AI Predicts Faster Global Warming, Surpassing Critical Thresholds

Limiting global warming to 1.5°C is 'almost certainly' out of reach - Earth.com

Researchers have recently concluded that the global goal of limiting warming to 1.5 degrees Celsius above pre-industrial levels is now almost certainly out of reach. This stark finding suggests that the years ahead will almost inevitably break existing heat records - no matter how quickly greenhouse gas emissions decline. The study, published in the journal Geophysical Research Letters, indicates a 50% chance that even if humanity achieves current targets for rapidly reducing greenhouse gas emissions to net-zero by the 2050s, global warming could breach two degrees Celsius above pre-industrial levels. Previous research, including assessments by the Intergovernmental Panel on Climate Change, had concluded that such decarbonization would likely keep warming below two degrees. Noah Diffenbaugh, a climate scientist at the Stanford Doerr School of Sustainability, co-authored the study with Colorado State University climate scientist Elizabeth Barnes. "We've been seeing accelerating impacts around the world in recent years, from heatwaves and heavy rainfall and other extremes," said Diffenbaugh. "This study suggests that, even in the best case scenario, we are very likely to experience conditions that are more severe than what we've been dealing with recently." The new findings emphasize the speed at which the world is moving past critical warming goals. This year stands poised to surpass 2023 as Earth's hottest year on record, with global average temperatures set to exceed 1.5 degrees Celsius (nearly 2.7 degrees Fahrenheit) above pre-industrial levels. According to the study, there is a nine-in-ten chance that the hottest year this century will be at least half a degree Celsius hotter - even if the world manages rapid decarbonization. These alarming projections underscore that surpassing the 1.5-degree threshold is no longer a question of "if" but "when." The significance is profound, given that this limit was a central target of the 2015 Paris Agreement, where nearly 200 nations pledged to keep warming "well below" two degrees while striving for 1.5 degrees. The study aligns with a growing body of evidence indicating that the 1.5-degree benchmark will be crossed, shifting the conversation toward how much hotter the planet will become. For this research, Diffenbaugh and Barnes employed an innovative approach: they trained an AI system to forecast global temperatures under various emissions scenarios. The AI integrated temperature and greenhouse gas data from extensive climate model simulations and real historical temperatures. Armed with these inputs, it provided more refined projections than previously possible. "AI is emerging as an incredibly powerful tool for reducing uncertainty in future projections. It learns from the many climate model simulations that already exist, but its predictions are then further refined by real-world observations," said Barnes, a professor of atmospheric science at Colorado State. This technique reduces uncertainty and hones in on more precise outcomes. By improving accuracy, policymakers gain a clearer understanding of the future they face, potentially guiding more informed decisions about mitigation and adaptation strategies. A second paper by Barnes, Diffenbaugh, and co-author Sonia Seneviratne from ETH-Zurich suggests that many regions - including South Asia, the Mediterranean, Central Europe, and parts of sub-Saharan Africa - will surpass three degrees Celsius of warming by 2060 under scenarios of increasing emissions. The study, published in the journal Environmental Research Letters, notes that this warming may come sooner than previous models anticipated, indicating that some parts of the world face rapidly intensifying climate conditions. The significance of surpassing such thresholds is immense. The consequences of even minor increases in temperature can cascade into extreme weather events, crop failures, water shortages, and heightened risks to human health and infrastructure. Both new studies build on earlier research by Diffenbaugh and Barnes that anticipated the timeline until warming goals are breached. However, rather than focusing solely on multi-year averages, the team shifted attention to the most extreme years and conditions. This perspective offers a glimpse into a future where temperatures and weather events are more volatile and challenging than the current average conditions can convey. "As we watched these severe impacts year after year, we became more and more interested in predicting how extreme the climate could get even if the world is fully successful at rapidly reducing emissions," said Diffenbaugh. This approach acknowledges that even meeting emissions targets may fail to shield humanity from extremes surpassing what we now experience. For a scenario in which emissions are cut rapidly and reach net-zero in the 2050s - the most optimistic widely modeled scenario - there is a nine-in-ten chance that the hottest year this century will be at least 1.8 degrees Celsius hotter than pre-industrial times. Moreover, there is a two-in-three chance it will be at least 2.1 degrees hotter. If emissions remain too high to reach net-zero by 2100, a nine-in-ten chance emerges that the hottest year will be three degrees Celsius hotter. Under such circumstances, many regions could experience anomalies at least triple what occurred in 2023. The projections highlight that even with robust decarbonization, the world must brace for greater extremes. Historically, climate policy and investment have prioritized mitigation - reducing carbon emissions - over adaptation, which focuses on reducing vulnerability to climate impacts. Decarbonization spending outpaces adaptation investments worldwide, as seen in policies like the 2022 Inflation Reduction Act in the United States. "Our results suggest that even if all the effort and investment in decarbonization is as successful as possible, there is a real risk that, without commensurate investments in adaptation, people and ecosystems will be exposed to climate conditions that are much more extreme than what they are currently prepared for," Diffenbaugh warned. Adapting to these changed conditions will be essential. Without measures to increase resilience - such as improved infrastructure, healthcare systems prepared for heat-related illnesses, agriculture tailored to new climate realities, and water resources managed to handle drought or flood - societies risk severe disruptions. As the planet warms and thresholds are surpassed, scientists and policymakers alike must grapple with uncertainty. The research reveals a persistent gap between decarbonization goals and the severity of future extremes. Meanwhile, the AI-driven approach to refine climate projections may become a cornerstone of climate modeling, offering a more accurate and immediate window into what lies ahead. The new knowledge that even optimistic emission scenarios may not prevent severe climate extremes underscores the importance of immediate and comprehensive action. Ensuring that investments in both mitigation and adaptation proceed in tandem could help protect human communities, ecosystems, and the global economy from the worst consequences of an increasingly warming world. -- - Like what you read? Subscribe to our newsletter for engaging articles, exclusive content, and the latest updates.

