research studies on global warming

• Ways to Give
• Contact an Expert
• Explore WRI Perspectives

Filter Your Site Experience by Topic

Applying the filters below will filter all articles, data, insights and projects by the topic area you select.

• All Topics Remove filter
• Climate filter site by Climate
• Cities filter site by Cities
• Energy filter site by Energy
• Food filter site by Food
• Forests filter site by Forests
• Freshwater filter site by Freshwater
• Ocean filter site by Ocean
• Business filter site by Business
• Economics filter site by Economics
• Finance filter site by Finance
• Equity & Governance filter site by Equity & Governance

Search WRI.org

Not sure where to find something? Search all of the site's content.

10 Big Findings from the 2023 IPCC Report on Climate Change

• climate change
• Climate Resilience
• climate science
• climatewatch-pinned

March 20 marked the release of the final installment of the Intergovernmental Panel on Climate Change’s (IPCC) Sixth Assessment Report (AR6) , an eight-year long undertaking from the world’s most authoritative scientific body on climate change. Drawing on the findings of 234 scientists on the  physical science of climate change , 270 scientists on  impacts, adaptation and vulnerability to climate change , and 278 scientists on  climate change mitigation , this  IPCC synthesis report  provides the most comprehensive, best available scientific assessment of climate change.

It also makes for grim reading. Across nearly 8,000 pages, the AR6 details the devastating consequences of rising greenhouse gas (GHG) emissions around the world — the destruction of homes, the loss of livelihoods and the fragmentation of communities, for example — as well as the increasingly dangerous and irreversible risks should we fail to change course.

But the IPCC also offers hope, highlighting pathways to avoid these intensifying risks. It identifies readily available, and in some cases, highly cost-effective actions that can be undertaken now to reduce GHG emissions, scale up carbon removal and build resilience. While the window to address the climate crisis is rapidly closing, the IPCC affirms that we can still secure a safe, livable future.

Here are 10 key findings you need to know:

1. Human-induced global warming of 1.1 degrees C has spurred changes to the Earth’s climate that are unprecedented in recent human history.

Already, with 1.1 degrees C (2 degrees F) of global temperature rise, changes to the climate system that are unparalleled over centuries to millennia are now occurring in every region of the world, from rising sea levels to more extreme weather events to rapidly disappearing sea ice.

Additional warming will increase the magnitude of these changes. Every 0.5 degree C (0.9 degrees F) of global temperature rise, for example, will cause clearly discernible increases in the frequency and severity of heat extremes, heavy rainfall events and regional droughts. Similarly, heatwaves that, on average, arose once every 10 years in a climate with little human influence will likely occur 4.1 times more frequently with 1.5 degrees C (2.7 degrees F) of warming, 5.6 times with 2 degrees C (3.6 degrees F) and 9.4 times with 4 degrees C (7.2 degrees F) — and the intensity of these heatwaves will also increase by 1.9 degrees C (3.4 degrees F), 2.6 degrees C (4.7 degrees F) and 5.1 degrees C (9.2 degrees F) respectively.

Rising global temperatures also heighten the probability of reaching dangerous tipping points in the climate system that, once crossed, can trigger self-amplifying feedbacks that further increase global warming, such as thawing permafrost or massive forest dieback. Setting such reinforcing feedbacks in motion can also lead to other substantial, abrupt and irreversible changes to the climate system. Should warming reach between 2 degrees C (3.6 degrees F) and 3 degrees C (5.4 degrees F), for example, the West Antarctic and Greenland ice sheets could melt almost completely and irreversibly over many thousands of years, causing sea levels to rise by several meters.

2. Climate impacts on people and ecosystems are more widespread and severe than expected, and future risks will escalate rapidly with every fraction of a degree of warming.

Described as an “an atlas of human suffering and a damning indictment of failed climate leadership” by United Nations Secretary-General António Guterres, one of AR6’s most alarming conclusions is that adverse climate impacts are already more far-reaching and extreme than anticipated. About half of the global population currently contends with severe water scarcity for at least one month per year, while higher temperatures are enabling the spread of vector-borne diseases, such as malaria, West Nile virus and Lyme disease. Climate change has also slowed improvements in agricultural productivity in middle and low latitudes, with crop productivity growth shrinking by a third in Africa since 1961. And since 2008, extreme floods and storms have forced over 20 million people from their homes every year.

Every fraction of a degree of warming will intensify these threats, and even limiting global temperature rise to 1.5 degree C is not safe for all. At this level of warming, for example, 950 million people across the world’s drylands will experience water stress, heat stress and desertification, while the share of the global population exposed to flooding will rise by 24%.

Similarly, overshooting 1.5 degrees C (2.7 degrees F), even temporarily, will lead to much more severe, oftentimes irreversible impacts, from local species extinctions to the complete drowning of salt marshes to loss of human lives from increased heat stress. Limiting the magnitude and duration of overshooting 1.5 degrees C (2.7 degrees F), then, will prove critical in ensuring a safe, livable future, as will holding warming to as close to 1.5 degrees C (2.7 degrees F) or below as possible. Even if this temperature limit is exceeded by the end of the century, the imperative to rapidly curb GHG emissions to avoid higher levels of warming and associated impacts remains unchanged.

3. Adaptation measures can effectively build resilience, but more finance is needed to scale solutions.

Climate policies in at least 170 countries now consider adaptation, but in many nations, these efforts have yet to progress from planning to implementation. Measures to build resilience are still largely small-scale, reactive and incremental, with most focusing on immediate impacts or near-term risks. This disparity between today’s levels of adaptation and those required persists in large part due to limited finance. According to the IPCC, developing countries alone will need $127 billion per year by 2030 and $295 billion per year by 2050 to adapt to climate change. But funds for adaptation reached just $23 billion to $46 billion from 2017 to 2018, accounting for only 4% to 8% of tracked climate finance.

The good news is that the IPCC finds that, with sufficient support, proven and readily available adaptation solutions can build resilience to climate risks and, in many cases, simultaneously deliver broader sustainable development benefits.

Ecosystem-based adaptation, for example, can help communities adapt to impacts that are already devastating their lives and livelihoods, while also safeguarding biodiversity, improving health outcomes, bolstering food security, delivering economic benefits and enhancing carbon sequestration. Many ecosystem-based adaptation measures — including the protection, restoration and sustainable management of ecosystems, as well as more sustainable agricultural practices like integrating trees into farmlands and increasing crop diversity — can be implemented at relatively low costs today. Meaningful collaboration with Indigenous Peoples and local communities is critical to the success of this approach, as is ensuring that ecosystem-based adaptation strategies are designed to account for how future global temperature rise will impact ecosystems.

4. Some climate impacts are already so severe they cannot be adapted to, leading to losses and damages.

Around the world, highly vulnerable people and ecosystems are already struggling to adapt to climate change impacts. For some, these limits are “soft” — effective adaptation measures exist, but economic, political and social obstacles constrain implementation, such as lack of technical support or inadequate funding that does not reach the communities where it’s needed most. But in other regions, people and ecosystems already face or are fast approaching “hard” limits to adaptation, where climate impacts from 1.1 degrees C (2 degrees F) of global warming are becoming so frequent and severe that no existing adaptation strategies can fully avoid losses and damages. Coastal communities in the tropics, for example, have seen entire coral reef systems that once supported their livelihoods and food security experience widespread mortality, while rising sea levels have forced other low-lying neighborhoods to move to higher ground and abandon cultural sites. 

Whether grappling with soft or hard limits to adaptation, the result for vulnerable communities is oftentimes irreversible and devastating. Such losses and damages will only escalate as the world warms. Beyond 1.5 degrees C (2.7 degrees F) of global temperature rise, for example, regions reliant on snow and glacial melt will likely experience water shortages to which they cannot adapt. At 2 degrees C (3.6 degrees F), the risk of concurrent maize production failures across important growing regions will rise dramatically. And above 3 degrees C (5.4 degrees F), dangerously high summertime heat will threaten the health of communities in parts of southern Europe.

Urgent action is needed to avert, minimize and address these losses and damages. At COP27, countries took a critical step forward by agreeing to establish funding arrangements for loss and damage, including a dedicated fund. While this represents  a historic breakthrough  in the climate negotiations, countries must now figure out the details of what these funding arrangements, as well as the new fund , will look like in practice — and it’s these details that will ultimately determine the adequacy, accessibility, additionality and predictability of these financial flows to those experiencing loss and damage.

5. Global GHG emissions peak before 2025 in 1.5 degrees C-aligned pathways.

The IPCC finds that there is a more than 50% chance that global temperature rise will reach or surpass 1.5 degrees C (2.7 degrees F) between 2021 and 2040 across studied scenarios, and under a high-emissions pathway, specifically, the world may hit this threshold even sooner — between 2018 and 2037. Global temperature rise in such a carbon-intensive scenario could also increase to 3.3 degrees C to 5.7 degrees C (5.9 degrees F to 10.3 degrees F) by 2100. To put this projected amount of warming into perspective, the last time global temperatures exceeded 2.5 degrees C (4.5 degrees F) above pre-industrial levels was more than 3 million years ago.

Changing course to limit global warming to 1.5 degrees C (2.7 degrees F) — with no or limited overshoot — will instead require deep GHG emissions reductions in the near-term. In modelled pathways that limit global warming to this goal, GHG emissions peak immediately and before 2025 at the latest. They then drop rapidly, declining 43% by 2030 and 60% by 2035, relative to 2019 levels.

While there are some bright spots — the annual growth rate of GHG emissions slowed from an average of 2.1% per year between 2000 and 2009 to 1.3% per year between 2010 and 2019, for example — global progress in mitigating climate change remains woefully off track. GHG emissions have climbed steadily over the past decade, reaching 59 gigatonnes of carbon dioxide equivalent (GtCO2e) in 2019 — approximately 12% higher than in 2010 and 54% greater than in 1990.

Even if countries achieved their climate pledges (also known as nationally determined contributions or NDCs),  WRI research  finds that they would reduce GHG emissions by just 7% from 2019 levels by 2030, in contrast to the 43% associated with limiting temperature rise to 1.5 degrees C (2.7 degrees F). And while handful of countries have submitted  new or enhanced NDCs  since the IPCC’s cut-off date,  more recent analysis  that takes these submissions into account finds that these commitments collectively still fall short of closing this emissions gap.

6. The world must rapidly shift away from burning fossil fuels — the number one cause of the climate crisis.

In pathways limiting warming to 1.5 degrees C (2.7 degrees F) with no or limited overshoot just a net 510 GtCO2 can be emitted before carbon dioxide emissions reach net zero in the early 2050s. Yet future carbon dioxide emissions from existing and planned fossil fuel infrastructure alone could surpass that limit by 340 GtCO2, reaching 850 GtCO2.

A mix of strategies can help avoid  locking in  these emissions, including retiring existing fossil fuel infrastructure, canceling new projects, retrofitting fossil-fueled power plants with carbon capture and storage (CCS) technologies and scaling up renewable energy sources like solar and wind (which are now cheaper than fossil fuels in many regions).

In pathways that limit warming to 1.5 degrees C (2.7 degrees F) — with no or limited overshoot — for example, global use of coal falls by 95% by 2050, oil declines by about 60% and gas by about 45%. These figures assume significant use of abatement technologies like CCS, and without them, these same pathways show much steeper declines by mid-century. Global use of coal without CCS, for example, is virtually phased out by 2050.

Although coal-fired power plants are starting to be retired across Europe and the United States, some multilateral development banks continue to invest in new coal capacity. Failure to change course risks stranding assets worth trillions of dollars.

7. We also need urgent, systemwide transformations to secure a net-zero, climate-resilient future.

While fossil fuels are the number one source of GHG emissions, deep emission cuts are necessary across all of society to combat the climate crisis. Power generation, buildings, industry, and transport are responsible for close to 80% of global emissions while agriculture, forestry and other land uses account for the remainder.

Take the  transport system , for instance. Drastically cutting emissions will require urban planning that minimizes the need for travel, as well as the build-out of shared, public and nonmotorized transport, such as rapid transit and bicycling in cities. Such a transformation will also entail increasing the supply of electric passenger vehicles, commercial vehicles and buses, coupled with wide-scale installation of rapid-charging infrastructure, investments in zero-carbon fuels for shipping and aviation and more.

Policy measures that make these changes less disruptive can help accelerate needed transitions, such as subsidizing zero-carbon technologies and taxing high-emissions technologies like fossil-fueled cars. Infrastructure design — like reallocating street space for sidewalks or bike lanes — can help people transition to lower-emissions lifestyles. It is important to note there are many co-benefits that accompany these transformations, too. Minimizing the number of passenger vehicles on the road, in this example, reduces harmful local air pollution and cuts traffic-related crashes and deaths.

Systems Change Lab  monitors, learns from and mobilizes action to achieve the far-reaching transformational shifts needed to limit global warming to 1.5 degrees C, halt biodiversity loss and build a just and equitable economy.

Transformative adaptation measures, too, are critical for securing a more prosperous future. The IPCC emphasizes the importance of ensuring that adaptation measures drive systemic change, cut across sectors and are distributed equitably across at-risk regions. The good news is that there are oftentimes strong synergies between transformational mitigation and adaptation. For example, in the global food system, climate-smart agriculture practices like shifting to  agroforestry  can improve resilience to climate impacts, while simultaneously advancing mitigation.  

8. Carbon removal is now essential to limit global temperature rise to 1.5 degrees C.

Deep decarbonization across all systems while building resilience won’t be enough to achieve global climate goals, though. The IPCC finds that all pathways that limit warming to 1.5 degrees C (2.7 degrees F) — with no or limited overshoot — depend on some quantity of  carbon removal . These approaches encompass both natural solutions, such as sequestering and storing carbon in trees and soil, as well as more nascent technologies that pull carbon dioxide directly from the air.

Hover over each carbon removal approach to learn more:

Note: This figure includes carbon removal approaches mentioned in countries' long-term climate strategies as well as other leading proposed approaches. The natural/biotic vs. technological/abiotic categorization shown here is illustrative rather than definitive and will vary depending on how approaches are applied, particularly for carbon removal approaches in the ocean.

The amount of carbon removal required depends on how quickly we reduce GHG emissions across other systems and the extent to which climate targets are overshot, with estimates ranging from between 5 GtCO2 to 16 GtCO2 per year needed by mid-century.

All carbon removal approaches have merits and drawbacks. Reforestation, for instance, represents a readily available, relatively low-cost strategy that, when implemented appropriately, can deliver a wide range of benefits to communities. Yet the carbon stored within these ecosystems is also vulnerable to disturbances like wildfires, which may increase in frequency and severity with additional warming. And, while technologies like bioenergy with carbon capture and storage (BECCS) may offer a more permanent solution, such approaches also risk displacing croplands, and in doing so, threatening food security. Responsibly researching, developing and deploying emerging carbon removal technologies, alongside existing natural approaches, will therefore require careful understanding of each solution’s unique benefits, costs and risks.

9. Climate finance for both mitigation and adaptation must increase dramatically this decade.

The IPCC finds that public and private finance flows for fossil fuels today far surpass those directed toward climate mitigation and adaptation. Thus, while annual public and private climate finance has risen by upwards of 60% since the IPCC’s Fifth Assessment Report, much more is still required to achieve global climate change goals. For instance, climate finance will need to increase between 3 and 6 times by 2030 to achieve mitigation goals, alone.

This gap is widest in developing countries, particularly those already struggling with debt, poor credit ratings and economic burdens from the COVID-19 pandemic. Recent mitigation investments, for example, need to increase by at least sixfold in Southeast Asia and developing countries in the Pacific, fivefold in Africa and fourteenfold in the Middle East by 2030 to hold warming below 2 degrees C (3.6 degrees F). And across sectors, this shortfall is most pronounced for agriculture, forestry and other land use, where recent financial flows are 10 to 31 times below what is required to achieve the Paris Agreement’s goals.

Finance for adaptation, as well as loss and damage, will also need to rise dramatically. Developing countries, for example, will need $127 billion per year by 2030 and $295 billion per year by 2050. While AR6 does not assess countries’ needs for finance to avert, minimize and address losses and damages,  recent estimates  suggest that they will be substantial in the coming decades. Current funds for both fall well below estimated needs, with the highest estimates of adaptation finance totaling under $50 billion per year.

10. Climate change — as well as our collective efforts to adapt to and mitigate it — will exacerbate inequity should we fail to ensure a just transition.  

Households with incomes in the top 10%, including a relatively large share in developed countries, emit upwards of 45% of the world's GHGs, while those families earning in the bottom 50% account for 15% at most. Yet the effects of climate change already — and will continue to — hit poorer, historically marginalized communities the hardest.

Today, between 3.3 billion and 3.6 billion people live in countries that are highly vulnerable to climate impacts, with global hotspots concentrated in the Arctic, Central and South America, Small Island Developing states, South Asia and much of sub-Saharan Africa. Across many countries in these regions, conflict, existing inequalities and development challenges (e.g., poverty and limited access to basic services like clean water) not only heighten sensitivity to climate hazards, but also limit communities’ capacity to adapt.  Mortality from storms, floods and droughts, for instance, was 15 times higher in countries with high vulnerability to climate change than in those with very low vulnerability from 2010 to 2020.

At the same time, efforts to mitigate climate change also risk disruptive changes and exacerbating inequity. Retiring coal-fired power plants, for instance, may displace workers, harm local economies and reconfigure the social fabric of communities, while inappropriately implemented efforts to halt deforestation could heighten poverty and intensify food insecurity. And certain climate policies, such as  carbon taxes  that raise the cost of emissions-intensive goods like gasoline, can also prove to be regressive, absent of efforts to recycle the revenues raised from these taxes back into programs that benefit low-income communities.

Fortunately, the IPCC identifies a range of measures that can support a just transition and help ensure that no one is left behind as the world moves toward a net-zero-emissions, climate-resilient future. Reconfiguring social protection programs (e.g., cash transfers, public works programs and social safety nets) to include adaptation, for example, can reduce communities’ vulnerability to a wide range of future climate impacts, while strengthening justice and equity. Such programs are particularly effective when paired with efforts to expand access to infrastructure and basic services.

Similarly, policymakers can design mitigation strategies to better distribute the costs and benefits of reducing GHG emissions. Governments can pair efforts to phase out coal-fired electricity generation, for instance, with subsidized job retraining programs that support workers in developing the skills needed to secure new, high-quality jobs. Or, in another example, officials can couple policy interventions dedicated to expanding access to public transit with interventions to improve access to nearby, affordable housing.

Across both mitigation and adaptation measures, inclusive, transparent and participatory decision-making processes will play a central role in ensuring a just transition. More specifically, these forums can help cultivate public trust, deepen public support for transformative climate action and avoid unintended consequences.

Looking Ahead

The IPCC’s AR6 makes clear that risks of inaction on climate are immense and the way ahead requires change at a scale not seen before. However, this report also serves as a reminder that we have never had more information about the gravity of the climate emergency and its cascading impacts — or about what needs to be done to reduce intensifying risks.

Limiting global temperature rise to 1.5 degrees C (2.7 degrees F) is still possible, but only if we act immediately. As the IPCC makes clear, the world needs to peak GHG emissions before 2025 at the very latest, nearly halve GHG emissions by 2030 and reach net-zero CO2 emissions around mid-century, while also ensuring a just and equitable transition. We’ll also need an all-hands-on-deck approach to guarantee that communities experiencing increasingly harmful impacts of the climate crisis have the resources they need to adapt to this new world. Governments, the private sector, civil society and individuals must all step up to keep the future we desire in sight. A narrow window of opportunity is still open, but there’s not one second to waste.

Note: In addition to showcasing findings from the IPCC’s AR6 Synthesis Report, this article also draws on previous articles detailing the IPCC’s findings on  the physical science of climate change ,  impacts, adaption and vulnerability ,  and  climate change mitigation .

Relevant Work

6 takeaways from the 2022 ipcc climate change mitigation report, 6 big findings from the ipcc 2022 report on climate impacts, adaptation and vulnerability, 5 big findings from the ipcc’s 2021 climate report, 8 things you need to know about the ipcc 1.5˚c report.

Join us on March 23 for a high-level webinar featuring IPCC authors, government representatives and leading carbon removal experts to discuss how carbon removal is a critical tool in our toolbox to address the climate crisis.

How You Can Help

WRI relies on the generosity of donors like you to turn research into action. You can support our work by making a gift today or exploring other ways to give.

Stay Informed

World Resources Institute 10 G Street NE Suite 800 Washington DC 20002 +1 (202) 729-7600

© 2024 World Resources Institute

Envision a world where everyone can enjoy clean air, walkable cities, vibrant landscapes, nutritious food and affordable energy.

Newsroom Post

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.
• Climate change is affecting rainfall patterns. In high latitudes, precipitation is likely to increase, while it is projected to decrease over large parts of the subtropics. Changes to monsoon precipitation are expected, which will vary by region.
• 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.

For more information contact:

IPCC Press Office [email protected] , +41 22 730 8120

Katherine Leitzell [email protected]

Nada Caud (French) [email protected]

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
• 167 – lead authors
• 36 – review editors
• 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.

The IPCC has three working groups: Working Group I , dealing with the physical science basis of climate change; Working Group II , dealing with impacts, adaptation and vulnerability; and Working Group III , dealing with the mitigation of climate change. It also has a Task Force on National Greenhouse Gas Inventories that develops methodologies for measuring emissions and removals. As part of the IPCC, a Task Group on Data Support for Climate Change Assessments (TG-Data) provides guidance to the Data Distribution Centre (DDC) on curation, traceability, stability, availability and transparency of data and scenarios related to the reports of the IPCC.

IPCC assessments provide governments, at all levels, with scientific information that they can use to develop climate policies. IPCC assessments are a key input into the international negotiations to tackle climate change. IPCC reports are drafted and reviewed in several stages, thus guaranteeing objectivity and transparency. An IPCC assessment report consists of the contributions of the three working groups and a Synthesis Report. The Synthesis Report integrates the findings of the three working group reports and of any special reports prepared in that assessment cycle.

About the Sixth Assessment Cycle

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.

The other two Working Group contributions to the AR6 will be finalized in 2022 and the AR6 Synthesis Report will be completed in the second half of 2022.

For more information go to www.ipcc.ch

The website includes outreach materials including videos about the IPCC and video recordings from outreach events conducted as webinars or live-streamed events.

Most videos published by the IPCC can be found on our YouTube and Vimeo channels.

Climate Change

From the unique vantage point in space, NASA collects critical long-term observations of our changing planet.

Latest News

NASA-Designed Greenhouse Gas-Detection Instrument Launches

NASA Invites Media to Event with Scientists, Research Plane in Alaska

NASA Data Shows July 22 Was Earth’s Hottest Day on Record

NASA Returns to Arctic Studying Summer Sea Ice Melt

Watch Carbon Dioxide Move Through Earth’s Atmosphere

How Do We Know Climate Change is Real?

There is unequivocal evidence that Earth is warming at an unprecedented rate. Human activity is the principal cause.

Earth-orbiting satellites and new technologies have helped scientists see the big picture, collecting many different types of information about our planet and its climate all over the world. These data, collected over many years, reveal the signs and patterns of a changing climate.

What is causing climate change?

Human activities are driving the global warming trend observed since the mid-20th century.

Scientists attribute the global warming trend observed since the mid-20 th century to the human expansion of the "greenhouse effect" — warming that results when the atmosphere traps heat radiating from Earth toward space. Over the last century, burning of fossil fuels like coal and oil has increased the concentration of atmospheric carbon dioxide (CO 2 ). This increase happens because the coal or oil burning process combines carbon with oxygen in the air to make CO 2 .

What are the effects of climate change?

The effects of human-caused global warming are happening now, are irreversible for people alive today, and will worsen as long as humans add greenhouse gases to the atmosphere.

We already see effects scientists predicted, such as the loss of sea ice, melting glaciers and ice sheets, sea level rise, and more intense heat waves. Scientists predict global temperature increases from human-made greenhouse gases will continue. Severe weather damage will also increase and intensify.

Images of Change

Before-and-after images of Earth.

Climate Change Resources

Climate Time Machine

Climate change in recent history

Global Ice Viewer

Climate change’s impact on ice

Vast library of images, videos, graphics, and more

Creciente biblioteca de recursos en español

Climate Data Resources

Sea Level Change Observations from Space

Established in 2014, this NASA-sponsored team works to improve the understanding of regional relative sea-level change on a range of timescales. They work with partners to translate the latest science and research into actionable information  and to communicate how impacts are increasing at the coast.

NASA Center for Climate Simulation (NCCS)

NCCS provides high performance computing for NASA-sponsored scientists and engineers. The purpose  is to enhance NASA capabilities in Earth science, with an emphasis on weather and climate prediction, and to enable future scientific discoveries that will benefit humankind.

GISS Surface Temperature Analysis (GISTEMP)

NASA’s Goddard Institute of Space Studies assembles one of the world's most trusted global temperature records, using a combination of surface air temperature data acquired by tens of thousands of meteorological stations, as well as sea surface temperature data from ship- and buoy-based instruments.

NASA Earth Exchange (NEX)

NEX combines state-of-the-art supercomputing, Earth system modeling, and NASA remote sensing data feeds to deliver a work environment for exploring and analyzing terabyte- to petabyte-scale datasets covering large regions, continents or the globe.

Global Modeling and Assimilation Office (GMAO)

GMAO members perform research, develop models and assimilation systems, and produce quasi-operational products in support of NASA's missions. The Goddard Earth Observing System" (GEOS) family of models is used for applications across a wide range of spatial scales, from kilometers to many tens of kilometers. 

World of Change

NASA Earth Observatory has produced a collection of image series that show some features of Earth that have changed over time due to both natural and human-induced causes.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Springer Nature - PMC COVID-19 Collection

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

Kashif abbass.

1 School of Economics and Management, Nanjing University of Science and Technology, Nanjing, 210094 People’s Republic of China

Muhammad Zeeshan Qasim

2 Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse, School of Environmental and Biological Engineering, Nanjing University of Science and Technology, Xiaolingwei 200, Nanjing, 210094 People’s Republic of China

Huaming Song

Muntasir murshed.

