giorgetta, M.A.; Jungclaus, J.; Reick, C.H.; Legutke, S.; Bader, J.; Böttinger, M.; Brovkin, V.; Crueger, T.; Esch, M.; Fieg, K.; et al. Climate and Carbon Cycle Changes from 1850 to 2100 in MPI-ESM Simulations for the Coupled Model Intercomparison Project Phase 5. J. Adv. Model Earth Syst. 2013 , 5 , 572–597. [ Google Scholar ] [ CrossRef ]
• Riahi, K.; Grübler, A.; Nakicenovic, N. Scenarios of Long-Term Socio-Economic and Environmental Development under Climate Stabilization. Technol. Forecast Soc. Change 2007 , 74 , 887–935. [ Google Scholar ] [ CrossRef ]
• Rafael, S.; Martins, H.; Marta-Almeida, M.; Sá, E.; Coelho, S.; Rocha, A.; Borrego, C.; Lopes, M. Quantification and Mapping of Urban Fluxes under Climate Change: Application of WRF-SUEWS Model to Greater Porto Area (Portugal). Environ. Res. 2017 , 155 , 321–334. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Klein Tank, A.M.; Zwiers, F.W.; Zhang, X.; Canada, E. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation ; World Meteorological Organization: Geneva, Switzerland, 2009. [ Google Scholar ]
• European Commission; Directorate-General for Research and Innovation. Evaluating the Impact of Nature-Based Solutions: A Handbook for Practitioners ; Dumitru, A., Wendling, L., Eds.; Publications Office of the European Union: Luxembourg, 2021; ISBN 978-92-76-22821-9. [ Google Scholar ]
• Lee, S.H.; Lee, K.S.; Jin, W.C.; Song, H.K. Effect of an Urban Park on Air Temperature Differences in a Central Business District Area. Landsc. Ecol. Eng. 2009 , 5 , 183–191. [ Google Scholar ] [ CrossRef ]
• Hamouda, M.E.; Pasquero, C. European Extreme Precipitation: The Effects of Spatio-Temporal Resolution of the Data. Weather Clim. Extrem. 2021 , 33 , 100337. [ Google Scholar ] [ CrossRef ]
• Marta-Almeida, M.; Teixeira, J.C.; Carvalho, M.J.; Melo-Gonçalves, P.; Rocha, A.M. High Resolution WRF Climatic Simulations for the Iberian Peninsula: Model Validation. Phys. Chem. Earth Parts A/B/C 2016 , 94 , 94–105. [ Google Scholar ] [ CrossRef ]
• Pieri, A.B.; von Hardenberg, J.; Parodi, A.; Provenzale, A. Sensitivity of Precipitation Statistics to Resolution, Microphysics, and Convective Parameterization: A Case Study with the High-Resolution WRF Climate Model over Europe. J. Hydrometeorol. 2015 , 16 , 1857–1872. [ Google Scholar ] [ CrossRef ]
• Yang, B.; Qian, Y.; Lin, G.; Leung, R.; Zhang, Y. Some Issues in Uncertainty Quantification and Parameter Tuning: A Case Study of Convective Parameterization Scheme in the WRF Regional Climate Model. Atmos. Chem. Phys. 2012 , 12 , 2409–2427. [ Google Scholar ] [ CrossRef ]
• Strangeways, I. Measuring Global Temperature: Their Analysis and Interpretation ; Cambridge University Press: Cambridge, UK, 2010. [ Google Scholar ]
• Wang, X.; Hou, X.; Piao, Y.; Feng, A.; Li, Y. Climate Change Projections of Temperature Over the Coastal Area of China Using SimCLIM. Front. Environ. Sci. 2021 , 9 , 548. [ Google Scholar ] [ CrossRef ]
• Cholakian, A.; Colette, A.; Coll, I.; Ciarelli, G.; Beekmann, M. Future Climatic Drivers and Their Effect on PM10 Components in Europe and the Mediterranean Sea. Atmos. Chem. Phys. 2019 , 19 , 4459–4484. [ Google Scholar ] [ CrossRef ]
• Warscher, M.; Wagner, S.; Marke, T.; Laux, P.; Smiatek, G.; Strasser, U.; Kunstmann, H. A 5 Km Resolution Regional Climate Simulation for Central Europe: Performance in High Mountain Areas and Seasonal, Regional and Elevation-Dependent Variations. Atmosphere 2019 , 10 , 682. [ Google Scholar ] [ CrossRef ]
• Ruosteenoja, K.; Markkanen, T.; Räisänen, J. Thermal Seasons in Northern Europe in Projected Future Climate. Int. J. Climatol. 2020 , 40 , 4444–4462. [ Google Scholar ] [ CrossRef ]
• KNMI KNMI’14: Climate Change Scenarios for the 21st Century–A Netherlands Perspective ; Hurk, B.; van den Siegmund, P.; Tank, A.K. (Eds.) KNMI: De Bilt, The Netherlands, 2014. [ Google Scholar ]
• Lecœur, È.; Seigneur, C.; Pagé, C.; Terray, L. A Statistical Method to Estimate PM2.5 Concentrations from Meteorology and Its Application to the Effect of Climate Change. J. Geophys. Res. Atmos. 2014 , 119 , 3537–3585. [ Google Scholar ] [ CrossRef ]
• D’Oria, M.; Cozzi, C.; Tanda, M.G. Future Precipitation and Temperature Changes over the Taro, Parma and Enza River Basins in Northern Italy. Ital. J. Eng. Geol. Environ. 2018 , 2018 , 49–63. [ Google Scholar ] [ CrossRef ]
• D’Oria, M.; Ferraresi, M.; Tanda, M.G. Historical Trends and High-Resolution Future Climate Projections in Northern Tuscany (Italy). J. Hydrol. 2017 , 555 , 708–723. [ Google Scholar ] [ CrossRef ]
• Ruosteenoja, K.; Jylhä, K.; Kämäräinen, M. Climate Projections for Finland Under the RCP Forcing Scenarios. Geophysica 2016 , 51 , 17–50. [ Google Scholar ]
• Keuler, K.; Radtke, K.; Kotlarski, S.; Lüthi, D. Regional Climate Change over Europe in COSMO-CLM: Influence of Emission Scenario and Driving Global Model. Meteorol. Z. 2016 , 25 , 121–136. [ Google Scholar ] [ CrossRef ]
• Collins, M.; Knutti, R.; Arblaster, J.; Dufresne, J.-L.; Fichefet, T.; Friedlingstein, P.; Gao, X.; Gutowski, W.J.; Johns, T.; Krinner, G.; et al. Long-Term Climate Change: Projections, Commitments and Irreversibility. In Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change ; Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Midgley, V.B., Eds.; Cambridge University Press: Cambridge, UK; New York, NY, USA, 2013. [ Google Scholar ]
• Maule, C.F.; Mendlik, T.; Christensen, O.B. The Effect of the Pathway to a Two Degrees Warmer World on the Regional Temperature Change of Europe. Clim. Serv. 2017 , 7 , 3–11. [ Google Scholar ] [ CrossRef ]
• Ban, N.; Schmidli, J.; Schär, C. Evaluation of the Convection-Resolving Regional Climate Modeling Approach in Decade-Long Simulations. J. Geophys. Res. Atmos. 2014 , 119 , 7889–7907. [ Google Scholar ] [ CrossRef ]
• Fernández, J.; Frías, M.D.; Cabos, W.D.; Cofiño, A.S.; Domínguez, M.; Fita, L.; Gaertner, M.A.; García-Díez, M.; Gutiérrez, J.M.; Jiménez-Guerrero, P.; et al. Consistency of Climate Change Projections from Multiple Global and Regional Model Intercomparison Projects. Clim. Dyn. 2019 , 52 , 1139–1156. [ Google Scholar ] [ CrossRef ]
• Giorgi, F.; Gutowski, W.J. Regional Dynamical Downscaling and the CORDEX Initiative. Annu. Rev. Environ. Resour. 2015 , 40 , 467–490. [ Google Scholar ] [ CrossRef ]
• Prein, A.F.; Gobiet, A.; Suklitsch, M.; Truhetz, H.; Awan, N.K.; Keuler, K.; Georgievski, G. Added Value of Convection Permitting Seasonal Simulations. Clim. Dyn. 2013 , 41 , 2655–2677. [ Google Scholar ] [ CrossRef ]
• Kim, S.; Sinclair, V.A.; Räisänen, J.; Ruuhela, R. Heat Waves in Finland: Present and Projected Summertime Extreme Temperatures and Their Associated Circulation Patterns. Int. J. Climatol. 2018 , 38 , 5253. [ Google Scholar ] [ CrossRef ]
• Jylhä, K.; Jokisalo, J.; Ruosteenoja, K.; Pilli-Sihvola, K.; Kalamees, T.; Seitola, T.; Mäkelä, H.M.; Hyvönen, R.; Laapas, M.; Drebs, A. Energy Demand for the Heating and Cooling of Residential Houses in Finland in a Changing Climate. Energy Build. 2015 , 99 , 104–116. [ Google Scholar ] [ CrossRef ]
• Pepin, N.; Bradley, R.S.; Diaz, H.F.; Baraer, M.; Caceres, E.B.; Forsythe, N.; Fowler, H.; Greenwood, G.; Hashmi, M.Z.; Liu, X.D.; et al. Elevation-Dependent Warming in Mountain Regions of the World. Nat. Clim. Change 2015 , 5 , 424–430. [ Google Scholar ] [ CrossRef ]
• Oswald, S.M.; Hollosi, B.; Žuvela-Aloise, M.; See, L.; Guggenberger, S.; Hafner, W.; Prokop, G.; Storch, A.; Schieder, W. Using Urban Climate Modelling and Improved Land Use Classifications to Support Climate Change Adaptation in Urban Environments: A Case Study for the City of Klagenfurt, Austria. Urban Clim. 2020 , 31 , 100582. [ Google Scholar ] [ CrossRef ]
• De Wit, R.; Kainz, A.; Goler, R.; Žuvela-Aloise, M.; Hahn, C.; Zuccaro, G.; Leone, M.; Loibl, W.; Tötzer, T.; Hager, W.; et al. Supporting Climate Proof Planning with CLARITY’s Climate Service and Modelling of Climate Adaptation Strategies—The Linz Use-Case. Urban Clim. 2020 , 34 , 100675. [ Google Scholar ] [ CrossRef ]
• Gál, T.; Mahó, S.I.; Skarbit, N.; Unger, J. Numerical Modelling for Analysis of the Effect of Different Urban Green Spaces on Urban Heat Load Patterns in the Present and in the Future. Comput. Environ. Urban Syst. 2021 , 87 , 101600. [ Google Scholar ] [ CrossRef ]
• He, C.; He, L.; Zhang, Y.; Kinney, P.L.; Ma, W. Potential Impacts of Cool and Green Roofs on Temperature-Related Mortality in the Greater Boston Region. Environ. Res. Lett. 2020 , 15 , 094042. [ Google Scholar ] [ CrossRef ]
• Rafael, S.; Correia, L.P.; Ascenso, A.; Augusto, B.; Lopes, D.; Miranda, A.I. Are Green Roofs the Path to Clean Air and Low Carbon Cities? Sci. Total Environ. 2021 , 798 , 149313. [ Google Scholar ] [ CrossRef ]
• Zhao, J.; Zhao, X.; Liang, S.; Wang, H.; Liu, N.; Liu, P.; Wu, D. Dynamic Cooling Effects of Permanent Urban Green Spaces in Beijing, China. Remote Sens. 2021 , 13 , 3282. [ Google Scholar ] [ CrossRef ]

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Ascenso, A.; Augusto, B.; Coelho, S.; Menezes, I.; Monteiro, A.; Rafael, S.; Ferreira, J.; Gama, C.; Roebeling, P.; Miranda, A.I. Assessing Climate Change Projections through High-Resolution Modelling: A Comparative Study of Three European Cities. Sustainability 2024 , 16 , 7276. https://doi.org/10.3390/su16177276

Ascenso A, Augusto B, Coelho S, Menezes I, Monteiro A, Rafael S, Ferreira J, Gama C, Roebeling P, Miranda AI. Assessing Climate Change Projections through High-Resolution Modelling: A Comparative Study of Three European Cities. Sustainability . 2024; 16(17):7276. https://doi.org/10.3390/su16177276

Ascenso, Ana, Bruno Augusto, Sílvia Coelho, Isilda Menezes, Alexandra Monteiro, Sandra Rafael, Joana Ferreira, Carla Gama, Peter Roebeling, and Ana Isabel Miranda. 2024. "Assessing Climate Change Projections through High-Resolution Modelling: A Comparative Study of Three European Cities" Sustainability 16, no. 17: 7276. https://doi.org/10.3390/su16177276

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Global Warming

Long-term warming trends and increases in extreme weather events have the potential to impact all life on Earth. Even though at least 97 percent of climate scientists agree that human activities have contributed to rising global temperatures, the predominance and causes of these phenomena continue to be debated and many Americans deny global warming.

Read the overview below to gain a balanced understanding of the issues and explore the previews of opinion articles that highlight many perspectives on the response to global warming and climate change.

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Global warming topic overview.

"Global Warming and Climate Change." Opposing Viewpoints Online Collection , Gale, 2023.

Though the terms global warming and climate change are often used interchangeably, they have different meanings. Climate change describes long-term shifts in Earth's weather patterns that affect temperature, humidity, wind, cloud cover, and precipitation. Global warming refers explicitly to an increase in Earth's average surface temperatures caused by human activities, primarily the burning of fossil fuels. Anthropogenic climate change refers to changes in the climate caused by human activity, particularly industrialization and agricultural practices that release pollutants into the atmosphere.

Overwhelming scientific evidence supports the existence of both global warming and climate change. Through the United Nations' (UN) Intergovernmental Panel on Climate Change (IPCC), thousands of scientists work together to collect and analyze the latest available research related to climate change, its effects, and potential responses. In an interim update to its Sixth Assessment Report (AR6) in 2023, the IPCC estimated that global surface temperatures increased by 1.1°C (1.98°F) between the latter half of the nineteenth century and the first two decades of the twenty-first century. The IPCC has linked climate change and global warming to the increased occurrence and severity of storms, floods, droughts, and wildfires, warning that such disasters will increase further if temperatures continue to rise. The scientists' group also identifies water availability and food production as well as health and wealth being as experiencing observable, widespread, and substantial changes related to climate change. These threats have led scientists to identify global warming and climate change as a climate crisis . The IPCC recognizes human activity, particularly industrialization and certain agricultural practices that release carbon dioxide (CO2), as the primary driver of global warming and climate change.

Despite substantial evidence and a consensus among the scientific community, a vocal minority continues to challenge the science behind climate change. These critics characterize climate change as a natural phenomenon and dispute assertions that human activity has contributed to rising global temperatures. This position may be referred to as climate denial , and those who reject the scientific consensus are considered climate deniers . Fossil fuel companies often provide financial support to politicians, media campaigns, and organizations that promote climate denial.