AI predicts Earth's peak warming

Researchers have found that the global goal of limiting warming to 1.5 degrees Celsius above pre-industrial levels is now almost certainly out of reach. The results, published Dec. 10 in Geophysical Research Letters, suggest the hottest years ahead will very likely shatter existing heat records. There is a 50% chance, the authors reported, that global warming will breach 2 degrees Celsius even if humanity meets current goals of rapidly reducing greenhouse gas emissions to net-zero by the 2050s. A number of previous studies, including the authoritative assessments by the Intergovernmental Panel on Climate Change, have concluded that decarbonization at this pace would likely keep global warming below 2 degrees. "We've been seeing accelerating impacts around the world in recent years, from heatwaves and heavy rainfall and other extremes. This study suggests that, even in the best case scenario, we are very likely to experience conditions that are more severe than what we've been dealing with recently," said Stanford Doerr School of Sustainability climate scientist Noah Diffenbaugh, who co-authored the study with Colorado State University climate scientist Elizabeth Barnes. This year is set to beat 2023 as Earth's hottest year on record, with global average temperatures expected to exceed 1.5 degrees Celsius or nearly 2.7 degrees Fahrenheit above the pre-industrial baseline, before people started burning fossil fuels widely to power industry. According to the new study, there is a nine-in-ten chance that the hottest year this century will be at least half a degree Celsius hotter even under rapid decarbonization. Using AI to refine climate projections For the new study, Diffenbaugh and Barnes trained an AI system to predict how high global temperatures could climb, depending on the pace of decarbonization. When training the AI, the researchers used temperature and greenhouse gas data from vast archives of climate model simulations. To predict future warming, however, they gave the AI the actual historical temperatures as input, along with several widely used scenarios for future greenhouse gas emissions. "AI is emerging as an incredibly powerful tool for reducing uncertainty in future projections. It learns from the many climate model simulations that already exist, but its predictions are then further refined by real-world observations," said Barnes, who is a professor of atmospheric science at Colorado State. The study adds to a growing body of research indicating that the world has almost certainly missed its chance to achieve the more ambitious goal of the 2015 Paris Climate Agreement, in which nearly 200 nations pledged to keep long-term warming "well below" 2 degrees while pursuing efforts to avoid 1.5 degrees. A second new paper from Barnes and Diffenbaugh, published Dec. 10 in Environmental Research Letterswith co-author Sonia Seneviratne of ETH-Zurich, suggests many regions including South Asia, the Mediterranean, Central Europe, and parts of sub-Saharan Africa will surpass 3 degrees Celsius of warming by 2060 in a scenario in which emissions continue to increase -- sooner than anticipated in earlier studies. Extremes matter Both new studies build on 2023 research in which Diffenbaugh and Barnes predicted the years remaining until the 1.5 and 2 degrees Celsius goals are breached. But because these thresholds are based on average conditions over many years, they don't tell the full story of how extreme the climate could become. "As we watched these severe impacts year after year, we became more and more interested in predicting how extreme the climate could get even if the world is fully successful at rapidly reducing emissions," said Diffenbaugh, the Kara J Foundation Professor and Kimmelman Family Senior Fellow at Stanford. For a scenario in which emissions reach net-zero in the 2050s -- the most optimistic scenario widely used in climate modeling -- the researchers found a nine-in-ten chance that the hottest year this century will be at least 1.8 degrees Celsius hotter globally than the pre-industrial baseline, with a two-in-three chance for at least 2.1 degrees Celsius. For a scenario in which emissions decline too slowly to reach net-zero by 2100, Diffenbaugh and Barnes found a nine-in-ten chance that the hottest year will be 3 degrees Celsius hotter globally than the pre-industrial baseline. In this scenario, many regions could experience temperature anomalies at least triple what occurred in 2023. Investing in adaptation The new predictions underline the importance of investing not only in decarbonization but also in measures to make human and natural systems more resilient to severe heat, intensified drought, heavy precipitation, and other consequences of continued warming. Historically, those efforts have taken a back seat to reducing carbon emissions, with decarbonization investments outstripping adaptation spending in global climate finance and policies such as the 2022 Inflation Reduction Act. "Our results suggest that even if all the effort and investment in decarbonization is as successful as possible, there is a real risk that, without commensurate investments in adaptation, people and ecosystems will be exposed to climate conditions that are much more extreme than what they are currently prepared for," Diffenbaugh said.