3 School of Business and Economics, North South University, Dhaka, 1229 Bangladesh

4 Department of Journalism, Media and Communications, Daffodil International University, Dhaka, Bangladesh

Haider Mahmood

5 Department of Finance, College of Business Administration, Prince Sattam Bin Abdulaziz University, 173, Alkharj, 11942 Saudi Arabia

Ijaz Younis

Associated data.

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

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.

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.

Methodology search for finalized articles for investigations.

Source : constructed by authors

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.

Global deaths from natural disasters, 1978 to 2020.

Source EMDAT ( 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 ​ (Table1). 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.

Main natural danger statistics for 1985–2020 at the global level

Source: EM-DAT ( 2020 )

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 .

A typical interaction between the susceptible and resistant strains.

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

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 ​ (Table2 2 ).

Examples of how various environmental changes affect various infectious diseases in humans

Source: Aron and Patz ( 2001 )

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 ​ Table3 3 demonstrates some of the particular considerations with practical examples that are essential while mitigating the impacts of CC in the forestry sector.

Essential considerations while mitigating the climate change impacts on the forestry sector

Source : Fischer ( 2019 )

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;

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 ).

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 ).

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.

Author contribution

KA: Writing the original manuscript, data collection, data analysis, Study design, Formal analysis, Visualization, Revised draft, Writing-review, and editing. MZQ: Writing the original manuscript, data collection, data analysis, Writing-review, and editing. HS: Contribution to the contextualization of the theme, Conceptualization, Validation, Supervision, literature review, Revised drapt, and writing review and editing. MM: Writing review and editing, compiling the literature review, language editing. HM: Writing review and editing, compiling the literature review, language editing. IY: Contribution to the contextualization of the theme, literature review, and writing review and editing.

Availability of data and material

Declarations.

Not applicable.

The authors declare no competing interests.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Kashif Abbass, Email: nc.ude.tsujn@ssabbafihsak .

Muhammad Zeeshan Qasim, Email: moc.kooltuo@888misaqnahseez .

Huaming Song, Email: nc.ude.tsujn@gnimauh .

Muntasir Murshed, Email: [email protected] .

Haider Mahmood, Email: moc.liamtoh@doomhamrediah .

Ijaz Younis, Email: nc.ude.tsujn@sinuoyzaji .

• 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 [ PubMed ]
• Abbass K, Song H, Shah SM, Aziz B. Determinants of Stock Return for Non-Financial Sector: Evidence from Energy Sector of Pakistan. J Bus Fin Aff. 2019; 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. An enzyme from bacteria able to destroy penicillin. 1940. Rev Infect Dis. 1988; 10 (4):677. [ PubMed ] [ Google Scholar ]
• Adger WN, Arnell NW, Tompkins EL. Successful adaptation to climate change across scales. Glob Environ Chang. 2005; 15 (2):77–86. doi: 10.1016/j.gloenvcha.2004.12.005. [ CrossRef ] [ Google Scholar ]
• Akkari C, Bryant CR. The co-construction approach as approach to developing adaptation strategies in the face of climate change and variability: A conceptual framework. Agricultural Research. 2016; 5 (2):162–173. doi: 10.1007/s40003-016-0208-8. [ CrossRef ] [ Google Scholar ]
• 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. Assessing farmer use of climate change adaptation practices and impacts on food security and poverty in Pakistan. Clim Risk Manag. 2017; 16 :183–194. doi: 10.1016/j.crm.2016.12.001. [ CrossRef ] [ Google Scholar ]
• Allen CD, Macalady AK, Chenchouni H, Bachelet D, McDowell N, Vennetier M, Hogg ET. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag. 2010; 259 (4):660–684. doi: 10.1016/j.foreco.2009.09.001. [ CrossRef ] [ Google Scholar ]
• 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. 10.1007/s10668-021-01716-2
• Araus JL, Slafer GA, Royo C, Serret MD. Breeding for yield potential and stress adaptation in cereals. Crit Rev Plant Sci. 2008; 27 (6):377–412. doi: 10.1080/07352680802467736. [ CrossRef ] [ Google Scholar ]
• Aron JL, Patz J (2001) Ecosystem change and public health: a global perspective: JHU Press
• Arshad MI, Iqbal MA, Shahbaz M. Pakistan tourism industry and challenges: a review. Asia Pacific Journal of Tourism Research. 2018; 23 (2):121–132. doi: 10.1080/10941665.2017.1410192. [ CrossRef ] [ Google Scholar ]
• Ashbolt NJ. Microbial contamination of drinking water and human health from community water systems. Current Environmental Health Reports. 2015; 2 (1):95–106. doi: 10.1007/s40572-014-0037-5. [ PMC free article ] [ PubMed ] [ CrossRef ] [ 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. Uncertainty in simulating wheat yields under climate change. Nat Clim Chang. 2013; 3 (9):827–832. doi: 10.1038/nclimate1916. [ CrossRef ] [ Google Scholar ]
• 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. Mainstreaming climate change adaptation into development in Bangladesh. Clim Dev. 2014; 6 :293–305. doi: 10.1080/17565529.2014.977761. [ CrossRef ] [ Google Scholar ]
• 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. The environmental Kuznets curve, based on the economic complexity, and the pollution haven hypothesis in PIIGS countries. Renew Energy. 2022; 185 :1441–1455. doi: 10.1016/j.renene.2021.10.059. [ CrossRef ] [ Google Scholar ]
• 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. Defining and observing stages of climate-mediated range shifts in marine systems. Glob Environ Chang. 2014; 26 :27–38. doi: 10.1016/j.gloenvcha.2014.03.009. [ CrossRef ] [ Google Scholar ]
• Battisti DS, Naylor RL. Historical warnings of future food insecurity with unprecedented seasonal heat. Science. 2009; 323 (5911):240–244. doi: 10.1126/science.1164363. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Beesley L, Close PG, Gwinn DC, Long M, Moroz M, Koster WM, Storer T. Flow-mediated movement of freshwater catfish, Tandanus bostocki, in a regulated semi-urban river, to inform environmental water releases. Ecol Freshw Fish. 2019; 28 (3):434–445. doi: 10.1111/eff.12466. [ CrossRef ] [ Google Scholar ]
• Benita F (2021) Human mobility behavior in COVID-19: A systematic literature review and bibliometric analysis. Sustain Cities Soc 70:102916 [ PMC free article ] [ PubMed ]
• Berendonk TU, Manaia CM, Merlin C, Fatta-Kassinos D, Cytryn E, Walsh F, Pons M-N. Tackling antibiotic resistance: the environmental framework. Nat Rev Microbiol. 2015; 13 (5):310–317. doi: 10.1038/nrmicro3439. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Berg MP, Kiers ET, Driessen G, Van DerHEIJDEN M, Kooi BW, Kuenen F, Ellers J. Adapt or disperse: understanding species persistence in a changing world. Glob Change Biol. 2010; 16 (2):587–598. doi: 10.1111/j.1365-2486.2009.02014.x. [ CrossRef ] [ Google Scholar ]
• Blum A, Klueva N, Nguyen H. Wheat cellular thermotolerance is related to yield under heat stress. Euphytica. 2001; 117 (2):117–123. doi: 10.1023/A:1004083305905. [ CrossRef ] [ Google Scholar ]
• Bonacci O. Air temperature and precipitation analyses on a small Mediterranean island: the case of the remote island of Lastovo (Adriatic Sea, Croatia) Acta Hydrotechnica. 2019; 32 (57):135–150. doi: 10.15292/acta.hydro.2019.10. [ CrossRef ] [ Google Scholar ]
• 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 [ PMC free article ] [ PubMed ]
• Brázdil R, Stucki P, Szabó P, Řezníčková L, Dolák L, Dobrovolný P, Suchánková S. Windstorms and forest disturbances in the Czech Lands: 1801–2015. Agric for Meteorol. 2018; 250 :47–63. doi: 10.1016/j.agrformet.2017.11.036. [ CrossRef ] [ Google Scholar ]
• Brown HCP, Smit B, Somorin OA, Sonwa DJ, Nkem JN. Climate change and forest communities: prospects for building institutional adaptive capacity in the Congo Basin forests. Ambio. 2014; 43 (6):759–769. doi: 10.1007/s13280-014-0493-z. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Bujosa A, Riera A, Torres CM. Valuing tourism demand attributes to guide climate change adaptation measures efficiently: the case of the Spanish domestic travel market. Tour Manage. 2015; 47 :233–239. doi: 10.1016/j.tourman.2014.09.023. [ CrossRef ] [ Google Scholar ]
• Calderini D, Abeledo L, Savin R, Slafer GA. Effect of temperature and carpel size during pre-anthesis on potential grain weight in wheat. J Agric Sci. 1999; 132 (4):453–459. doi: 10.1017/S0021859699006504. [ CrossRef ] [ Google Scholar ]
• Cammell M, Knight J. Effects of climatic change on the population dynamics of crop pests. Adv Ecol Res. 1992; 22 :117–162. doi: 10.1016/S0065-2504(08)60135-X. [ CrossRef ] [ Google Scholar ]
• Cavanaugh KC, Kellner JR, Forde AJ, Gruner DS, Parker JD, Rodriguez W, Feller IC. Poleward expansion of mangroves is a threshold response to decreased frequency of extreme cold events. Proc Natl Acad Sci. 2014; 111 (2):723–727. doi: 10.1073/pnas.1315800111. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Defining the process to literature searching in systematic reviews: a literature review of guidance and supporting studies. BMC Med Res Methodol. 2018; 18 (1):1–14. doi: 10.1186/s12874-018-0545-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Costello A, Abbas M, Allen A, Ball S, Bell S, Bellamy R, Kett M. Managing the health effects of climate change: lancet and University College London Institute for Global Health Commission. The Lancet. 2009; 373 (9676):1693–1733. doi: 10.1016/S0140-6736(09)60935-1. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Cruz DLA (2015) Mother Figured. University of Chicago Press. Retrieved from, 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 [ PMC free article ] [ PubMed ]
• Davidson D. Gaps in agricultural climate adaptation research. Nat Clim Chang. 2016; 6 (5):433–435. doi: 10.1038/nclimate3007. [ CrossRef ] [ Google Scholar ]
• Diffenbaugh NS, Singh D, Mankin JS, Horton DE, Swain DL, Touma D, Tsiang M. Quantifying the influence of global warming on unprecedented extreme climate events. Proc Natl Acad Sci. 2017; 114 (19):4881–4886. doi: 10.1073/pnas.1618082114. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Dimri A, Kumar D, Choudhary A, Maharana P. Future changes over the Himalayas: mean temperature. Global Planet Change. 2018; 162 :235–251. doi: 10.1016/j.gloplacha.2018.01.014. [ CrossRef ] [ Google Scholar ]
• Dullinger S, Gattringer A, Thuiller W, Moser D, Zimmermann N, Guisan A. Extinction debt of high-mountain plants under twenty-first-century climate change. Nat Clim Chang: Nature Publishing Group; 2012. [ Google Scholar ]
• Dupuis I, Dumas C. Influence of temperature stress on in vitro fertilization and heat shock protein synthesis in maize (Zea mays L.) reproductive tissues. Plant Physiol. 1990; 94 (2):665–670. doi: 10.1104/pp.94.2.665. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Edreira JR, Otegui ME. Heat stress in temperate and tropical maize hybrids: a novel approach for assessing sources of kernel loss in field conditions. Field Crop Res. 2013; 142 :58–67. doi: 10.1016/j.fcr.2012.11.009. [ CrossRef ] [ Google Scholar ]
• Edreira JR, Carpici EB, Sammarro D, Otegui M. Heat stress effects around flowering on kernel set of temperate and tropical maize hybrids. Field Crop Res. 2011; 123 (2):62–73. doi: 10.1016/j.fcr.2011.04.015. [ CrossRef ] [ Google Scholar ]
• Ellison D, Morris CE, Locatelli B, Sheil D, Cohen J, Murdiyarso D, Pokorny J. Trees, forests and water: Cool insights for a hot world. Glob Environ Chang. 2017; 43 :51–61. doi: 10.1016/j.gloenvcha.2017.01.002. [ CrossRef ] [ Google Scholar ]
• Elsayed ZM, Eldehna WM, Abdel-Aziz MM, El Hassab MA, Elkaeed EB, Al-Warhi T, Mohammed ER. Development of novel isatin–nicotinohydrazide hybrids with potent activity against susceptible/resistant Mycobacterium tuberculosis and bronchitis causing–bacteria. J Enzyme Inhib Med Chem. 2021; 36 (1):384–393. doi: 10.1080/14756366.2020.1868450. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Will climate change pose serious threat to crop pest management: a critical review. Int J Sci Res Publ. 2012; 2 (11):1–14. [ Google Scholar ]
• 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. Heat stress in wheat during reproductive and grain-filling phases. Crit Rev Plant Sci. 2011; 30 (6):491–507. doi: 10.1080/07352689.2011.615687. [ CrossRef ] [ Google Scholar ]
• 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. Changing climates, changing forests: a western North American perspective. J Forest. 2013; 111 (3):214–228. doi: 10.5849/jof.12-085. [ CrossRef ] [ Google Scholar ]
• Fischer AP. Characterizing behavioral adaptation to climate change in temperate forests. Landsc Urban Plan. 2019; 188 :72–79. doi: 10.1016/j.landurbplan.2018.09.024. [ CrossRef ] [ Google Scholar ]
• Flannigan M, Cantin AS, De Groot WJ, Wotton M, Newbery A, Gowman LM. Global wildland fire season severity in the 21st century. For Ecol Manage. 2013; 294 :54–61. doi: 10.1016/j.foreco.2012.10.022. [ CrossRef ] [ Google Scholar ]
• Fossheim M, Primicerio R, Johannesen E, Ingvaldsen RB, Aschan MM, Dolgov AV. Recent warming leads to a rapid borealization of fish communities in the Arctic. Nat Clim Chang. 2015; 5 (7):673–677. doi: 10.1038/nclimate2647. [ CrossRef ] [ Google Scholar ]
• 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. Source–sink relations and kernel weight differences in maize temperate hybrids. Field Crop Res. 2006; 95 (2–3):316–326. doi: 10.1016/j.fcr.2005.04.002. [ CrossRef ] [ Google Scholar ]
• Gambín B, Borrás L. Resource distribution and the trade-off between seed number and seed weight: a comparison across crop species. Annals of Applied Biology. 2010; 156 (1):91–102. doi: 10.1111/j.1744-7348.2009.00367.x. [ CrossRef ] [ Google Scholar ]
• Gampe D, Nikulin G, Ludwig R. Using an ensemble of regional climate models to assess climate change impacts on water scarcity in European river basins. Sci Total Environ. 2016; 573 :1503–1518. doi: 10.1016/j.scitotenv.2016.08.053. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• García GA, Dreccer MF, Miralles DJ, Serrago RA. High night temperatures during grain number determination reduce wheat and barley grain yield: a field study. Glob Change Biol. 2015; 21 (11):4153–4164. doi: 10.1111/gcb.13009. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Garner E, Inyang M, Garvey E, Parks J, Glover C, Grimaldi A, Edwards MA. Impact of blending for direct potable reuse on premise plumbing microbial ecology and regrowth of opportunistic pathogens and antibiotic resistant bacteria. Water Res. 2019; 151 :75–86. doi: 10.1016/j.watres.2018.12.003. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Food security: the challenge of feeding 9 billion people. Science. 2010; 327 (5967):812–818. doi: 10.1126/science.1185383. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Crop productivity and adaptation to climate change in Pakistan. Environ Dev Econ. 2018; 23 (6):679–701. doi: 10.1017/S1355770X18000232. [ CrossRef ] [ Google Scholar ]
• Gosling SN, Arnell NW. A global assessment of the impact of climate change on water scarcity. Clim Change. 2016; 134 (3):371–385. doi: 10.1007/s10584-013-0853-x. [ CrossRef ] [ Google Scholar ]
• Gössling S, Scott D, Hall CM, Ceron J-P, Dubois G. Consumer behaviour and demand response of tourists to climate change. Ann Tour Res. 2012; 39 (1):36–58. doi: 10.1016/j.annals.2011.11.002. [ CrossRef ] [ Google Scholar ]
• Gourdji SM, Sibley AM, Lobell DB. Global crop exposure to critical high temperatures in the reproductive period: historical trends and future projections. Environ Res Lett. 2013; 8 (2):024041. doi: 10.1088/1748-9326/8/2/024041. [ CrossRef ] [ Google Scholar ]
• 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. On climate change skepticism and denial in tourism. J Sustain Tour. 2015; 23 (1):4–25. doi: 10.1080/09669582.2014.953544. [ CrossRef ] [ Google Scholar ]
• Hartmann H, Moura CF, Anderegg WR, Ruehr NK, Salmon Y, Allen CD, Galbraith D. Research frontiers for improving our understanding of drought-induced tree and forest mortality. New Phytol. 2018; 218 (1):15–28. doi: 10.1111/nph.15048. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hatfield JL, Prueger JH. Temperature extremes: Effect on plant growth and development. Weather and Climate Extremes. 2015; 10 :4–10. doi: 10.1016/j.wace.2015.08.001. [ CrossRef ] [ Google Scholar ]
• Hatfield JL, Boote KJ, Kimball B, Ziska L, Izaurralde RC, Ort D, Wolfe D. Climate impacts on agriculture: implications for crop production. Agron J. 2011; 103 (2):351–370. doi: 10.2134/agronj2010.0303. [ CrossRef ] [ Google Scholar ]
• Hendriksen RS, Munk P, Njage P, Van Bunnik B, McNally L, Lukjancenko O, Kjeldgaard J. Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage. Nat Commun. 2019; 10 (1):1124. doi: 10.1038/s41467-019-08853-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Effect of urban symbiosis development in China on GHG emissions reduction. Adv Clim Chang Res. 2016; 7 (4):247–252. doi: 10.1016/j.accre.2016.12.003. [ CrossRef ] [ Google Scholar ]
• 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. More than drought: precipitation variance, excessive wetness, pathogens and the future of the western edge of the eastern deciduous forest. Sci Total Environ. 2016; 566 :463–467. doi: 10.1016/j.scitotenv.2016.05.108. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hussain M, Butt AR, Uzma F, Ahmed R, Irshad S, Rehman A, Yousaf B. A comprehensive review of climate change impacts, adaptation, and mitigation on environmental and natural calamities in Pakistan. Environ Monit Assess. 2020; 192 (1):48. doi: 10.1007/s10661-019-7956-4. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Hussain M, Liu G, Yousaf B, Ahmed R, Uzma F, Ali MU, Butt AR. 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. 2018; 200 :791–808. doi: 10.1016/j.jclepro.2018.07.272. [ CrossRef ] [ Google Scholar ]
• Intergov. Panel Clim Chang 33 from 10.1017/CBO9781107415324
• Ionescu C, Klein RJ, Hinkel J, Kumar KK, Klein R. Towards a formal framework of vulnerability to climate change. Environ Model Assess. 2009; 14 (1):1–16. doi: 10.1007/s10666-008-9179-x. [ CrossRef ] [ Google Scholar ]
• 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. Climate change risk to global port operations. Nat Clim Chang. 2021; 11 (1):14–20. doi: 10.1038/s41558-020-00937-z. [ CrossRef ] [ Google Scholar ]
• Jactel H, Koricheva J, Castagneyrol B (2019) Responses of forest insect pests to climate change: not so simple. Current opinion in insect science [ PubMed ]
• Jahanzad E, Holtz BA, Zuber CA, Doll D, Brewer KM, Hogan S, Gaudin AC. Orchard recycling improves climate change adaptation and mitigation potential of almond production systems. PLoS ONE. 2020; 15 (3):e0229588. doi: 10.1371/journal.pone.0229588. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Jurgilevich A, Räsänen A, Groundstroem F, Juhola S. A systematic review of dynamics in climate risk and vulnerability assessments. Environ Res Lett. 2017; 12 (1):013002. doi: 10.1088/1748-9326/aa5508. [ CrossRef ] [ Google Scholar ]
• 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. Antibiotic-resistance genes in waste water. Trends Microbiol. 2018; 26 (3):220–228. doi: 10.1016/j.tim.2017.09.005. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kohfeld KE, Le Quéré C, Harrison SP, Anderson RF. Role of marine biology in glacial-interglacial CO2 cycles. Science. 2005; 308 (5718):74–78. doi: 10.1126/science.1105375. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Kongsager R. Linking climate change adaptation and mitigation: a review with evidence from the land-use sectors. Land. 2018; 7 (4):158. doi: 10.3390/land7040158. [ CrossRef ] [ Google Scholar ]
• Kurz WA, Dymond C, Stinson G, Rampley G, Neilson E, Carroll A, Safranyik L. Mountain pine beetle and forest carbon feedback to climate change. Nature. 2008; 452 (7190):987. doi: 10.1038/nature06777. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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 [ PubMed ]
• Lehner F, Coats S, Stocker TF, Pendergrass AG, Sanderson BM, Raible CC, Smerdon JE. Projected drought risk in 1.5 C and 2 C warmer climates. Geophys Res Lett. 2017; 44 (14):7419–7428. doi: 10.1002/2017GL074117. [ CrossRef ] [ Google Scholar ]
• 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. Effect of climate change on humic substances and associated impacts on the quality of surface water and groundwater: a review. Sci Total Environ. 2018; 640 :1548–1565. doi: 10.1016/j.scitotenv.2018.05.376. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Global scale climate–crop yield relationships and the impacts of recent warming. Environ Res Lett. 2007; 2 (1):014002. doi: 10.1088/1748-9326/2/1/014002. [ CrossRef ] [ Google Scholar ]
• Lobell DB, Gourdji SM. The influence of climate change on global crop productivity. Plant Physiol. 2012; 160 (4):1686–1697. doi: 10.1104/pp.112.208298. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Ma L, Li B, Zhang T. New insights into antibiotic resistome in drinking water and management perspectives: a metagenomic based study of small-sized microbes. Water Res. 2019; 152 :191–201. doi: 10.1016/j.watres.2018.12.069. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Increased wind risk from sting-jet windstorms with climate change. Environ Res Lett. 2018; 13 (4):044002. doi: 10.1088/1748-9326/aaae3a. [ CrossRef ] [ Google Scholar ]
• Matsui T, Omasa K, Horie T. The difference in sterility due to high temperatures during the flowering period among japonica-rice varieties. Plant Production Science. 2001; 4 (2):90–93. doi: 10.1626/pps.4.90. [ CrossRef ] [ Google Scholar ]
• 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. Awareness of climate change and its associated risks jointly explain context-specific adaptation in the Arid-tropics. Northeast Ethiopia SN Social Sciences. 2021; 1 (2):1–18. [ Google Scholar ]
• Millar CI, Stephenson NL. Temperate forest health in an era of emerging megadisturbance. Science. 2015; 349 (6250):823–826. doi: 10.1126/science.aaa9933. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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 [ PMC free article ] [ PubMed ]
• 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. 10.1007/s11356-020-09497-3 [ PMC free article ] [ PubMed ]
• Murshed M. 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. 2022; 30 :396–412. doi: 10.1016/j.spc.2021.12.016. [ CrossRef ] [ Google Scholar ]
• Murshed M, Dao NTT. Revisiting the CO2 emission-induced EKC hypothesis in South Asia: the role of Export Quality Improvement. GeoJournal. 2020 doi: 10.1007/s10708-020-10270-9. [ CrossRef ] [ Google Scholar ]
• Murshed M, Abbass K, Rashid S. Modelling renewable energy adoption across south Asian economies: Empirical evidence from Bangladesh, India, Pakistan and Sri Lanka. Int J Finan Eco. 2021; 26 (4):5425–5450. doi: 10.1002/ijfe.2073. [ CrossRef ] [ Google Scholar ]
• Murshed M, Nurmakhanova M, Elheddad M, Ahmed R. 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. 2020; 27 (31):38951–38973. doi: 10.1007/s11356-020-09593-4. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. 10.1080/15567249.2022.2038730
• Neuvonen M, Sievänen T, Fronzek S, Lahtinen I, Veijalainen N, Carter TR. Vulnerability of cross-country skiing to climate change in Finland–an interactive mapping tool. J Outdoor Recreat Tour. 2015; 11 :64–79. doi: 10.1016/j.jort.2015.06.010. [ CrossRef ] [ Google Scholar ]
• 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. Climate change, pathogens, and people: the challenges of monitoring a moving target. Bioscience. 2018; 68 (10):733–739. doi: 10.1093/biosci/biy101. [ CrossRef ] [ Google Scholar ]
• Ortiz AMD, Outhwaite CL, Dalin C, Newbold T. A review of the interactions between biodiversity, agriculture, climate change, and international trade: research and policy priorities. One Earth. 2021; 4 (1):88–101. doi: 10.1016/j.oneear.2020.12.008. [ CrossRef ] [ Google Scholar ]
• Ortiz R. Crop genetic engineering under global climate change. Ann Arid Zone. 2008; 47 (3):343. [ Google Scholar ]
• Otegui MAE, Bonhomme R. Grain yield components in maize: I. Ear growth and kernel set. Field Crop Res. 1998; 56 (3):247–256. doi: 10.1016/S0378-4290(97)00093-2. [ CrossRef ] [ Google Scholar ]
• 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. Visualizing the knowledge outburst in global research on COVID-19. Scientometrics. 2021; 126 (5):4173–4193. doi: 10.1007/s11192-021-03912-3. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Panda R, Behera S, Kashyap P. Effective management of irrigation water for wheat under stressed conditions. Agric Water Manag. 2003; 63 (1):37–56. doi: 10.1016/S0378-3774(03)00099-4. [ CrossRef ] [ Google Scholar ]
• Pärnänen KM, Narciso-da-Rocha C, Kneis D, Berendonk TU, Cacace D, Do TT, Jaeger T. Antibiotic resistance in European wastewater treatment plants mirrors the pattern of clinical antibiotic resistance prevalence. Sci Adv. 2019; 5 (3):eaau9124. doi: 10.1126/sciadv.aau9124. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Impact of regional climate change on human health. Nature. 2005; 438 (7066):310–317. doi: 10.1038/nature04188. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Patz JA, Graczyk TK, Geller N, Vittor AY. Effects of environmental change on emerging parasitic diseases. Int J Parasitol. 2000; 30 (12–13):1395–1405. doi: 10.1016/S0020-7519(00)00141-7. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pautasso M, Döring TF, Garbelotto M, Pellis L, Jeger MJ. Impacts of climate change on plant diseases—opinions and trends. Eur J Plant Pathol. 2012; 133 (1):295–313. doi: 10.1007/s10658-012-9936-1. [ CrossRef ] [ Google Scholar ]
• Peng S, Huang J, Sheehy JE, Laza RC, Visperas RM, Zhong X, Cassman KG. Rice yields decline with higher night temperature from global warming. Proc Natl Acad Sci. 2004; 101 (27):9971–9975. doi: 10.1073/pnas.0403720101. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Pereira HM, Ferrier S, Walters M, Geller GN, Jongman R, Scholes RJ, Cardoso A. Essential biodiversity variables. Science. 2013; 339 (6117):277–278. doi: 10.1126/science.1229931. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Perera K, De Silva K, Amarasinghe M. 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. 2018; 161 :162–171. doi: 10.1016/j.gloplacha.2017.12.016. [ CrossRef ] [ Google Scholar ]
• 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. Environmental gradients and complexity in coastal landscape response to sea level rise. CATENA. 2018; 169 :107–118. doi: 10.1016/j.catena.2018.05.036. [ CrossRef ] [ Google Scholar ]
• 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 [ PMC free article ] [ PubMed ]
• Pruden A, Larsson DJ, Amézquita A, Collignon P, Brandt KK, Graham DW, Snape JR. Management options for reducing the release of antibiotics and antibiotic resistance genes to the environment. Environ Health Perspect. 2013; 121 (8):878–885. doi: 10.1289/ehp.1206446. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Qasim MZ, Hammad HM, Abbas F, Saeed S, Bakhat HF, Nasim W, Fahad S. The potential applications of picotechnology in biomedical and environmental sciences. Environ Sci Pollut Res. 2020; 27 (1):133–142. doi: 10.1007/s11356-019-06554-4. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Qasim MZ, Hammad HM, Maqsood F, Tariq T, Chawla MS Climate Change Implication on Cereal Crop Productivity
• Rahman M, Alam K. Forest dependent indigenous communities’ perception and adaptation to climate change through local knowledge in the protected area—a Bangladesh case study. Climate. 2016; 4 (1):12. doi: 10.3390/cli4010012. [ CrossRef ] [ Google Scholar ]
• Ramankutty N, Mehrabi Z, Waha K, Jarvis L, Kremen C, Herrero M, Rieseberg LH. Trends in global agricultural land use: implications for environmental health and food security. Annu Rev Plant Biol. 2018; 69 :789–815. doi: 10.1146/annurev-arplant-042817-040256. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Aspects of forest biomass in the Earth system: its role and major unknowns. Surv Geophys. 2019; 40 (4):693–707. doi: 10.1007/s10712-019-09551-x. [ CrossRef ] [ Google Scholar ]
• Reidsma P, Ewert F, Boogaard H, van Diepen K. Regional crop modelling in Europe: the impact of climatic conditions and farm characteristics on maize yields. Agric Syst. 2009; 100 (1–3):51–60. doi: 10.1016/j.agsy.2008.12.009. [ CrossRef ] [ Google Scholar ]
• Ritchie H, Roser M (2014) Natural disasters. Our World in Data
• Rizvi AR, Baig S, Verdone M. Ecosystems based adaptation: knowledge gaps in making an economic case for investing in nature based solutions for climate change. Gland, Switzerland: IUCN; 2015. p. 48. [ Google Scholar ]
• Roscher C, Fergus AJ, Petermann JS, Buchmann N, Schmid B, Schulze E-D. What happens to the sown species if a biodiversity experiment is not weeded? Basic Appl Ecol. 2013; 14 (3):187–198. doi: 10.1016/j.baae.2013.01.003. [ CrossRef ] [ Google Scholar ]
• Rosenzweig C, Elliott J, Deryng D, Ruane AC, Müller C, Arneth A, Khabarov N. Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proc Natl Acad Sci. 2014; 111 (9):3268–3273. doi: 10.1073/pnas.1222463110. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Environmental modulation of yield components in cereals: heritabilities reveal a hierarchy of phenotypic plasticities. Field Crop Res. 2012; 127 :215–224. doi: 10.1016/j.fcr.2011.11.014. [ CrossRef ] [ Google Scholar ]
• Salvucci ME, Crafts-Brandner SJ. Inhibition of photosynthesis by heat stress: the activation state of Rubisco as a limiting factor in photosynthesis. Physiol Plant. 2004; 120 (2):179–186. doi: 10.1111/j.0031-9317.2004.0173.x. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Santos WS, Gurgel-Gonçalves R, Garcez LM, Abad-Franch F. Deforestation effects on Attalea palms and their resident Rhodnius, vectors of Chagas disease, in eastern Amazonia. PLoS ONE. 2021; 16 (5):e0252071. doi: 10.1371/journal.pone.0252071. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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 [ PMC free article ] [ PubMed ]
• Schlenker W, Roberts MJ. Nonlinear temperature effects indicate severe damages to US crop yields under climate change. Proc Natl Acad Sci. 2009; 106 (37):15594–15598. doi: 10.1073/pnas.0906865106. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Schoene DH, Bernier PY. Adapting forestry and forests to climate change: a challenge to change the paradigm. Forest Policy Econ. 2012; 24 :12–19. doi: 10.1016/j.forpol.2011.04.007. [ CrossRef ] [ Google Scholar ]
• Schuurmans C (2021) The world heat budget: expected changes Climate Change (pp. 1–15): CRC Press
• Scott D. Sustainable Tourism and the Grand Challenge of Climate Change. Sustainability. 2021; 13 (4):1966. doi: 10.3390/su13041966. [ CrossRef ] [ Google Scholar ]
• Scott D, McBoyle G, Schwartzentruber M. Climate change and the distribution of climatic resources for tourism in North America. Climate Res. 2004; 27 (2):105–117. doi: 10.3354/cr027105. [ CrossRef ] [ Google Scholar ]
• Semenov MA. Impacts of climate change on wheat in England and Wales. J R Soc Interface. 2009; 6 (33):343–350. doi: 10.1098/rsif.2008.0285. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Shaffril HAM, Krauss SE, Samsuddin SF. A systematic review on Asian’s farmers’ adaptation practices towards climate change. Sci Total Environ. 2018; 644 :683–695. doi: 10.1016/j.scitotenv.2018.06.349. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Impacts on human health of climate and land use change in the Hindu Kush-Himalayan region. Mt Res Dev. 2012; 32 (4):480–486. doi: 10.1659/MRD-JOURNAL-D-12-00068.1. [ CrossRef ] [ Google Scholar ]
• Sharma R, Sinha A, Kautish P. Examining the impacts of economic and demographic aspects on the ecological footprint in South and Southeast Asian countries. Environ Sci Pollut Res. 2020; 27 (29):36970–36982. doi: 10.1007/s11356-020-09659-3. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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 [ PMC free article ] [ PubMed ]
• 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. Revisiting the past to foretell the future: summer temperature and habitat area predict pika extirpations in California. J Biogeogr. 2015; 42 (5):880–890. doi: 10.1111/jbi.12466. [ CrossRef ] [ Google Scholar ]
• 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. Wheat cultivars vary widely in their responses of grain yield and quality to short periods of post-anthesis heat stress. Funct Plant Biol. 1994; 21 (6):887–900. doi: 10.1071/PP9940887. [ CrossRef ] [ Google Scholar ]
• Su H-C, Liu Y-S, Pan C-G, Chen J, He L-Y, Ying G-G. Persistence of antibiotic resistance genes and bacterial community changes in drinking water treatment system: from drinking water source to tap water. Sci Total Environ. 2018; 616 :453–461. doi: 10.1016/j.scitotenv.2017.10.318. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Sunderlin WD, Angelsen A, Belcher B, Burgers P, Nasi R, Santoso L, Wunder S. Livelihoods, forests, and conservation in developing countries: an overview. World Dev. 2005; 33 (9):1383–1402. doi: 10.1016/j.worlddev.2004.10.004. [ CrossRef ] [ Google Scholar ]
• 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 [ PMC free article ] [ PubMed ]
• Tao F, Yokozawa M, Xu Y, Hayashi Y, Zhang Z. Climate changes and trends in phenology and yields of field crops in China, 1981–2000. Agric for Meteorol. 2006; 138 (1–4):82–92. doi: 10.1016/j.agrformet.2006.03.014. [ CrossRef ] [ Google Scholar ]
• Tebaldi C, Hayhoe K, Arblaster JM, Meehl GA. Going to the extremes. Clim Change. 2006; 79 (3–4):185–211. doi: 10.1007/s10584-006-9051-4. [ CrossRef ] [ Google Scholar ]
• 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. Towards a methodology for developing evidence-informed management knowledge by means of systematic review. Br J Manag. 2003; 14 (3):207–222. doi: 10.1111/1467-8551.00375. [ CrossRef ] [ Google Scholar ]
• 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. Pollution concern during globalization mode in financially resource-rich countries: Do financial development, natural resources, and renewable energy consumption matter? Rene. Energy. 2022; 183 :90–102. doi: 10.1016/j.renene.2021.10.067. [ CrossRef ] [ Google Scholar ]
• 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. What determines environmental deficit in Asia? Embossing the role of renewable and non-renewable energy utilization. Renew Energy. 2021; 168 :1165–1176. doi: 10.1016/j.renene.2021.01.012. [ CrossRef ] [ Google Scholar ]
• Urban MC. Accelerating extinction risk from climate change. Science. 2015; 348 (6234):571–573. doi: 10.1126/science.aaa4984. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Climate change in the Western Himalayas of India: a study of local perception and response. Climate Res. 2001; 19 (2):109–117. doi: 10.3354/cr019109. [ CrossRef ] [ Google Scholar ]
• Vega CR, Andrade FH, Sadras VO, Uhart SA, Valentinuz OR. Seed number as a function of growth. A comparative study in soybean, sunflower, and maize. Crop Sci. 2001; 41 (3):748–754. doi: 10.2135/cropsci2001.413748x. [ CrossRef ] [ Google Scholar ]
• Vergés A, Doropoulos C, Malcolm HA, Skye M, Garcia-Pizá M, Marzinelli EM, Vila-Concejo A. Long-term empirical evidence of ocean warming leading to tropicalization of fish communities, increased herbivory, and loss of kelp. Proc Natl Acad Sci. 2016; 113 (48):13791–13796. doi: 10.1073/pnas.1610725113. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Climate Change Policy Coherence across Policies, Plans, and Strategies in Pakistan—implications for the China-Pakistan Economic Corridor Plan. Environ Manage. 2021; 67 (5):793–810. doi: 10.1007/s00267-021-01449-y. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Health and climate change: policy responses to protect public health. The Lancet. 2015; 386 (10006):1861–1914. doi: 10.1016/S0140-6736(15)60854-6. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Weed AS, Ayres MP, Hicke JA. Consequences of climate change for biotic disturbances in North American forests. Ecol Monogr. 2013; 83 (4):441–470. doi: 10.1890/13-0160.1. [ CrossRef ] [ Google Scholar ]
• 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. Climate-driven regime shift of a temperate marine ecosystem. Science. 2016; 353 (6295):169–172. doi: 10.1126/science.aad8745. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• WHO (2018) WHO, 2018. Antimicrobial resistance
• Wilkinson DM, Sherratt TN. Why is the world green? The interactions of top–down and bottom–up processes in terrestrial vegetation ecology. Plant Ecolog Divers. 2016; 9 (2):127–140. doi: 10.1080/17550874.2016.1178353. [ CrossRef ] [ Google Scholar ]
• Wiranata IJ, Simbolon K. 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. 2021; 5 (2):129–146. doi: 10.22303/pir.5.2.2021.129-146. [ CrossRef ] [ Google Scholar ]
• Wiréhn L. Nordic agriculture under climate change: a systematic review of challenges, opportunities and adaptation strategies for crop production. Land Use Policy. 2018; 77 :63–74. doi: 10.1016/j.landusepol.2018.04.059. [ CrossRef ] [ Google Scholar ]
• Wu D, Su Y, Xi H, Chen X, Xie B. Urban and agriculturally influenced water contribute differently to the spread of antibiotic resistance genes in a mega-city river network. Water Res. 2019; 158 :11–21. doi: 10.1016/j.watres.2019.03.010. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• 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. Assessment of agricultural drought vulnerability in the Guanzhong Plain. China Water Resources Management. 2017; 31 (5):1557–1574. doi: 10.1007/s11269-017-1594-9. [ CrossRef ] [ Google Scholar ]
• 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. Critical linkages between land-use transition and human health in the Himalayan region. Environ Int. 2008; 34 (2):239–247. doi: 10.1016/j.envint.2007.08.004. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Yadav MK, Singh R, Singh K, Mall R, Patel C, Yadav S, Singh M. Assessment of climate change impact on productivity of different cereal crops in Varanasi. India J Agrometeorol. 2015; 17 (2):179–184. doi: 10.54386/jam.v17i2.1000. [ CrossRef ] [ Google Scholar ]
• Yang B, Usman M. 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. 2021; 28 :893–910. [ Google Scholar ]
• 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. Biotic multipliers of climate change. Science. 2012; 336 (6088):1516–1518. doi: 10.1126/science.1222732. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Zhang M, Liu N, Harper R, Li Q, Liu K, Wei X, Liu S. A global review on hydrological responses to forest change across multiple spatial scales: importance of scale, climate, forest type and hydrological regime. J Hydrol. 2017; 546 :44–59. doi: 10.1016/j.jhydrol.2016.12.040. [ CrossRef ] [ Google Scholar ]
• 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. 10.1016/j.renene.2022.03.050