• Climate chang e refers to long-term shifts in weather patterns. Global warming is the increase in the planet's average surface temperatures caused by human activities such as the burning of fossil fuels.
• Causes of climate change related to human activity are referred to as anthropogenic . Natural causes of climate change are called naturogenic .
• Earth's atmosphere contains several gases that trap heat from the sun and prevent it from escaping into space. These gases are called greenhouse gases (GHGs).
• July 2023 was the hottest month ever recorded on Earth.
• Global warming has the potential to cause disruptions in the food supply, harm ecosystems and wildlife habitats, and threaten the planet's biodiversity.
• Countries that experience the harshest effects of climate change are often low- and middle-income countries who contribute fewer greenhouse gas emissions than wealthier countries that do not experience the effects so intensely.
• The United States has joined other countries in making commitments to fight climate change, but that commitment has largely depended on the country's leadership.
• Though the administration of President Joe Biden has taken more aggressive steps to combat the climate crisis, critics question whether these steps will meet the administration's ambitious goals and whether those goals are sufficient.

CAUSES OF CLIMATE CHANGE

Earth's atmosphere contains several gases that trap heat from the sun and prevent it from escaping into space. This phenomenon is known as the greenhouse effect , and the gases are called greenhouse gases (GHGs). The main GHGs in nature are carbon dioxide, methane, and nitrous oxide. Without the greenhouse effect, Earth would be too cold to support life. Over time, the amount of GHGs trapped in Earth's atmosphere has increased significantly, causing worldwide temperatures to rise.

Natural processes on Earth constantly create and destroy GHGs. For example, plant and animal matter decay produce carbon dioxide, which plants then absorb during photosynthesis. This natural cycle stabilizes atmospheric levels of carbon dioxide. Climate change scientists at the National Aeronautics and Space Administration (NASA) and other federal and international agencies recognize that natural factors, including volcanic activity and shifts in the planet's crust, continue to play a role in climate change. However, they generally agree that these factors alone do not explain the substantial rise in Earth's temperature. Natural causes of climate change are referred to as naturogenic , while causes of climate change related to human activity are called anthropogenic .

Earth's vegetation releases and absorbs over two hundred billion metric tons of carbon dioxide annually. Human activities, such as the burning of fossil fuels, add approximately seven billion metric tons per year. Climate scientists believe the cumulative effect of this additional carbon dioxide has had a dramatic impact on the atmosphere. Deforestation has also contributed to this increase by releasing carbon dioxide stored in trees and eliminating forests that would continue to absorb many tons of carbon dioxide. According to the National Oceanic and Atmospheric Administration (NOAA), as of 2023 the amount of carbon dioxide in the atmosphere had increased by 50 percent since the beginning of the Industrial Revolution in Great Britain in the eighteenth century.

Increased levels of other GHGs, such as nitrous oxide and methane, have also resulted from human activity. Several agricultural and industrial processes, such as the use of certain fertilizers in farming, produce extensive amounts nitrous oxide. Methane emissions come from fossil fuel production, landfills, and livestock. Though much smaller quantities of these gases exist in Earth's atmosphere, some scientists believe they cause more harm than carbon dioxide. Methane, for example, is about twenty-one times as potent as carbon dioxide at trapping heat. Humans have also created and released GHGs that do not occur in nature. These include hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6). These gases, released during industrial processes such as aluminum production and electrical transmission, trap thousands of times more heat in the atmosphere than carbon dioxide.

CLIMATE CHANGE PREDICTIONS

A broad consensus exists in the scientific community that the consequences of climate change may be devastating, though the exact nature of the changes is difficult to predict. No model to chart climate patterns has had complete accuracy. For instance, most climate models failed to predict a slowdown in rising temperatures starting in 1998 and ending in 2012. The slowdown was attributed to volcanic eruptions that blocked out the sun and cooled temperatures, low levels of solar activity, and naturally occurring variability. Similarly, some predictions have underestimated threats.

In its initial assessment of rising sea levels in 1990, the IPCC initially anticipated a sea level rise of 1.9 millimeters per year from that year onward. However, as of 2023, the IPCC reports that sea levels rose at a rate of 3.7 millimeters per year between 2006 and 2018. Sea level rise contributes to increased flooding and the damage caused by extreme storms such as hurricanes in coastal cities. The IPCC predicts that sea level rise could threaten as many as one billion people living in low-lying cities and communities by 2041, noting the threats to livelihoods, cultural heritage, and the existence of many island nations.

US PUBLIC OPINION ON CLIMATE CHANGE

The effects of human activities on global warming and climate change are acknowledged and accepted by most people in the United States. According to annual polls conducted by Gallup since 2001, the public's beliefs in anthropogenic climate change has increased. In 2023, 62 percent of Americans accepted that human activities cause climate change (up from 61 percent in 2001), 60 percent believed that the effects have begun (up from 54 percent), and 46 percent stated that global warming will soon pose a serious threat (up from 31 percent).

Researchers have observed a strong correlation between Americans' political affiliations and their acceptance of climate science and levels of concern about global warming. In 2023, about 85 percent of Democrats believed the effects of global warming were already apparent, and 88 percent believed humans caused them. In comparison, only 33 percent of Republicans agreed with the first statement and 29 percent agreed with the second. Most independents believed both statements (61 and 66 percent, respectively). However, further analysis by Gallup in 2022 revealed that Republicans under age fifty-five expressed greater concern about global warming than those age fifty-five and older but still significantly fewer than Democrats or Independents of any age group.

EFFECTS OF GLOBAL WARMING

The potential consequences of global warming remain an issue of great debate and uncertainty. However, most experts predict dramatic and severe problems for future generations. Warmer oceans could result in stronger and more frequent hurricanes. As temperatures climb, some regions could experience frequent heat waves that bring devastating droughts and wildfires. In the United States, the 2023 summer season experienced a series of heat waves that broke temperature records in different parts of the country, particularly in Washington and Oregon. In July 2023, heat waves also affected many countries in the Northern Hemisphere, including Canada, China, and some European countries. NASA has confirmed that July 2023 was the hottest month ever recorded on Earth by a significant margin, identifying global warming as the principal causal factor.

Climate change has been linked to severe, exceptional droughts across several western states, including Arizona, California, Colorado, Idaho, Montana, Nevada, New Mexico, Oregon, Utah, and Washington. Climate scientists refer to this phenomenon a "megadrought," and it has contributed to massive wildfires in the first decades of the twenty-first century.

From 2018 to 2021, California and Oregon endured massive wildfires that burned millions of acres and led to the displacement of thousands of residents, widespread destruction of property, and the deaths of dozens of people. California had a record-breaking wildfire season in 2020, including the state's first gigafire —a blaze that burned over one million acres of land. By the end of the year, wildfires burned more than four million acres throughout the state. Though wildfires were less frequent throughout the United States from 2022 to 2023 than in the preceding several years, the effects of global warming and the federal and state governments' lack of emergency preparedness led to one of the deadliest wildfires in recorded history. In August 2023 a small brush fire that a broken powerline may have caused started burning just outside the town of Lahaina on the island of Maui in Hawaii. In just a few minutes, winds blew the fire toward town, devouring wooden buildings, telephone and electric power lines, and water pipes. Without enough water pressure, Lahaina's fire department failed to contain the wildfire, and with the town's communication and power systems down, residents were not immediately alerted. As of September 2023, authorities had confirmed that ninety-seven people had been killed in the wildfire and thirty-one individuals were still missing in what had become the eleventh deadliest wildfire in world history.

A megadrought could also lead to water shortages. For example, the US government issued its first Tier 1 federal water shortage declaration in August 2021 for the Colorado River. The river provides water for several US states and parts of Mexico. The first cuts to state water supplies took effect in October in Arizona and Nevada. Upon revisiting the issue in August 2022, the government intensified its alarm, raising the classification to a Tier 2 federal water shortage and issuing drastic cuts to state water allowances. In August 2023, the government announced that the Colorado River water shortage would return to Tier 1 in 2024 and that water restrictions would be eased. The government's decision came after an unusually high amount of snowpack formed on the mountains near the Colorado River during the 2022–2023 winter season.

Many coastal areas worldwide could also face severe flooding due to rising sea levels. Low-lying islands in the Pacific Ocean would eventually become uninhabitable. From 1880 to 2022, sea levels rose about eight to nine inches worldwide. The hurricane season of 2017 proved to be the costliest hurricane season since 1900, causing over $265 billion of property damage in the United States and more than three thousand deaths in Florida, Texas, and Puerto Rico. The year 2020 experienced thirty named storms, the most to ever occur in a single hurricane season. The first hurricane to make landfall in 2022 was Hurricane Fiona, which struck Puerto Rico and other Caribbean Islands in September. All of Puerto Rico, which was still recovering from devastating hurricanes in 2017, lost power, and several areas suffered flooding and landslides. Though twenty tropical storms affected the United States during the 2023 hurricane season, only three made landfall. One of them, Hurricane Idalia, was the strongest hurricane to hit Florida's Big Bend region since 1950, leaving over $1 billion worth of damages.

Global warming also threatens vulnerable ecosystems and wildlife habitats. Extended periods of drought can turn fertile lands into deserts with little vegetation. Plants and animals may not survive the rapid changes caused by global warming and could become extinct. Over the long term, such changes would negatively affect Earth's biodiversity. Environmental scientists warn that some ecosystems, such as coral reefs and coastal mangrove swamps, will likely disappear entirely.

The climate crisis also threatens to disrupt the global food supply, worsen economic inequality, and create security issues. Some areas might become too dry or too wet to support agriculture. As global warming causes more places to become uninhabitable, such displacement can drive mass migration. Communities struggle to recover from climate disasters, often exacerbating existing problems in those areas. Disputes over access to water have arisen in several states, including those with areas that rely on Colorado River water. Around the world, some water disputes have developed into armed conflicts.

CRITICAL THINKING QUESTIONS

• For what reasons do you think perceptions of anthropogenic climate change vary among Democrats and Republicans in the United States?
• What potential long-term consequences of climate change do you think will be the most difficult to manage? Explain your reasoning.
• In what ways, if at all, do you think the federal government could change its approach to address climate change more effectively? Explain your answer.

INTERNATIONAL RESPONSE AND US POLICY

The scope and global nature of the climate crisis necessitate that countries work together. Because an effective response requires countries to make sacrifices, negotiations to develop a coordinated international response have encountered repeated obstacles. Further, industrialized countries have contributed a disproportionate amount to the crisis. In contrast, less industrialized, lower-income countries have disproportionately felt the effects of the crisis and often lack the resources and infrastructure for climate change mitigation and adaptation.

Since 1995, the UN has hosted annual conferences to discuss climate change as part of its Framework Convention on Climate Change (UNFCCC). In 1997, delegates gathered in Kyoto, Japan, to negotiate an international treaty known as the Kyoto Protocol. This treaty required industrialized countries to reduce their GHG emissions by a certain percentage over five years. As of November 2023, 191 countries and the European Union had ratified the Kyoto Protocol. The United States has not ratified the agreement, citing concerns that it does not impose restrictions on China and India. Canada withdrew in 2011.

In 2015, world leaders set new climate goals at the UNFCCC conference (COP21) in Paris, France. The resultant Paris Agreement aimed to limit the rise in global temperatures to less than 2°C (3.6°F) above preindustrial levels and provide countries with the tools needed to counteract climate change. President Barack Obama played a leading role in brokering the Paris Agreement and pushed for greater environmental restrictions during his presidency. The Paris Agreement went into effect with the commitment of the United States and seventy-three other parties in November 2016. Obama's successor, Donald Trump, announced in 2017 that the United States would withdraw its support. After a required period, the United States officially withdrew from the agreement in November 2020.

Upon taking office in January 2021, President Joe Biden reentered the country in the Paris Agreement. Biden vowed that his administration would prioritize climate policy and issued several executive orders that made sustainability and addressing climate change important considerations across all federal government agencies. In April 2021, the president hosted a virtual climate summit attended by forty world leaders and pledged that the United States would reduce its carbon emissions to half of 2005 levels by 2030. In June 2022, the Biden administration experienced a setback when the Supreme Court ruled in West Virginia v. Environmental Protection Agency (EPA) that the Clean Air Act did not grant the EPA authority to regulate GHG emissions without Congress passing additional legislation.

In August 2022, Biden signed the Inflation Reduction Act, a law promoting a sustainable green economy by incentivizing emissions reductions, supporting clean energy projects, and requiring the wealthiest individuals and corporations to pay more taxes. Though many advocates celebrated the law as the federal government's most aggressive step to combat the climate crisis, the law has also attracted criticism. Some detractors contend that the law remains insufficient to have a meaningful impact on the climate crisis or its other targets, which include health care costs, worker protections, and inflation. Further, Republicans have framed the law as an undue empowerment of the Internal Revenue Service (IRS), the agency responsible for collecting taxes. Public reception of Biden's climate policies has largely split along party lines. A June 2023 Pew Research Center survey revealed that 76 percent of Democrats approved of Biden's climate policies while 82 percent of Republicans disapproved.

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Climate change/global warming/climate emergency versus general climate research: comparative bibliometric trends of publications

Rafael m. santos.

a School of Engineering, University of Guelph, Guelph, Ontario, N1G 2W1, Canada

Reza Bakhshoodeh

b Department of Civil, Environmental and Mining Engineering, University of Western Australia, Perth, 6009, Australia

Associated Data

Data will be made available on request.

This article presents and discusses the scientific publication record from 1910 to 2020 on two topics: "climate" (CL) and "climate change/global warming/climate emergency" (CC/GW/CE). The goal is to comparatively visualize how these two distinct publication records have evolved over time, from different classification perspectives, using publication ratios as the key indicator. It is found that research output related to the Earth's contemporary changing climate overtook that of general climate research in 2010, and the publication ratio (CC/GW/CE)/(CL) has been expanding in the last decade. There are significant differences in the publication countries and sources between the two topics. Differentiation factors that affect the level of research output and engagement on the climate challenge include island versus landlocked nations, specialized versus general scientific journals, academic versus institutional organizations. The future of the publication records is discussed, such as the emergence of new terms to refer to the climate challenge, such as “climate emergency”.

Bibliometric analysis; Scientometrics; Human influence on climate; Natural control of climate; Improving climate monitoring; Climate variability; Climate models; CO 2 .