AI predicts Earth's peak warming

This year is set to beat 2023 as Earth's hottest year on record, with global average temperatures expected to exceed 1.5 degrees Celsius or nearly 2.7 degrees Fahrenheit above the pre-industrial baseline, before people started burning fossil fuels widely to power industry. According to the new study, there is a nine-in-10 chance that the hottest year this century will be at least half a degree Celsius hotter even under rapid decarbonization. For the new study, Diffenbaugh and Barnes trained an AI system to predict how high global temperatures could climb, depending on the pace of decarbonization. When training the AI, the researchers used temperature and greenhouse gas data from vast archives of climate model simulations. To predict future warming, however, they gave the AI the actual historical temperatures as input, along with several widely used scenarios for future greenhouse gas emissions. "AI is emerging as an incredibly powerful tool for reducing uncertainty in future projections. It learns from the many climate model simulations that already exist, but its predictions are then further refined by real-world observations," said Barnes, who is a professor of atmospheric science at Colorado State. The study adds to a growing body of research indicating that the world has almost certainly missed its chance to achieve the more ambitious goal of the 2015 Paris Climate Agreement, in which nearly 200 nations pledged to keep long-term warming "well below" 2 degrees while pursuing efforts to avoid 1.5 degrees. A second new paper from Barnes and Diffenbaugh, published Dec. 10 in Environmental Research Letters with co-author Sonia Seneviratne of ETH-Zurich, suggests many regions including South Asia, the Mediterranean, Central Europe, and parts of sub-Saharan Africa will surpass 3 degrees Celsius of warming by 2060 in a scenario in which emissions continue to increase - sooner than anticipated in earlier studies. Both new studies build on 2023 research in which Diffenbaugh and Barnes predicted the years remaining until the 1.5 and 2 degrees Celsius goals are breached. But because these thresholds are based on average conditions over many years, they don't tell the full story of how extreme the climate could become. "As we watched these severe impacts year after year, we became more and more interested in predicting how extreme the climate could get even if the world is fully successful at rapidly reducing emissions," said Diffenbaugh, the Kara J Foundation Professor and Kimmelman Family Senior Fellow at Stanford. For a scenario in which emissions reach net zero in the 2050s - the most optimistic scenario widely used in climate modeling - the researchers found a nine-in-ten chance that the hottest year this century will be at least 1.8 degrees Celsius hotter globally than the pre-industrial baseline, with a two-in-three chance for at least 2.1 degrees Celsius. For a scenario in which emissions decline too slowly to reach net zero by 2100, Diffenbaugh and Barnes found a nine-in-10 chance that the hottest year will be 3 degrees Celsius hotter globally than the pre-industrial baseline. In this scenario, many regions could experience temperature anomalies at least triple what occurred in 2023. The new predictions underline the importance of investing not only in decarbonization but also in measures to make human and natural systems more resilient to severe heat, intensified drought, heavy precipitation, and other consequences of continued warming. Historically, those efforts have taken a back seat to reducing carbon emissions, with decarbonization investments outstripping adaptation spending in global climate finance and policies such as the 2022 Inflation Reduction Act. "Our results suggest that even if all the effort and investment in decarbonization is as successful as possible, there is a real risk that, without commensurate investments in adaptation, people and ecosystems will be exposed to climate conditions that are much more extreme than what they are currently prepared for," Diffenbaugh said.