Suggestions or feedback?

MIT News | Massachusetts Institute of Technology

• Machine learning
• Sustainability
• Black holes
• Classes and programs

Departments

• Aeronautics and Astronautics
• Brain and Cognitive Sciences
• Architecture
• Political Science
• Mechanical Engineering

Centers, Labs, & Programs

• Abdul Latif Jameel Poverty Action Lab (J-PAL)
• Picower Institute for Learning and Memory
• Lincoln Laboratory
• School of Architecture + Planning
• School of Engineering
• School of Humanities, Arts, and Social Sciences
• Sloan School of Management
• School of Science
• MIT Schwarzman College of Computing

Earth can regulate its own temperature over millennia, new study finds

Press contact :, media download.

*Terms of Use:

Images for download on the MIT News office website are made available to non-commercial entities, press and the general public under a Creative Commons Attribution Non-Commercial No Derivatives license . You may not alter the images provided, other than to crop them to size. A credit line must be used when reproducing images; if one is not provided below, credit the images to "MIT."

Previous image Next image

The Earth’s climate has undergone some big changes, from global volcanism to planet-cooling ice ages and dramatic shifts in solar radiation. And yet life, for the last 3.7 billion years, has kept on beating.

Now, a study by MIT researchers in Science Advances confirms that the planet harbors a “stabilizing feedback” mechanism that acts over hundreds of thousands of years to pull the climate back from the brink, keeping global temperatures within a steady, habitable range.

Just how does it accomplish this? A likely mechanism is “silicate weathering” — a geological process by which the slow and steady weathering of silicate rocks involves chemical reactions that ultimately draw carbon dioxide out of the atmosphere and into ocean sediments, trapping the gas in rocks.

Scientists have long suspected that silicate weathering plays a major role in regulating the Earth’s carbon cycle. The mechanism of silicate weathering could provide a geologically constant force in keeping carbon dioxide — and global temperatures — in check. But there’s never been direct evidence for the continual operation of such a feedback, until now.

The new findings are based on a study of paleoclimate data that record changes in average global temperatures over the last 66 million years. The MIT team applied a mathematical analysis to see whether the data revealed any patterns characteristic of stabilizing phenomena that reined in global temperatures on a  geologic timescale.

They found that indeed there appears to be a consistent pattern in which the Earth’s temperature swings are dampened over timescales of hundreds of thousands of years. The duration of this effect is similar to the timescales over which silicate weathering is predicted to act.

The results are the first to use actual data to confirm the existence of a stabilizing feedback, the mechanism of which is likely silicate weathering. This stabilizing feedback would explain how the Earth has remained habitable through dramatic climate events in the geologic past.

“On the one hand, it’s good because we know that today’s global warming will eventually be canceled out through this stabilizing feedback,” says Constantin Arnscheidt, a graduate student in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “But on the other hand, it will take hundreds of thousands of years to happen, so not fast enough to solve our present-day issues.”

The study is co-authored by Arnscheidt and Daniel Rothman, professor of geophysics at MIT.

Stability in data

Scientists have previously seen hints of a climate-stabilizing effect in the Earth’s carbon cycle: Chemical analyses of ancient rocks have shown that the flux of carbon in and out of Earth’s surface environment has remained relatively balanced, even through dramatic swings in global temperature. Furthermore, models of silicate weathering predict that the process should have some stabilizing effect on the global climate. And finally, the fact of the Earth’s enduring habitability points to some inherent, geologic check on extreme temperature swings.

“You have a planet whose climate was subjected to so many dramatic external changes. Why did life survive all this time? One argument is that we need some sort of stabilizing mechanism to keep temperatures suitable for life,” Arnscheidt says. “But it’s never been demonstrated from data that such a mechanism has consistently controlled Earth’s climate.”

Arnscheidt and Rothman sought to confirm whether a stabilizing feedback has indeed been at work, by looking at data of global temperature fluctuations through geologic history. They worked with a range of global temperature records compiled by other scientists, from the chemical composition of ancient marine fossils and shells, as well as preserved Antarctic ice cores.

“This whole study is only possible because there have been great advances in improving the resolution of these deep-sea temperature records,” Arnscheidt notes. “Now we have data going back 66 million years, with data points at most thousands of years apart.”

Speeding to a stop

To the data, the team applied the mathematical theory of stochastic differential equations, which is commonly used to reveal patterns in widely fluctuating datasets.

“We realized this theory makes predictions for what you would expect Earth’s temperature history to look like if there had been feedbacks acting on certain timescales,” Arnscheidt explains.

Using this approach, the team analyzed the history of average global temperatures over the last 66 million years, considering the entire period over different timescales, such as tens of thousands of years versus hundreds of thousands, to see whether any patterns of stabilizing feedback emerged within each timescale.

“To some extent, it’s like your car is speeding down the street, and when you put on the brakes, you slide for a long time before you stop,” Rothman says. “There’s a timescale over which frictional resistance, or a stabilizing feedback, kicks in, when the system returns to a steady state.”

Without stabilizing feedbacks, fluctuations of global temperature should grow with timescale. But the team’s analysis revealed a regime in which fluctuations did not grow, implying that a stabilizing mechanism reigned in the climate before fluctuations grew too extreme. The timescale for this stabilizing effect — hundreds of thousands of years — coincides with what scientists predict for silicate weathering.

Interestingly, Arnscheidt and Rothman found that on longer timescales, the data did not reveal any stabilizing feedbacks. That is, there doesn’t appear to be any recurring pull-back of global temperatures on timescales longer than a million years. Over these longer timescales, then, what has kept global temperatures in check?

“There’s an idea that chance may have played a major role in determining why, after more than 3 billion years, life still exists,” Rothman offers.

In other words, as the Earth’s temperatures fluctuate over longer stretches, these fluctuations may just happen to be small enough in the geologic sense, to be within a range that a stabilizing feedback, such as silicate weathering, could periodically keep the climate in check, and more to the point, within a habitable zone.

“There are two camps: Some say random chance is a good enough explanation, and others say there must be a stabilizing feedback,” Arnscheidt says. “We’re able to show, directly from data, that the answer is probably somewhere in between. In other words, there was some stabilization, but pure luck likely also played a role in keeping Earth continuously habitable.”

This research was supported, in part, by a MathWorks fellowship and the National Science Foundation.

Share this news article on:

Press mentions.

A new study by MIT scientists finds that Earth can self-regulate its temperature thanks to a stabilizing feedback mechanism that works over hundreds of thousands of years, reports Troy Farah for Salon . “The finding has big implications for our understanding of the past, but also how global heating is shaping the future of our home world,” writes Farah. “It even helps us better understand the evolution of planetary temperatures that can make the search for alien-inhabited exoplanets more fruitful.”

Previous item Next item

Related Links

• Daniel Rothman
• Constantin Arnscheidt
• Department of Earth, Atmospheric and Planetary Sciences

Related Topics

• Climate change
• Earth and atmospheric sciences
• Environment
• Global Warming
• Mathematics
• Natural disasters
• Planetary science
• National Science Foundation (NSF)

Related Articles

Microbes and minerals may have set off Earth’s oxygenation

Global warming begets more warming, new paleoclimate study finds

Study: A plunge in incoming sunlight may have triggered “Snowball Earths”

Breaching a “carbon threshold” could lead to mass extinction

More mit news.

Toward a code-breaking quantum computer

Read full story →

Uphill battles: Across the country in 75 days

3 Questions: From the bench to the battlefield

Duane Boning named vice provost for international activities

Q&A: Undergraduate admissions in the wake of the 2023 Supreme Court ruling

Study reveals the benefits and downside of fasting

• More news on MIT News homepage →

Massachusetts Institute of Technology 77 Massachusetts Avenue, Cambridge, MA, USA

• Map (opens in new window)
• Events (opens in new window)
• People (opens in new window)
• Careers (opens in new window)
• Accessibility
• Social Media Hub
• MIT on Facebook
• MIT on YouTube
• MIT on Instagram

News | August 14, 2023

Nasa study reveals compounding climate risks at two degrees of warming.

This map shows global change in a measure called “fire weather index” (FWI) predicted by the study's analysis for the year 2045 (red: greater extreme fire weather; blue: less). FWI captures a combination of conditions, including low rainfall and high winds, that together increase a region’s extreme fire weather condition.

Analysis by the NASA Earth Exchange of high-resolution climate projections concludes that, if global temperatures keep rising and reach 2 degrees above pre-industrial levels, people worldwide could face multiple impacts of climate change simultaneously, with serious consequences. Credit: NASA/Taejin Park

If global temperatures keep rising and reach 2 degrees Celsius (3.6 degrees Fahrenheit) above pre-industrial levels, people worldwide could face multiple impacts of climate change simultaneously. This is according to a NASA-led study that analyzed the projected impacts of such warming to understand how different climate effects might combine. A 2-degree rise in global temperatures is considered a critical threshold above which dangerous and cascading effects of human-generated climate change will occur.

The researchers found that more than a quarter of the world’s population could experience an additional month of severe heat stress each year compared to the middle of the 20th century (1950-1979). High temperatures and drought could combine dangerously in places like the Amazon, increasing the risk of wildfire. In the American West, extreme fire weather will likely be more intense and last longer.

To investigate potentially compounding effects of rising temperatures, the study’s authors worked with a specially processed set of climate predictions. The predictions were originally generated by 35 of the world’s leading climate models – specifically, contributors to the Coupled Model Intercomparison Project (CMIP), which includes models developed by the NASA Goddard Institute for Space Studies . CMIP provides climate projections that help the Intergovernmental Panel on Climate Change and other international and national climate groups understand historical, current, and future climate changes.

Researchers at the NASA Earth Exchange (NEX) then took the output from CMIP6 models and used advanced statistical techniques to “downscale” them, improving the resolution significantly. NEX uses supercomputers at NASA’s Ames Research Center in California’s Silicon Valley to analyze vast amounts of data collected by aircraft and satellites or, in this case, projections produced by climate models. The resulting NEX dataset supporting this research is available to the public and can be found online .

Combining Climate Impacts

With the new dataset in hand, NEX researchers at Ames analyzed the downscaled projections to assess the changes predicted for six key climate variables. They examined changes in air temperature, precipitation, relative humidity, short- and longwave solar radiation, and wind speed at a point when warming passes 2°C.

“We wanted to study how these aspects of the environment are projected to change and what their combined impacts could mean for people around the world,” said Taejin Park, first author on the paper and a researcher at Ames with the Bay Area Environmental Research Institute (BAERI).

The researchers paid special attention to two climate indicators: heat stress – or the combined effects of temperature and humidity on the human body – and fire weather – which considers temperature, rainfall, humidity, and wind. Most regions of the world will experience higher heat stress, they found, while countries closer to the equator will suffer from a greater number of days considered extreme.

“The escalating impacts of all the climate extremes studied could cause significant damage to communities and economies, from fires, floods, landslides, and crop failures that may result,” said Ramakrishna Nemani, senior scientist at BAERI and co-author of the study.

Democratizing Climate Data

The NEX downscaled dataset used for this research provides global, daily climate projections, derived from CMIP6 climate models , out to the year 2100. The day-to-day nature of the NEX product is important for capturing the extremes. If merged into a monthly average, Park explained, a few days projected to be dangerously hot and humid could get lost in the numbers, concealing the risk for human lives.

The level of local and regional detail – the resolution of the projections – is higher in the NEX product than most climate projections, which could help leaders develop targeted climate adaptation and mitigation plans. Raw climate model projections typically give results for areas of about 120 by 120 miles (200 by 200 kilometers), while the NEX downscaling work increases that resolution to about 15 by 15 miles (25 by 25 kilometers).

Downscaling this much data is a big job, and NEX researchers relied on NASA’s powerful Pleiades supercomputer at Ames. Pleiades helps solve some of NASA’s most challenging problems, playing an important role in rocket launches for the Artemis program, fuel-efficient aircraft designs, and studies of Earth’s climate.

NEX scientists hope that the downscaled climate projections could help decision-makers prepare for and protect their regions against climate impacts. For example,a local policymaker could decide to build more flood barriers or pursue less development in flood-prone areas, said Ian Brosnan, co-author of the paper and principal scientist at NEX.The NEX dataset can also help new commercial and non-profit enterprises develop customized climate-risk assessments for the private and public sectors.

“The downscaled NASA data is in really accessible form,” Brosnan said. “People everywhere with some technical ability – from undergraduate students to experienced climate scientists – can dig into the information these projections contain.”