1. Introduction

The climate of a region is its average or typical weather over a long period of time; for example, the climate of Antarctica is freezing cold, and Hawaii is warm and sunny. Climate change, therefore, is a long-term change in the typical or average weather of a region; in the last few decades, industrial and human activities have led to gradually accelerating changes in the climate, including an annually incremental increase in the average surface temperature, which has been defined as climate change ( IPCC, 2014 ). Climate change also has noticeable negative impacts on other parts of the planet, like changes in ecosystems and desertification, rise in sea level, flooding, and drought ( Hisano et al., 2018 ; Ouhamdouch et al., 2019 ). The Intergovernmental Panel on Climate Change (IPCC) defines climate change as “a change in the state of the climate that can be identified… by changes in the mean and/or the variability of its properties and that persists for an extended period” ( IPCC, 2018 ). Climate Change (CC), Global Warming (GW) and more recently Climate Emergency (CE) have been, in the past decade and longer, terms synonymous with the greatest sustainability challenge of the 21 st century ( Munasinghe, 2010 ; Kyte, 2014 ; Princiotta and Loughlin, 2014 ; Martens et al., 2016 ).

Climate change mitigation is a technological measure aiming to reduce the amount of anthropogenic emissions of greenhouse gases (GHG) ( Fawzy et al., 2020 ), and can be divided mainly into: (i) mitigation technologies, which focus on reducing fossil-based CO 2 emissions, including nuclear power, renewable energies, and carbon capture and storage ( Ricke et al., 2017 ; Bustreo et al., 2019 ); (ii) negative emissions technologies, which aim to capture and sequester atmospheric carbon to reduce carbon dioxide levels, and include approaches such as BECCS (bioenergy with carbon capture and storage), DACCS (direct air carbon capture and storage), enhanced rock weathering, and ocean fertilization ( Goglio et al., 2020 ; Khalidy and Santos, 2021 ; Lezaun, 2021 ); and (iii) geoengineering techniques that change the Earth's radiative energy budget to stabilize or reduce global temperatures, such as stratospheric aerosol injection, and marine cloud brightening ( Lockley et al., 2019 ; Osman et al., 2020 ). Controlling and reversing climate change is expected to be a major concern and undertaking for mankind in the forthcoming decades.

Bibliometric analysis is a popular technique commonly employed to investigate the internal relationships in the body of scientific outputs in the literature. This method is helpful for researchers who are interested in but unfamiliar with a specific field to understand the status of this field quickly. Various bibliometric studies have explored different topics related to climate change ( Demiroglu and Hall, 2020 ), global warming ( Marx et al., 2017 ), climate change's impact on human health, agriculture, and water resource management ( Wang et al., 2014 ; Janssen et al., 2006 ; Li et al., 2011 ; Wei et al., 2015 ), and various scientific ( Oliveira et al., 2020 ) and technological ( Sobreira et al., 2020 ) questions. Studies that merge traditional bibliometrics with scientific topics also term these types of studies scientometrics ( Janmaijaya et al., 2018 ; Sobreira et al., 2020 ). Such studies often rely on the most comprehensive literature databases available, including Web of Science and Scopus ( Sobreira et al., 2020 ; Salmerón-Manzano and Manzano-Agugliaro, 2017 ; Macchi Silva et al., 2019 ). It is also common for such studies to span several decades ( Janmaijaya et al., 2018 ; Oliveira et al., 2020 ), and cover regional ( Marx et al., 2017 ; Demiroglu and Hall, 2020 ) to global ( Salmerón-Manzano and Manzano-Agugliaro, 2017 ; Oliveira et al., 2020 ) topics.

In the last years, scientific publications and reports by scholars that study different aspects of climate change have rapidly increased ( Aleixandre-Benavent et al., 2017 ). Aleixandre-Benevant et al. (2017) evaluated that the number of publications increase by over six-fold between 2005 and 2014. They used social networks to conclude that the United States is at the center of much of the research, and found relationships between keywords to find to which fields of research climate change research is primarily interconnected with (main keywords were: CO 2 , adaptation, model, temperature, and impact). According to the results of Fu and Waltman (2021) , the number of publications on climate change topics in a country reflects the priorities set by its government to cover some of the existing issues. Geography and level of economic development were other factors associated with the scientific output of various countries or regions. Fu and Waltman (2021) also point to how the purpose of the research has been shifting in the last two decades from that concerned with the causes and effects of climate change to measures to reverse or incentivize the reversal of climate change. Due to the growing scientific and public attention to climate change, researchers have used the bibliometric method to characterize the intellectual landscape of climate change, including the impact of climate change on migration ( Milán-García et al., 2021 ), tourism ( Fang et al., 2018 ), and infectious diseases ( Li et al., 2020 ).

An important aspect of bibliometric studies is the choice of search string used to retrieve publications from databases ( Haunschild et al., 2016 ). Using too restrictive or specific keywords (e.g., simply “climate change”) can lead to an incomplete search record, so authors frequently use combinations and variations of keywords. For example: Aleixandre-Benevant et al. (2017) utilized [“climate change” OR “climate changes” OR “climatic change” OR “climatic changes”]; Fu and Waltman (2021) utilized [“climate chang∗” OR “climatic chang∗” OR “climate variabilit∗” OR “climatic variabilit∗” OR “global warming” OR “climate warming” OR “climatic warming”]; and Tan et al. (2021) utilized the largest combination among these three, [“climate change∗” OR “climatic change∗” OR “climatic variation” OR “climatic oscillation” OR “environmental risk∗” OR “environmental exposure” OR “environmental externalities” OR “ecological risk∗” OR “eco-risk∗” OR “climatic risk∗” OR “ecological management∗” OR “ecological governance” OR “ecological control” OR “environmental governance, environmental management∗” OR “environmental control” OR “environmental improvement” OR “eco-environmental risk∗” OR “low carbon” OR “carbon emission∗” OR “cost of emission reduction” OR “emission reducing potential” OR “emission reduction”]. Evidently, the search of Tan et al. (2021) would lead to inclusion of papers not related to climate change, such as those related to general climate research and those related to all forms of environmental impact and pollution. Fu and Waltman's search string also runs the risk of including general climate research via the term “climate variability”, but is the only one of the three to have included the term “global warming”. Haunschild et al. (2016) present a detailed discussed on how truncation and other operators can be used to narrowed down a bibliometric search to a specific area of research (climate change in their case), and also how additional keywords can then be used to split a large dataset into sub-sets based on specific sub-areas of the research field (e.g., the effects of climate change on ice and snow using the search terms [“∗ice∗” OR “∗glacier∗” OR “∗snow∗” OR “∗frost∗”] or on oceanic currents using the search terms [“∗el nino∗” OR “∗elnino∗” OR “∗southern oscillation∗” OR “∗enso∗” OR “∗Walker circulation∗” OR “∗north atlantic oscillation∗” OR “∗nao∗”]). Two things can be concluded from inspecting the various search strings used by authors of bibliometric studies: (i) it is critical to find a good balance between inclusion and exclusion of articles, and this is done by careful selection of search terms, focusing on the ones known to be frequently associated with the research topic, and by the use of the truncation (∗) operator; and (ii) there has not been a bibliometric study that has attempted to separate and analyze the unique research records related to climate change research from those related to general climate research. These are two important motivators on our present work.

In this article, we aim to comparatively explore the bibliometric and scientometric data on two topics: general “climate” research and “climate change/global warming/climate emergency” research. The former relates to research that builds on our understanding of what naturally governs the Earth's climate, and how the climate regulates natural processes on the Earth's surface; the latter relates to research that investigates what is causing the Earth's climate to change rapidly, primarily as a result of anthropogenic drivers, and what effects climate change has on the Earth's systems, and what could be done to mitigate or adapt to this. An inspiration we have used for this work is the historical importance of the work of British engineer Guy Callendar, who in 1938 pointed to the anthropogenic contribution to global temperature rise ( Callendar, 1938 ), at a time before climate change research took off. That is, climate change research originated from general climate research, and at some point in the 20 th century, as will be presented later on in this article, became a unique field of research with a unique publication record.

Apart from the novel comparative topical theme, another differentiator of this article is its use of publication ratio values. We define the publication ratios as the number of publications in a category in one record over that in another record, which help us to distinguish and contrast CC/GW/CE versus general climate (CL) research. This approach differs from other comparative studies (e.g., Baek et al. (2020) , Arana Barbier (2020) , Wang et al. (2021) ), in that the traditional approach for comparing records is to plot or tabulate the data of each record separately, and then compare the trends seen in each record. The publication ratio method allows more direct and precise comparisons, as are shown in this article. Yet another differentiator is that this article is hypothesis-driven; that is, hypotheses (presented below) are posed to guide the collection and analysis of the bibliometric and scientometric data. The testing of hypotheses allows for evaluation of the quality and effectiveness of the data analysis performed, and thus acts as a verification mechanism that often is lacking in traditional literature reviews. past studies on climate change do not attempt to isolate or exclude papers that relate to general climate research. To this end, we hereafter explore the publication trends of two records (CL and CC/GW/CE), since the topical terms appeared in the journal records in the early part of the 20 th century, to test the following hypotheses:

• 1. It is possible to substantially distinguish the scientific literature that pertains to the study of the aforementioned climate challenge (or solutions for mitigating it) from studies that address gaining a better understanding of the earth's climate itself, using topical keyword searches.
• 2. The scientific literature has become so enriched in works addressing the climate challenge that it surpassed climate research in terms of the number of publications sometime in the late part of the 20 th century.
• 3. The scientific literature that pertains to the climate challenge is at least partly distinct from that on climate research in terms of the venue of publication, country of origin of studies, and organizations that have conducted these works.

The present study is global in scope and covers a century of data, as it looks to highlight key moments in the publication record and scientific advancement histories, in addition to the temporal and various categorical trends. The following research questions have been formulated to contrast CL research versus CC/GW/CE research via hypothesis testing: (i) what are the dynamics of the conceptual structure of CC/GW/CE versus CL research; (ii) when the scientific record has become more enriched in CC/GW/CE versus CL research; (iii) in which countries the climate challenge has become the dominant topic and are there any relationships between countries and the dominant scientific topic?

2. Methodology

Web of Science (WoS) was used to search the scientific literature and collect the relevant publication data for analysis. The searches were conducted on August 7 th , 2021 (for 1900 to complete 2020 data); all data were collected within a short time on those days to obtain a snapshot of the publication record. Figure 1 shows the protocol used for this bibliometric study, which is classified into five steps detailed below.

Protocol used for the bibliometric study.

Step one: The search used a time span of 1900–2020 and all indexes within the Web of Science Core Collection, namely: Science Citation Index Expanded: SCI-EXPANDED (1900–2020), Social Sciences Citation Index: SSCI (1900–2020), Arts & Humanities Citation Index: A&HCI (1975–2020), Conference Proceedings Citation Index - Science: CPCI–S (1990–2020), Conference Proceedings Citation Index - Social Science & Humanities: CPCI-SSH (1990–2020), and Emerging Sources Citation Index: ESCI (2015–2020). The two search strings used were: (i) TOPIC: ("climat∗ chang∗" OR "global warming∗" OR "climat∗ emergenc∗"); and (ii) TOPIC: ("climate" NOT ("climat∗ chang∗" OR "global warming∗" OR "climat∗ emergenc∗")). The former search string was used to collect papers related to research on the climate challenge (CC/GW/CE), and the latter search string was used to collect papers related to general research on the Earth's climate (CL). That is, these search strings tested Hypothesis 1.

Step two: In the results section, the document type was refined to ‘Article’. These searches yield 245,391 on the CC/GW/CE topic and 228,280 papers on the CL topic. The use of the NOR logical operator in the CL search string ensures that the two records are unique; that is, there are no repeating papers.

To verify if the search string used for CC/GW/CE research may have missed a substantial portion of research papers that did not use the three searched keywords, a third search was conducted using the following search string: TOPIC: ((("greenhouse gas∗" OR "GHG∗") NOT ("climate" OR "climate change" OR "global warming" OR "climate emergency"))). This search yielded 29,943 articles. This represents 11.56% of articles obtained with the combined search strings. In the Discussion and Conclusions section, the omission of these articles from the data analysis is explained.

Step three: The search results were at first analyzed using the Analyze Results feature of WoS. On the analysis page, it is possible to download tab-delimited text files containing a set of publication data according to the WoS category selected. Data files were obtained for the following four categories: publication years; organizations-enhanced; source titles; countries/regions. The data from these text files were then imported into Microsoft Excel for further processing and analysis. These data and analyses enabled testing Hypotheses 2 and 3. More details on the data handling procedure are provided in the Data Analysis section.

One additional procedure used was to recover keywords from the search records. This was done using the Export feature of WoS on the search results page to generate Excel files containing various attributes of each paper, including the keywords. Keywords were compiled from the top 100 cited papers from both topics (CC/GW/CE and CL) as of August 7 th , 2021. These keywords were used to generate word clouds using the software Wordle ( Feinberg, 2020 ).

Step four: A bibliometric analysis including keywords co-occurrence, countries collaboration, most relevant words, beamplots and affiliations was also performed on the full search results, which was exported from WoS as a bibtex or CSV file, using the bibliometrix package ( Aria and Cuccurullo, 2017 ) in RStudio software Version 1.2.5001 ( R Core Team, 2019 ). The bibliometrix R-package provides a set of tools for quantitative research in bibliometrics and scientometrics. It is written in the R language ( Ihaka, 1998 ), which is an open-source environment and ecosystem ( Aria and Cuccurullo, 2017 ). The codes used in this paper are provided at the end of the Supplementary Materials. Beamplot percentile data was obtained from author profiles found within Web of Science.

These data and analyses enabled testing Hypotheses 2 and 3, which are shown in the Supplementary Materials. This package uses the meta-data in the Web of Science citations to calculate and rank country production, journal sources, and country collaborations.

Step five: The previous steps (step one to four) were for all selected databases. In this step, each database was separately selected for analysis. Therefore, steps 2 to 4 were repeated again, and the results from each search were imported to Excel and Rstudio for further analysis.

3. Publication record highlights

From 1910 to 1970, the publications record for CC/GW/CE shows only eight entries, with 1971 being the first year with multiple (three) records. In fact, a line can be drawn at 1970 with the publication of Berton's paper titled “Carbon dioxide and its role in climate change” ( Benton, 1970 ). This is the first of the papers on record to specifically address contemporary anthropogenic climate change. It does not mean that only in 1970 the role of humans on climate change was understood; such hypothesis dates to decades earlier. But it may be one of the first papers to consistently use the term “climate change” to describe the observed phenomena (increasing atmospheric concentration of greenhouse gases and increasing global surface temperatures, as discussed in the paper). Another evidence of this shift in terminology is that two of the three 1971 papers, those by Frisken (1971) and Kopec (1971) , address the pressing climate challenge. This is in contrast with the first paper on this record, the 1910 Nature article by Lockyer titled “Does the Indian climate change?” ( Lockyer, 1910 ), which discusses short term observations of changing frequency of monsoons to conclude that the climate on the sub-continent varies from year to year, with both short- and long-term trends, but the influence of humans on these trends is not addressed, in fact, the opposite (the natural control of climate) is inferred. Notably, both Frisken (1971) and Kopec (1971) highlight that by the early 1970's it is well accepted that humans can have a significant effect on the climate by air emissions, but that at that time (when CO 2 atmospheric concentration have just surpassed 320 ppm ( Benton, 1970 )), the role of nature was still deemed stronger than the role of humans.