AI Model Indicates Global Temperatures Will Rise Faster Than Expected

Ten climate models and a machine learning approach offer an alarming new timeline for the rate of climate change. Combined insights from 10 models of the worldwide climate suggest that temperatures are rising faster than previously expected. The alarming finding, published today in Environmental Research Letters, indicates that most land regions assessed by the Intergovernmental Panel on Climate Change (IPCC) will surpass the 2.7 degrees Fahrenheit (1.5 degrees Celsius) threshold above pre-industrial temperatures. The researchers worked with an artificially intelligent system known as a convolutional neural network. Neural networks process and interpret information in a way inspired by the human brain. Convolutional neural networks are different from artificial neural networks in that they preserve spatial and temporal relationships in the data, and are very good at solving problems related to image recognition. The research team trained a convolutional neural network on each of the 43 regions defined by the IPCC. The models were thus trained to predict future temperature changes based on region, rather than on a global scale, providing a more localized and equally weighted vision of shifts in the climate. The team also added a step of transfer learning, which fine-tuned the trained neural network with observational data that made the model's predictions more realistic. Transfer learning was possible with data from 34 of the IPCC regions. “It is important to focus not only on global temperature increases but also on specific changes happening in local and regional areas," said Noah Diffenaugh, a climate scientist at Stanford University and co-author of the research, in a university release. "By constraining when regional warming thresholds will be reached, we can more clearly anticipate the timing of specific impacts on society and ecosystems." "The challenge is that regional climate change can be more uncertain," Diffenbaugh added, "both because the climate system is inherently more noisy at smaller spatial scales and because processes in the atmosphere, ocean and land surface create uncertainty about exactly how a given region will respond to global-scale warming.†The team predicted temperature increases at multiple temperature thresholds: the 2.7 degrees Fahrenheit (1.5 degrees Celsius) mark, 3.6 degrees Fahrenheit (2 degrees C), and 5.4 degrees Fahrenheit (3 degrees C). The group found that 34 regions are likely to exceed the first threshold by 2040â€"which sounds relatively far away until you realize how short 16 years can be. Of those 34 regions, the team found that 31 are expected to reach the second warming threshold by 2040, and 26 of them will surpass the third threshold by 2060. “Our research underscores the importance of incorporating innovative AI techniques like transfer learning into climate modelling to potentially improve and constrain regional forecasts and provide actionable insights for policymakers, scientists, and communities worldwide," said Elizabeth Barnes, a climate scientist at Colorado State University and lead author of the study, in the same release. Diffenbaugh and Barnes also published results in Geophysical Research Letters today indicating a 50/50 chance that global warming will still exceed 3.6° Fahrenheit (2 degrees Celsius) even if humankind meets its goals of curtailing greenhouse gas emissions to net-zero in the next 30-odd years. Unfortunately (shocking the first time that word is used in this article), when Earth's climate is bent too far out of whack, certain changes are irreversible. Global temperature rises can cause "dangerous and cascading effects," according to NASA, including heat stress to Earth's denizens, including humans. The recent team's study uses a new approach to confirm the hazards of climate change, courtesy of new, AI-fueled projections.