Learn more:

• A Degree of Concern: Why Global Temperatures Matter , a two-part series.

For researchers:

• “ What does global land climate look like at 2 degrees warming? ”, published in the journal Earth’s Future.
• Data description paper for the NEX-GDDP dataset: NASA Global Daily Downscaled Projections, CMIP6

For news media:

Animated map visuals showing projected change in the fire weather index are available in GIF and MP4 file formats for the following regions:

• western United States
• sub-Saharan Africa
• the Amazon region

Members of the news media interested in covering these topics should reach out to the NASA Ames newsroom .

Related Stories

What evidence exists that Earth is warming and that humans are the main cause?

We know the world is warming because people have been recording daily high and low temperatures at thousands of weather stations worldwide, over land and ocean, for many decades and, in some locations, for more than a century. When different teams of climate scientists in different agencies (e.g., NOAA and NASA) and in other countries (e.g., the U.K.’s Hadley Centre) average these data together, they all find essentially the same result: Earth’s average surface temperature has risen by about 1.8°F (1.0°C) since 1880. 

( bar chart ) Yearly temperature compared to the twentieth-century average from 1850–2023. Red bars mean warmer-than-average years; blue bars mean colder-than-average years. (line graph) Atmospheric carbon dioxide amounts: 1850-1958 from IAC , 1959-2023 from NOAA Global Monitoring Lab . NOAA Climate.gov graph, adapted from original by Dr. Howard Diamond (NOAA ARL).

In addition to our surface station data, we have many different lines of evidence that Earth is warming ( learn more ). Birds are migrating earlier, and their migration patterns are changing.  Lobsters  and  other marine species  are moving north. Plants are blooming earlier in the spring. Mountain glaciers are melting worldwide, and snow cover is declining in the Northern Hemisphere (Learn more  here  and  here ). Greenland’s ice sheet—which holds about 8 percent of Earth’s fresh water—is melting at an accelerating rate ( learn more ). Mean global sea level is rising ( learn more ). Arctic sea ice is declining rapidly in both thickness and extent ( learn more ).

The Greenland Ice Sheet lost mass again in 2020, but not as much as it did 2019. Adapted from the 2020 Arctic Report Card, this graph tracks Greenland mass loss measured by NASA's GRACE satellite missions since 2002. The background photo shows a glacier calving front in western Greenland, captured from an airplane during a NASA Operation IceBridge field campaign. Full story.

We know this warming is largely caused by human activities because the key role that carbon dioxide plays in maintaining Earth’s natural greenhouse effect has been understood since the mid-1800s. Unless it is offset by some equally large cooling influence, more atmospheric carbon dioxide will lead to warmer surface temperatures. Since 1800, the amount of carbon dioxide in the atmosphere  has increased  from about 280 parts per million to 410 ppm in 2019. We know from both its rapid increase and its isotopic “fingerprint” that the source of this new carbon dioxide is fossil fuels, and not natural sources like forest fires, volcanoes, or outgassing from the ocean.

Philip James de Loutherbourg's 1801 painting, Coalbrookdale by Night , came to symbolize the start of the Industrial Revolution, when humans began to harness the power of fossil fuels—and to contribute significantly to Earth's atmospheric greenhouse gas composition. Image from Wikipedia .

Finally, no other known climate influences have changed enough to account for the observed warming trend. Taken together, these and other lines of evidence point squarely to human activities as the cause of recent global warming.

USGCRP (2017). Climate Science Special Report: Fourth National Climate Assessment, Volume 1 [Wuebbles, D.J., D.W. Fahey, K.A. Hibbard, D.J. Dokken, B.C. Stewart, and T.K. Maycock (eds.)]. U.S. Global Change Research Program, Washington, DC, USA, 470 pp, doi:  10.7930/J0J964J6 .

National Fish, Wildlife, and Plants Climate Adaptation Partnership (2012):  National Fish, Wildlife, and Plants Climate Adaptation Strategy . Association of Fish and Wildlife Agencies, Council on Environmental Quality, Great Lakes Indian Fish and Wildlife Commission, National Oceanic and Atmospheric Administration, and U.S. Fish and Wildlife Service. Washington, D.C. DOI: 10.3996/082012-FWSReport-1

IPCC (2019). Summary for Policymakers. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate. [H.-O. Pörtner, D.C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegría, M. Nicolai, A. Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)]. In press.

NASA JPL: "Consensus: 97% of climate scientists agree."  Global Climate Change . A website at NASA's Jet Propulsion Laboratory (climate.nasa.gov/scientific-consensus). (Accessed July 2013.)

We value your feedback

Help us improve our content

Related Content

News & features, 2017 state of the climate: mountain glaciers, warming waters shift fish communities northward in the arctic, climate & fish sticks, maps & data, past climate, future climate, ocean - oceanic climate variables, teaching climate, toolbox for teaching climate & energy, student climate & conservation congress (sc3), climate youth engagement, climate resilience toolkit, arctic oceans, sea ice, and coasts, alaska and the arctic, food safety and nutrition.

• Climate Change - A Global Issue
• Dag Hammarskjöld Library
• Research Guides

Major Reports

• A Global Issue
• At the United Nations
• Books & Journals
• Consulting the Experts
• Keeping up to date
• Data & Statistics
• AR6 - 6th IPCC Assessment Report / Intergovernmental Panel on Climate Change The main activity of the IPCC is to, at regular intervals, provide Assessment Reports of the state of knowledge on climate change. The IPCC is now in its sixth assessment cycle, in which it is producing the Sixth Assessment Report (AR6) with contributions by its three Working Groups and a Synthesis Report, three Special Reports, and a refinement to its latest Methodology Report.

• Global Landscape of Climate Finance 2023 / Climate Policy Initiative Date: 2023 Provides information about which sources and financial instruments are driving investments, and how much climate finance is flowing globally. The report aims to provide an updated picture on how, where, and from whom finance is flowing toward low-carbon and climate-resilient actions globally, and to improve understanding of how public and private sources of finance interact.

• << Previous: At the United Nations
• Next: Books & Journals >>
• Last Updated: May 6, 2024 4:22 PM
• URL: https://research.un.org/en/climate-change

The ‘97% climate consensus’ is over. Now it’s well above 99% (and the evidence is even stronger than that)

Adjunct Professor of Environmental Geography, CQUniversity Australia

Disclosure statement

Steve Turton has previously received funding from the Australian Government. Steve is the independent chair of the Wet Tropics Healthy Waterways Partnership, an initiative of the Reef 2050 Long Term Sustainability Plan.

CQUniversity Australia provides funding as a member of The Conversation AU.

View all partners

Despite the overwhelming evidence , it’s still common to see politicians , media commentators or social media users cast doubt on the role of humans in driving climate change.

But this denialism is now almost nonexistent among climate scientists, as a study released this month confirms. US researchers examined the peer-reviewed literature and found more than 99% of climate scientists now endorse the evidence for human-induced climate change.

That’s even higher than the 97% reported by an influential 2013 study , which has become a widely cited statistic by both climate change deniers and those who accept the evidence.

Why has the needle evidently shifted even more firmly in favour of the evidence-based consensus? Or, to put it another way, what happened to the 3% of researchers who rejected the consensus of human caused climate change? Is this change purely because of the growing weight of evidence published over the past few years?

Unpicking the polls

We must first ask whether the two studies are directly comparable. The answer is yes. The latest study has reexamined the literature published since 2012, and is based on the same methods as the 2013 study , albeit with some important refinements.

Read more: Consensus confirmed: over 90% of climate scientists believe we're causing global warming

Both studies searched the Web of Science database – an independent worldwide repository of scientific paper citations – using the keywords “global climate change” and “global warming”. However, the recent study added “climate change” to the other two keyword searches, because the authors found that most climate-contrarian papers would not have been returned with only the two original terms.

The 2013 study examined 11,944 climate research papers and found almost one-third of them expressed a position on the cause of global warming. Of these 4,014 papers, 97% endorsed the consensus position that humans are the cause, 1% were uncertain, and 2% explicitly rejected it.

A 2015 review examined 38 climate-contrarian papers published over the preceding decade, and identified a range of methodological flaws and sources of bias.

One of the reviewers commented that “every single one of those analyses had an error – in their assumptions, methodology, or analysis – that, when corrected, brought their results into line with the scientific consensus”.

For example, many of the contrarian papers had “ cherrypicked ” results that supported their conclusion, while ignoring important context and other data sources that contradicted it. Some of them simply ignored fundamental physics.

The 2015 reviewers also made the important point that “science is never settled and that both mainstream and contrarian papers must be subjected to sustained scrutiny”. This is the cornerstone of the scientific method , and few if any climate scientists would disagree with this statement.

Separating the human influence from the natural

The recently published Intergovernmental Panel for Climate Change (IPCC) Synthesis Report , says “it is unequivocal that human influence has warmed the atmosphere, ocean and land”, and warns that the Paris Agreement goals of 1.5°C and 2°C above pre-industrial levels will be exceeded during this century without dramatic emissions reductions.

In reaching this conclusion, it is important to distinguish between changes caused by human activities altering the atmosphere’s chemistry, and climate variability caused by natural factors.

These natural variations include small changes in the Sun’s energy output due to sunspots and solar flares, infrequent volcanic eruptions , and the effects of El Niño weather patterns in the Pacific Ocean.

Excluding these natural variations, Earth’s surface temperature was generally stable from about 2,000 to 1,000 years ago. After that, the planet cooled by about 0.3°C over several centuries , before the advent of fossil fuel-based industrialisation in the 1800s.

One study identified 12 major volcanic eruptions from 100 to 1200 CE, compared with 17 eruptions from 1200 to 1900 CE. Hence, heightened volcanic activity over roughly the past 800 years was associated with a general global cooling before the industrial revolution.

Current rates of global warming are unprecedented in more than 2,000 years and temperatures now exceed the warmest (multi-century) period in more than 100,000 years . Global average surface temperature for the decade from 2011-20 was about 1.1°C higher than in 1850-1900. Each of the past four decades has been warmer than any preceding decade since 1850, when reliable weather observations began.

Read more: 99.999% certainty humans are driving global warming: new study

Researchers can separate human and natural factors in the modern global temperature record. This involves a process called hindcasting , in which a climate model is run backwards in time to simulate human and natural factors, and then compared with the observed data to see which combination of factors most accurately recreates the real world.

If human factors are removed from the data set and only volcanic and solar factors are included, then global average surface temperatures since 1950 should have remained similar to those over the preceding 100 years. But of course they haven’t.

The evidence, and the scientific consensus on it, are both clearer than ever.

• Climate change
• Climate modelling
• Scientific method
• Climate change denial
• Global warming
• Scientific research
• Climate consensus
• Global heating

Head of Evidence to Action

Supply Chain - Assistant/Associate Professor (Tenure-Track)

Education Research Fellow

OzGrav Postdoctoral Research Fellow

Casual Facilitator: GERRIC Student Programs - Arts, Design and Architecture

Featured Topics

Featured series.

A series of random questions answered by Harvard experts.

Explore the Gazette

Read the latest, should kids play wordle.

How moms may be affecting STEM gender gap

How did life begin on Earth? A lightning strike of an idea.

Exxon disputed climate findings for years. its scientists knew better..

View of ExxonMobil storage tanks of the petrochemical industry in the port of Rotterdam, Netherlands.

AP Photo/Peter Dejong

Alice McCarthy

Harvard Correspondent

Research shows that company modeled and predicted global warming with ‘shocking skill and accuracy’ starting in the 1970s

Projections created internally by ExxonMobil starting in the late 1970s on the impact of fossil fuels on climate change were very accurate, even surpassing those of some academic and governmental scientists, according to an analysis published Thursday in Science by a team of Harvard-led researchers. Despite those forecasts, team leaders say, the multinational energy giant continued to sow doubt about the gathering crisis.

In “Assessing ExxonMobil’s Global Warming Projections,” researchers from Harvard and the Potsdam Institute for Climate Impact Research show for the first time the accuracy of previously unreported forecasts created by company scientists from 1977 through 2003. The Harvard team discovered that Exxon researchers created a series of remarkably reliable models and analyses projecting global warming from carbon dioxide emissions over the coming decades. Specifically, Exxon projected that fossil fuel emissions would lead to 0.20 degrees Celsius of global warming per decade, with a margin of error of 0.04 degrees — a trend that has been proven largely accurate.

“This paper is the first ever systematic assessment of a fossil fuel company’s climate projections, the first time we’ve been able to put a number on what they knew,” said Geoffrey Supran, lead author and former research fellow in the History of Science at Harvard. “What we found is that between 1977 and 2003, excellent scientists within Exxon modeled and predicted global warming with, frankly, shocking skill and accuracy only for the company to then spend the next couple of decades denying that very climate science.”

“This paper is the first ever systematic assessment of a fossil fuel company’s climate projections, the first time we’ve been able to put a number on what they knew,” said Geoffrey Supran, lead author.

File photo by Stephanie Mitchell/Harvard Staff Photographer

“We thought this was a unique opportunity to understand what Exxon knew about this issue and what level of scientific understanding they had at the time,” added co-author Naomi Oreskes , Henry Charles Lea Professor of the History of Science whose work looks at the causes and effects of climate change denial. “We found that not only were their forecasts extremely skillful, but they were also often more skillful than forecasts made by independent academic and government scientists at the exact same time.”

Allegations that oil company executives sought to mislead the public about the industry’s role in climate change have drawn increasing scrutiny in recent years, including lawsuits by several states and cities and a recent high profile U.S. House committee investigation.

Harvard’s scientists used established Intergovernmental Panel on Climate Change (IPCC) statistical techniques to test the performance of Exxon’s models. They found that, depending on the metric used, 63-83 percent of the global warming projections reported by Exxon scientists were consistent with actual temperatures over time. Moreover, the corporation’s own projections had an average “skill score” of 72 percent, plus or minus 6 percent, with the highest scoring 99 percent. A skill score relates to how well a forecast compares to what happens in real life. For comparison, NASA scientist James Hansen’s global warming predictions presented to the U.S. Congress in 1988 had scores from 38 to 66 percent.

The researchers report that Exxon scientists correctly dismissed the possibility of a coming ice age, accurately predicted that human-caused global warming would first be detectable in the year 2000, plus or minus five years, and reasonably estimated how much CO 2 would lead to dangerous warming.

The current debate about when Exxon knew about the impact on climate change carbon emissions began in 2015 following news reports of internal company documents describing the multinational’s early knowledge of climate science.  Exxon disagreed with the reports, even providing a link to internal studies and memos from their own scientists and suggesting that interested parties should read them and make up their own minds.

“That’s exactly what we did,” said Supran, who is now at the University of Miami. Together, he and Oreskes spent a year researching those documents and in 2017 published a series of three papers analyzing Exxon’s 40-year history of climate communications . They were able to show there was a systematic discrepancy between what Exxon was saying internally and in academic circles versus what they were telling the public. “That led us to conclude that they had quantifiably misled the public, by essentially contributing quietly to climate science and yet loudly promoting doubt about that science,” said Supran.

“I think this new study is the smoking gun, the proof, because it shows the degree of understanding … this really deep, really sophisticated, really skillful understanding that was obscured by what came next,” said Harvard Professor Naomi Oreskes.

Harvard file photo

In 2021, the team published a new study in One Earth using algorithmic techniques to identify ways in which ExxonMobil used increasingly subtle but systematic language to shape the way the public talks and thinks about climate change — often in misleading ways.

These findings were hardly a surprise to Oreskes, given her long history of studying climate communications from fossil fuel companies, work that drew national attention with her 2010 bestseller, “Merchants of Doubt.” In it she and co-author, Caltech researcher Erik Conway, argued that Exxon was aware of the threat of carbon emissions on climate change yet waged a disinformation campaign about the problem.  Despite the book’s popularity and the peer-reviewed papers with Supran, however, some continued to wonder whether she could prove the effect these campaigns had, if they indeed made a difference.

“I think this new study is the smoking gun, the proof, because it shows the degree of understanding … this really deep, really sophisticated, really skillful understanding that was obscured by what came next,” Oreskes said. “It proves a point I’ve argued for years that ExxonMobil scientists knew about this problem to a shockingly fine degree as far back as the 1980s, but company spokesmen denied, challenged, and obscured this science, starting in the late 1980s/early 1990s.”

Added Supran: “Our analysis here I think seals the deal on that matter. We now have totally unimpeachable evidence that Exxon accurately predicted global warming years before it turned around and publicly attacked climate science and scientists.”

The authors of this research were supported by a Rockefeller Family Fund grant and Harvard University Faculty Development funds.

Share this article

You might like.

Early childhood development expert has news for parents who think the popular online game will turn their children into super readers

Research suggests encouragement toward humanities appears to be very influential for daughters

Researchers mimic early conditions on barren planet to test hypothesis of ancient electrochemistry

John Manning named next provost

His seven-year tenure as Law School dean noted for commitments to academic excellence, innovation, collaboration, and culture of free, open, and respectful discourse

Loving your pup may be a many splendored thing

New research suggests having connection to your dog may lower depression, anxiety  

Good genes are nice, but joy is better

Harvard study, almost 80 years old, has proved that embracing community helps us live longer, and be happier

Along with Stanford news and stories, show me:

• Student information
• Faculty/Staff information

We want to provide announcements, events, leadership messages and resources that are relevant to you. Your selection is stored in a browser cookie which you can remove at any time using “Clear all personalization” below.

Researchers at Stanford and Colorado State University have developed a rapid, low-cost approach for studying how individual extreme weather events have been affected by global warming. Their method, detailed in a Aug. 21  study in Science Advances , uses machine learning to determine how much global warming has contributed to heat waves in the U.S. and elsewhere in recent years. The approach proved highly accurate and could change how scientists study and predict the impact of climate change on a range of extreme weather events. The results can also help to guide climate adaptation strategies and are relevant for lawsuits that seek to collect compensation for damages caused by climate change.

“We’ve seen the impacts that extreme weather events can have on human health, infrastructure, and ecosystems,” said study lead author  Jared Trok , a PhD student in Earth system science at the  Stanford Doerr School of Sustainability . “To design effective solutions, we need to better understand the extent to which global warming drives changes in these extreme events.”

Trok and his co-authors trained AI models to predict daily maximum temperatures based on the regional weather conditions and the global mean temperature. For training the AI models, they used data from a large database of climate model simulations extending from 1850 to 2100. But once the AI models were trained and verified, the researchers used the actual weather conditions from specific real-world heat waves to predict how hot the heat waves would have been if the exact same weather conditions occurred but at different levels of global warming. They then compared these predictions at different global warming levels to estimate how climate change influenced the frequency and severity of historical weather events.

Case studies and beyond

The researchers first put their AI method to work analyzing the 2023 Texas heat wave,  which contributed to a record number of heat-related deaths in the state that year. The team found that global warming made the historic heat wave 1.18 to 1.42 degrees Celsius (2.12 to 2.56 F) hotter than it would have been without climate change. The researchers also found that their new technique accurately predicted the magnitude of record-setting heat waves in other parts of the world, and that the results were consistent with previously published studies of those events.

 Based on this, the researchers used the AI to predict how severe heat waves could become if the same weather patterns that caused previous record-breaking heat waves instead occurred under higher levels of global warming. They found that events equal to some of the worst heat waves in Europe, Russia, and India over the past 45 years could happen multiple times per decade if global temperatures reach 2.0 C above pre-industrial levels. Global warming  is currently approaching 1.3 C above pre-industrial levels.

“Machine learning creates a powerful new bridge between the actual meteorological conditions that cause a specific extreme weather event and the climate models that enable us to run more generalized virtual experiments on the Earth system,” said study senior author  Noah Diffenbaugh , the Kara J Foundation Professor and professor of Earth system science in the Stanford Doerr School of Sustainability. “AI hasn’t solved all the scientific challenges, but this new method is a really exciting advance that I think will get adopted for a lot of different applications.”

The new AI method addresses some limitations of existing approaches – including  those previously developed at Stanford – by using actual historical weather data when predicting the effect of global warming on extreme events. It does not require expensive new climate model simulations because the AI can be trained using existing simulations. Together, these innovations will enable accurate, low-cost analyses of extreme events in more parts of the world, which is crucial for developing effective climate adaptation strategies. It also opens up new possibilities for fast, real-time analysis of the contribution of global warming to extreme weather.

The team plans to apply their method to a wider range of extreme weather events and refine the AI networks to improve their predictions, including using new approaches to quantify the full range of uncertainty in the AI predictions.

“We’ve shown that machine learning is a powerful and efficient new tool for studying the impact of global warming on historical weather events,” said Trok. “We hope that this study helps promote future research into using AI to improve our understanding of how human emissions influence extreme weather, helping us better prepare for future extreme events.”

For more information

Diffenbaugh is also the Kimmelman Family Senior Fellow in the  Stanford Woods Institute for the Environment . Co-authors of the study also include Elizabeth Barnes and Frances Davenport of Colorado State University. The study was funded by Stanford University and the U.S. Department of Energy.

Related story

AI predicts global warming will exceed 1.5 degrees in 2030s

Understanding extreme weather

Risk of extreme weather events higher if Paris Agreement goals aren’t met

Stanford scientists test links between extreme weather and climate change

Climate change means more extreme weather than predicted

Media contacts Noah Diffenbaugh, Stanford Doerr School of Sustainability: (650) 223-9425, [email protected] Jared Trok, Stanford Doerr School of Sustainability: (760) 504-9675, [email protected] Rob Jordan, Stanford Woods Institute for the Environment: (415) 760-8058, [email protected]

• History & Society
• Science & Tech
• Biographies
• Animals & Nature
• Geography & Travel
• Arts & Culture
• Games & Quizzes
• On This Day
• One Good Fact
• New Articles
• Lifestyles & Social Issues
• Philosophy & Religion
• Politics, Law & Government
• World History
• Health & Medicine
• Browse Biographies
• Birds, Reptiles & Other Vertebrates
• Bugs, Mollusks & Other Invertebrates
• Environment
• Fossils & Geologic Time
• Entertainment & Pop Culture
• Sports & Recreation
• Visual Arts
• Demystified
• Image Galleries
• Infographics
• Top Questions
• Britannica Kids
• Saving Earth
• Space Next 50
• Student Center
• Introduction & Top Questions
• Climatic variation since the last glaciation
• The greenhouse effect
• Radiative forcing
• Water vapour
• Carbon dioxide
• Surface-level ozone and other compounds
• Nitrous oxides and fluorinated gases
• Land-use change
• Stratospheric ozone depletion
• Volcanic aerosols
• Variations in solar output
• Variations in Earth’s orbit
• Water vapour feedback
• Cloud feedbacks
• Ice albedo feedback
• Carbon cycle feedbacks
• Modern observations
• Prehistorical climate records
• Theoretical climate models
• Patterns of warming
• Precipitation patterns
• Regional predictions
• Ice melt and sea level rise
• Ocean circulation changes
• Tropical cyclones
• Environmental consequences of global warming
• Socioeconomic consequences of global warming

How does global warming work?

Where does global warming occur in the atmosphere, why is global warming a social problem, where does global warming affect polar bears.

global warming

Our editors will review what you’ve submitted and determine whether to revise the article.

• U.S. Department of Transportation - Global Warming: A Science Overview
• NOAA Climate.gov - Climate Change: Global Temperature
• Natural Resources Defense Council - Global Warming 101
• American Institute of Physics - The discovery of global warming
• LiveScience - Causes of Global Warming
• global warming - Children's Encyclopedia (Ages 8-11)
• global warming - Student Encyclopedia (Ages 11 and up)
• Table Of Contents

Human activity affects global surface temperatures by changing Earth ’s radiative balance—the “give and take” between what comes in during the day and what Earth emits at night. Increases in greenhouse gases —i.e., trace gases such as carbon dioxide and methane that absorb heat energy emitted from Earth’s surface and reradiate it back—generated by industry and transportation cause the atmosphere to retain more heat, which increases temperatures and alters precipitation patterns.

Global warming, the phenomenon of increasing average air temperatures near Earth’s surface over the past one to two centuries, happens mostly in the troposphere , the lowest level of the atmosphere, which extends from Earth’s surface up to a height of 6–11 miles. This layer contains most of Earth’s clouds and is where living things and their habitats and weather primarily occur.

Continued global warming is expected to impact everything from energy use to water availability to crop productivity throughout the world. Poor countries and communities with limited abilities to adapt to these changes are expected to suffer disproportionately. Global warming is already being associated with increases in the incidence of severe and extreme weather, heavy flooding , and wildfires —phenomena that threaten homes, dams, transportation networks, and other facets of human infrastructure. Learn more about how the IPCC’s Sixth Assessment Report, released in 2021, describes the social impacts of global warming.

Polar bears live in the Arctic , where they use the region’s ice floes as they hunt seals and other marine mammals . Temperature increases related to global warming have been the most pronounced at the poles, where they often make the difference between frozen and melted ice. Polar bears rely on small gaps in the ice to hunt their prey. As these gaps widen because of continued melting, prey capture has become more challenging for these animals.

Recent News

global warming , the phenomenon of increasing average air temperatures near the surface of Earth over the past one to two centuries. Climate scientists have since the mid-20th century gathered detailed observations of various weather phenomena (such as temperatures, precipitation , and storms) and of related influences on climate (such as ocean currents and the atmosphere’s chemical composition). These data indicate that Earth’s climate has changed over almost every conceivable timescale since the beginning of geologic time and that human activities since at least the beginning of the Industrial Revolution have a growing influence over the pace and extent of present-day climate change .

Giving voice to a growing conviction of most of the scientific community , the Intergovernmental Panel on Climate Change (IPCC) was formed in 1988 by the World Meteorological Organization (WMO) and the United Nations Environment Program (UNEP). The IPCC’s Sixth Assessment Report (AR6), published in 2021, noted that the best estimate of the increase in global average surface temperature between 1850 and 2019 was 1.07 °C (1.9 °F). An IPCC special report produced in 2018 noted that human beings and their activities have been responsible for a worldwide average temperature increase between 0.8 and 1.2 °C (1.4 and 2.2 °F) since preindustrial times, and most of the warming over the second half of the 20th century could be attributed to human activities.