One way to contrast the publication record of CC/GW/CE versus that of CL is to compare their most cited works. Tables S-1 and S-2 in the Supplementary Materials also present the classification of 50 top cited papers for each record. Briefly reviewing these papers (i.e., reading the paper's aims and conclusions) helps understanding if the two data records contain the required topical selection of CC/GW/CE versus CL. Based on the results from these tables, for CC/GW/CE records, 45 papers are correctly classified, two are unusually misclassified, and three of them are outliers. While for CL records, 41 papers are correctly classified in CL subject, eight are misclassified, and one is an outlier. Within the top 5 most cited papers of each record, seven of the ten papers are correctly classified, two are unusually misclassified, and one is an outlier, as follows. Table 1 presents the publication history of the first authors of the five most cited journal articles from each record (according to Tables S-1 and S-2), in terms of the three most cited papers authored or co-authored by these first authors, on any topic (in some cases, the same topic as the record, and in some cases on other topics). Notable, the first most cited paper of each of these authors is also their highly cited paper according to Tables S-1 and S-2.

Table 1

The first three most cited journal articles of the five first authors of the highest cited papers from the two records (CC/GW/CE and CL), as tabulated in Tables S-1 and S-2.

Rayner et al. (2003) present sea ice and sea surface temperature and nighttime marine air temperature data sets, starting from 1871. That is, the study covers parameters pertinent for climate change research and the contemporary post-industrial revolution period attributed to anthropogenic climate change; after 18 years since their first publication in 1985, the first author reached their most cited paper in 2003. Parmesan and Yohe (2003) showed that climate change effects on living systems could be discerned from non-climatic effects by looking for systematic trends over diverse species and geographic regions; after 16 years since their first publication in 1987, the first author had reached their most cited paper in 2003. Kottek et al. (2006) provide a climate classification map update valid for the second half of the 20 th century, which was updated from the original 1961 Wladimir Köppen map. One motivation for this update was that climate changes have occurred and thus up-to-date global temperature and precipitation data sets were required to update the geographical distribution of the various climate zones (equatorial, arid, warm temperate, snow, and polar, and the various sub-classifications); one year after the first author's first publication on 2005, they reached their most cited paper in 2006. Thomas et al. (2004) showed how climate change leads to species-level extinction. They concluded that 18%–35% of species would be committed to extinction by 2050 because of climate change, in part because of habit loss due to changes in biome; after 20 years since the first author's first publication in 1984, they had reached their most cited paper in 2004. Allen et al. (2010) studied the effect of climate change and drought on trees mortality risks. They concluded that there is a direct relationship between tree mortality rates and heat severity and climate change; after 16 years since the first author's first publication in 1994, they had reached their most cited paper in 2010. All of these five highly cited papers are thus correctly classified under the CC/GW/CE topic. In addition, most (7 out of 10) of their second and third most cited papers are in the same research area (CC/GW/CE) as the record.

Kalnay et al. (1996) investigated how improvements to climate monitoring can avoid misinterpretation of climate variations that are not a result of climate change. The study is not concerned about studying climate change directly, even if the advances can benefit climate change research, and after 20 years since the first author's first publication in 1976, they had reached their most cited paper in 1996. Hijmans et al. (2005) developed a method for very high-resolution interpolation of temperature and precipitation climate data, which can be used to generate accurate climate surfaces (i.e., continuous grids); and after nine years since the first author's first publication in 1996, they had reached their most cited paper in 2005. This advance can help improve the analysis of climate change since more accurate values are obtained, though this was not the main aim of the study. An example was provided on how for Madagascar, the newly interpolated data set does not show direct evidence of climate change between 1930 and 1990. Another example stated that an insufficiently dense station network could lead to erroneous climate change conclusions. Phillips et al. (2006) present a model of the distribution of biological species due to geographic distribution, including climatic variables and conditions. The model was posed as being able to predict the movement of species due to climate change, such as invasive species, but this was not the study's main aim; after 37 years since the first author's first publication in 1969, they had reached their most cited paper in 2006. These are the three out of five highly cited papers correctly classified under CL. In addition, nearly all (5 out of 6) of their second, third most cited papers are also classified as CL research.

Tenenbaum et al. (2000) is the outlier. This paper does have relevance for CL research, as it pertains to the development of nonlinear algorithms to find trends in complex and large data sets, such as climate data sets, and is certainly not about CC/GW/CE. So while correctly classified, due to the use of the word “climate” in the abstract, the paper's topic is largely mathematical rather than about natural or engineering sciences. Taylor et al. (2012) is the paper that was unusually misclassified. This article does not have an abstract registered in WoS, and the article's single keyword registered in WoS is "climate" (the article itself does not have a keywords list). The article is in fact, about CC/GW/CE research; thus, the unusually incomplete record for this article caused it to be misclassified. These two papers highlight that the CL record is less robust than the CC/GW/CE record, particularly because of the CL record's less specific search string. While a weakness, the more analytical data processing presented in the Data Analysis section will show that this record is still useful for contrasting against the CC/GW/CE to yield dataset level (as opposed to paper-by-paper) trends and conclusions.

Table S-3 in the Supplementary Materials shows the top 5 cited paper in both records, which highlighted in blue (similar to the first column of Table 1 ) and 5 top papers in terms of citations which have cited these papers which are highlighted in grey. Almost all papers in each row are following the main papers’ topics (paper in the first column). For example, all articles that cited Hijmans et al. (2005) and Kalnay et al. (1996) were about climate modelling. Table S-4 in the Supplementary Materials lists the top 5 hot papers in both records which are highlighted in blue, and the top 5 hot papers in terms of citations that have cited the paper in the first column, which are highlighted in grey. According to WoS, hot papers are those that have been published in the last two years and have received enough citations to place them in the top 0.1% of papers in their academic fields. These papers demonstrate potential research hotspots and future research directions, providing readers with a more comprehensive understanding of these two studies. COVID-19 topics are one of the hottest topics due to the current situation and pandemic that most countries are dealing with; these papers cover the impact of COVID-19 on various aspects of our climate such as air pollution and microplastics. Furthermore, the majority of COVID-19-related papers are about climate change, which is classified in the CC/GW/CE record. Other hot topics in both records include air quality and wildlife conservation, such as insect extinction.

Bornmann and Marx first introduced beamplots in 2014 to better visualize the citation impact and productivity of researchers. In addition, beamplots are used to see performance variation over time to make more informed decisions about research impact and evaluation ( Bornmann and Marx, 2014 ). The beamplot represents a single frame of an author's output (the citation performance of an author's entire publication list), which reflects how it varies over time. In the beamplot, each dot represents a specific publication and its position is based on its publication year and its normalized citation percentile score (0–100). For example, a score of 90 for an article means that the article is among the top 10% most cited publications of the subject area, document type, and year.

For the first authors of the top 3 most cited papers in each record, as listed in Table 1 , the citation percentiles of their first authors were higher after publishing these articles, except in the case of Camile Parmesan, first author of Parmesan and Yohe (2003) . Figure S-1 in the Supplementary Materials shows the beamplots of these six authors from both records. For example, in the case of N.A. Rayner, who has published the highest cited paper in the CC/GW/CE record, the mean citation percentile of their papers published after their highest cited paper ( Rayner et al., 2003 ) has increased from 58% to 80%. Likewise but to a much lesser extent, for Eugenia Kalnay, who has published the highest cited paper in the CL record, the citation percentile was increased from 64.7% to 65.3%. This indicates that these authors either had more impactful research output following the publication of their most cited paper, or became better or more widely known after that date and hence received more citations to their latter work than their earlier work. The citation percentile of Camille Parmesan, who has the second highest cited paper ( Parmesan and Yohe, 2003 ) in the CC/GW/CE record, was lower after 2003, when they published their highest cited paper, than before 2003. Figure S-1 shows that their citation percentiles during 2009 and 2010 were zero, which were for five book chapters, and causes this difference between the citation percentile before and after publishing their highest cited paper in 2003. Excluding these book chapters from the beamplot analysis leads to the conclusion that the author's performance actually improved after 2003. In summary, it is commonly the case that highly cited papers, whether they be on CC/GW/CE or CL topics, typically boost an author's citation profile.

Figures  2 and ​ and3 3 present the word clouds generated for the keywords extracted from the top 100 most cited papers in each record. In contrast to the aforementioned analysis of the top 5 most cited papers in each record, which showed significant differences in the two records, the word clouds are qualitatively less precise. Table 2 also presents the top 10 words frequency for the top 100 cited papers in each record. It is understandable that research on CC/GW/CE will use many similar keywords to more general research on the Earth's climate, thus several terms are similarly enlarged on both clouds. For example, model, variability, temperature, precipitation and circulation are some of the main words on both clouds. In fact, the vast majority of words from Figure 2 also appear in Figure 3 , even if in a different size. Climate change and CO 2 are the two terms in Figure 2 that are particularly distinct from Figure 3 , which is expected given that these are key topics of CC/GW/CE research. Figure S-2 in the Supplementary Materials also shows the word dynamic of both records over time. Based on the results from this figure, “climate change” and “climate” terms had the highest increase over time in terms of occurrence in articles. The conclusion from word clouds is that they are visually interesting, but are not ideal tools to evaluate two unique but topically similar publication records. As aforementioned, the Data Analysis section presents more deeply analytical comparisons between the two records, from which clearer trends can be seen.

Word cloud of keywords from top 100 most cited papers on CC/GW/CE research.

Word cloud of keywords from top 100 most cited papers on CL research.

Table 2

Word frequency of top ten used words in Figures  2 and ​ and3 3 .

Figure S-3 in the Supplementary Materials shows the co-occurrence analysis of keywords using the bibliometrix package in Rstudio in order to find research focus ( Aria and Cuccurullo, 2017 ). Based on results from this figure, “climate change”, “climate”, and “variability” were the most frequent words among all keywords from 500 top most cited papers, which were similar to the key topics from the word clouds (Figures  2 and ​ and3 3 ).

4. Data analysis

This section is sub-divided into the four categories of data collection and analysis of the publication records: (i) year of publication; (ii) country (corresponding author's) of publication; (iii) source (i.e., journal) of publication; and (iv) organization (corresponding author's) of publication.

4.1. Year of publication

Figure 4 and Table S-5 in the Supplementary Materials present the data analysis for the year of publication, ranging from 1910 to 2020. The number of articles published per year in the two publication records (CC/GW/CE and CL) was compiled from WoS. For each year, a ratio of the number of articles in the CC/GW/CE record over the number of articles in the CL record was calculated. This ratio is plotted as a function of time in Figure 3 a. The purpose of this ratio is to help visualize when the scientific record became more enriched in CC/GW/CE versus general CL research; that is when the ratio surpasses a value of one. This occurred in 2010, and the ratio has since increased to 1.36 in 2019 and then to 1.45 in 2020 (a full-year record). Notably, before 1989, the ratio was consistently smaller than 0.1, meaning that CC/GW/CE research was scarce for much of the 20 th century. The exceptions in 1910, 1939 and 1941 are due to the very small number of CL publications on record for those decades. From 1989 onwards, the ratio increases nearly every year (in fact, it increases 28 out of 31 times, and every year since 1997).

Data for CC/GW/CE and CL records for year of publication: a) Publication ratio ((CC/GW/CE)/(CL)) as a function of time (years); b) Number of publications per year in the CC/GW/CE record versus those in the CL record (dashed line illustrates the 1:1 mark), which are labelled with the year of each ratio for the period 2006 to 2020 (over this recent period, the annual CL publications continuously increased).

The number of publications in both records rose by orders of magnitude over the last several decades, and Figure 4 b helps to visualize this climb. The CL record crossed 100 publications per year in 1975 versus 1990 for the CC/GW/CE record. The CL record crossed 1,000 publication per year also first, in 1991, followed by the CC/GW/CE record in 1996. Then both records breached 10,000 articles in a year in 2012. This coincides almost exactly with the 2010 threshold when the CC/GW/CE record overtook the CL in the number of publications per year. Points on Figure 4 b above the dashed line indicate the records from the last decade, while those below the dashed line correspond to the pre-2010 record.

Figure 5 breaks down the two data records for the number of articles per year ranging from 1910 to 2020 according to the databases that make up the Web of Science Core Collection. The purpose of this analysis is to visualize if any unusual or sudden changes in the underlying databases could contribute to the trends observed in the full data sets. This could include the effect of databases entering the coverage of the Core Collection in a particular year, or the databases changing their coverage at some point in time. Figure 5 shows that the two largest and oldest databases, namely SCI-EXPANDED and SSCI (with coverage commencing in 1900), have similar temporal trends, to each other and to the Core Collection, given that they make up the most substantial portion of the latter. The ESCI is a newer database (started in 2015), and the A&HCI is a database with a focus on research areas far from the theme of climate research, hence the smaller size of its records in this analysis; their data set trends also are also in overall agreement. Figure 5 is plotted on a log-scale to magnify trends of the smaller data sets, and variability in the two CPCI data sets is evident for both records. Likely this variability is at least partly related with variable number of conference proceedings being indexed by Web of Science each year, and underlying changes in the types of venues used for publication of peer-reviewed papers. Notwithstanding, the small numbers of these data sets (in the order of tens to hundreds of papers per year in the last decades) have insignificant impact on the trends of the much larger overall Core Collection data sets. Tables S-6 and S-7 in the Supplementary Materials show the number of articles in the CL and CC/GW/CE records per year for all databases.

Data for the number of articles per year for all databases in logarithmic scale: a) CC/GW/CE and b) CL.

4.2. Country/region of publication

Figure 6 , Figures S-4 and S-5 in the Supplementary Materials, and Table S-8 in the Supplementary Materials present the data analysis for the country (or region) of publication for the full records ranging from 1910 to 2020. The number of articles published per country/region in the two publication records (CC/GW/CE and CL), from 1910 to 2020, was compiled from WoS. For each country/region, a ratio of the number of articles in the CC/GW/CE record over the number of articles in the CL record was calculated. This ratio is plotted for each country/region in Figure S-4, ordered from largest to smallest ratio. Countries/regions with a ratio greater than one have been more engaged in CC/GW/CE research, while those with a ratio smaller than one have been more engaged in CL research. The number of countries/regions for which a ratio was calculated is 210. An additional 32 countries of regions did not have a ratio calculated, either due to no CC/GW/CE or CL articles on record (this occurs for small states such as Equatorial Guinea and Turks and Caicos). In addition, countries that no longer exist and became part of other countries were merged with their successor countries which include the Soviet Union with Russia; Western Germany with Germany; Serbia Montenegro with Serbia; Yugoslavia with Serbia; Czechoslovakia with the Czech Republic; and Swaziland with Eswatini. The number of studies in these countries before and after merging is shown in Table S-7 in the Supplementary Materials. Figure S-4 shows that slightly more than half of the countries/regions have a ratio greater than one, indicating that the climate challenge has become a dominant scientific topic in many parts of the world. It is notable that the majority of countries/regions with ratios greater than 2 are island states, such as Philippines (ratio = 2.21), Fiji (ratio = 2.92), Bahamas (ratio = 3.23), Palau (ratio = 6.25), Micronesia (ratio = 11), and Kiribati (ratio = 11). This highlights that small island states are at most risk of the catastrophic effects of climate change, particularly rising sea levels ( Vitousek et al., 2017 ; Horton et al., 2014 ; Nunn, 2009 ; King and Harrington, 2018 ; Widlansky et al., 2015 ).

