show index hide index
The period between 2011 and 2020 was marked by global temperatures 1.1°C higher than the pre-industrial era, primarily due to massive emissions of greenhouse gases, such as carbon dioxide. While current policies could lead us to a 3°C warming by 2100, innovations in artificial intelligence reveal an even more alarming scenario. In 2024, leading researchers used advanced machine learning techniques to refine climate forecasts, identifying earlier and more regional temperature increases. The models demonstrate that many regions will exceed critical warming thresholds well before previously anticipated. It is therefore essential to leverage the capabilities of AI to refine climate models and guide informed policy decisions. Recent climate projections using artificial intelligence technologies reveal a far more worrying climate future than that described by the IPCC. Using advanced techniques, researchers warn that many warming thresholds will be crossed sooner than expected, thus highlighting the need for immediate and concerted global action. Understanding the IPCC Climate ProjectionsThe Intergovernmental Panel on Climate Change (IPCC), in its 2021 report, had already emphasized the dangerous progression of global warming. Based on data observed up to 2019-2020, it predicted a 1.1°C increase in global temperatures since the pre-industrial period. This estimate, while alarming, is lower than the new projections obtained by researchers from various universities worldwide using AI.The Limitations of Traditional IPCC Approaches The traditional climate models used by the IPCC were based on past trends and available historical observations. However, these methods have their limitations and can underestimate certain local and regional dynamics. For example, current climate policies could lead us toward a scenario of
+3°C warming by 2100. The Revolutionary Role of Artificial Intelligence The combination ofartificial intelligence (AI) with climate modeling has made it possible to refine forecasts with unprecedented regional
accuracy. In 2024, climate scientists from Colorado State University, Stanford University, and ETH Zurich used
transfer learning techniques to analyze data from ten different climate models. Grimer forecasts at the regional levelThe results obtained by these researchers are alarming: of the 46 regions studied, 34 will exceed 1.5°C of warming as early as 2040, and 26 will reach warming of more than 3°C by 2060. These thresholds are predicted earlier than in previous IPCC studies. AI has thus revealed crucial regional disparities and challenges that require immediate and specific attention.
Implications for policy decisions
Research conducted using AI reinforces the need to revise current climate strategies. By highlighting the importance of a regional approach, these technological advances allow policymakers to better understand the specific challenges of each region. As the researchers point out, « At this scale, climate change is more uncertain, but innovative techniques can help us finally provide forecasts and inform policy decisions. »