AR6 produced a series of global climate predictions based on modeling five greenhouse gas emission scenarios that accounted for future emissions, mitigation (severity reduction) measures, and uncertainties in the model projections. Some of the main uncertainties include the precise role of feedback processes and the impacts of industrial pollutants known as aerosols , which may offset some warming. The lowest-emissions scenario, which assumed steep cuts in greenhouse gas emissions beginning in 2015, predicted that the global mean surface temperature would increase between 1.0 and 1.8 °C (1.8 and 3.2 °F) by 2100 relative to the 1850–1900 average. This range stood in stark contrast to the highest-emissions scenario, which predicted that the mean surface temperature would rise between 3.3 and 5.7 °C (5.9 and 10.2 °F) by 2100 based on the assumption that greenhouse gas emissions would continue to increase throughout the 21st century. The intermediate-emissions scenario, which assumed that emissions would stabilize by 2050 before declining gradually, projected an increase of between 2.1 and 3.5 °C (3.8 and 6.3 °F) by 2100.

Many climate scientists agree that significant societal, economic, and ecological damage would result if the global average temperature rose by more than 2 °C (3.6 °F) in such a short time. Such damage would include increased extinction of many plant and animal species, shifts in patterns of agriculture , and rising sea levels. By 2015 all but a few national governments had begun the process of instituting carbon reduction plans as part of the Paris Agreement , a treaty designed to help countries keep global warming to 1.5 °C (2.7 °F) above preindustrial levels in order to avoid the worst of the predicted effects. Whereas authors of the 2018 special report noted that should carbon emissions continue at their present rate, the increase in average near-surface air temperature would reach 1.5 °C sometime between 2030 and 2052, authors of the AR6 report suggested that this threshold would be reached by 2041 at the latest.

The AR6 report also noted that the global average sea level had risen by some 20 cm (7.9 inches) between 1901 and 2018 and that sea level rose faster in the second half of the 20th century than in the first half. It also predicted, again depending on a wide range of scenarios, that the global average sea level would rise by different amounts by 2100 relative to the 1995–2014 average. Under the report’s lowest-emission scenario, sea level would rise by 28–55 cm (11–21.7 inches), whereas, under the intermediate emissions scenario, sea level would rise by 44–76 cm (17.3–29.9 inches). The highest-emissions scenario suggested that sea level would rise by 63–101 cm (24.8–39.8 inches) by 2100.

The scenarios referred to above depend mainly on future concentrations of certain trace gases, called greenhouse gases , that have been injected into the lower atmosphere in increasing amounts through the burning of fossil fuels for industry, transportation , and residential uses. Modern global warming is the result of an increase in magnitude of the so-called greenhouse effect , a warming of Earth’s surface and lower atmosphere caused by the presence of water vapour , carbon dioxide , methane , nitrous oxides , and other greenhouse gases. In 2014 the IPCC first reported that concentrations of carbon dioxide, methane, and nitrous oxides in the atmosphere surpassed those found in ice cores dating back 800,000 years.

Of all these gases, carbon dioxide is the most important, both for its role in the greenhouse effect and for its role in the human economy. It has been estimated that, at the beginning of the industrial age in the mid-18th century, carbon dioxide concentrations in the atmosphere were roughly 280 parts per million (ppm). By the end of 2022 they had risen to 419 ppm, and, if fossil fuels continue to be burned at current rates, they are projected to reach 550 ppm by the mid-21st century—essentially, a doubling of carbon dioxide concentrations in 300 years.

A vigorous debate is in progress over the extent and seriousness of rising surface temperatures, the effects of past and future warming on human life, and the need for action to reduce future warming and deal with its consequences. This article provides an overview of the scientific background related to the subject of global warming. It considers the causes of rising near-surface air temperatures, the influencing factors, the process of climate research and forecasting, and the possible ecological and social impacts of rising temperatures. For an overview of the public policy developments related to global warming occurring since the mid-20th century, see global warming policy . For a detailed description of Earth’s climate, its processes, and the responses of living things to its changing nature, see climate . For additional background on how Earth’s climate has changed throughout geologic time , see climatic variation and change . For a full description of Earth’s gaseous envelope, within which climate change and global warming occur, see atmosphere .

• EO Explorer

• Global Maps

Global Warming

Throughout its long history, Earth has warmed and cooled time and again. Climate has changed when the planet received more or less sunlight due to subtle shifts in its orbit, as the atmosphere or surface changed, or when the Sun’s energy varied. But in the past century, another force has started to influence Earth’s climate: humanity.

(NASA astronaut photograph ISS022-E-6674. )

What is Global Warming?

Global warming is the unusually rapid increase in Earth’s average surface temperature over the past century primarily due to the greenhouse gases released by people burning fossil fuels.

How Does Today’s Warming Compare to Past Climate Change?

Earth has experienced climate change in the past without help from humanity. But the current climatic warming is occurring much more rapidly than past warming events.

Why Do Scientists Think Current Warming Isn’t Natural?

In Earth’s history before the Industrial Revolution, Earth’s climate changed due to natural causes unrelated to human activity. These natural causes are still in play today, but their influence is too small or they occur too slowly to explain the rapid warming seen in recent decades.

How Much More Will Earth Warm?

Models predict that as the world consumes ever more fossil fuel, greenhouse gas concentrations will continue to rise, and Earth’s average surface temperature will rise with them. Based on plausible emission scenarios, average surface temperatures could rise between 2°C and 6°C by the end of the 21st century. Some of this warming will occur even if future greenhouse gas emissions are reduced, because the Earth system has not yet fully adjusted to environmental changes we have already made.

How Will Earth Respond to Warming Temperatures?

The impact of global warming is far greater than just increasing temperatures. Warming modifies rainfall patterns, amplifies coastal erosion, lengthens the growing season in some regions, melts ice caps and glaciers, and alters the ranges of some infectious diseases. Some of these changes are already occurring.

References and Related Resources

Throughout its long history, Earth has warmed and cooled time and again. Climate has changed when the planet received more or less sunlight due to subtle shifts in its orbit, as the atmosphere or surface changed, or when the Sun’s energy varied. But in the past century, another force has started to influence Earth’s climate: humanity

How does this warming compare to previous changes in Earth’s climate? How can we be certain that human-released greenhouse gases are causing the warming? How much more will the Earth warm? How will Earth respond? Answering these questions is perhaps the most significant scientific challenge of our time.

Global warming is the unusually rapid increase in Earth’s average surface temperature over the past century primarily due to the greenhouse gases released as people burn fossil fuels. The global average surface temperature rose 0.6 to 0.9 degrees Celsius (1.1 to 1.6° F) between 1906 and 2005, and the rate of temperature increase has nearly doubled in the last 50 years. Temperatures are certain to go up further.

Despite ups and downs from year to year, global average surface temperature is rising. By the beginning of the 21st century, Earth’s temperature was roughly 0.5 degrees Celsius above the long-term (1951–1980) average. (NASA figure adapted from Goddard Institute for Space Studies Surface Temperature Analysis. )

Earth’s natural greenhouse effect

Earth’s temperature begins with the Sun. Roughly 30 percent of incoming sunlight is reflected back into space by bright surfaces like clouds and ice. Of the remaining 70 percent, most is absorbed by the land and ocean, and the rest is absorbed by the atmosphere. The absorbed solar energy heats our planet.

As the rocks, the air, and the seas warm, they radiate “heat” energy (thermal infrared radiation). From the surface, this energy travels into the atmosphere where much of it is absorbed by water vapor and long-lived greenhouse gases such as carbon dioxide and methane.

When they absorb the energy radiating from Earth’s surface, microscopic water or greenhouse gas molecules turn into tiny heaters— like the bricks in a fireplace, they radiate heat even after the fire goes out. They radiate in all directions. The energy that radiates back toward Earth heats both the lower atmosphere and the surface, enhancing the heating they get from direct sunlight.

This absorption and radiation of heat by the atmosphere—the natural greenhouse effect—is beneficial for life on Earth. If there were no greenhouse effect, the Earth’s average surface temperature would be a very chilly -18°C (0°F) instead of the comfortable 15°C (59°F) that it is today.

See Climate and Earth’s Energy Budget to read more about how sunlight fuels Earth’s climate.

The enhanced greenhouse effect

What has scientists concerned now is that over the past 250 years, humans have been artificially raising the concentration of greenhouse gases in the atmosphere at an ever-increasing rate, mostly by burning fossil fuels, but also from cutting down carbon-absorbing forests. Since the Industrial Revolution began in about 1750, carbon dioxide levels have increased nearly 38 percent as of 2009 and methane levels have increased 148 percent.

Increases in concentrations of carbon dioxide (top) and methane (bottom) coincided with the start of the Industrial Revolution in about 1750. Measurements from Antarctic ice cores (green lines) combined with direct atmospheric measurements (blue lines) show the increase of both gases over time. (NASA graphs by Robert Simmon, based on data from the NOAA Paleoclimatology and Earth System Research Laboratory. )

The atmosphere today contains more greenhouse gas molecules, so more of the infrared energy emitted by the surface ends up being absorbed by the atmosphere. Since some of the extra energy from a warmer atmosphere radiates back down to the surface, Earth’s surface temperature rises. By increasing the concentration of greenhouse gases, we are making Earth’s atmosphere a more efficient greenhouse.

How is Today’s Warming Different from the Past?

Earth has experienced climate change in the past without help from humanity. We know about past climates because of evidence left in tree rings, layers of ice in glaciers, ocean sediments, coral reefs, and layers of sedimentary rocks. For example, bubbles of air in glacial ice trap tiny samples of Earth’s atmosphere, giving scientists a history of greenhouse gases that stretches back more than 800,000 years. The chemical make-up of the ice provides clues to the average global temperature.

See the Earth Observatory’s series Paleoclimatology for details about how scientists study past climates.

Glacial ice and air bubbles trapped in it (top) preserve an 800,000-year record of temperature & carbon dioxide. Earth has cycled between ice ages (low points, large negative anomalies) and warm interglacials (peaks). (Photograph courtesy National Snow & Ice Data Center. NASA graph by Robert Simmon, based on data from Jouzel et al., 2007. )

Using this ancient evidence, scientists have built a record of Earth’s past climates, or “paleoclimates.” The paleoclimate record combined with global models shows past ice ages as well as periods even warmer than today. But the paleoclimate record also reveals that the current climatic warming is occurring much more rapidly than past warming events.

As the Earth moved out of ice ages over the past million years, the global temperature rose a total of 4 to 7 degrees Celsius over about 5,000 years. In the past century alone, the temperature has climbed 0.7 degrees Celsius, roughly ten times faster than the average rate of ice-age-recovery warming.

Temperature histories from paleoclimate data (green line) compared to the history based on modern instruments (blue line) suggest that global temperature is warmer now than it has been in the past 1,000 years, and possibly longer. (Graph adapted from Mann et al., 2008. )

Models predict that Earth will warm between 2 and 6 degrees Celsius in the next century. When global warming has happened at various times in the past two million years, it has taken the planet about 5,000 years to warm 5 degrees. The predicted rate of warming for the next century is at least 20 times faster. This rate of change is extremely unusual.

Is Current Warming Natural?

In Earth’s history before the Industrial Revolution, Earth’s climate changed due to natural causes not related to human activity. Most often, global climate has changed because of variations in sunlight. Tiny wobbles in Earth’s orbit altered when and where sunlight falls on Earth’s surface. Variations in the Sun itself have alternately increased and decreased the amount of solar energy reaching Earth. Volcanic eruptions have generated particles that reflect sunlight, brightening the planet and cooling the climate. Volcanic activity has also, in the deep past, increased greenhouse gases over millions of years, contributing to episodes of global warming.

A biographical sketch of Milutin Milankovitch describes how changes in Earth’s orbit affects its climate.

These natural causes are still in play today, but their influence is too small or they occur too slowly to explain the rapid warming seen in recent decades. We know this because scientists closely monitor the natural and human activities that influence climate with a fleet of satellites and surface instruments.

Remote meteorological stations (left) and orbiting satellites (right) help scientists monitor the causes and effects of global warming. [Images courtesy NOAA Network for the Detection of Atmospheric Composition Change (left) and Environmental Visualization Laboratory (right).]

NASA satellites record a host of vital signs including atmospheric aerosols (particles from both natural sources and human activities, such as factories, fires, deserts, and erupting volcanoes), atmospheric gases (including greenhouse gases), energy radiated from Earth’s surface and the Sun, ocean surface temperature changes, global sea level, the extent of ice sheets, glaciers and sea ice, plant growth, rainfall, cloud structure, and more.

On the ground, many agencies and nations support networks of weather and climate-monitoring stations that maintain temperature, rainfall, and snow depth records, and buoys that measure surface water and deep ocean temperatures. Taken together, these measurements provide an ever-improving record of both natural events and human activity for the past 150 years.

Scientists integrate these measurements into climate models to recreate temperatures recorded over the past 150 years. Climate model simulations that consider only natural solar variability and volcanic aerosols since 1750—omitting observed increases in greenhouse gases—are able to fit the observations of global temperatures only up until about 1950. After that point, the decadal trend in global surface warming cannot be explained without including the contribution of the greenhouse gases added by humans.

Though people have had the largest impact on our climate since 1950, natural changes to Earth’s climate have also occurred in recent times. For example, two major volcanic eruptions, El Chichon in 1982 and Pinatubo in 1991, pumped sulfur dioxide gas high into the atmosphere. The gas was converted into tiny particles that lingered for more than a year, reflecting sunlight and shading Earth’s surface. Temperatures across the globe dipped for two to three years.

Although Earth’s temperature fluctuates naturally, human influence on climate has eclipsed the magnitude of natural temperature changes over the past 120 years. Natural influences on temperature—El Niño, solar variability, and volcanic aerosols—have varied approximately plus and minus 0.2° C (0.4° F), (averaging to about zero), while human influences have contributed roughly 0.8° C (1° F) of warming since 1889. (Graphs adapted from Lean et al., 2008.)

Although volcanoes are active around the world, and continue to emit carbon dioxide as they did in the past, the amount of carbon dioxide they release is extremely small compared to human emissions. On average, volcanoes emit between 130 and 230 million tonnes of carbon dioxide per year. By burning fossil fuels, people release in excess of 100 times more, about 26 billion tonnes of carbon dioxide, into the atmosphere every year (as of 2005). As a result, human activity overshadows any contribution volcanoes may have made to recent global warming.

Changes in the brightness of the Sun can influence the climate from decade to decade, but an increase in solar output falls short as an explanation for recent warming. NASA satellites have been measuring the Sun’s output since 1978. The total energy the Sun radiates varies over an 11-year cycle. During solar maxima, solar energy is approximately 0.1 percent higher on average than it is during solar minima.

The transparent halo known as the solar corona changes between solar maximum (left) and solar minimum (right). (NASA Extreme Ultraviolet Telescope images from the SOHO Data Archive. )

Each cycle exhibits subtle differences in intensity and duration. As of early 2010, the solar brightness since 2005 has been slightly lower, not higher, than it was during the previous 11-year minimum in solar activity, which occurred in the late 1990s. This implies that the Sun’s impact between 2005 and 2010 might have been to slightly decrease the warming that greenhouse emissions alone would have caused.

Satellite measurements of daily (light line) and monthly average (dark line) total solar irradiance since 1979 have not detected a clear long-term trend. (NASA graph by Robert Simmon, based on data from the ACRIM Science Team. )

Scientists theorize that there may be a multi-decadal trend in solar output, though if one exists, it has not been observed as yet. Even if the Sun were getting brighter, however, the pattern of warming observed on Earth since 1950 does not match the type of warming the Sun alone would cause. When the Sun’s energy is at its peak (solar maxima), temperatures in both the lower atmosphere (troposphere) and the upper atmosphere (stratosphere) become warmer. Instead, observations show the pattern expected from greenhouse gas effects: Earth’s surface and troposphere have warmed, but the stratosphere has cooled.

Satellite measurements show warming in the troposphere (lower atmosphere, green line) but cooling in the stratosphere (upper atmosphere, red line). This vertical pattern is consistent with global warming due to increasing greenhouse gases, but inconsistent with warming from natural causes. (Graph by Robert Simmon, based on data from Remote Sensing Systems, sponsored by the NOAA Climate and Global Change Program.)

The stratosphere gets warmer during solar maxima because the ozone layer absorbs ultraviolet light; more ultraviolet light during solar maxima means warmer temperatures. Ozone depletion explains the biggest part of the cooling of the stratosphere over recent decades, but it can’t account for all of it. Increased concentrations of carbon dioxide in the troposphere and stratosphere together contribute to cooling in the stratosphere.

To further explore the causes and effects of global warming and to predict future warming, scientists build climate models—computer simulations of the climate system. Climate models are designed to simulate the responses and interactions of the oceans and atmosphere, and to account for changes to the land surface, both natural and human-induced. They comply with fundamental laws of physics—conservation of energy, mass, and momentum—and account for dozens of factors that influence Earth’s climate.

Though the models are complicated, rigorous tests with real-world data hone them into powerful tools that allow scientists to explore our understanding of climate in ways not otherwise possible. By experimenting with the models—removing greenhouse gases emitted by the burning of fossil fuels or changing the intensity of the Sun to see how each influences the climate—scientists use the models to better understand Earth’s current climate and to predict future climate.

The models predict that as the world consumes ever more fossil fuel, greenhouse gas concentrations will continue to rise, and Earth’s average surface temperature will rise with them. Based on a range of plausible emission scenarios, average surface temperatures could rise between 2°C and 6°C by the end of the 21st century.

Model simulations by the Intergovernmental Panel on Climate Change estimate that Earth will warm between two and six degrees Celsius over the next century, depending on how fast carbon dioxide emissions grow. Scenarios that assume that people will burn more and more fossil fuel provide the estimates in the top end of the temperature range, while scenarios that assume that greenhouse gas emissions will grow slowly give lower temperature predictions. The orange line provides an estimate of global temperatures if greenhouse gases stayed at year 2000 levels. (©2007 IPCC WG1 AR-4.)

Climate Feedbacks

Greenhouse gases are only part of the story when it comes to global warming. Changes to one part of the climate system can cause additional changes to the way the planet absorbs or reflects energy. These secondary changes are called climate feedbacks, and they could more than double the amount of warming caused by carbon dioxide alone. The primary feedbacks are due to snow and ice, water vapor, clouds, and the carbon cycle.

Snow and ice

Perhaps the most well known feedback comes from melting snow and ice in the Northern Hemisphere. Warming temperatures are already melting a growing percentage of Arctic sea ice, exposing dark ocean water during the perpetual sunlight of summer. Snow cover on land is also dwindling in many areas. In the absence of snow and ice, these areas go from having bright, sunlight-reflecting surfaces that cool the planet to having dark, sunlight-absorbing surfaces that bring more energy into the Earth system and cause more warming.

Canada’s Athabasca Glacier has been shrinking by about 15 meters per year. In the past 125 years, the glacier has lost half its volume and has retreated more than 1.5 kilometers. As glaciers retreat, sea ice disappears, and snow melts earlier in the spring, the Earth absorbs more sunlight than it would if the reflective snow and ice remained. (Photograph ©2005 Hugh Saxby. )

Water Vapor

The largest feedback is water vapor. Water vapor is a strong greenhouse gas. In fact, because of its abundance in the atmosphere, water vapor causes about two-thirds of greenhouse warming, a key factor in keeping temperatures in the habitable range on Earth. But as temperatures warm, more water vapor evaporates from the surface into the atmosphere, where it can cause temperatures to climb further.

The question that scientists ask is, how much water vapor will be in the atmosphere in a warming world? The atmosphere currently has an average equilibrium or balance between water vapor concentration and temperature. As temperatures warm, the atmosphere becomes capable of containing more water vapor, and so water vapor concentrations go up to regain equilibrium. Will that trend hold as temperatures continue to warm?

The amount of water vapor that enters the atmosphere ultimately determines how much additional warming will occur due to the water vapor feedback. The atmosphere responds quickly to the water vapor feedback. So far, most of the atmosphere has maintained a near constant balance between temperature and water vapor concentration as temperatures have gone up in recent decades. If this trend continues, and many models say that it will, water vapor has the capacity to double the warming caused by carbon dioxide alone.

Closely related to the water vapor feedback is the cloud feedback. Clouds cause cooling by reflecting solar energy, but they also cause warming by absorbing infrared energy (like greenhouse gases) from the surface when they are over areas that are warmer than they are. In our current climate, clouds have a cooling effect overall, but that could change in a warmer environment.

Clouds can both cool the planet (by reflecting visible light from the sun) and warm the planet (by absorbing heat radiation emitted by the surface). On balance, clouds slightly cool the Earth. (NASA Astronaut Photograph STS31-E-9552 courtesy Johnson space Center Earth Observations Lab. )

If clouds become brighter, or the geographical extent of bright clouds expands, they will tend to cool Earth’s surface. Clouds can become brighter if more moisture converges in a particular region or if more fine particles (aerosols) enter the air. If fewer bright clouds form, it will contribute to warming from the cloud feedback.

See Ship Tracks South of Alaska to learn how aerosols can make clouds brighter.

Clouds, like greenhouse gases, also absorb and re-emit infrared energy. Low, warm clouds emit more energy than high, cold clouds. However, in many parts of the world, energy emitted by low clouds can be absorbed by the abundant water vapor above them. Further, low clouds often have nearly the same temperatures as the Earth’s surface, and so emit similar amounts of infrared energy. In a world without low clouds, the amount of emitted infrared energy escaping to space would not be too different from a world with low clouds.

Clouds emit thermal infrared (heat) radiation in proportion to their temperature, which is related to altitude. This image shows the Western Hemisphere in the thermal infrared. Warm ocean and land surface areas are white and light gray; cool, low-level clouds are medium gray; and cold, high-altitude clouds are dark gray and black. (NASA image courtesy GOES Project Science. )

High cold clouds, however, form in a part of the atmosphere where energy-absorbing water vapor is scarce. These clouds trap (absorb) energy coming from the lower atmosphere, and emit little energy to space because of their frigid temperatures. In a world with high clouds, a significant amount of energy that would otherwise escape to space is captured in the atmosphere. As a result, global temperatures are higher than in a world without high clouds.

If warmer temperatures result in a greater amount of high clouds, then less infrared energy will be emitted to space. In other words, more high clouds would enhance the greenhouse effect, reducing the Earth’s capability to cool and causing temperatures to warm.

See Clouds and Radiation for a more complete description.

Scientists aren’t entirely sure where and to what degree clouds will end up amplifying or moderating warming, but most climate models predict a slight overall positive feedback or amplification of warming due to a reduction in low cloud cover. A recent observational study found that fewer low, dense clouds formed over a region in the Pacific Ocean when temperatures warmed, suggesting a positive cloud feedback in this region as the models predicted. Such direct observational evidence is limited, however, and clouds remain the biggest source of uncertainty--apart from human choices to control greenhouse gases—in predicting how much the climate will change.

The Carbon Cycle

Increased atmospheric carbon dioxide concentrations and warming temperatures are causing changes in the Earth’s natural carbon cycle that also can feedback on atmospheric carbon dioxide concentration. For now, primarily ocean water, and to some extent ecosystems on land, are taking up about half of our fossil fuel and biomass burning emissions. This behavior slows global warming by decreasing the rate of atmospheric carbon dioxide increase, but that trend may not continue. Warmer ocean waters will hold less dissolved carbon, leaving more in the atmosphere.

About half the carbon dioxide emitted into the air from burning fossil fuels dissolves in the ocean. This map shows the total amount of human-made carbon dioxide in ocean water from the surface to the sea floor. Blue areas have low amounts, while yellow regions are rich in anthropogenic carbon dioxide. High amounts occur where currents carry the carbon-dioxide-rich surface water into the ocean depths. (Map adapted from Sabine et al., 2004.)

See The Ocean’s Carbon Balance on the Earth Observatory.

On land, changes in the carbon cycle are more complicated. Under a warmer climate, soils, especially thawing Arctic tundra, could release trapped carbon dioxide or methane to the atmosphere. Increased fire frequency and insect infestations also release more carbon as trees burn or die and decay.

On the other hand, extra carbon dioxide can stimulate plant growth in some ecosystems, allowing these plants to take additional carbon out of the atmosphere. However, this effect may be reduced when plant growth is limited by water, nitrogen, and temperature. This effect may also diminish as carbon dioxide increases to levels that become saturating for photosynthesis. Because of these complications, it is not clear how much additional carbon dioxide plants can take out of the atmosphere and how long they could continue to do so.

The impact of climate change on the land carbon cycle is extremely complex, but on balance, land carbon sinks will become less efficient as plants reach saturation, where they can no longer take up additional carbon dioxide, and other limitations on growth occur, and as land starts to add more carbon to the atmosphere from warming soil, fires, and insect infestations. This will result in a faster increase in atmospheric carbon dioxide and more rapid global warming. In some climate models, carbon cycle feedbacks from both land and ocean add more than a degree Celsius to global temperatures by 2100.

Emission Scenarios

Scientists predict the range of likely temperature increase by running many possible future scenarios through climate models. Although some of the uncertainty in climate forecasts comes from imperfect knowledge of climate feedbacks, the most significant source of uncertainty in these predictions is that scientists don’t know what choices people will make to control greenhouse gas emissions.

The higher estimates are made on the assumption that the entire world will continue using more and more fossil fuel per capita, a scenario scientists call “business-as-usual.” More modest estimates come from scenarios in which environmentally friendly technologies such as fuel cells, solar panels, and wind energy replace much of today’s fossil fuel combustion.

It takes decades to centuries for Earth to fully react to increases in greenhouse gases. Carbon dioxide, among other greenhouse gases, will remain in the atmosphere long after emissions are reduced, contributing to continuing warming. In addition, as Earth has warmed, much of the excess energy has gone into heating the upper layers of the ocean. Like a hot water bottle on a cold night, the heated ocean will continue warming the lower atmosphere well after greenhouse gases have stopped increasing.

These considerations mean that people won’t immediately see the impact of reduced greenhouse gas emissions. Even if greenhouse gas concentrations stabilized today, the planet would continue to warm by about 0.6°C over the next century because of greenhouses gases already in the atmosphere.