Data for CC/GW/CE and CL records for country/region of publication: Number of publications per country/region in the CC/GW/CE record versus those in the CL record (dashed line illustrates the 1:1 mark), which are labeled with the names of outlier countries.

In contrast, countries and regions with a ratio lower than 0.50 tend to be those of lower gross domestic product, those in arid regions of the world, or those landlocked nations, such as Albania, Djibouti, Algeria and Turkmenistan. Other countries of interest to view ratios for are those with long publication history (USA (0.91), England (1.17), France (0.86), Germany (0.92)) and the emerging/fast growing economies (China (1.07), India (1.00), Brazil (0.76), South Africa (1.27)). The average ratio of these eight countries is very close to 1 (0.99), showing that such countries contribute with diverse research. On a case-by-case basis, it may be possible to claim which countries are more engaged in the climate challenge, but this has to also take into account the fact that a rich amount of older literature from some countries, when CL research was dominant, may be holding back their ratio, but that it does not mean that currently, these countries are just as engaged as others in CC/GW/CE research.

Figure 6 provides a different view of the country/region publication records. By plotting the number of CC/GW/CE publications for each country/region versus the number of CL publications in the same country/region, it is possible to see a focusing effect about the 1:1 dashed line. Countries that have published more, have more diverse body of literature and tend towards the 1:1 line (the USA is the highest point). Countries that have published less are more likely to be more engaged in recent research and thus have more CC/GW/CE articles than CL articles. Notable outliers with more than 10 CL publications (i.e., farthest from the 1:1 line and with a robust body of literature) are Fiji (with the ratio of 2.92) and Monaco (with the ratio of 4.82), both above the line.

4.2.1. Country collaboration

Figure S-6 shows the countries of collaboration of the first authors of the five most cited articles in the CC/GW/CE and CL records, based on the affiliations listed in these authors' articles. For the authors from the CC/GW/CE record, apart from the countries of affiliation of the authors (the USA, England and Austria), the most frequent countries of collaboration have been Germany, the USA, Australia, France and Spain. For the CL record, apart from the country of affiliation of the authors (all from the USA), the most frequent countries of collaboration have been England, Germany, Australia, Canada, China, and Japan. Notably, there is more variety in collaboration in the articles from the CL record. For example, Robert J. Hijmans has collaborated with Peru and the Philippines, which have serious problems with droughts and floods ( Elith et al., 2006 ; Fick and Hijmans, 2017 ). Perhaps unsurprisingly, these highly cited authors collaborate most with anglophone and European countries far more than with others. With climate changing affecting every country on Earth, and disproportionally threatening populations in smaller and less wealthy countries, it would be great to see in the near future deeper engagement of lead researchers directly with the scientific communities in those countries. Among the top 500 articles in the CC/GW/CE record some of these engagements are happing, as seen in Figure S-8 in the Supplementary Materials. Moreover, according to Figures S-5, S-7 and S-8 in the Supplementary Materials, the countries' scientific production and collaboration for the CC/GW/CE record are significantly more diverse than that of the CL record. As mentioned earlier, small island states are at most risk of the catastrophic effects of climate change, particularly rising sea levels ( Vitousek et al., 2017 ; Horton et al., 2014 ; Nunn, 2009 ; King and Harrington, 2018 ; Widlansky et al., 2015 ), which is reflected in the countries’ scientific production and collaboration maps for the CC/GW/CE record (Figures S-5 and S-8).

4.3. Source of publication

Table 3 , Figure 7 , present the data analysis for the source (i.e., journals indexed in WoS) of publication for a part of the records, ranging from 1910 to 2020. The sources analyzed are the top 20 venues of publications from each record in terms of the number of publications in each source. The top 20 were chosen to make the analysis manageable from a reporting and graphing perspective. The top 20 of the CC/GW/CE record represents 18.20% of all articles in this record, and the top 20 of the CL record represents a very similar 18.05% of that record. It is deemed that observations and trends made from the top 20 will be valid as a proxy for the trends of the full record.

Table 3

Top 20 sources of articles from the two records (CC/GW/CE and CL). The number of articles in each source, the percentage of the total number of articles in the full record, and the publication ratios ((CC/GW/CE)/(CL)). Bolded entries are the top 20 of each record, and bolded values reflect the entries that are top 20 on both records (i.e., “match”).

Publication ratio ((CC/GW/CE)/(CL)) for 27 journals, categorized as ‘match’ or ‘non-match’ based on appearance or not in both top 20 lists, ordered from highest to lowest ratio (one curve contains 13 entries and the other 14).

Table 3 presents the number of articles from each record that appear in these journals. A total of 27 journals appear in Table 3 , organized in alphabetic order since there is a partial overlap of the top 20 from each record; in fact, there are 13 journals that are common to both top 20's (these are referred to as ‘match’ journals), and 14 journals in each top 20 that is not in the other top 20 (these are referred to as ‘non-match’ journals). The top journal in the CC/GW/CE record is PLOS ONE, with 3,602 articles representing 1.468% of the full record. The top journal in the CL record is the Journal of Climate, with 5,279 articles representing 2.284% of the full record. Both of these journals are in both top 20 lists, with PLOS ONE having a stronger record of CC/GW/CE articles as given by a ratio (as previously calculated to compare records) of 2.20, while the Journal of Climate has a stronger record of general CL research, with a 0.42 ratio. The ‘match’ journal with the highest ratio (2.36) is Science of the Total Environment, while the Journal of Geophysical Research Atmospheres has the lowest ratio of 0.34. The range of ratios is larger for ‘non-match’ journals. Here the highest ratio is 2.83 for the journal of Sustainability, and the smallest ratio is 0.31 for the journal of Atmospheric Chemistry and Physics. These ratios agree with the perception that can be taken about each of these journals. Journals like PLOS One, Science of the Total Environment and Global Change Biology appeal to more applied areas of research, including the applied sciences and engineering, and have wider aims and scopes, while journals such as the Journal of Climate, Journal of Geophysical Research Atmosphere and Atmospheric Chemistry and Physics appeal to more fundamental and specialized research.

Figure 7 helps to highlight the different scopes of the 27 journals listed in Table 3 . Here, the ratios for each journal are plotted and categorized according to ‘match’ or ‘non-match’ journals. The spider plot shows data arranged from largest to smallest ratio for each category (i.e., each line). Had there been no significant difference in the distribution of the articles across the various journals, both of these lines would be very close to the value of 1. It is clear that the ‘non-match’ line deviates the most from 1, with nearly every value much higher or much lower than 1. Even the ‘match’ line deviates significantly from 1. The ratio value closest to 1 from both categories is that of the journal Remote Sensing (0.94). This is not surprising as remote sensing is a climate monitoring technique that can be used both for general climate research as well as to track changes in the climate due to anthropogenic effects ( Kuenzer et al., 2011 , Levizzani and Cattani, 2019 ; Milesi and Churkina, 2020 ). What can be concluded from this analysis is that journals and authors are able to distinguish the research topics sufficiently to steer more CC/GW/CE research to certain journals and more general CL research to other journals. This helps to confirm that these two topics are distinct in practice.

4.4. Organization of publication

Table 4 , Figure 8 , present the data analysis for organization (i.e., universities, research institutes, and other research-intensive organizations, associated with the corresponding author's primary affiliation) of publication, for a part of the records, ranging from 1910 to 2020. As with sources, the organizations analyzed are the top 20 from each record, and an identical data analysis procedure was used here. The top 20 of the CC/GW/CE record represents 36.72% of all articles in this record, and the top 20 of the CL record represents a slightly higher 38.53% of that record. A total of 26 organizations appear in Table 4 , signifying that there are 14 common organizations within the top 20 (i.e., ‘match’ organizations), and 12 ‘non-match’ organizations. Here, the top three organizations are the same on both records, with the Chinese Academy of Sciences (China) being slightly more engaged in CC/GW/CE research than the the University of California System (USA) and the Centre National de la Recherche Scientifique (France); the ratios of these three organizations are very close to 1 (1.22, 1.05, and 1.02, respectively). In fact, the ratios of these organizations are much closer to 1, on average, than those of the journals. The highest ratio among the 26 organizations is 1.87 for the United States Forest Service, and the lowest ratio is 0.43 for the National Aeronautics Space Administration. This suggests that academic organizations may have more varied research, and hence ratios closer to 1, while governmental organizations may be more focused on a particular line of research, and thus rations more different than 1. Although such a conclusion would require analysis of a large set of organizations, and is complicated by some countries having organizations that have a dual academic and institutional role.

Table 4

Top 20 organizations of articles from the two records (CC/GW/CE and CL). The number of articles from each organization, the percentage of total number of articles in the full record, and the publication ratios ((CC/GW/CE)/(CL)). Bolded entries are the top 20 of each record, and bolded values reflect the entries that are top 20 on both records (i.e., “match”).

Publication ratio ((CC/GW/CE)/(CL)) for 26 organizations, categorized as ‘match’ or ‘non-match’ based on appearance or not in both top 20 lists, ordered from highest to lowest ratio (one curve contains 14 entries and the other 12).

Figure 8 , in contrast to Figure 7 , makes it clear that organizational information is not enough to place research as belonging to one record or another. Both the ‘match’ and ‘non-match’ lines deviated by small extents away from the ratio of 1 level, with the ‘non-match’ line deviating more, as would be expected. For comparison with the earlier case, one of the ratio values closest to 1 from both categories is that of the University of California System (1.05). Notable about this organization is that it consists of nine campuses offering comprehensive education, with varying levels of research excellence (e.g., excellent (Berkeley), very good (Davis), less highly ranked (Riverside), emerging (Merced) ( Gibson et al., 2014 ). This can explain the diversity of research output, covering both CC/GW/CE and CL topics. Of course, this diversity of topic is an average since 1900, and it is possible that in recent years the research in many organizations has shifted towards the climate challenge, as the year and country trends presented earlier suggest.

5. Discussion

Here, we can revisit the three hypotheses and reach conclusions about their claims. With regards to hypothesis 1, it was possible to distinguish the scientific literature linked to CC/GW/CE research from that pertaining to CL research using the two search strings tested. This was verified by reviewing the scope of a number of highly cited papers in both records and is further supported by the trends seen with regards to years of publication, country/region of publication, and source of publication. That is, in these three categories, the publication records showed significant numerical and graphical differences, and these could at times be explained rationally, with basis on data interpretation. Evidence was found that the two publication records contained some misinterpreted publications and outliers, but it is deemed that the consistency of trends observed signify that these issues are minor and acceptable given the simplicity of the publication record assemblage method. A third search string, related to the topic of greenhouse gases, was also tested, but its data did not become part of this study's analysis. The reason for this is that such search string finds many articles that discuss the emissions of greenhouse gases (e.g., from flue gas stacks ( Su et al., 2009 ) or from livestock farming ( Herrero et al., 2013 )) and technologies to control or mitigate these emissions (e.g., via carbon sequestration ( Santos et al., 2013 ) or green energy ( Panepinto et al., 2013 )). As such, these articles fall outside the scope of the two topical records of interest here. This is further evidence that the two search strings used are effective in reaching their intended goal.

With hypothesis 1 confirmed, it is also possible to confirm hypothesis 2. The publication year data clearly shows that the scientific literature has become enriched in CC/GW/CE works in relation to CL works. This is despite both of these records experiencing massive growth over the decades (from under 100 articles per year in the first half of the 20 th century to over 10,000 articles per year in recent years). It is clear that the more pressing the climate challenge becomes, and its effects actually witnessed ( Mahé et al., 2013 ), the more research is being undertaken to forecast the avoidable or unavoidable impacts ( Ito et al., 2020 ; Döll et al., 2020 ). It is difficult to foresee for how much longer the publication ratio devised in this study will continue to rise, globally or country-by-country, as climate research will become increasingly important in the framework of a sustainable society, so it will be worth revisiting this in a decade or more. Perhaps by then another keyword could be added to complement CC/GW/CE. As of August 7 th 2021, 85.82% of this record is retrieved using only CC and excluding (via the NOT operator) the other two search terms (("climat∗ chang∗" NOT ("global warming∗" OR "climat∗ emergenc∗"))); this compares to only 8.32% of the record that only contains GW (("global warming∗" NOT ("climat∗ chang∗" OR "climat∗ emergenc∗"))), and a mere 0.0248% of the record that only contains CE (("climat∗ emergenc∗" NOT ("global warming∗" OR "climat∗ chang∗"))). A simple search for CE yields 61 articles, 53 of which published since 2019, and the oldest from 2011 ( McMichael, 2011 ) being the most cited to date. This shows that this popular term (in the greater public sphere) is not yet commonly used scientifically; will it eventually be?

Hypothesis 3 was partly confirmed. The data and its interpretation show that the two publications records have distinct differences in terms of size (i.e., the number of publications) when it comes to the originating country/region and venue (journal) of publication. Yet, the two records are nearly indistinguishable when the criteria used are the organizations responsible for producing the work. As was explained, research organizations have broad research interests, and it is understandable that the same departments and research groups that perform CC/GW/CE research also tend to perform CL research. Of course, this would not be the case at the researcher level since expertise for these two topics of research is sufficiently different. WoS allows data analysis at the researcher (i.e., corresponding author level). However, in addition to the number of entries being very large (there are over 100,000 corresponding authors listed in the most recent CC/GW/CE and CL records), there is ambiguity with common author names (i.e., same last name and the same first letter of the first name), making any possible analysis less accurate. Such analysis would thus require close scrutiny at the article level.