AI predicts that most of the world will see temperatures rise to 3°C much faster than previously expected

Three leading climate scientists have combined insights from 10 global climate models and, with the help of artificial intelligence (AI), conclude that regional warming thresholds are likely to be reached faster than previously estimated. The study, published in Environmental Research Letters, projects that most land regions as defined by the Intergovernmental Panel on Climate Change (IPCC) will likely surpass the critical 1.5°C threshold by 2040 or earlier. Similarly, several regions are on track to exceed the 3.0°C threshold by 2060 -- sooner than anticipated in earlier studies. Regions including South Asia, the Mediterranean, Central Europe and parts of sub-Saharan Africa are expected to reach these thresholds faster, compounding risks for vulnerable ecosystems and communities. The research, conducted by Elizabeth Barnes, professor at Colorado State University, Noah Diffenbaugh, professor at Stanford University, and Sonia Seneviratne, professor at the ETH-Zurich, used a cutting-edge AI transfer-learning approach, which integrates knowledge from multiple climate models and observations to refine previous estimates and deliver more accurate regional predictions. Key findings Using AI-based transfer learning, the researchers analyzed data from 10 different climate models to predict temperature increases and found: Elizabeth Barnes says, "Our research underscores the importance of incorporating innovative AI techniques like transfer learning into climate modeling to potentially improve and constrain regional forecasts and provide actionable insights for policymakers, scientists, and communities worldwide." Noah Diffenbaugh, co-author and professor at Stanford University, added, "It is important to focus not only on global temperature increases but also on specific changes happening in local and regional areas. By constraining when regional warming thresholds will be reached, we can more clearly anticipate the timing of specific impacts on society and ecosystems. "The challenge is that regional climate change can be more uncertain, both because the climate system is inherently more noisy at smaller spatial scales and because processes in the atmosphere, ocean and land surface create uncertainty about exactly how a given region will respond to global-scale warming."

AI predicts that most of the world will see temperatures rise to 3°C much faster than previously expected

Three leading climate scientists have combined insights from 10 global climate models and, with the help of artificial intelligence (AI), conclude that regional warming thresholds are likely to be reached faster than previously estimated. The study, published in Environmental Research Letters by IOP Publishing, projects that most land regions as defined by the Intergovernmental Panel on Climate Change (IPCC) will likely surpass the critical 1.5°C threshold by 2040 or earlier. Similarly, several regions are on track to exceed the 3.0°C threshold by 2060 -- sooner than anticipated in earlier studies. Regions including South Asia, the Mediterranean, Central Europe and parts of sub-Saharan Africa are expected to reach these thresholds faster, compounding risks for vulnerable ecosystems and communities. The research, conducted by Elizabeth Barnes, professor at Colorado State University, Noah Diffenbaugh, professor at Stanford University, and Sonia Seneviratne, professor at the ETH-Zurich, used a cutting-edge AI transfer-learning approach, which integrates knowledge from multiple climate models and observations to refine previous estimates and deliver more accurate regional predictions. Key Findings Using AI-based transfer learning, the researchers analysed data from 10 different climate models to predict temperature increases and found: Elizabeth Barnes says: "Our research underscores the importance of incorporating innovative AI techniques like transfer learning into climate modelling to potentially improve and constrain regional forecasts and provide actionable insights for policymakers, scientists, and communities worldwide." Noah Diffenbaugh, co-author and professor at Stanford University, added: "It is important to focus not only on global temperature increases but also on specific changes happening in local and regional areas. By constraining when regional warming thresholds will be reached, we can more clearly anticipate the timing of specific impacts on society and ecosystems. The challenge is that regional climate change can be more uncertain, both because the climate system is inherently more noisy at smaller spatial scales and because processes in the atmosphere, ocean and land surface create uncertainty about exactly how a given region will respond to global-scale warming."