See Earth’s Big Heat Bucket, Correcting Ocean Cooling, and Climate Q&A: If we immediately stopped emitting greenhouse gases, would global warming stop? to learn more about the ocean heat and global warming.

How Will Global Warming Change Earth?

The impact of increased surface temperatures is significant in itself. But global warming will have additional, far-reaching effects on the planet. Warming modifies rainfall patterns, amplifies coastal erosion, lengthens the growing season in some regions, melts ice caps and glaciers, and alters the ranges of some infectious diseases. Some of these changes are already occurring.

Global warming will shift major climate patterns, possibly prolonging and intensifying the current drought in the U.S. Southwest. The white ring of bleached rock on the once-red cliffs that hold Lake Powell indicate the drop in water level over the past decade—the result of repeated winters with low snowfall. (Photograph ©2006 Tigresblanco. )

Changing Weather

For most places, global warming will result in more frequent hot days and fewer cool days, with the greatest warming occurring over land. Longer, more intense heat waves will become more common. Storms, floods, and droughts will generally be more severe as precipitation patterns change. Hurricanes may increase in intensity due to warmer ocean surface temperatures.

Apart from driving temperatures up, global warming is likely to cause bigger, more destructive storms, leading to an overall increase in precipitation. With some exceptions, the tropics will likely receive less rain (orange) as the planet warms, while the polar regions will receive more precipitation (green). White areas indicate that fewer than two-thirds of the climate models agreed on how precipitation will change. Stippled areas reveal where more than 90 percent of the models agreed. (©2007 IPCC WG1 AR-4.)

It is impossible to pin any single unusual weather event on global warming, but emerging evidence suggests that global warming is already influencing the weather. Heat waves, droughts, and intense rain events have increased in frequency during the last 50 years, and human-induced global warming more likely than not contributed to the trend.

Rising Sea Levels

The weather isn’t the only thing global warming will impact: rising sea levels will erode coasts and cause more frequent coastal flooding. Some island nations will disappear. The problem is serious because up to 10 percent of the world’s population lives in vulnerable areas less than 10 meters (about 30 feet) above sea level.

Between 1870 and 2000, the sea level increased by 1.7 millimeters per year on average, for a total sea level rise of 221 millimeters (0.7 feet or 8.7 inches). And the rate of sea level rise is accelerating. Since 1993, NASA satellites have shown that sea levels are rising more quickly, about 3 millimeters per year, for a total sea level rise of 48 millimeters (0.16 feet or 1.89 inches) between 1993 and 2009.

Sea levels crept up about 20 centimeters (7.9 inches) during the twentieth century. Sea levels are predicted to go up between 18 and 59 cm (7.1 and 23 inches) over the next century, though the increase could be greater if ice sheets in Greenland and Antarctica melt more quickly than predicted. Higher sea levels will erode coastlines and cause more frequent flooding. (Graph ©2007 Robert Rohde. )

The Intergovernmental Panel on Climate Change (IPCC) estimates that sea levels will rise between 0.18 and 0.59 meters (0.59 to 1.9 feet) by 2099 as warming sea water expands, and mountain and polar glaciers melt. These sea level change predictions may be underestimates, however, because they do not account for any increases in the rate at which the world’s major ice sheets are melting. As temperatures rise, ice will melt more quickly. Satellite measurements reveal that the Greenland and West Antarctic ice sheets are shedding about 125 billion tons of ice per year—enough to raise sea levels by 0.35 millimeters (0.01 inches) per year. If the melting accelerates, the increase in sea level could be significantly higher.

Impacting Ecosystems

More importantly, perhaps, global warming is already putting pressure on ecosystems, the plants and animals that co-exist in a particular climate zone, both on land and in the ocean. Warmer temperatures have already shifted the growing season in many parts of the globe. The growing season in parts of the Northern Hemisphere became two weeks longer in the second half of the 20th century. Spring is coming earlier in both hemispheres.

This change in the growing season affects the broader ecosystem. Migrating animals have to start seeking food sources earlier. The shift in seasons may already be causing the lifecycles of pollinators, like bees, to be out of synch with flowering plants and trees. This mismatch can limit the ability of both pollinators and plants to survive and reproduce, which would reduce food availability throughout the food chain.

See Buzzing About Climate Change to read more about how the lifecycle of bees is synched with flowering plants.

Warmer temperatures also extend the growing season. This means that plants need more water to keep growing throughout the season or they will dry out, increasing the risk of failed crops and wildfires. Once the growing season ends, shorter, milder winters fail to kill dormant insects, increasing the risk of large, damaging infestations in subsequent seasons.

In some ecosystems, maximum daily temperatures might climb beyond the tolerance of indigenous plant or animal. To survive the extreme temperatures, both marine and land-based plants and animals have started to migrate towards the poles. Those species, and in some cases, entire ecosystems, that cannot quickly migrate or adapt, face extinction. The IPCC estimates that 20-30 percent of plant and animal species will be at risk of extinction if temperatures climb more than 1.5° to 2.5°C.

Impacting People

The changes to weather and ecosystems will also affect people more directly. Hardest hit will be those living in low-lying coastal areas, and residents of poorer countries who do not have the resources to adapt to changes in temperature extremes and water resources. As tropical temperature zones expand, the reach of some infectious diseases, such as malaria, will change. More intense rains and hurricanes and rising sea levels will lead to more severe flooding and potential loss of property and life.

One inevitable consequence of global warming is sea-level rise. In the face of higher sea levels and more intense storms, coastal communities face greater risk of rapid beach erosion from destructive storms like the intense nor’easter of April 2007 that caused this damage. (Photograph ©2007 metimbers2000. )

Hotter summers and more frequent fires will lead to more cases of heat stroke and deaths, and to higher levels of near-surface ozone and smoke, which would cause more ‘code red’ air quality days. Intense droughts can lead to an increase in malnutrition. On a longer time scale, fresh water will become scarcer, especially during the summer, as mountain glaciers disappear, particularly in Asia and parts of North America.

On the flip side, there could be “winners” in a few places. For example, as long as the rise in global average temperature stays below 3 degrees Celsius, some models predict that global food production could increase because of the longer growing season at mid- to high-latitudes, provided adequate water resources are available. The same small change in temperature, however, would reduce food production at lower latitudes, where many countries already face food shortages. On balance, most research suggests that the negative impacts of a changing climate far outweigh the positive impacts. Current civilization—agriculture and population distribution—has developed based on the current climate. The more the climate changes, and the more rapidly it changes, the greater the cost of adaptation.

Ultimately, global warming will impact life on Earth in many ways, but the extent of the change is largely up to us. Scientists have shown that human emissions of greenhouse gases are pushing global temperatures up, and many aspects of climate are responding to the warming in the way that scientists predicted they would. This offers hope. Since people are causing global warming, people can mitigate global warming, if they act in time. Greenhouse gases are long-lived, so the planet will continue to warm and changes will continue to happen far into the future, but the degree to which global warming changes life on Earth depends on our decisions now.

• Anthes, R.A., Corell, R.W., Holland, G., Hurrell, J.W., MacCracken, M.C., & Trenberth, K. (2010, February 12). Hurricanes and Global Warming—Potential Linkages and Consequences. Bulletin of the American Meteorological Society, 87: 623-628. Accessed April 15, 2010.
• Arctic Council. (2004). Arctic Climate Impact Assessment Report. Accessed March 22, 2007.
• Balachandran, N., Rind, D., Lonergan, P., & Shindell, D. (1999). Effects of solar cycle variability on the lower stratosphere and the troposphere. Journal of Geophysical Research, 104(D22), 27, 321-327, 339.
• Bender, M. A., Knutson, T. R., Tuleya, R. E., Sirutis, J. J., Vecchi, G. A., Garner, S. T., and Held, I. M. (2010). Modeled Impact of Anthropogenic Warming on the Frequency of Intense Atlantic Hurricanes. Science, 327(5964), 454-458.
• Bonan, G. B. (2008). Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests. Science, 320(5882), 1444-1449.
• Cazenave, A. (2006). How fast are the ice sheets melting? Science, 314, 1251-1252.
• Clement, A.C., Burgman, R., Norris, J.R. (2009, July 24) Observational and model evidence for positive low-level cloud feedback. Science, 325 (5939), 460-464.
• Dessler, A., Zhang, Z., Yang, P. (2008, October 23). Water-vapor climate feedback inferred from climate fluctuations, 2003-2008. Geophysical Research Letters, 35, L20704.
• Emanuel, K. (2005). Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436, 686-688.
• Foucal, P., Frölich, C., Spruit, H., and Wigley, T. (2006). Variations in solar luminosity and their effect on the Earth’s climate. Nature, 443, 161-166.
• Hansen, J., Sato, M., Ruedy, R., Kharecha, P., Lacis, A., Miller, R., Nazarenko, L., et al. (2007). Climate simulations for 1880–2003 with GISS model E. Climate Dynamics, 29(7), 661-696.
• Hansen, J., Nazarenko, L., Ruedy, R., Sato, M., Willis, J., Del Genio, A., Koch, D., Lacis, A., Lo, K., Menon, S., Novakov, T., Perlwitz, J., Russell, G., Schmidt, G.A., and Tausnev, N. (2005, June 3). Earth’s energy imbalance: confirmation and implications. Science, 308, 1431-1435.
• Intergovernmental Panel on Climate Change. (2007). Climate Change 2007: The Physical Science Basis Summary for Policymakers. A Report of Working Group 1 to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.
• Intergovernmental Panel on Climate Change. (2007). Climate Change 2007: Climate Change Impacts, Adaptation and Vulnerability Summary for Policymakers. A Report of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.
• Joint Science Academies. (2005). Joint Science Academies’ Statement: Global Response to Climate Change. June 2005.
• Jouzel, J., Masson-Delmotte, V., Cattani, O., Dreyfus, G., Falourd, S., Hoffmann, G., Minster, B., et al. (2007). Orbital and Millennial Antarctic Climate Variability over the Past 800,000 Years. Science , 317(5839), 793-796.
• Labitzke, K., Butchart, N., Knight, J., Takahashi, M., Nakamoto, M., Nagashima, T., Haigh, J., et al. (2002). The global signal of the 11-year solar cycle in the stratosphere: observations and models. Journal of Atmospheric and Solar-Terrestrial Physics, 64(2), 203-210.
• Laštovička, J., Akmaev, R. A., Beig, G., Bremer, J., & Emmert, J. T. (2006). ATMOSPHERE: Global Change in the Upper Atmosphere. Science, 314(5803), 1253-1254.
• Lau, K. M., and H. T. Wu. (2007). Detecting trends in tropical rainfall characteristics, 1979-2003. International Journal of Climatology, 27.
• Lean, J. L., & Rind, D. H. (2009). How will Earth’s surface temperature change in future decades? Geophysical Research Letters, 36, L15708.
• Lean, J. L., & Rind, D. H. (2008). How natural and anthropogenic influences alter global and regional surface temperatures: 1889 to 2006. Geophysical Research Letters, 35(18).
• Luthcke, S.B., Zwally, H.J., Abdalati, W., Rowlands, D.D., Ray, R.D., Nerem, R.S., Lemoine, F.G., McCarthy, J.J., and Chinn, D.S. (2006). Recent Greenland ice mass loss by drainage system from satellite gravity observations. Science, 314, 1286-1289.
• Mann, M. E., Zhang, Z., Hughes, M. K., Bradley, R. S., Miller, S. K., Rutherford, S., & Ni, F. (2008). Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia. Proceedings of the National Academy of Sciences, 105(36), 13252-13257.
• Manvendra K. Dubey, Petr Chylek, Charlie S. Zender, & Chris K. Folland. (2010, February 12). Global Warming and the Next Ice Age. Bulletin of the American Meteorological Society, 89 (12), 1905-1909.
• McGranahan, G., D. Balk and B. Anderson. (2007). The rising tide: assessing the risks of climate change and human settlements in low elevation coastal zones. Environment & Urbanization, 19 (1), 17-37.
• Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-being: Synthesis. Island Press, Washington, DC.
• Oren, R., Ellsworth, D. S., Johnsen, K. H., Phillips, N., Ewers, B. E., Maier, C., Schafer, K. V., et al. (2001). Soil fertility limits carbon sequestration by forest ecosystems in a CO2-enriched atmosphere. Nature, 411(6836), 469-472.
• Ramanathan, V., & Feng, Y. (2008). On avoiding dangerous anthropogenic interference with the climate system: Formidable challenges ahead. Proceedings of the National Academy of Sciences, 105(38), 14245-14250.
• Rind, D., Lean, J.L., Lerner, J., Lonergan, P., and Leboissetier, A. (2008). Exploring the stratospheric/tropospheric response to solar forcing. Journal of Geophysical Research, 113, D24103.
• Robock, A., Marquardt, A., Kravitz, B., & Stenchikov, G. (2009). Benefits, risks, and costs of stratospheric geoengineering. Geophysical Research Letters, 36, L19703.
• Sabine, C. L. (2004). The Oceanic Sink for Anthropogenic CO2. Science, 305(5682), 367-371.
• Schimel, D. (2007). Carbon cycle conundrums. Proceedings of the National Academy of Sciences, 104(47), 18353-18354.
• Seager, R., Ting, M., Held, I., Kushnir, Y., Lu, J., Vecchi, G., Huang, H., et al. (2007). Model Projections of an Imminent Transition to a More Arid Climate in Southwestern North America. Science, 316(5828), 1181-1184.
• Shepherd, A., and Wingham, D. (2007). Recent sea-level contributions of the Antarctic and Greenland Ice Sheets. Science, 315, 1529-1532.
• Soden, B. J. and Held, I.M. (2006, July). An assessment of climate feedbacks in coupled ocean-atmosphere models. Journal of Climate, 19: 3354-3360.
• Stainforth, D. A., Aina, T., Christensen, C., Collins, M., Faull, N., Frame, D. J., Kettleborough, J. A., et al. (2005). Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature, 433(7024), 403-406.
• U.S. Climate Change Science Program. (April 2006). Temperature Trends in the Lower Atmosphere. Accessed April 13, 2007.
• U.S. Environmental Protection Agency. (2007). Climate Change. Accessed March 22, 2007.
• U.S. Geological Survey. (2009, December 29). Volcanic gases and their effects. Volcano Hazards Program. Accessed March 29, 2010.
• Velicogna, I., and Wahr, J., (2006). Measurements of time-variable gravity show mass loss in Antarctica. Science, 311 (5768), 1754-1756.
• Weir, J. (2002, April 8). Global Warming . Earth Observatory. Accessed April 13, 2007.

Related Reading

• United States Global Change Research Program.
• Real Climate

Atmosphere Heat Land Water

ENCYCLOPEDIC ENTRY

Global warming.

The causes, effects, and complexities of global warming are important to understand so that we can fight for the health of our planet.

Earth Science, Climatology

Tennessee Power Plant

Ash spews from a coal-fueled power plant in New Johnsonville, Tennessee, United States.

Photograph by Emory Kristof/ National Geographic

Global warming is the long-term warming of the planet’s overall temperature. Though this warming trend has been going on for a long time, its pace has significantly increased in the last hundred years due to the burning of fossil fuels . As the human population has increased, so has the volume of fossil fuels burned. Fossil fuels include coal, oil, and natural gas, and burning them causes what is known as the “greenhouse effect” in Earth’s atmosphere.

The greenhouse effect is when the sun’s rays penetrate the atmosphere, but when that heat is reflected off the surface cannot escape back into space. Gases produced by the burning of fossil fuels prevent the heat from leaving the atmosphere. These greenhouse gasses are carbon dioxide , chlorofluorocarbons, water vapor , methane , and nitrous oxide . The excess heat in the atmosphere has caused the average global temperature to rise overtime, otherwise known as global warming.

Global warming has presented another issue called climate change. Sometimes these phrases are used interchangeably, however, they are different. Climate change refers to changes in weather patterns and growing seasons around the world. It also refers to sea level rise caused by the expansion of warmer seas and melting ice sheets and glaciers . Global warming causes climate change, which poses a serious threat to life on Earth in the forms of widespread flooding and extreme weather. Scientists continue to study global warming and its impact on Earth.

Media Credits

The audio, illustrations, photos, and videos are credited beneath the media asset, except for promotional images, which generally link to another page that contains the media credit. The Rights Holder for media is the person or group credited.

Production Managers

Program specialists, last updated.

February 21, 2024

User Permissions

For information on user permissions, please read our Terms of Service. If you have questions about how to cite anything on our website in your project or classroom presentation, please contact your teacher. They will best know the preferred format. When you reach out to them, you will need the page title, URL, and the date you accessed the resource.

If a media asset is downloadable, a download button appears in the corner of the media viewer. If no button appears, you cannot download or save the media.

Text on this page is printable and can be used according to our Terms of Service .

Interactives

Any interactives on this page can only be played while you are visiting our website. You cannot download interactives.

Related Resources

• Share full article

Advertisement

Supported by

Many Climate Policies Struggle to Cut Emissions, Study Finds

The most effective ones tend to combine several emissions-cutting strategies, not a stand-alone approach, according to an examination of 1,500 policies globally.

By Austyn Gaffney

First, the good news: 1,500 climate policies aimed at reducing emissions of planet-warming greenhouse gases have been implemented across dozens of countries over the past two decades.

The more troubling news: Only around 4 percent may have substantially reduced emissions, according to a new study.

“We’re finding good and bad news together,” said Nicolas Koch, a climate economist at the Potsdam Institute for Climate Impact Research and a co-author of the study published Thursday in Science. “It’s highlighting opportunities, like that larger reductions are possible, but also challenging the political will for policy design.”

While 63 policies highlighted in the study successfully reduced as much as 1.8 billion metric tons of carbon, the United Nations estimates that emissions must fall by 23 billion metric tons by 2030 to reach targets laid out in the 2015 Paris Agreement. Those targets aimed to limit the increase in the global average temperature to 1.5 degrees Celsius, or 2.7 degrees Fahrenheit, in order to preserve a livable planet.

With less than a decade left before that benchmark, the research could provide models for the best paths forward. “There is no silver bullet policy solution for climate mitigation,” said Jonas Meckling, an associate professor at University of California Berkeley and a climate fellow at Harvard Business School.

We are having trouble retrieving the article content.

Please enable JavaScript in your browser settings.

Thank you for your patience while we verify access. If you are in Reader mode please exit and  log into  your Times account, or  subscribe  for all of The Times.

Thank you for your patience while we verify access.

Already a subscriber?  Log in .

Want all of The Times?  Subscribe .

World's most effective climate policies identified in new study

Mix of carrots and sticks tends to work better than single policies, research finds.

Social Sharing

Countries around the world have implemented carbon pricing, electric vehicle incentives and thousands of other policies in an effort to cut carbon emissions and slow climate change. But which ones actually work? A new global study has uncovered 63 of the most effective policies, and found some helpful patterns.

Felix Pretis, a Canadian-based co-author of the study published today in Science , said the research offers both hope and pointers to drive more effective climate action.

"There's a whole set of policies that have already led to significant reductions," said Pretis, an associate professor of economics at the University of Victoria "There are definitely success stories we can turn to."

One was a big drop in the U.K.'s emissions from electricity with a combination of carbon pricing, subsidies for renewable energy and a coal phase-out plan. The U.S. cut transportation emissions with a mix of tax incentives and subsidies for EVs and tighter standards on carbon emissions.

A notable Canadian example was a drop in industrial carbon emissions with carbon pricing and emissions cap-and-trade policies.

All 63 success stories have been compiled into a searchable online dashboard that the researchers hope will help policy makers.

The study uncovered some key patterns about what works best. First of all, mixes of policies that include both incentives to reduce carbon emissions and deterrents to generating emissions tended to be more effective than single policies, such as incentives, carbon pricing or regulations, alone. Secondly, it found that carbon pricing was more effective in the industrial and electricity sector, dominated by businesses, than in the building and transportation sector, where individual consumers make decisions about their homes and cars and mixes of "carrots" and "sticks" were key.

How researchers figured out which policies work

Human-caused climate change is driven mainly by burning fossil fuels, which releases heat-trapping carbon emissions into the atmosphere. Under the Paris Agreement on climate change, many countries, including Canada, have implemented policies to cut emissions and eventually reach net zero emissions (where they are absorbing as many emissions as they emit.)

Pretis said the problem is "we really lack an understanding of which ones work."

Many past studies have tried to uncover the effect of individual policies, but have looked at only a small fraction of 1,500 policies around the world.

Why the federal carbon tax is 'a very emotional policy' for Canadians

Pretis and collaborators in Germany and the U.K., led by Annika Stechemesser at the Potsdam Institute for Climate Research in Germany, took a different approach.

They started with a database of climate policies in 41 countries managed by the Organisation for Economic Co-operation and Development (OECD), which divided them into four sectors: industry, electricity, transport and buildings.The researchers used computer algorithms to look for big emissions drops — larger than 4.5 per cent — in those sectors and countries, while filtering out economic fluctuations such as the COVID-19 pandemic. They compared the timing of those emissions drops to the implementation of 1,500 climate policies listed in a database between 1998 and 2022 and used statistics to link them.

The 63 successful policies identified led to emissions reductions of between 0.6 billion and 1.8 billion metric tonnes.

The researchers said implementing some of those policies in other countries before 2030 could significantly cut countries' emissions and help them get closer to meeting their emissions targets.

Carbon pricing works for developed countries – but not developing ones

Jennifer Winter is an economics professor at the University of Calgary whose research is also focused on climate policy.

She said the approach used by Pretis and his colleagues was novel and interesting, and she appreciated that the paper included both developed economies and developing ones, which are less studied.

The new study found that carbon pricing didn't work as well for developing countries.

The researchers said that was consistent with other research showing incentives and disincentives that rely on pricing don't work well without "liberalized markets."

Pretis said in lower-income countries, economies are less formal, and there may not be anyone to calculate, collect or track things like carbon taxes.

For developed countries, the study found a combination of pricing, subsidies and regulation worked.

"What's quite interesting," Winter observed, "is that … all three types of emission reduction policies matter for reducing emissions."

Carbon pricing and incentives work together

She said the new study provides important evidence that climate policies are working.

"One of the most common questions I'm asked in interviews is 'Does carbon pricing work?'" she said. The new research is "evidence that yes, with the data we have available, emission pricing is resulting in emissions reductions. And we also now have evidence that the other policies introduced by governments to help reduce emissions are also resulting in emissions reductions."

Winter and some colleagues published a blog post Thursday on trends in climate policies within Canada , based on a national database of climate policies analogous to the OECD's international one. The database is a collaboration with the Canadian Climate Institute's 440 Megatonnes project, which tracks Canada's progress in cutting emissions.

It found that in Canada, policy "carrots" that incentivize voluntary action make up 71.5 per cent of policies, vastly outnumbering policy "sticks."

Stewart Elgie, an environmental law professor at the University of Ottawa and founder of Sustainable Prosperity, a sustainable economy think-tank, points out that the new study shows subsidies are most effective when combined with pricing, regulation or both.

"We're not going to reduce emissions unless we use both carrots and sticks," he said.

He said he thought the way the study was done was "really clever" and it's probably the most comprehensive study of climate policies and their impacts worldwide to date, with some important insights.

"First, we're making progress in the fight against climate change," he said. "We're on the right path … but we need to keep going. We need to keep bringing in the types of policies that are underway [in other countries] right now, and we need to stick with carbon pricing as the foundation of our climate policies."

ABOUT THE AUTHOR

Science, Climate, Environment Reporter

Emily Chung covers science, the environment and climate for CBC News. She has previously worked as a digital journalist for CBC Ottawa and as an occasional producer at CBC's Quirks & Quarks. She has a PhD in chemistry from the University of British Columbia. In 2019, she was part of the team that won a Digital Publishing Award for best newsletter for "What on Earth." You can email story ideas to [email protected].

• Subscribe to the What on Earth newsletter

Related Stories

• The Netherlands generates way more solar power than Canada. Here's how they do it
• The carbon tax has plagued the Liberals politically. Research says that's not surprising

Add some “good” to your morning and evening.

The environment is changing. This newsletter is your weekly guide to what we’re doing about it.

This site is protected by reCAPTCHA and the Google Privacy Policy and Google Terms of Service apply.

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 11 August 2022

The Arctic has warmed nearly four times faster than the globe since 1979

• Mika Rantanen   ORCID: orcid.org/0000-0003-4279-0322 1 ,
• Alexey Yu. Karpechko 1 ,
• Antti Lipponen   ORCID: orcid.org/0000-0002-6902-9974 2 ,
• Kalle Nordling 1 , 3 ,
• Otto Hyvärinen 1 ,
• Kimmo Ruosteenoja 1 ,
• Timo Vihma   ORCID: orcid.org/0000-0002-6557-7084 1 &
• Ari Laaksonen 1 , 4  

Communications Earth & Environment volume  3 , Article number:  168 ( 2022 ) Cite this article

135k Accesses

808 Citations

7619 Altmetric

Metrics details

• Climate change
• Environmental sciences

In recent decades, the warming in the Arctic has been much faster than in the rest of the world, a phenomenon known as Arctic amplification. Numerous studies report that the Arctic is warming either twice, more than twice, or even three times as fast as the globe on average. Here we show, by using several observational datasets which cover the Arctic region, that during the last 43 years the Arctic has been warming nearly four times faster than the globe, which is a higher ratio than generally reported in literature. We compared the observed Arctic amplification ratio with the ratio simulated by state-of-the-art climate models, and found that the observed four-fold warming ratio over 1979–2021 is an extremely rare occasion in the climate model simulations. The observed and simulated amplification ratios are more consistent with each other if calculated over a longer period; however the comparison is obscured by observational uncertainties before 1979. Our results indicate that the recent four-fold Arctic warming ratio is either an extremely unlikely event, or the climate models systematically tend to underestimate the amplification.

Similar content being viewed by others

Steady threefold Arctic amplification of externally forced warming masked by natural variability

Enhanced Arctic warming amplification revealed in a low-emission scenario

New climate models reveal faster and larger increases in Arctic precipitation than previously projected

Introduction.