6. Conclusions

This article presented and discussed the scientific publication record from 1910 to 2020 on two topics: "climate" and "climate change/global warming/climate emergency". The goal is to comparatively visualize how these two distinct publication records have evolved over time, from different classification perspectives, using publication ratios as the key indicator, which were presented as three hypotheses. To test our hypotheses, we defined publication ratios as the number of publications in a category in one record over that in another record, which allowed us to distinguish and contrast CC/GW/CE versus general CL research. The hypotheses can also be expressed as the following questions: (i) what are the dynamics of the conceptual structure of CC/GW/CE versus general CL research; (ii) when has the scientific record in CC/GW/CE versus general climate (CL) research become more enriched; (iii) which countries have made the climate challenge the dominant topic, and are there any links between countries and the dominant scientific topic? The following are the answers to these questions, which present the study's conclusions:

• - The journal name and scope had a direct relationship with the number and ratio of publications in these two records; for example, journals like PLOS One, Science of the Total Environment, and Global Change Biology appealed to more applied areas of research, including the applied sciences and engineering, and have wider aims and scopes, while journals such as the Journal of Climate, Journal of Geophysical Research Atmosphere, and Journal of the Atmospheric Sciences appealed to more fundamental and specialized research.
• - Governmental organizations focused more on a specific line of research (publication ratios farther from a value of 1), whereas academic organizations' research areas were broader and covered a wide range of topics (publication ratios closer to 1).
• - It was discovered that research output related to the Earth's current changing climate surpassed that of general climate research in 2010, and the publication ratio (CC/GW/CE)/(CL) has been increasing over the last decade.
• - Among other countries, island states such as the Philippines, Fiji, Bahamas, Palau, Micronesia, and Kiribati had the highest ratios, highlighting the fact that small island states are most vulnerable to the catastrophic effects of climate change, particularly rising sea levels.
• - Ideas for future bibliometric studies that employ our hypothesis-driven approach and the use of publication ratios as the key trends indicator include: (i) inspecting more closely how non-scientific publications, such as those indexed by databases such as SSCI and A&HCI, have been evolving in covering the topics of climate change, global warming and the climate emergency; (ii) comparing the scientific literature that studies the causes and effects of climate change to the scientific literature that develops ways of mitigating or adapting to climate change or being resilient to it; (iii) identifying important topical gaps in the literature review record (e.g., well-cited articles or articles published in high impact journals that have not been covered in literature reviews); among other possibilities.

Declarations

Author contribution statement.

Rafael M. Santos: Conceived and designed the experiments; Analyzed and interpreted the data; Wrote the paper.

Reza Bakhshoodeh: Performed the experiments; Analyzed and interpreted the data; Contributed reagents, materials, analysis tools or data; Wrote the paper.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Data availability statement

Declaration of interests statement.

The authors declare no conflict of interest.

Additional information

No additional information is available for this paper.

Acknowledgements

The authors acknowledge the University of Guelph Library and the University of Western Australia Library for the Web of Science access provided, which made this study possible.

Appendix A. Supplementary data

The following is the supplementary data related to this article:

• Aleixandre-Benavent R., Aleixandre-Tudó J.L., Castelló-Cogollos L., Aleixandre J.L. Trends in scientific research on climate change in agriculture and forestry subject areas (2005–2014) J. Clean. Prod. 2017; 147 :406–418. [ Google Scholar ]
• Allen C.D., Macalady A.K., Chenchouni H., Bachelet D., Mcdowell N., Vennetier M., Kitzberger T., Rigling A., Breshears D.D., Hogg E.T. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manag. 2010; 259 :660–684. [ Google Scholar ]
• Arana Barbier P.J. Situation of trust in grounded theory versus structural equation modeling: a comparative bibliometric study for management. Invest. Bibl. 2020; 34 :37–53. [ Google Scholar ]
• Aria M., Cuccurullo C. bibliometrix: an R-tool for comprehensive science mapping analysis. J. Inf. 2017; 11 (4):959–975. [ Google Scholar ]
• Baek S., Yoon D.Y., Lim K.J., Hong J.H., Moon J.Y., Seo Y.L., Yun E.J. Top-cited articles versus top Altmetric articles in nuclear medicine: a comparative bibliometric analysis. Acta Radiol. 2020; 61 :1343–1349. [ PubMed ] [ Google Scholar ]
• Benton G.S. Carbon dioxide and its role in climate change. Proc. Natl. Acad. Sci. U.S.A. 1970; 67 :898. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Biesmeijer J.C., Roberts S.P.M., Reemer M., Ohlemuller R., Edwards M., Peeters T., Schaffers A.P., Potts S.G., Kleukers R., Thomas C.D., Settele J., Kunin W.E. Parallel declines in pollinators and insect-pollinated plants in Britain and The Netherlands. Science. 2006; 313 :351–354. [ PubMed ] [ Google Scholar ]
• Bornmann L., Marx W. Distributions instead of single numbers: percentiles and beam plots for the assessment of single researchers. J. Assoc. Inf. Sci. Technol. 2014; 65 :206–208. [ Google Scholar ]
• Breshears D.D., Cobb N.S., Rich P.M., Price K.P., Allen C.D., Balice R.G., Romme W.H., Kastens J.H., Floyd M.L., Belnap J., Anderson J.J., Myers O.B., Meyer C.W. Regional vegetation die-off in response to global-change-type drought. Proc. Natl. Acad. Sci. U.S.A. 2005; 102 :15144–15148. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Bustreo C., Giuliani U., Maggio D., Zollino G. How fusion power can contribute to a fully decarbonized European power mix after 2050. Fusion Eng. Des. 2019; 146 :2189–2193. [ Google Scholar ]
• Callendar G.S. The artificial production of carbon dioxide and its influence on temperature. Q. J. R. Meteorol. Soc. 1938; 64 :223–240. [ Google Scholar ]
• Chen I.C., Hill J.K., Ohlemuller R., Roy D.B., Thomas C.D. Rapid range shifts of species associated with high levels of climate warming. Science. 2011; 333 :1024–1026. [ PubMed ] [ Google Scholar ]
• Demiroglu O.C., Hall C.M. Geobibliography and bibliometric networks of polar tourism and climate change research. Atmosphere. 2020; 11 :498. [ Google Scholar ]
• Döll P., Trautmann T., Göllner M., Schmied H.M. A global-scale analysis of water storage dynamics of inland wetlands: quantifying the impacts of human water use and man-made reservoirs as well as the unavoidable and avoidable impacts of climate change. Ecohydrology. 2020; 13 [ Google Scholar ]
• Elith J., Graham C.H., Anderson R.P., Dudik M., Ferrier S., Guisan A., Hijmans R.J., Huettmann F., Leathwick J.R., Lehmann A., Li J., Lohmann L.G., Loiselle B.A., Manion G., Moritz C., Nakamura M., Nakazawa Y., Overton J.M., Peterson A.T., Phillips S.J., Richardson K., Scachetti-Pereira R., Schapire R.E., Soberon J., Williams S., Wisz M.S., Zimmermann N.E. Novel methods improve prediction of species' distributions from occurrence data. Ecography. 2006; 29 :129–151. [ Google Scholar ]
• Fang Y., Yin J., Wu B. Climate change and tourism: a scientometric analysis using CiteSpace. J. Sustain. Tourism. 2018; 26 :108–126. [ Google Scholar ]
• Fawzy S., Osman A.I., Doran J., Rooney D.W. Strategies for mitigation of climate change: a review. Environ. Chem. Lett. 2020; 18 :2069–2094. [ Google Scholar ]
• Feinberg, J. 2020. Jonathan Feinberg. http://mrfeinberg.com/ .
• Fick S.E., Hijmans R.J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 2017; 37 :4302–4315. [ Google Scholar ]
• Frisken W. Extended industrial revolution and climate change. EOS Trans. Am. Geophys. Union. 1971; 52 :500–508. [ Google Scholar ]
• Fu H.-Z., Waltman L. 2021. A Large-Scale Bibliometric Analysis of Global Climate Change Research between 2001 and 2018. arXiv preprint arXiv:2107.08214. [ Google Scholar ]
• Gibson J., Anderson D.L., Tressler J. Which journal rankings best explain academic salaries? Evidence from the University of California. Econ. Inq. 2014; 52 :1322–1340. [ Google Scholar ]
• Goglio P., Williams A.G., Balta-Ozkan N., Harris N.R., Williamson P., Huisingh D., Zhang Z., Tavoni M. Advances and challenges of life cycle assessment (LCA) of greenhouse gas removal technologies to fight climate changes. J. Clean. Prod. 2020; 244 :118896. [ Google Scholar ]
• Haunschild R., Bornmann L., Marx W. Climate change research in view of bibliometrics. PLoS One. 2016; 11 (7) [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Herrero M., Havlík P., Valin H., Notenbaert A., Rufino M.C., Thornton P.K., Blümmel M., Weiss F., Grace D., Obersteiner M. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proc. Natl. Acad. Sci. Unit. States Am. 2013; 110 :20888–20893. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hijmans R.J., Cameron S.E., Parra J.L., Jones P.G., Jarvis A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 2005; 25 :1965–1978. [ Google Scholar ]
• Hisano M., Searle E.B., Chen H.Y. Biodiversity as a solution to mitigate climate change impacts on the functioning of forest ecosystems. Biol. Rev. 2018; 93 :439–456. [ PubMed ] [ Google Scholar ]
• Horton B.P., Rahmstorf S., Engelhart S.E., Kemp A.C. Expert assessment of sea-level rise by AD 2100 and AD 2300. Quat. Sci. Rev. 2014; 84 :1–6. [ Google Scholar ]
• Ihaka R. Statistics Department, The University of Auckland; Auckland, New Zealand: 1998. R : Past and Future History (Technical Report). Interface '98. [ Google Scholar ]
• IPCC . In: Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team. Pachauri R.K., Meyer L.A., editors. IPCC; Geneva, Switzerland: 2014. p. 151. [ Google Scholar ]
• IPCC . In: In: Global Warming of 1.5°C. An IPCC Special Report on the Impacts of Global Warming of 1.5°C above Pre-industrial Levels and Related Global Greenhouse Gas Emission Pathways, in the Context of Strengthening the Global Response to the Threat of Climate Change, Sustainable Development, and Efforts to Eradicate Poverty. Matthews J.B.R., editor. 2018. Annex I: glossary. [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. [ Google Scholar ]
• Ito A., Reyer C.P., Gädeke A., Ciais P., Chang J., Chen M., François L., Forrest M., Hickler T., Ostberg S. Pronounced and unavoidable impacts of low-end global warming on northern high-latitude land ecosystems. Environ. Res. Lett. 2020; 15 [ Google Scholar ]
• Janmaijaya M., Shukla A.K., Abraham A., Muhuri P.K. Scientometric study of neurocomputing publications (1992–2018): An aerial overview of intrinsic structure. Publications. 2018; 6 [ Google Scholar ]
• Janssen M.A., Schoon M.L., Ke W., Börner K. Scholarly networks on resilience, vulnerability and adaptation within the human dimensions of global environmental change. Global Environ. Change. 2006; 16 :240–252. [ Google Scholar ]
• Kalnay E., Kanamitsu M., Kistler R., Collins W., Deaven D., Gandin L., Iredell M., Saha S., White G., Woollen J., Zhu Y., Chelliah M., Ebisuzaki W., Higgins W., Janowiak J., Mo K.C., Ropelewski C., Wang J., Leetmaa A., Reynolds R., Jenne R., Joseph D. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 1996; 77 :437–471. [ Google Scholar ]
• Khalidy R., Santos R.M. The fate of atmospheric carbon sequestrated through weathering in mine tailings. Miner. Eng. 2021; 163 :106767. [ Google Scholar ]
• King A.D., Harrington L.J. The inequality of climate change from 1.5 to 2 °C of global warming. Geophys. Res. Lett. 2018; 45 :5030–5033. [ Google Scholar ]
• Kistler R., Kalnay E., Collins W., Saha S., White G., Woollen J., Chelliah M., Ebisuzaki W., Kanamitsu M., Kousky V., Van Den Dool H., Jenne R., Fiorino M. The NCEP-NCAR 50-year reanalysis: monthly means CD-ROM and documentation. Bull. Am. Meteorol. Soc. 2001; 82 :247–267. [ Google Scholar ]
• Kopec R.J. Global climate change and the impact of a maximum sea level on coastal settlement. J. Geogr. 1971; 70 :541–550. [ Google Scholar ]
• Kottek M., Grieser J., Beck C., Rudolf B., Rubel F. World map of the Köppen-Geiger climate classification updated. Meteorol. Z. 2006; 15 (3):259–263. [ Google Scholar ]
• Kuenzer C., Bluemel A., Gebhardt S., Quoc T.V., Dech S. Remote sensing of mangrove ecosystem: a review. Rem. Sens. 2011; 3 :878–928. [ Google Scholar ]
• Kyte R. Gaidar Forum Moscow, Russian Federation; 2014. Climate Change Is a Challenge for Sustainable Development. https://www.worldbank.org/en/news/speech/2014/01/15/climate-change-is-challenge-for-sustainable-development URL. [ Google Scholar ]
• Levizzani V., Cattani E. Satellite remote sensing of precipitation and the terrestrial water cycle in a changing climate. Rem. Sens. 2019; 11 :2301. [ Google Scholar ]
• Lezaun J. Hugging the shore: tackling marine carbon dioxide removal as a local governance problem. Front. Climate. 2021; 3 :684063. [ Google Scholar ]
• Li F., Zhou H., Huang D.-S., Guan P. Global research output and theme trends on climate change and infectious diseases: a restrospective bibliometric and Co-word biclustering investigation of papers indexed in PubMed (1999–2018) Int. J. Environ. Res. Publ. Health. 2020; 17 :5228. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Li J., Wang M.-H., Ho Y.-S. Trends in research on global climate change: a Science Citation Index Expanded-based analysis. Global Planet. Change. 2011; 77 :13–20. [ Google Scholar ]
• Lockley A., Mi Z., Coffman D.M. Geoengineering and the blockchain: coordinating carbon dioxide removal and solar radiation management to tackle future emissions. Front. Eng. Manag. 2019; 6 :38–51. [ Google Scholar ]
• Lockyer W.J. Does the Indian climate change? Nature. 1910; 84 :178. [ Google Scholar ]
• Macchi Silva V.V., Ribeiro J.L.D., Alvarez G.R., Caregnato S.E. Competence-based management research in the web of science and scopus databases: scientific production, collaboration, and impact. Publications. 2019; 7 [ Google Scholar ]
• Mahé G., Lienou G., Descroix L., Bamba F., Paturel J.-E., Laraque A., Meddi M., Habaieb H., Adeaga O., Dieulin C. The rivers of Africa: witness of climate change and human impact on the environment. Hydrol. Process. 2013; 27 :2105–2114. [ Google Scholar ]
• Martens P., Mcevoy D., Chang C.T. Sustainability Science. Springer; 2016. Climate change: responding to a major challenge for sustainable development. [ Google Scholar ]
• Marx W., Haunschild R., Bornmann L. Global warming and tea production—the bibliometric view on a newly emerging research topic. Climate. 2017; 5 :46. [ Google Scholar ]
• Mcdowell N., Pockman W.T., Allen C.D., Breshears D.D., Cobb N., Kolb T., Plaut J., Sperry J., West A., Williams D.G., Yepez E.A. Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? New Phytol. 2008; 178 :719–739. [ PubMed ] [ Google Scholar ]
• Mcmichael P. Food system sustainability: questions of environmental governance in the new world (dis)order. Global Environ. Change. 2011; 21 :804–812. [ Google Scholar ]
• Meehl G.A., Covey C., Delworth T., Latif M., Mcavaney B., Mitchell J.F.B., Stouffer R.J., Taylor K.E. The WCRP CMIP3 multimodel dataset - a new era in climate change research. Bull. Am. Meteorol. Soc. 2007; 88 :1383–1394. [ Google Scholar ]
• Mesinger F., Dimego G., Kalnay E., Mitchell K., Shafran P.C., Ebisuzaki W., Jovic D., Woollen J., Rogers E., Berbery E.H., Ek M.B., Fan Y., Grumbine R., Higgins W., Li H., Lin Y., Manikin G., Parrish D., Shi W. North American regional reanalysis. Bull. Am. Meteorol. Soc. 2006; 87 :343–360. [ Google Scholar ]
• Milán-García J., Caparrós-Martínez J.L., Rueda-López N., De Pablo Valenciano J. Climate change-induced migration: a bibliometric review. Glob. Health. 2021; 17 :1–10. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Milesi C., Churkina G. Measuring and monitoring urban impacts on climate change from space. Rem. Sens. 2020; 12 :3494. [ Google Scholar ]
• Munasinghe M. Addressing the sustainable development and climate change challenges together: applying the sustainomics framework. Procedia Social Behavl. Sci. 2010; 2 :6634–6640. [ Google Scholar ]
• Nunn P.D. Responding to the challenges of climate change in the Pacific Islands: management and technological imperatives. Clim. Res. 2009; 40 :211–231. [ Google Scholar ]
• Oliveira C.Y.B., Oliveira C.D.L., Müller M.N., Santos E.P., Dantas D.M., Gálvez A.O. A scientometric overview of global dinoflagellate research. Publications. 2020; 8 :50. [ Google Scholar ]
• Osman A.I., Hefny M., Maksoud M.A., Elgarahy A.M., Rooney D.W. Recent advances in carbon capture storage and utilisation technologies: a review. Environ. Chem. Lett. 2020; 19 :797–849. [ Google Scholar ]
• Ouhamdouch S., Bahir M., Ouazar D., Carreira P.M., Zouari K. Evaluation of climate change impact on groundwater from semi-arid environment (Essaouira Basin, Morocco) using integrated approaches. Environ. Earth Sci. 2019; 78 :1–14. [ Google Scholar ]
• Panepinto D., Genon G., Brizio E., Russolillo D. Production of green energy from co-digestion: perspectives for the Province of Cuneo, energetic balance and environmental sustainability. Clean Technol. Environ. Policy. 2013; 15 :1055–1062. [ Google Scholar ]
• Parmesan C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Evol. Systemat. 2006; 37 :637–669. [ Google Scholar ]
• Parmesan C., Yohe G. A globally coherent fingerprint of climate change impacts across natural systems. Nature. 2003; 421 :37–42. [ PubMed ] [ Google Scholar ]
• Phillips S.J., Anderson R.P., Schapire R.E. Maximum entropy modeling of species geographic distributions. Ecol. Model. 2006; 190 :231–259. [ Google Scholar ]
• Phillips S.J., Dudik M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography. 2008; 31 :161–175. [ Google Scholar ]
• Princiotta F.T., Loughlin D.H. Global climate change: the quantifiable sustainability challenge. J. Air Waste Manag. Assoc. 2014; 64 :979–994. [ PubMed ] [ Google Scholar ]
• R core team . R Foundation for Statistical Computing; Vienna, Austria: 2019. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ URL. [ Google Scholar ]
• Rayner N.A., Parker D.E., Horton E.B., Folland C.K., Alexander L.V., Rowell D.P., Kent E.C., Kaplan A. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J. Geophys. Res.: Atmosphere. 2003; 108 :37. [ Google Scholar ]
• Reynolds R.W., Rayner N.A., Smith T.M., Stokes D.C., Wang W.Q. An improved in situ and satellite SST analysis for climate. J. Clim. 2002; 15 :1609–1625. [ Google Scholar ]
• Ricke K., Millar R., Macmartin D.G. Constraints on global temperature target overshoot. Sci. Rep. 2017; 7 :1–7. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Rubel F., Kottek M. Observed and projected climate shifts 1901-2100 depicted by world maps of the Koppen-Geiger climate classification. Meteorol. Z. 2010; 19 :135–141. [ Google Scholar ]
• Rubel F., Kottek M. The thermal zones of the earth" by Wladimir Koppen (1884) Meteorol. Z. 2011; 20 :361–365. [ Google Scholar ]
• Salmerón-Manzano E., Manzano-Agugliaro F. Worldwide scientific production indexed by scopus on labour relations. Publications. 2017; 5 [ Google Scholar ]
• Santos R.M., Verbeeck W., Knops P., Rijnsburger K., Pontikes Y., Van Gerven T. Integrated mineral carbonation reactor technology for sustainable carbon dioxide sequestration: ‘CO 2 Energy Reactor. Energy Procedia. 2013; 37 :5884–5891. [ Google Scholar ]
• Sobreira C., Klu J.K., Cole C., Nic Daéid N., Ménard H. Reviewing research trends—a scientometric approach using gunshot residue (GSR) literature as an example. Publications. 2020; 8 :7. [ Google Scholar ]
• Steyvers M., Tenenbaum J.B. The large-scale structure of semantic networks: statistical analyses and a model of semantic growth. Cognit. Sci. 2005; 29 :41–78. [ PubMed ] [ Google Scholar ]
• Su F., Lu C., Cnen W., Bai H., Hwang J.F. Capture of CO 2 from flue gas via multiwalled carbon nanotubes. Sci. Total Environ. 2009; 407 :3017–3023. [ PubMed ] [ Google Scholar ]
• Tan X.-C., Zhu K.-W., Sun Y.-L., Zhao W.-Y., Chen F. Bibliometric research on the development of climate change in the BRI regions. Adv. Clim. Change Res. 2021; 12 (2):254–262. [ Google Scholar ]
• Taylor K.E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res.: Atmosphere. 2001; 106 :7183–7192. [ Google Scholar ]
• Taylor K.E., Stouffer R.J., Meehl G.A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 2012; 93 :485–498. [ Google Scholar ]
• Tenenbaum J.B., De Silva V., Langford J.C. A global geometric framework for nonlinear dimensionality reduction. Science. 2000; 290 :2319–2323. [ PubMed ] [ Google Scholar ]
• Tenenbaum J.B., Kemp C., Griffiths T.L., Goodman N.D. How to grow a mind: statistics, structure, and abstraction. Science. 2011; 331 :1279–1285. [ PubMed ] [ Google Scholar ]
• Thomas C.D., Cameron A., Green R.E., Bakkenes M., Beaumont L.J., Collingham Y.C., Erasmus B.F., De Siqueira M.F., Grainger A., Hannah L. Extinction risk from climate change. Nature. 2004; 427 :145–148. [ PubMed ] [ Google Scholar ]
• Uppala S.M., Kallberg P.W., Simmons A.J., Andrae U., Bechtold V.D., Fiorino M., Gibson J.K., Haseler J., Hernandez A., Kelly G.A., Li X., Onogi K., Saarinen S., Sokka N., Allan R.P., Andersson E., Arpe K., Balmaseda M.A., Beljaars A.C.M., Van de Berg L., Bidlot J., Bormann N., Caires S., Chevallier F., Dethof A., Dragosavac M., Fisher M., Fuentes M., Hagemann S., Holm E., Hoskins B.J., Isaksen L., Janssen P., Jenne R., Mcnally A.P., Mahfouf J.F., Morcrette J.J., Rayner N.A., Saunders R.W., Simon P., Sterl A., Trenberth K.E., Untch A., Vasiljevic D., Viterbo P., Woollen J. The ERA-40 re-analysis. Q. J. R. Meteorol. Soc. 2005; 131 :2961–3012. [ Google Scholar ]
• Vitousek S., Barnard P.L., Fletcher C.H., Frazer N., Erikson L., Storlazzi C.D. Doubling of coastal flooding frequency within decades due to sea-level rise. Sci. Rep. 2017; 7 :1–9. [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Walther G.R., Post E., Convey P., Menzel A., Parmesan C., Beebee T.J.C., Fromentin J.M., Hoegh-Guldberg O., Bairlein F. Ecological responses to recent climate change. Nature. 2002; 416 :389–395. [ PubMed ] [ Google Scholar ]
• Wang B., Pan S.-Y., Ke R.-Y., Wang K., Wei Y.-M. An overview of climate change vulnerability: a bibliometric analysis based on Web of Science database. Nat. Hazards. 2014; 74 :1649–1666. [ Google Scholar ]
• Wang Y., Xie Y., Zhou R., Hu X., Li X. A comparative bibliometric analysis of Chinese and foreign articles in environmental footprint family (EFF) research. Environ. Sci. Pollut. Control Ser. 2021; 28 :26280–26293. [ PubMed ] [ Google Scholar ]
• Wei Y.-M., Mi Z.-F., Huang Z. Climate policy modeling: an online SCI-E and SSCI based literature review. Omega. 2015; 57 :70–84. [ Google Scholar ]
• Widlansky M.J., Timmermann A., Cai W. Future extreme sea level seesaws in the tropical Pacific. Sci. Adv. 2015; 1 (8) [ PMC free article ] [ PubMed ] [ Google Scholar ]

Chemical Communications

Mechanistic insights into c–c coupling in electrocatalytic co2 reduction reaction.

The utilization of CO2 has become an emerging area of research in response to climate change and global warming. Electrochemical CO2 reduction reaction (CO2RR) holds significant promise as a technology to address this issue by converting CO2 molecules into various commercially valuable chemicals. While CO2RR to C1 hydrocarbons has achieved high activity and selectivity, the C–C coupling to produce higher hydrocarbons remains challenging due to low energy efficiency and the prevalent hydrogen evolution reaction (HER) on the same catalyst, leading to high hydrogenation rates. In this review, we aim to elucidate the fundamental challenges of C–C coupling and explore potential strategies to enhance the selectivity for higher hydrocarbon products. We discuss the mechanisms underlying the formation of C2 and C3 products, focusing on molecular catalysts that facilitate C–C coupling by positioning CO2 molecules in close proximity. Additionally, we provide a comprehensive overview of different approaches to improve higher hydrocarbon selectivity, along with future suggestions and recommendations for new researchers in the field. This review serves as a valuable resource for both academic researchers and industrial stakeholders aiming for the commercialization of CO2RR technologies.

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Y. Hu, M. K. khan, J. Gong, H. Zeb, H. Lan, M. Asif, H. Xia and M. Du, Chem. Commun. , 2024, Accepted Manuscript , DOI: 10.1039/D4CC03964E

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• Explainer: Why is climate change causing ‘record-shattering’ extreme heat?

Daisy Dunne

The small village of Lytton in British Columbia, Canada was once a pitstop for hikers and tourists taking in nearby scenic mountain ranges and rivers.

But, in 2021, a devastating wildfire – fuelled by an unprecedented heatwave sweeping much of the Pacific north-west – destroyed nearly all of its houses and buildings, killing two of its 250 residents.

Amid the disaster, temperatures in Lytton reached 49.6C – the highest temperature ever recorded in Canada, smashing the previous record for the country by 4.6C.

Climate scientists studying the heatwave were left stunned by the record-shattering temperatures.

“Within our knowledge, this [heatwave] is basically impossible,” the late pioneering extreme weather scientist, Dr Geert Jan van Oldenborgh, told a press conference at the time.

Since then, the Earth has experienced more “record-shattering” extremes.

In 2022, temperatures in the UK reached 40.3C amid a scorching summer heatwave – 1.6C above the previous record. A year later, the national record in China was blown by 1.9C as temperatures hit 52.2C .

At the same time, leading climate scientists have been racing to understand why these events are happening, how they are linked to rapidly rising global temperatures and what this could mean for Earth’s future.

Below, Carbon Brief speaks to experts and assesses the latest scientific evidence to explore why climate change is causing record-shattering extreme heat across the world.

What is ‘record-shattering’ extreme heat?

Why are heat records being shattered by huge margins, how could record-shattering extreme heat increase in future.

In this era of rapid human-caused climate change, the setting of new regional and national temperature records during heatwaves happens so frequently that it can sometimes feel commonplace.

However, every so often, a record is broken by a large margin – often driving unprecedented impacts, as well as alarm about what it might signify about the pace of climate change.

Researchers call this “record-shattering” or “record-smashing” heat, explains Prof Erich Fischer , a climate extremes scientist at ETH Zurich and a lead author of the most recent landmark assessment by the Intergovernmental Panel on Climate Change (IPCC). He tells Carbon Brief:

“I would define it as a class of record-breaking events in which the record breaks the previous one by a large margin.”

What that margin is depends on the event in question, he says.

For example, a new national temperature record that is a few tenths of a degree higher than the previous would not be considered record-shattering.

However, global average temperatures in 2023 were record-shattering – even though they were only 0.14-0.17C above the previous record in 2016.

This is because taking an average over a large area and timescale is more likely to minimise the influence of natural variability in the climate – making smaller upward trends more meaningful, Fischer explains:

“You would expect global temperature to increase rather smoothly, with some wiggles. It’s not like the temperature in our backyard, which goes crazy up and down.”

To quantify the size of record-shattering events at different timescales and in different geographic areas, scientists often use standard deviation . This is a measure of how spread out data is from the mean. 

In what is known as a “normal distribution” of data, 68% of the data points will fall within one standard deviation of the mean , 95% will be within two standard deviations and 99.7% will be within three standard deviations. 

So, for a specific heatwave, scientists calculate how many standard deviations that event is away from the average climate for that location. A record-shattering extreme event will be multiple standard deviations beyond the average.

The last few years have seen a wide variety of record-shattering heat extremes.

Record-shattering new national temperatures have been recorded during heatwaves across western Europe, including in France and the UK, as well as in China and Canada. 

The Pacific north-west heatwave in 2021, when Canada’s temperature record was smashed in Lytton, is among the largest record-shattering heatwaves ever recorded – although there have been a couple of events that were more extreme in terms of standard deviations, research finds.

That research paper found that the Pacific north-west heatwave broke temperature records by just over four standard deviations, while the most extreme heatwave ever recorded, in south-east Asia in 1998, broke records by just over five standard deviations.

Other record-shattering heat events from recent years include a year-long marine heatwave in the north Atlantic Ocean beginning in March 2023, when sea surface temperatures were up to 5C hotter than normal.

The event caused deadly heat stress to hit nearly all of the Atlantic’s tropical reefs and contributed to a very active 2023 Atlantic hurricane season .