The faster warming rate in the Arctic compared to the globe as a whole is nowadays considered a robust fact. The phenomenon, called Arctic or polar amplification (AA), can be seen in both instrumental observations 1 , 2 , 3 and climate models 4 as well as in paleoclimate proxy records 5 .

During the last decade, multiple factors have been proposed to explain the potential causes of AA: enhanced oceanic heating and ice-albedo feedback due diminishing sea ice 6 , 7 , 8 , 9 , Planck feedback 10 , lapse-rate feedback 11 , near-surface air temperature inversion 12 , cloud feedback 13 , ocean heat transport 14 and meridional atmospheric moisture transport 15 , 16 , 17 . Furthermore, the reduced air pollution in Europe may have contributed to the Arctic warming during the last decades 18 , 19 , and possible reductions of Asian aerosols under a strong mitigation policy may increase the future AA 20 . In climate models, it has been shown 21 that AA occurs rapidly in response to external forcings due to atmospheric lapse rate feedback, with sea ice-related feedbacks becoming more important later on. A recent study 22 reported a stronger future AA in a low than a high-emission scenario due to the faster melting of sea ice and weaker ice-albedo feedback.

There is little consensus on the magnitude of the recent AA. Numerous recent studies report the Arctic having warmed either almost twice 23 , about twice 24 , or more than twice 25 , 26 as fast as the global average. However, the warming ratios reported in these and many other studies have usually been only referenced from older, possibly outdated, estimates and have not included recent observations. The recent Arctic Monitoring and Assessment Programme (AMAP) report 27 states the rate of Arctic warming as being three times as fast as the global warming during the period 1971–2019.

The lack of consensus on the magnitude of AA stems from the various definitions of AA: both the period of interest and the area of the Arctic have been defined in multiple ways. The warming can be calculated using linear trends for the last 30-50 years or even longer periods. Moreover, the area of Arctic can be defined using the area poleward of 60 ∘ N, 65 ∘ N or 70 ∘ N, or using definitions not based on latitude 28 . Uncertainties arising when calculating AA in observations and models have also been emphasized 28 , 29 .

While there have been improvements in climate models to realistically represent the evolution of Arctic climate 30 , 31 and sea ice 32 under global warming, most models in the latest generation of Coupled Model Intercomparison Project phase 6 (CMIP6) still fail to simulate plausible sensitivity of Arctic sea-ice loss to the rise of global temperatures 33 . In earlier studies, the discrepancy between observed and simulated sea ice trends have been attributed to a lower sensitivity of modelled Arctic sea ice trends to global warming 34 or anthropogenic CO 2 emissions 35 . However, Swart et al. 36 argued that the observed and simulated September Arctic sea-ice trends over 1979–2013 are not inconsistent when accounting properly for the internal climate variability. According to Ding et al. 37 , even up to 50% of the recent multi-decadal decline in Arctic sea ice may be due to internal variability.

Because the sea ice loss is one of the main mechanisms causing AA, and given that up to 50% of the recent loss may be due to realization-dependent internal variability, a relevant follow-up question is whether the climate models are able to reproduce the magnitude of the observed AA over the past 40 years or so. Earlier studies have suggested that AA is indeed weaker in climate models than in observations 38 , 39 , 40 , 41 , but a comprehensive comparison between the observed and simulated AA ratio, using the most up-to-date observations and multiple climate model ensembles, has not yet been performed.

The first objective of this study is to quantify the magnitude of AA by utilizing most recent observational datasets covering the Arctic region, and a diagnostic equation for AA. Our focus is in the 1979–2021 period, as more accurate remote sensing observations from the Arctic have been available since 1979, and because this era is characterized by strong Arctic warming. Secondly, we assess the ability of climate models to reproduce the observed AA. We show that during 1979–2021, the Arctic has warmed nearly four times faster than the globe, and provide evidence that climate models struggle to simulate this four-fold Arctic amplification ratio.

Observed arctic amplification

The evolution of global mean and Arctic mean temperatures during 1950–2021 is shown in Fig.  1 a by considering the four observational datasets: NASA’s Goddard Institute for Space Studies Surface Temperature version 4 (GISTEMP), the Berkeley Earth temperature dataset (BEST), the Met Office Hadley Centre/Climatic Research Unit version 5.0.1.0 (HadCRUT5) and ERA5 reanalysis. Compared to the global temperatures (Fig.  1 a, light colours), the warming in the Arctic (Fig.  1 a, dark colours) is much more pronounced, especially since the late 1970s. We note also that the different datasets are in a close agreement since 1979, but in the pre-1979 period ERA5 is markedly colder than the three other datasets. Reasons for this cold bias are presumably related to lower number of assimilated observations, as discussed in earlier studies 42 , 43 .

a Annual mean temperature anomalies in the Arctic (66.5 ∘ –90 ∘ N) (dark colours) and globally (light colours) during 1950–2021 derived from the various observational datasets. Temperature anomalies have been calculated relative to the standard 30-year period of 1981–2010. Shown are also the linear temperature trends for 1979–2021. b Annual mean temperature trends for the period 1979–2021, derived from the average of the observational datasets. Areas without a statistically significant change are masked out. c Local amplification ratio calculated for the period 1979–2021, derived from the average of the observational datasets. The dashed line in ( b ) and ( c ) depicts the Arctic Circle (66.5 ∘ N latitude).

Due to the good agreement over the last 43 years, we next consider the average of these four datasets as an observational estimate. The observations indicate that, during 1979–2021, a large fraction of the Arctic Ocean was warming faster than 0.75  ∘ C decade −1 (Fig.  1 b), with a maximum warming in the Eurasian sector of the Arctic Ocean, near Svalbard and Novaya Zemlya. In this region, the temperature trend over 1979–2021 locally exceeds 1.25  ∘ C decade −1 (Fig.  1 b). In contrast, large continental regions in the North America and, to a lesser extent, in Western Siberia, do not manifest statistically significant trends in temperatures; however these regions are mainly located in mid-latitudes and are only indirectly affected by AA. The spatial patterns of temperature trends are broadly consistent across the individual observational datasets (Fig. S 2) , with GISTEMP and HadCRUT5 showing somewhat less pronounced warming maxima near Svalbard and Bering Strait (Fig. S 2 a and c) than BEST and ERA5.

When the temperature trends shown in Fig.  1 b are divided by the multi-dataset global mean temperature trend at each grid-point, we get the spatial map of 43-year local Arctic amplification (AA 43 ), or simply local amplification when calculated for areas south of the Arctic circle (Fig.  1 c). Values higher than one indicate that those regions are warming faster than the global average, while values below one correspondingly indicate a slower warming. The AA 43 maps for individual observational datasets are provided in the Supplementary Fig. S 3 .

During 1979–2021, major portions of the Arctic Ocean were warming at least four times as fast as the global average (Fig.  1 c). The most extreme AA values occur in the sea areas near Novaya Zemlya, which were locally warming up to seven times as fast as the global average. These high warming rates are consistent with recent research 44 , and evidently, the primary reason for such a high amplification ratio is the reduction of cold-season ice cover, which has been most pronounced in the Barents Sea 44 , 45 . Furthermore, it has been found that changes in atmospheric circulation have amplified the warming in this area 46 , 47 . In general, there are no regions within the Arctic Circle where AA 43 is smaller than two, apart from the northern North Atlantic.

The observed multi-dataset mean temperature trend in the Arctic is 0.73  ∘ C decade −1 and for the globe as a whole 0.19  ∘ C decade −1 , with small differences between the individual datasets (Fig. S 4 a). Using Eq. ( 1 ) and the multi-dataset mean values for the Arctic and global mean warming trends, we arrive at AA 43 (hereafter referred as observed AA 43 ) of 3.8 for the latest 43-year period of 1979–2021. The individual AA 43 values range from 3.7 in ERA5 to 4.1 in BEST (Table  1 and Fig. S 4 b). Thus, referring Arctic warming as being two times as fast as the global mean clearly underestimates the situation during the recent 43 years.

When different southern boundaries for the Arctic region are considered, AA 43 ranges generally between 3 and 4 (Fig.  2 a). In general, with any reasonable combination for the length of the time window (≥20 years) and for the southern boundary of the Arctic (60 ∘ –75 ∘ N), the value of AA is greater than 3. The magnitude of AA increases towards higher Arctic latitude thresholds, because with higher latitude a larger proportion of the area encircled by the boundary is ocean, where AA is the strongest (Fig.  1 c).

The sensitivity of Arctic amplification (AA) ( a ) to the time window used in calculating the linear trends (x-axis) and the southern boundary of the Arctic (y-axis), and ( b ) the percentile rank of the observed AA in the CMIP6 ensemble distribution. The end year of all linear trends is fixed to 2021. Thus, for example, 50 years on the x-axis corresponds to the trend calculated for 1972–2021. The star marks the baseline value used in the study, corresponding to the 43-year linear trend and the southern boundary of 66.5 ∘ N. The observed AA is derived from the average of the four observational datasets.

Arctic amplification in CMIP5 and CMIP6 simulations

Figure  3 demonstrates how the observed AA 43 has intensified in the course of time: while in the beginning of the century the warming ratio of the Arctic to the globe over the previous 43 years was smaller than three, the recent amplified Arctic warming 48 relative to the globe has raised the ratio close to four.

The 43-year Arctic amplification (AA) ratio derived from ( a ) CMIP5, ( b ) CMIP6, ( c ) MPI-GE and ( d ) CanESM5 realizations (thin grey lines) for all 43-year periods ending in 2000–2040. The x-axis represents the ending year of the 43-year AA ratios. Thick black lines represents the ensemble mean AA, calculated as a mean of ratios, not ratio of means. Observations (red lines) extend to 2021. 43-year AA ratios starting after 1970 and ending by 2040 are considered in the probability calculations (Section “Likelihood of observed Arctic amplification 1979–2021 in climate model simulations”) and shown with light background. The Arctic is defined as the area north of 66.5 ∘ N.

The observed four-fold warming in the Arctic fits poorly in the spread of the CMIP5 and CMIP6 multi-model ensembles (Fig.  3 ). Compared with the observed AA 43 in 2021 (3.8), the CMIP5 ensemble-mean AA 43 (2.5) and CMIP6 ensemble-mean (2.7) are underestimated by 34% and 29%, respectively (Fig.  3 a, b and S 5 b). However, the observed AA 43 reflects both the forced response to external forcing as well as the internal climate variability on the multi-decadal timescales considered here. Instead, in the ensemble mean of the climate models, the internal variability of climate system has been effectively averaged out, and thus the ensemble mean reflects only the models’ response to the external forcing. For this reason, comparing the observations only to the ensemble mean may be misleading, and therefore, the observed AA 43 needs to be put into context of the envelope of simulated AA 43 .

In the CMIP5 ensemble, there are only a few realizations which simulate stronger amplification than the observations (Fig.  3 a). However, the fact that only one realization per model is used in the CMIP5 ensemble may imply that some of the extreme cases are missing. In general, CMIP6 models simulate slightly stronger AA 43 than CMIP5 models. Nonetheless, the majority of CMIP6 realizations in which the simulated AA 43 is stronger than the observed AA 43 , occur earlier in the 21st century (Fig.  3 b). It is also worth noting that CMIP6 models have generally a larger spread in AA 43 than CMIP5, even when considering only one realization per CMIP6 model (not shown). Some CMIP6 realizations simulate cooling for the Arctic (negative AA 43 ) while some other realizations have higher than five-fold warming in the Arctic compared to the globe (Fig.  3 b). The large spread in CMIP6-simulated AA is in line with an earlier study 39 and highlights the effect of large internal variability for AA, even on a 43-year time scale.

Figure  4 shows AA as a function of the starting year used for calculating the trends. In general, the shorter the time period for which AA is calculated, the larger role the internal variability plays, and therefore the ensemble spread of the models tends to explode towards the right edge of the panels (i.e., towards shorter trends, Fig.  4 ). Considerable fraction of simulations with negative AA or very large AA (above 6) for trends shorter than 20 years suggest that such short periods may not be suitable for reliable estimation of AA. The long trends, on the other hand, are more representative of the forced amplification and therefore have less spread between the realizations. The observed AA is outside the spread of CMIP5 under wide range of the trend lengths (Fig.  4 a). In CMIP6, the spread of AA is clearly wider than in CMIP5 and thus, the observed AA does not fall fully outside the CMIP6 ensemble at any starting year (Fig.  4 b). Nevertheless, the observed AA is a very rare occasion in CMIP6 model simulations as Fig.  2 b shows that in most cases when AA is calculated over time period longer than 20 years and for southern boundary poleward from 60 ∘ N, the observed AA falls to the top 10% of the CMIP6 model ensemble and reaching to the 99th percentile of the ensemble in several window-latitude combinations. Remarkably, for CMIP5, the observed AA is fully outside the ensemble spread at all 30-45-year trend lengths regardless of southern boundary (Fig. S 6 b).

Arctic amplification (AA) ratio as a function of the starting year of the trend derived from ( a ) CMIP5, ( b ) CMIP6, ( c ) MPI-GE and ( d ) CanESM5 realizations (thin grey lines). The end year of all linear trends is fixed to 2021. Thus, for example, 1950 on the x-axis corresponds to AA calculated for 1950–2021. Thick black lines represents the ensemble mean AA, calculated as a mean of ratios, not ratio of means. AA ratios shorter than 10 years are not shown. The dashed vertical line represents the 43-year AA, as calculated for 1979–2021. The Arctic is defined as the area north of 66.5 ∘ N.

It is important to note that the discrepancy between the observational and modelled AA is sensitive to the starting year of the trend. For example, when AA is calculated using the 1950–2021 time period, the observed AA is very close to the ensemble means of all climate model datasets (the left edge of the panels in Fig.  4 ). However, this time period includes a 30-year period of 1950–1979 when the global mean temperatures did not rise mostly due to opposing effect of the anthropogenic aerosols counteracting the greenhouse gas-induced warming 49 . In 1950–1979, the temperatures in the Arctic were slightly cooling (except in ERA5, see Fig.  1 a). Because of this non-linearity in the observations, the linear trend estimate over the whole 1950–2021 does not capture the entire dynamics of the recent warming in the Arctic and thus should be interpreted with caution.

By considering the seasonality of AA (Fig.  5 ), we see that AA is the strongest in the late autumn (November) and the weakest in the warm season (July). This is consistent in both CMIP6 models and the observations, and in line with the earlier study conducted with ERA-Interim reanalysis data and CMIP5 models 8 . Thus, over the past 43 years, the October-December months in the Arctic have warmed five times faster than the globe, while the warming ratio is close to two in June-August (Fig.  5 ). The stronger AA in late autumn arises from the newly opened water areas that act to enhance upwelling longwave radiation and turbulent fluxes of sensible and latent heat from the sea into the atmosphere 8 .

The red circles indicate the observed AA, as derived from the average of the four observational datasets. The orange lines indicate the medians of CMIP6 realizations, boxes show the first and third quartiles, and whiskers extend to the 5–95th percentiles of the realizations. The numbers in the upper row give the percent rank of the observed AA in the CMIP6 ensemble distribution. The Arctic is defined as the area north of 66.5 ∘ N.

The observations systematically indicate larger AA than CMIP6 models around the year. In all months, the observed AA 43 falls to the upper 25 % of the CMIP6 ensemble, and even to the top 5% in April, May, June, and August. The monthly comparison of observations to CMIP5 models indicate even more pronounced underestimation of AA, especially in the melting season (Fig. S 7) . An interesting finding from Fig.  5 is the anomalously high observed AA in April. The high AA 43 in April is consistent in all four observational datasets (not shown), and has been reported also in the earlier studies 41 , 50 . However, while Hahn et al. 41 noted that the warming in April falls within the intermodel spread for CMIP6 in 1979–2014, we found that when normalized with global warming, the warming in April is distinctly outside the CMIP6 ensemble (Fig.  5 ). According to Hahn et al. 41 , model biases in the reductions of spring snow cover may contribute to the discrepancy between observations and models in the melting season.

Likelihood of observed Arctic amplification 1979–2021 in climate model simulations

How likely is the nearly four-fold warming in the Arctic, as observed in 1979–2021? To answer this question, we investigate all possible AA 43 ratios starting after 1970 and ending by 2040 from all four climate model ensembles (see Section “Comparison between simulated and observed Arctic amplification”). While these 43-year periods overlap, and therefore not fully independent, we consider all these periods together because the internal climate variability is not expected to be in phase in models and observations.

In the CMIP5 simulations, there are only three realizations which simulate equally strong AA as observed between 1979 and 2021, even when the longer time window from 1970 to 2040 is allowed. This means that AA greater than or equal to the observed value of 3.8 occurs with a probability of p  = 0.006 across the models (Fig.  6 a). For CMIP6, we obtain a probability p  = 0.028 for the occurrence of AA ≥ 3.8. If only one realization per model were used in CMIP6, the probability is p  = 0.015 (Fig. S 8) . Thus, the CMIP6 models seem to reproduce the observed AA 43 marginally better than CMIP5 models, consistent with the higher sensitivity of sea ice loss to cumulative CO 2 emissions and global warming in the CMIP6 than in CMIP5 models 33 . Nevertheless, the likelihood of a fourfold warming in the Arctic in CMIP6 models remains still very small, indicating that the recent Arctic amplification in 1979–2021 is either extremely unlikely or the climate models systematically tend to underestimate AA.

Frequency distributions of all possible 43-year AA ratios between 1970 and 2040 in ( a ) CMIP5, ( b ) CMIP6, ( c ) MPI-GE, and ( d ) CanESM5 ensemble. The red line denotes the observed 43-year AA ratio, as calculated for 1979–2021.

The spread of simulated AA in CMIP5 and CMIP6 realizations arises from both internal climate variability and the inter-model spread. To assess the role of internal variability in the AA uncertainty, we next consider the two single-model initial-condition large ensembles (hereafter SMILEs). The individual members of SMILEs are initialized from different initial conditions with identical external forcing; thus the spread in these ensembles is solely due to internal variability 51 , 52 . In principle, SMILEs are thus powerful tool to quantify the internal variability of the climate system.

Looking at the spreads of AA 43 in SMILEs, we find that they explain a majority of the total CMIP5 and CMIP6 spread, suggesting that the model uncertainty plays a relatively small role in this comparison (Fig.  6 ). The observed AA 43 in 1979–2021 (red line) is fully outside the spread of MPI-GE (Fig.  6 c), thus giving a probability p  ≈ 0.00. This means explicitly that MPI-GE does not capture the observed Arctic amplification as none of its 100 ensemble members can simulate sufficiently strong AA 43 in any 43-year periods between 1970 and 2040.

For CanESM5, AA 43 ≥ 3.8 occurs with a probability of p  = 0.054 (Fig.  6 d). However, it is known that CanESM5 has a particularly high equilibrium climate sensitivity 53 , which indicates considerable higher rates of warming both in the Arctic and the globe compared to other models with the same external forcing (Fig. S 5 and S 9) . Thus, while some members of CanESM5 simulate realistic AA 43 , they do so in a modelled climate which is warming much faster than the real world (Fig. S 9 d). In addition, the behaviour of simulated AA 43 ratios in CanESM5 differ from those in other models: while in CMIP5, CMIP6 and MPI-GE simulations the most extreme AA 43 values tend to occur in the beginning of 21st century, in the CanESM5 simulations AA is generally at its lowest in the beginning of the 21st century and intensifies towards 2040 (Fig.  3 d).

A robust statistical test (see Section “Comparison between simulated and observed Arctic amplification” and Supplementary Methods) yields further support for the evidence that climate models as a group underestimate the present Arctic amplification. The test has been tailored to properly take into account the two main sources of uncertainty: the internal climate variability and the model uncertainty. The test returns p values of 0.00 for CMIP5 and 0.027 for CMIP6. When the test is further applied for the two SMILEs, we obtain p values of 0.00 and 0.091 for MPI-GE, and CanESM5, respectively. Thus, we can reject the null hypothesis at the 5 % level for CMIP5, CMIP6 and MPI-GE ensembles. This provides additional evidence that climate models, as a group, are not able to reproduce the observed AA 43 even when properly accounting for the internal variability and the model uncertainty.

Finally, we acknowledge that the p values calculated with the statistical test are dependent on the starting year of the trends. Here we used the 43-year trends calculated over 1979–2021, which showed large discrepancy (and thus low p values) between the observations and model realizations. The longer trends, which should in principle better reflect the externally forced response of the climate system, show a closer agreement (and evidently higher p values) with the climate models (Fig.  4 ). However, going back in time from 1979 increases the observational uncertainty, and the resulting linear trends do not fully represent the recent warming period in the Arctic due to a non-linear evolution of the temperature (Fig.  1 a).

We present evidence that during 1979–2021 the Arctic has been warming nearly four times as fast as the entire globe. Thus, we caution that referring to Arctic warming as to being twice as fast as the global warming, as frequently stated in literature, is a clear underestimation of the situation during the last 43 years since the start of the satellite observations. At a regional scale, areas in the Eurasian sector of the Arctic Ocean have warmed even up to seven times as fast as the globe (Fig.  1 c).

There are two main reasons why our calculation of AA is greater than the earlier estimates generally referenced in literature: (1) the earlier estimates may be outdated due to continued warming in the Arctic (Figs.  1 a and 3 ), and (2) the period of interest and the area of the Arctic can be defined in multiple ways. We used the satellite era (1979–2021) when the remote sensed observations from the Arctic are available, and defined the area of the Arctic using the Arctic Circle as the southern boundary (66.5 ∘ –90 ∘ N). With these parameters, the observed rate of warming in the Arctic is 3.8 times as strong as the global average (Table  1 ). A more inclusive definition for the Arctic (e.g., >60 ∘ N) would yield smaller ratio (3.2 for 60 ∘ N, see Fig.  2 a), but this include more land areas where the sea ice loss feedback is absent.

The advanced interpolation methods in the observational datasets 54 , 55 mean that we now have an improved estimate of the warming trends in areas with scarce data such as the Arctic. However, although the modern observational datasets used in this study produce a spatially comprehensive temperature fields for the Arctic, the low number of observations, particularly from the ice-covered Arctic Ocean, implies that the estimates can have substantial uncertainties. For example, Simmons et al. 42 discusses the peculiar cooling, or the lack of warming trend in ERA5 in the area north of Greenland, and link this with questionably low values of the sea ice concentration in ERA5 prior to 1990. This inconsistency in the temperature trends is also visible in our study (Fig. S 2 d). On the other hand, it has been evaluated that out of five different reanalysis datasets, ERA5 performs the best over the open Arctic ocean 56 . ERA5 was also found to generally describe well the temporal and spatial characteristics of near-surface temperatures in the Arctic in 1979–2014 31 . Nevertheless, when averaging the temperature trends across the whole Arctic, the inconsistencies in the regional trends appear to cancel out. As a result, the regional averages are surprisingly well aligned (Fig. S 4 a). Still, we acknowledge the possibility that the observed temperature trends may have common biases for example over the polar ice cap that can affect the magnitude of observed AA, and thus also the model vs. observation differences.

One potential factor increasing the observed AA is the hiatus phase in global warming that occurred between about 1998 and 2012 57 , although the existence of the hiatus has been questioned by a thorough statistical analysis 58 . Nevertheless, in these years global mean temperature rose more slowly, which acts to reduce the denominator of Eq. ( 1 ) for the entire period 1979–2021. According to a previous study 59 , an important contributing factor to the hiatus was the low sea surface temperature in the equatorial Pacific Ocean. Nevertheless, the impact of tropical Pacific temperature anomalies did not extend to high northern latitudes where warming continued unabatedly (Fig.  1 a), keeping the numerator of Eq. ( 1 ) large.

Our results demonstrate that climate models as a group tend to underestimate the observed Arctic amplification in the 1979–2021 time period, i.e. since the beginning of the recent period of global warming. This is also true for the latest CMIP6 models despite the fact that some of these models better reproduce the absolute warming rate in the Arctic. However, those models that show plausible Arctic warming trend typically have too much global warming as well when compared to observations. In contrast, those models that simulate global warming close to that observed, generally have too weak Arctic warming (Fig. S 9) . Thus, our results show that most climate models are unable to simulate a fast-warming Arctic simultaneously with weaker global warming, as found earlier for the relationship of Arctic sea ice decline and global atmospheric warming 34 . Most strikingly the underestimation was true for the CMIP5 and MPI-GE ensembles, which altogether included only three realizations simulating as high AA as observed in 1979–2021. These results, i.e., lower AA in CMIP5 and CMIP6 models compared to the observations, are consistent with earlier studies 38 , 40 , 41 . Nevertheless, we also found that the discrepancy in AA between climate models and observations is smaller when calculated over longer periods, such as 1950–2021 (Fig.  4 ).

The physical mechanisms behind the underestimation of AA in climate models remain unknown, but may be related to, e.g., errors in the model sensitivity to greenhouse gas forcing and in the distribution of the forced heating between the atmosphere, cryosphere and the ocean, and in different heights/depths in the atmosphere/ocean. Moreover, internal variability or uncertainties in observations may also contribute to the difference in AA between climate models and observations.

We found that the recent near-surface Arctic amplification ratio is about 40–50% stronger than the multi-model mean amplification derived from CMIP5 and CMIP6 ensembles (Fig.  3 and Table  1 ). If assuming that these multi-model means represent the externally forced signal for AA, our findings suggest that the unforced climate variability has played a large role in intensifying the recent amplification. This resonates with the results by Ding et al. 37 who found that internal climate variability has contributed to about 40–50% of observed multi-decadal decline in Arctic sea ice over 1979–2013. There is also evidence that climate models underestimate the multi-decadal internal variability of the extratropical atmospheric circulation 60 , 61 , thus potentially underestimating the temperature variability in the Arctic as well. Nevertheless, if the internal variability indeed proves to be an important source for the difference of AA between the model simulations and observations, one can expect that the observed AA will be reduced in the long term, along with the reduction of the ratio of forced to unforced climate change.