It is worth noting that understanding of such extremes is generally better for global-north countries than those in the global south.

Reasons for this include that temperature records in global-north countries are longer and more complete, plus there are more weather stations, too. Previous Carbon Brief analysis found that Africa has the lowest density of weather stations out of any continent, followed by South America and Asia.

This means that scientists do not have a full understanding of the geographic distribution of record-shattering heat, says Dr Robert Vautard , a senior climate scientist at the National Centre for Scientific Research at Institut Pierre-Simon Laplace in Paris and co-chair of the climate science working group of the IPCC. He tells Carbon Brief:

“We don’t know fully where record-shattering events are more expected than in other places…That is an area where I would expect progress in the coming years.”

Back to top

In the aftermath of the 2021 heatwave in the Pacific north-west, scientists were left scratching their heads about the kind of temperatures they were studying.

At the time, researchers at the World Weather Attribution service, a consortium of scientists studying the influence of climate change on extreme events, suggested that it might indicate the Earth had “crossed a non-linear threshold” – where even small increases in global temperature is causing much larger rises in extreme heat than scientists expected.

“It’s an extraordinary event,” van Oldenborgh, who co-founded the WWA, told a press conference , adding that it was “surprising and shaking” to find out that “our theoretical picture of how heatwaves would behave” in a warming climate “was broken” so dramatically.

Since then, several studies have looked into the possible causes of the extremes seen in the Pacific north-west heatwave and the occurrence of record-shattering heat more broadly.

The emerging consensus is that – while staggering and dangerous – these extremes are within the realms of what the world can expect as global temperatures continue to rise rapidly.

Vautard, who recently led a study in Environmental Research Letters looking into whether heat extremes are increasing in a way that is beyond what scientists anticipated, tells Carbon Brief:

“The study shows that this is really what we expect with climate change. There is not anything else that we don’t understand. It’s terrible, but we understand it.”

The reason why records are sometimes broken by large margins – rather than incremental increases – can be understood by considering the rapid rise in global temperatures, explains Fischer, who has also published papers looking into the phenomenon. He says:

“The rate of warming plays an important role. If you have, say, a one-in-50-year event – if it happens once and then reoccurs [on average] 50 years later, the climate in between has been warming very, very rapidly, so the difference in the magnitude of these two events is going to be much larger.”

In other words, every so often, a range of climate factors – both natural and human-caused – will combine to cause an extreme heat event.

Scientists use return periods to describe such events, with a larger return period indicating a more extreme event that is less likely to occur at any given time.

This was the case during the Pacific north-west heatwave, when a “ blocking ” weather pattern – a region of high pressure in the atmosphere – stalled over the region, creating a dome of unusually high temperatures. At the same time, temperatures were exacerbated further by the effect of dry soils .

Each time an event like this occurs, it is against a backdrop of human-caused climate change, which is making heatwaves more intense and more frequent.

As global temperatures continue to rise, their influence on extreme heat events gets larger and larger. 

Therefore, when a very rare heat event combines with ever-increasing temperature rise, it can cause a record-shattering event, says Dr Clair Barnes , a climate statistician at Imperial College London , who was a co-author on the recent Environmental Research Letters study. She tells Carbon Brief:

“The heat extremes that we are seeing are not unexpected.”

In 2021, Fischer led a study published in Nature Climate Change that explored how record-shattering heat events could increase in future.

The research considered such events to be week-long heat extremes that break previous records by two, three or four standard deviations.

Events falling under the two standard deviations category include the 2003 European heatwave , which killed 30,000 people, and the 2010 Russian heatwave , which killed at least 5,000 people in Moscow.

The researchers looked at the probability of such events occurring under a range of future scenarios.

This included a future scenario where greenhouse gas emissions are extremely high (known as “ RCP8.5 ”) and a scenario where global temperature rise is limited to below 2C by 2100 (known as “ RCP2.6 ”). (Limiting global warming to “well-below 2C” is part of the long-term goal set by countries under the Paris Agreement .)

The research found that, under the scenario of very high greenhouse gas emissions, week-long heat events that break records by three or more standard deviations will be come between two and seven times more likely in the period 2021-50 and three-to-21 times more likely in the period 2051-80, when compared to the past three decades.

Conversely, if the world can limit global warming to 2C, which would involve stabilising the climate by reaching net-zero greenhouse gas emissions, the occurrence of record-shattering heat events will rapidly decrease, Fischer says:

“If you manage to stabilise the climate, record-shattering events would decrease. You would still see worrying heatwaves, but that record-shattering aspect would decline.”

This is because the rate of global temperature rise – the main driver of record-shattering extremes – would no longer be increasing.

Even slowing down the pace of global warming, by slashing global emissions, would reduce the probability of such events occuring, he adds:

“This is one of the few early benefits [of mitigating climate change]. I think it’s an important one, because usually we say we will only see benefits once we actually stabilise the climate, but here is one we will see even before we reach this.”

This is a clear example of where “mitigation can help out a lot with adaptation”, adds Vautard:

“Very often we are adapting to what we just saw – or what we saw over our lifetime. But record-shattering events are unthinkable.

“If we stop warming [the planet], the probability of record-shattering events will very rapidly go back to zero. That will help a lot with adaptation.” 

English schools face ‘overheating’ for one-third of year under 2C warming

How Nigeria is reeling from extreme heat fuelled by climate change

Risk of heat-related deaths has ‘increased rapidly’ over past 20 years

Heat-related deaths ‘56% higher among women’ during record-breaking 2022 European summer

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Researchers analyze 1,500 climate policies to find what works—these are the lessons for Australia

by John Quiggin, The Conversation

Almost 35 years have passed since the Intergovernmental Panel on Climate Change released its first assessment report . It found human activities were substantially increasing concentrations of carbon dioxide (CO₂) and other gases in the atmosphere, which was warming the global climate.

Since then, countries around the world have introduced a slew of policies designed to reduce greenhouse gas emissions . But what actually worked?

This question is at the heart of a landmark new paper by German researchers. They analyzed 1,500 climate policies implemented around the world over the past two decades, and found only a small fraction were effective.

Importantly, they found most emissions reduction relied on a mix of policies. The results point to a way forward for Australia, where an economy-wide carbon price is currently politically impossible.

Untangling the policy labyrinth

At a global level, emissions-reduction policies have yet to produce the sustained reduction in CO₂ emissions needed to hold global heating below 2°C.

So it's important to understand how well, or badly, emissions-reduction policies in various countries have worked.

A few ad hoc observations can be made. For example, Australia's carbon emissions fell during the brief period of the Gillard Labor government's carbon price, then rose when the Abbott government removed the policy. It is not hard to identify causality here.

Rarely is the cause for success or failure so clear-cut. Globally, in the past few decades, various policies have been introduced, modified, and in some cases, abandoned. It can be seemingly impossible to disentangle their effects.

But a new paper attempts this task.

'Difference in difference'

The research was led by Annika Stechemesser from Germany's Potsdam Institute for Climate Impact Research. It employs a standard technique for determining the effects of a policy intervention, known as the "differences in differences" approach.

This approach compares changes in outcomes over time between two groups. If a policy was ineffective, the differences between the groups should stay the same over time. If the gap changes in the expected direction, the policy is assumed to be effective.

The method was applied most famously in a 1994 study in the United States by economists David Card and Alan Kreuger. They compared fast-food restaurants in New Jersey, where minimum wages were increased, with those in Pennsylvania, where wages were unchanged.

They found the rise in the minimum wage had no effect on the number of people employed by restaurants. The analysis led to a radical change in thinking about minimum wages.

But that analysis involved a single change. The Potsdam team sought to distinguish the effects of more than 1,500 climate policy interventions, implemented across 41 countries over two decades.

It required sorting through a huge volume of data, while applying the "differences in differences" approach. The researchers did this using artificial intelligence.

They analyzed four sectors: buildings, electricity, industry and transport. They examined eight kinds of policy interventions, primarily focused on:

• pricing policies, such as carbon taxes and permits that can be bought and sold
• regulation, such as bans, building codes and energy efficiency rules
• applying or removing subsidies, such as governments paying property owners to install rooftop solar, or removing tax breaks for the fossil fuel industry.

What the research found

The researchers identified 63 cases where climate policies had led to large emissions reduction.

Unsurprisingly, though a little disappointingly, no "silver bullet" policy emerged. Rather, most successful cases—at least in developed economies—were the result of two or more policies working together.

This might mean, for example, a fuel efficiency mandate for vehicles, combined with subsidies to help develop a network of charging stations for electric vehicles.

The study also found successful policy mixes vary across sectors. For example, in developed countries, pricing was particularly effective policy in sectors dominated by profit-oriented companies, such as electricity and industry. But a mix of incentives and regulations worked best in the buildings and transport sectors.

And countries have different needs, depending on income. In developing countries, for example, pricing interventions did not lead to large emission reductions in the electricity sector. This may change, however, as China gradually develops carbon markets .

The researchers have made the data available to the public in a handy tool . It is easily searchable by sector and country.

The strength of this approach is the ability to integrate analysis across many different countries. However, this global approach precludes a fine-grained analysis for each country.

For example, because Australia's carbon pricing scheme was so short-lived, and its effects rapidly reversed, the differences-in-differences analysis did not capture its significance.

What can Australia learn?

The research is an impressive effort to distill lessons from the mass of confusing data surrounding climate policy.

The findings would once have been unwelcome news to the economics profession, which in the past has largely advocated for one stand-alone policy applied across the economy—most commonly, putting a price on carbon.

Carbon prices are not a complete solution, but they are important. Research in 2020 showed countries with carbon prices, on average, had annual carbon emissions growth rates two percentage points lower than countries without a carbon price.

Unfortunately, in Australia, the federal Coalition is resolutely opposed to any kind of price-based measure to cut emissions. And following the Gillard government's politically bruising experience over the carbon price , the Albanese government is allergic to any mention of such policies.

So, while price-based mechanisms are, theoretically, the ideal way to cut emissions, most economists now accept there's no point holding out for it. If a combination of measures in different parts of the economy is the best we can do, it's better than nothing. The important task is to reduce emissions.

The political constraints on price-based policy mean Australia must push harder on other policy approaches—namely regulations and subsidies—to reach net-zero by 2050.

Provided by The Conversation

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• 05 January 2022

How researchers can help fight climate change in 2022 and beyond

You have full access to this article via your institution.

Devastating floods that hit Germany last July were made more likely by the warming climate. Credit: Christof Stache/AFP/Getty

Late last year, the major climate summit in Glasgow, UK — the 26th Conference of the Parties to the United Nations climate convention (COP26) — injected much-needed momentum into the political and business community in the fight to stop climate change. The year ahead represents an opportunity for scientists of all stripes to offer up expertise and ensure that they have a voice in this monumental effort.

Science is already baked into the UN’s formal climate agenda for 2022. In February, the Intergovernmental Panel on Climate Change (IPCC) is scheduled to release its assessment of the latest research into how climate warming is affecting people and ecosystems; a month later, the panel is set to provide an analysis of the options for curbing emissions and halting global warming. Combined with last year’s report on climate science , the governments of the world will have a solid review of the state-of-the-art of research on climate change. But the research community’s work stretches far beyond the IPCC.

At the top of governments’ climate agenda is innovation. Existing technologies such as wind and solar power, whose price has plummeted over the past decade, and more-efficient lighting, buildings and vehicles will help to reduce emissions. But if green energy is to push out fossil fuels and fulfil the rising demand for reliable power in low-income countries, scientists and engineers will be needed to solve a range of problems. These include finding ways to cut the price of grid-scale electricity storage and to address technical challenges that arise when integrating massive amounts of intermittent renewable energy. Research will also be required to provide a new generation of affordable vehicles powered by electricity and hydrogen, and low-carbon fuels for those that are harder to electrify, such as aircraft.

Even in the most optimistic scenarios, such clean-energy deployments are unlikely to be enough to enable countries to keep their climate commitments. More innovation will also be needed — for example, in the form of technologies that can pull carbon dioxide out of the atmosphere. These have yet to be tested and demonstrated at any significant scale. Governments and funders also need to support scientists in efforts to understand the safety and efficacy of various controversial geoengineering technologies — methods for artificially cooling the planet, such as the addition of particles to the stratosphere to reflect sunlight back into space — if only to determine whether there is sense in even contemplating such alternatives.

Give research into solar geoengineering a chance

There are signs of renewed support for research and innovation in helping to address climate change. In Glasgow, 22 countries, as well as the European Commission (EC), announced plans to cooperate on innovation focused on greening cities, curbing industrial emissions, promoting CO 2 capture and developing renewable fuels, chemicals and materials. The EC has also announced efforts to drive new funds into demonstration projects to help commercialize low-carbon technologies. And China, currently the world’s largest emitter of greenhouse gases, is creating a vast research infrastructure focused on technologies that will help to eliminate carbon emissions.

China creates vast research infrastructure to support ambitious climate goals

In the United States, under President Joe Biden, the Democrats have also made innovation a linchpin of efforts to address climate change. A bipartisan bill enacted in November will expand green-infrastructure investments, as well as providing nearly US$42 billion for clean-energy research and development at the US Department of Energy over the next 5 years, roughly doubling the current budget, according to the Information Technology and Innovation Foundation, a think tank in Washington DC. Another $550 billion for climate and clean-energy programmes is included in a larger budget bill that Democrats hope to pass this year. Economic modelling suggests that the spending surge could help to lower emissions in the coming decade while teeing up technologies that will be crucial to eliminating greenhouse-gas emissions in the latter half of the century.

In addition to enabling green innovation, scientists have an important part to play in evaluating climate policies and tracking commitments made by governments and businesses. Many of the initiatives that gained traction at COP26 need science to succeed. That includes evaluating how climate finance — money that wealthy nations have committed to help low-income nations to curb emissions and cope with climate change — is spent. Research is also needed to understand the impacts of carbon offsets and carbon trading, for which new rules were agreed at COP26.

COP26 climate pledges: What scientists think so far

Climate science, too, must continue apace, helping governments and the public to understand the impact of climate change. From floods in Germany to fires in Australia, the evolving field of climate attribution has already made it clear that global warming is partly to blame for numerous tragedies. Attribution science will also feed into an ongoing geopolitical debate about who should pay for the rising costs of climate-related natural disasters, as many low-income countries seek compensation from wealthy countries that are responsible for the bulk of the greenhouse-gas emissions so far.

These and other issues will be discussed again in November at COP27 in Sharm El-Sheikh, Egypt, where it will be crucial to make sure that everyone has a voice and that research supports climate monitoring and innovation everywhere, not just in richer nations.

A new agreement made at COP26 that requires governments to report annually on their climate progress should help to maintain pressure on them to act on climate change. But science and innovation will be equally important to driving ever-bolder climate policies.

Nature 601 , 7 (2022)

doi: https://doi.org/10.1038/d41586-021-03817-4

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