Further, the inability of climate models to simulate realistic AA, here defined in terms of 2-m air temperature, may have implications for future climate projections. Specifically, the tug of war between the near-surface AA and upper-tropospheric tropical amplification of climate warming over the future changes in storm tracks 62 , 63 projected by climate models may be biased towards the forcing by tropical warming, implicating that both projected storm track changes and associated regional climate changes may be biased. Our results call for more detailed investigation of mechanisms behind AA and their representation in climate models.

Observational data

For the near-surface air temperature, we used three in-situ temperature records and one reanalysis dataset. For in-situ datasets, we used NASA’s Goddard Institute for Space Studies Surface Temperature version 4 (GISTEMP) 64 , the Berkeley Earth temperature dataset (BEST) 54 , and the Met Office Hadley Centre/Climatic Research Unit version 5.0.1.0 (HadCRUT5) 55 . In these datasets, near-surface air temperature is based on a combination of 2-m temperature observations over land and sea surface temperature (SST) observations over the ocean.

GISTEMP spatially extrapolates temperatures into unmeasured regions using a 1200-km radius of influence for the stations. BEST employs kriging-based spatial interpolation, and HadCRUT5 uses their own statistical infilling method. In all these datasets, areas of sea ice are treated as if they were land, and SST observations are used and extrapolated only at the grid cells which are ice free. The coverage of sea ice is obtained from Met Office Hadley Centre sea ice and sea surface temperature data set, HadISST2 65 .

In addition to the three purely observational datasets, we used ERA5 reanalysis 66 , which has been produced by the European Centre for Medium-Range Weather Forecasts. We used monthly mean 2-m temperature fields in the native, 0.25 ∘ horizontal resolution. The first release of ERA5 covers the years from 1979 to the present, but a preliminary extension for 1950–1978 was recently released 43 . We used the whole time series, from 1950 to 2021. All the observational temperature datasets used are listed in Table S 1 .

To assess the accuracy of the four datasets applied in our study (GISTEMP, BEST, HadCRUT5, ERA5) in the Arctic, we conducted a validation against the Global Historical Climatology Network monthly (GHCN-M) station data 67 . We used the station data which was bias-adjusted for non-climatic effects (indicated by the suffix “.qcf” in the GHCN-M database). We selected all the stations located north of 66.5 ∘ N that had at least 39 years of data over the 43-year period of 1979–2021. In total, these criteria resulted in 87 stations. We calculated the temperature trends for each station, and compared them with the average across the four gridded datasets. These results are shown in Fig. S 1 . The median difference between the trends estimated from the gridded data and the 87 station observations (gridded minus stations) is −0.019  ∘ C decade −1 . Therefore, we conclude that the average of the four gridded temperature datasets generally captures well the temporal trends of the near-surface mean temperature in the Arctic, which makes it suitable to be used as a basis of our study.

Climate model data

We compared the observed temperatures to four climate model ensembles, which are listed in Table S 2 . These ensembles are (i) one realization from each model in the CMIP5 multi-model ensemble 68 , (ii) all available realizations from each model in the CMIP6 multi-model ensemble 69 , (iii) the 100-member Max-Planck Institute Grand Ensemble (MPI-GE) 70 , and (iv) the 50-member Canadian Earth System Model version 5 (CanESM5) 53 . CanESM5 is a part of CMIP6 ensemble but we examine it separately because the large ensemble size provides an opportunity to highlight the role of internal variability. Thus, in our analysis, CanESM5 was not included in CMIP6. MPI-GE and CanESM5 were chosen as they provide large ensembles for RCP4.5 or SSP2-4.5 emission scenarios and represent opposite sides of the equilibrium climate sensitivity with 2.8 K 70 for MPI-GE and 5.6 K for CanESM5 53 . Our key results were not notably affected if CanESM5 was considered as a part of CMIP6.

All four climate model datasets consisted of historical simulations (1950–2005 for CMIP5 and MPI-GE, and 1950–2014 for CMIP6 and CanESM5) and future projections forced by the RCP4.5 scenario for CMIP5 and MPI-GE, and SSP2-4.5 for CMIP6 and CanESM5 (Table S 2) . As we focus only on the pre-2040 period, our main results do not markedly depend on the choice of the emission scenario. In all climate model datasets, monthly averaged data for 2-m air temperature were used. The list of all the CMIP5 and CMIP6 models used can be found from the supplement Tables S 3 and S 4 .

We acknowledge that the three in-situ temperature records (GISTEMP, BEST and HadCRUT5) do not provide a fully like-for-like comparison to climate models since the in-situ datasets report a blend of land 2-m temperature and SST, whereas the model output is the 2-m air temperature (SAT). According to Cowtan et al. 71 , the global warming trend derived from the model blended fields are about 7 % lower than the trend from the model SAT fields over the 1975–2014 period. To reduce the potential impacts of this difference, we conducted our analysis also with ERA5 reanalysis data which provides like-for-like comparison to climate models.

Defining the Arctic amplification

We follow the recommendation of Smith et al. 72 , and define Arctic amplification (AA) as the ratio of Arctic warming to the global-mean warming:

where d T / d t A and d T / d t G are the slopes of linear trends of near-surface temperature, calculated using a least-squares fitting for the annual and monthly mean values for the Arctic and global domain. The trends were calculated for different time periods (see Fig.  2 a), but 43-year AA ratios (hereafter referred to A A 43 ) were chosen to be of the primary interest, because (i) 43 years covers the majority of the recent warming period when the warming has been approximately linear (Fig.  1 a), (ii) the reanalysis products, such as ERA5, are known to be more reliable during this period because satellite remote sensing data on atmospheric variables and sea ice concentration have become largely available since 1979 73 , and (iii) there is disagreement between ERA5 and the three in-situ datasets in the Arctic prior to 1979 (see Fig.  1 a). Furthermore, the definition of AA naturally only makes physical sense if there is global warming on which Arctic warming is superimposed. Therefore, those modelled AA ratios for which the global warming trend was not significant according to non-parametric Mann-Kendall test 74 were neglected.

While different areal definitions for the Arctic exist, we use the area encircled by the Arctic Circle (66.5 ∘ –90 ∘ N) as the primary definition of the Arctic, because this is the area that most scientists consider the Arctic 75 , and it is one of the definitions used by AMAP 76 . The fifth assessment report (AR5) of the Intergovernmental Panel on Climate Change defined the Arctic as the region poleward from 67.5 ∘ N 77 , and AR6 used 67.7 ∘ N as the southern boundary 78 . For a sensitivity assessment, d T / d t A was also calculated using different definitions for the southern boundary of the Arctic, ranging from 55 ∘ N to 80 ∘ N (Fig.  2 a).

Comparison between simulated and observed Arctic amplification

We compare the simulated AA with observations using two approaches. In the first approach, we extract all possible AA 43 ratios for the 43-year periods starting from 1970 and ending by 2040 from all four climate model ensembles. Accordingly, there are 29 43-year periods in total, which are overlapping partly with each other (1970–2012, 1971–2013, ..., 1998–2040). The time window of 1970–2040 was chosen to avoid the nearly ice-free climate conditions later in the 21st century, the comparison of which with the currently-observed values would be meaningless. The starting year 1970 reflects approximately the time when the recent period of sustained global warming has started 79 . All possible 43-year time windows were considered because the internal climate variability in the models is not expected to be in phase with the real climate system. Using all realizations and the 29 different 43-year periods gives us an opportunity to assess in total 11020 simulated AA 43 ratios (29 periods x 380 realizations), with a sample of 1044 in CMIP5, 5626 in CMIP6, 2900 in MPI-GE, and 1450 in CanESM5. The probabilities are calculated as the number of simulated AA 43 equal to or greater than the observed AA 43 , divided by the total number of simulated AA 43 ratios. For the CMIP6 ensemble, the probability has been calculated first for each model separately, then taking the average across the models. This gives a weight of 1 for each model.

To further assess the robustness of our findings, we utilize an alternative statistical test employed earlier for global warming 80 and for sea ice trends 36 as a second approach. The details of the test are fully explained in the  Supplementary Methods . In the test, we compare the observed AA 43 in 1979–2021 to the values of AA 43 over the same period simulated by the climate models belonging to the four datasets. The null hypothesis of the test is that the observed and simulated AA ratios are equal, assuming that the models are exchangeable with each other. The differences between the observed and simulated AA ratios have p-values which tell the evidence against the null hypothesis. The smaller the p-value, the stronger is the evidence against the null hypothesis. We use p  = 0.05 as a threshold to reject the null hypothesis.

Data availability

The datafiles for producing the charts and graphs of this manuscript are deposited in the public repository of the Finnish Meteorological Institute at https://doi.org/10.23728/fmi-b2share.5d81ded56e984072a5f7162a18b60cb9 . Gistemp data are available from https://data.giss.nasa.gov/gistemp/ , Berkeley Earth data from http://berkeleyearth.org/data/ , HadCRUT5 data from https://www.metoffice.gov.uk/hadobs/hadcrut5/data/current/download.html , and ERA5 data from https://cds.climate.copernicus.eu . CMIP5 and CMIP6 data are available from Earth System Grid Federation (ESGF) archive at https://esgf-node.llnl.gov/projects/cmip5/ and https://esgf-data.dkrz.de/search/cmip6-dkrz/ , respectively. MPI-GE data is available under licence from https://mpimet.mpg.de/en/grand-ensemble/ .

Code availability

Python- and R-language scripts used for this analysis are available from Github: https://github.com/mikarant/arctic-amplification .

Serreze, M. C. & Francis, J. A. The Arctic amplification debate. Clim. Change 76 , 241–264 (2006).

Article   CAS   Google Scholar  

Serreze, M., Barrett, A., Stroeve, J., Kindig, D. & Holland, M. The emergence of surface-based Arctic amplification. Cryosphere 3 , 11 (2009).

Article   Google Scholar  

England, M. R., Eisenman, I., Lutsko, N. J. & Wagner, T. J. The recent emergence of Arctic Amplification. Geophys. Res. Lett. 48 , e2021GL094086 (2021).

Holland, M. M. & Bitz, C. M. Polar amplification of climate change in coupled models. Clim. Dyn. 21 , 221–232 (2003).

Park, H.-S., Kim, S.-J., Stewart, A. L., Son, S.-W. & Seo, K.-H. Mid-holocene Northern Hemisphere warming driven by Arctic amplification. Sci. Adv. 5 , eaax8203 (2019).

Screen, J. A. & Simmonds, I. The central role of diminishing sea ice in recent Arctic temperature amplification. Nature 464 , 1334–1337 (2010).

Thackeray, C. W. & Hall, A. An emergent constraint on future Arctic sea-ice albedo feedback. Nat. Clim. Change 9 , 972–978 (2019).

Dai, A., Luo, D., Song, M. & Liu, J. Arctic amplification is caused by sea-ice loss under increasing CO 2 . Nat. Commun. 10 , 1–13 (2019).

Jenkins, M. & Dai, A. The impact of sea-ice loss on arctic climate feedbacks and their role for Arctic amplification. Geophys. Res. Lett. 48 , e2021GL094599 (2021).

Pithan, F. & Mauritsen, T. Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nat. Geosci. 7 , 181–184 (2014).

Stuecker, M. F. et al. Polar amplification dominated by local forcing and feedbacks. Nat. Clim. Change 8 , 1076–1081 (2018).

Bintanja, R., Graversen, R. & Hazeleger, W. Arctic winter warming amplified by the thermal inversion and consequent low infrared cooling to space. Nat. Geosci. 4 , 758–761 (2011).

Taylor, P. C. et al. A decomposition of feedback contributions to polar warming amplification. J. Clim. 26 , 7023–7043 (2013).

Beer, E., Eisenman, I. & Wagner, T. J. Polar amplification due to enhanced heat flux across the halocline. Geophys. Res. Lett. 47 , e2019GL086706 (2020).

Graversen, R. G. & Burtu, M. Arctic amplification enhanced by latent energy transport of atmospheric planetary waves. Q. J. R. Meteorological Soc. 142 , 2046–2054 (2016).

Woods, C. & Caballero, R. The role of moist intrusions in winter Arctic warming and sea ice decline. J. Clim. 29 , 4473–4485 (2016).

Kim, B.-M. et al. Major cause of unprecedented Arctic warming in January 2016: Critical role of an Atlantic windstorm. Sci. Rep. 7 , 1–9 (2017).

CAS   Google Scholar  

Navarro, J. A. et al. Amplification of Arctic warming by past air pollution reductions in Europe. Nat. Geosci. 9 , 277–281 (2016).

Krishnan, S. et al. The roles of the atmosphere and ocean in driving Arctic warming due to European aerosol reductions. Geophys. Res. Lett. 47 , e2019GL086681 (2020).

Merikanto, J. et al. How asian aerosols impact regional surface temperatures across the globe. Atmos. Chem. Phys. 21 , 5865–5881 (2021).

Previdi, M., Janoski, T. P., Chiodo, G., Smith, K. L. & Polvani, L. M. Arctic amplification: A rapid response to radiative forcing. Geophys. Res. Lett. 47 , e2020GL089933 (2020).

Ono, J., Watanabe, M., Komuro, Y., Tatebe, H. & Abe, M. Enhanced Arctic warming amplification revealed in a low-emission scenario. Commun. Earth Environ. 3 , 1–9 (2022).

Yu, L., Zhong, S., Vihma, T. & Sun, B. Attribution of late summer early autumn Arctic sea ice decline in recent decades. npj Clim. Atmos. Sci. 4 , 3 (2021).

Walsh, J. E. Intensified warming of the Arctic: Causes and impacts on middle latitudes. Glob. Planet. Change 117 , 52–63 (2014).

Richter-Menge, J. & Druckenmiller, M. L. (eds.) The Arctic [In “State of the Climate in 2019“]. Bull. Am. Meteorological Soc. 101 , S239–S285 (2020).

Jansen, E. et al. Past perspectives on the present era of abrupt Arctic climate change. Nat. Clim. Change 10 , 714–721 (2020).

AMAP. Arctic climate change update 2021: key trends and impacts. Summary for policy-makers. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway (2021).

Davy, R., Chen, L. & Hanna, E. Arctic amplification metrics. Int. J. Climatol. 38 , 4384–4394 (2018).

Hind, A., Zhang, Q. & Brattström, G. Problems encountered when defining Arctic amplification as a ratio. Sci. Rep. 6 , 30469 (2016).

Davy, R. & Outten, S. The Arctic surface climate in CMIP6: status and developments since CMIP5. J. Clim. 33 , 8047–8068 (2020).

Cai, Z. et al. Arctic warming revealed by multiple CMIP6 models: evaluation of historical simulations and quantification of future projection uncertainties. J. Clim. 34 , 4871–4892 (2021).

Google Scholar  

Stroeve, J. C. et al. Trends in Arctic sea ice extent from CMIP5, CMIP3 and observations. Geophys. Res. Lett. 39 , L16502 (2012).

Notz, D. & Community, S. Arctic sea ice in CMIP6. Geophys. Res. Lett. 47 , e2019GL086749 (2020).

Rosenblum, E. & Eisenman, I. Sea ice trends in climate models only accurate in runs with biased global warming. J. Clim. 30 , 6265–6278 (2017).

Notz, D. & Stroeve, J. Observed Arctic sea-ice loss directly follows anthropogenic CO 2 emission. Science 354 , 747–750 (2016).

Swart, N. C., Fyfe, J. C., Hawkins, E., Kay, J. E. & Jahn, A. Influence of internal variability on Arctic sea-ice trends. Nat. Clim. Change 5 , 86–89 (2015).

Ding, Q. et al. Fingerprints of internal drivers of Arctic sea ice loss in observations and model simulations. Nat. Geosci. 12 , 28–33 (2019).

Cohen, J. et al. Divergent consensuses on Arctic amplification influence on midlatitude severe winter weather. Nat. Clim. Change 10 , 20–29 (2020).

Ye, K. & Messori, G. Inter-model spread in the wintertime Arctic amplification in the CMIP6 models and the important role of internal climate variability. Glob. Planet. Change 204 , 103543 (2021).

Previdi, M., Smith, K. L. & Polvani, L. M. Arctic amplification of climate change: a review of underlying mechanisms. Environ. Res. Lett. 16 , 093003 (2021).

Hahn, L. C., Armour, K. C., Zelinka, M. D., Bitz, C. M. & Donohoe, A. Contributions to polar amplification in CMIP5 and CMIP6 models. Front. Earth Sci. 725 , 710036 (2021).

Simmons, A. et al. Low frequency variability and trends in surface air temperature and humidity from ERA5 and other datasets, EMCWF Tech. Mem. 881, https://doi.org/10.21957/ly5vbtbfd (2021).

Bell, B. et al. The ERA5 global reanalysis: preliminary extension to 1950. Q. J. R. Meteorol. Soc. 147 , 4186–4227 (2021).

Isaksen, K. et al. Exceptional warming over the Barents area. Sci. Rep. 12 , 9371 (2022).

Onarheim, I. H. & Årthun, M. Toward an ice-free Barents sea. Geophys. Res. Lett. 44 , 8387–8395 (2017).

Wickström, S., Jonassen, M., Vihma, T. & Uotila, P. Trends in cyclones in the high-latitude North Atlantic during 1979–2016. Q. J. R. Meteorological Soc. 146 , 762–779 (2020).

Räisänen, J. Effect of atmospheric circulation on surface air temperature trends in years 1979–2018. Clim. Dyn. 56 , 2303–2320 (2021).

Huang, J. et al. Recently amplified arctic warming has contributed to a continual global warming trend. Nat. Clim. Change 7 , 875–879 (2017).

Hegerl, G. C. et al. Causes of climate change over the historical record. Environ. Res. Lett. 14 , 123006 (2019).

Screen, J. A., Deser, C. & Simmonds, I. Local and remote controls on observed Arctic warming. Geophys. Res. Lett. 39 (2012).

Maher, N., Milinski, S. & Ludwig, R. Large ensemble climate model simulations: introduction, overview, and future prospects for utilising multiple types of large ensemble. Earth Syst. Dyn. 12 , 401–418 (2021).

Suarez-Gutierrez, L., Milinski, S. & Maher, N. Exploiting large ensembles for a better yet simpler climate model evaluation. Clim. Dyn. 57 , 2557–2580 (2021).

Swart, N. C. et al. The Canadian Earth System Model version 5 (CanESM5.0.3). Geoscientific Model Dev. 12 , 4823–4873 (2019).

Rohde, R. A. & Hausfather, Z. The Berkeley Earth land/ocean temperature record. Earth Syst. Sci. Data 12 , 3469–3479 (2020).

Morice, C. P. et al. An Updated Assessment of Near-Surface Temperature Change From 1850: The HadCRUT5 Data Set. J. Geophys. Res.: Atmospheres 126 , e2019JD032361 (2021).

Graham, R. M., Hudson, S. R. & Maturilli, M. Improved Performance of ERA5 in Arctic Gateway Relative to Four Global Atmospheric Reanalyses. Geophys. Res. Lett. 46 , 6138–6147 (2019).

Medhaug, I., Stolpe, M. B., Fischer, E. M. & Knutti, R. Reconciling controversies about the global warming hiatus. Nature 545 , 41–47 (2017).

Mudelsee, M. Trend analysis of climate time series: A review of methods. Earth-Sci. Rev. 190 , 310–322 (2019).

Stolpe, M. B., Cowtan, K., Medhaug, I. & Knutti, R. Pacific variability reconciles observed and modelled global mean temperature increase since 1950. Clim. Dyn. 56 , 613–634 (2021).

Kravtsov, S. Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century. Geophys. Res. Lett. 44 , 5749–5757 (2017).

O’Reilly, C. H. et al. Projections of northern hemisphere extratropical climate underestimate internal variability and associated uncertainty. Commun. Earth Environ. 2 , 1–9 (2021).

Shaw, T. et al. Storm track processes and the opposing influences of climate change. Nat. Geosci. 9 , 656–664 (2016).

Peings, Y., Cattiaux, J. & Magnusdottir, G. The polar stratosphere as an arbiter of the projected tropical versus polar tug of war. Geophys. Res. Lett. 46 , 9261–9270 (2019).

Lenssen, N. J. et al. Improvements in the GISTEMP uncertainty model. J. Geophys. Res.: Atmospheres 124 , 6307–6326 (2019).

Titchner, H. A. & Rayner, N. A. The Met Office Hadley Centre sea ice and sea surface temperature data set, version 2: 1. Sea ice concentrations. J. Geophys. Res.: Atmospheres 119 , 2864–2889 (2014).

Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorological Soc. 146 , 1999–2049 (2020).

Menne, M. J., Williams, C. N., Gleason, B. E., Rennie, J. J. & Lawrimore, J. H. The global historical climatology network monthly temperature dataset, version 4. J. Clim. 31 , 9835–9854 (2018).

Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorological Soc. 93 , 485–498 (2012).

Eyring, V. et al. Overview of the coupled model intercomparison project phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9 , 1937–1958 (2016).

Maher, N. et al. The Max Planck Institute Grand Ensemble: enabling the exploration of climate system variability. J. Adv. Modeling Earth Syst. 11 , 2050–2069 (2019).

Cowtan, K. et al. Robust comparison of climate models with observations using blended land air and ocean sea surface temperatures. Geophys. Res. Lett. 42 , 6526–6534 (2015).

Smith, D. M. et al. The Polar Amplification Model Intercomparison project (PAMIP) contribution to CMIP6: Investigating the causes and consequences of polar amplification. Geoscientific Model Dev. 12 , 1139–1164 (2019).

Fujiwara, M. et al. Introduction to the SPARC Reanalysis Intercomparison Project (S-RIP) and overview of the reanalysis systems. Atmos. Chem. Phys. 17 , 1417–1452 (2017).

Hussain, M. & Mahmud, I. Pymannkendall: a python package for non parametric Mann Kendall family of trend tests. J. Open Source Softw. 4 , 1556 (2019).

NSIDC. What is the Arctic? https://nsidc.org/cryosphere/arctic-meteorology/arctic.html (2020). Accessed: 2021-02-04.

AMAP. AMAP Assessment 2009: Human Health in the Arctic. Arctic Monitoring and Assessment Programme (AMAP), Oslo, Norway (2009).

Collins, M. 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 , 1029–1136 (Cambridge University Press, 2013).

Lee, J.-Y. et al. Future global climate: Scenario-based projections and near-term information. In Climate change 2021: The physical science basis. Contribution of Working Group I to the sixth assessment report of the intergovernmental panel on climate change (eds. Masson-Delmotte, V. et al.) pp. 553–672 (Cambridge University Press, Cambridge, UK and New York, NY, USA, 2021).

Gulev, S. K. et al. Changing state of the climate system. In Climate change 2021: The Physical Science Basis. Contribution of Working Group I to the sixth assessment report of the intergovernmental panel on climate change (eds Masson-Delmotte, V. et al.) pp. 287–422 (Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2021).

Fyfe, J. C., Gillett, N. P. & Zwiers, F. W. Overestimated global warming over the past 20 years. Nat. Clim. Change 3 , 767–769 (2013).

Download references

Acknowledgements

This research has been supported by the ACCC Flagship funded by the Academy of Finland (decision no 337552). The work of MR was supported by the Academy of Finland (contract 342890). The work of TV was supported by the Academy of Finland (contract 317999) and the work of AK by the European Commission H2020 project Polar Regions in the Earth System (PolarRES, grant 101003590). CSC - IT Centre for Science, Finland, is acknowledged for computational resources, and Copernicus Climate Change Service is acknowledged for making ERA5 reanalysis available. We acknowledge the World Climate Research Programme, which is responsible for CMIP5 and CMIP6. We thank the climate modelling groups for making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP5, CMIP6, and ESGF. We thank Max Planck Institute for Meteorology for making MPI-GE publicly available.

Author information

Authors and affiliations.

Finnish Meteorological Institute, Helsinki, Finland

Mika Rantanen, Alexey Yu. Karpechko, Kalle Nordling, Otto Hyvärinen, Kimmo Ruosteenoja, Timo Vihma & Ari Laaksonen

Finnish Meteorological Institute, Kuopio, Finland

Antti Lipponen

CICERO Center for International Climate Research, Oslo, Norway

Kalle Nordling

Department of Applied Physics, University of Eastern Finland, Kuopio, Finland

Ari Laaksonen

You can also search for this author in PubMed   Google Scholar

Contributions

The study was initialized together by A.L.i., A.La., M.R., and K.N.. M.R. wrote the initial draft of the manuscript, conducted most of the data analysis and created the figures. A.K. contributed to the downloading climate model data and the initial preparation of the manuscript. K.N. and K.R. contributed to the downloading of CMIP model data, and O.H. calculated the uncertainty estimates of the results. T.V. and A.La. contributed to the commenting of the results and revising of the manuscript. All authors commented the manuscript and discussed the results at all stages.

Corresponding author

Correspondence to Mika Rantanen .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Peer review

Peer review information.

Communications Earth & Environment thanks Russell Blackport and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Viviane V. Menezes, Clare Davis, Heike Langenberg.  Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary information, peer review file, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Rantanen, M., Karpechko, A.Y., Lipponen, A. et al. The Arctic has warmed nearly four times faster than the globe since 1979. Commun Earth Environ 3 , 168 (2022). https://doi.org/10.1038/s43247-022-00498-3

Download citation

Received : 25 January 2022

Accepted : 11 July 2022

Published : 11 August 2022

DOI : https://doi.org/10.1038/s43247-022-00498-3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Role of atmospheric rivers in shaping long term arctic moisture variability.

• Zhibiao Wang
• Qinghua Ding

Nature Communications (2024)

Amplified warming of North American cold extremes linked to human-induced changes in temperature variability

• Russell Blackport
• John C. Fyfe

Paleoclimate data provide constraints on climate models' large-scale response to past CO2 changes

• Daniel J. Lunt
• Bette L. Otto-Bliesner

Communications Earth & Environment (2024)

Carbon and oxygen isotopes in mummified wood reveal warmer and wetter winters in the Siberian Arctic 3000 years ago

• Brian A. Schubert
• William E. Lukens
• A. Hope Jahren

Scientific Reports (2024)

Upland Yedoma taliks are an unpredicted source of atmospheric methane

• K. M. Walter Anthony

By submitting a comment you agree to abide by our Terms and Community Guidelines . If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.