AI Model Links Global Warming to Daily Rainfall Changes
Scientists have created a deep-learning AI model that reveals how global warming is influencing daily rainfall patterns worldwide. The study, published in Nature, demonstrates that human-induced climate change is making daily precipitation more variable and extreme.
The team, comprising researchers from GEOMAR, the Christian-Albrechts-University in Kiel, and other institutions, developed the deepseek model to analyze daily precipitation patterns. Traditional methods often miss the subtle changes in data, but this deep-learning approach captures the nuances.
The deepseek model predicts the annual global mean temperature (AGMT) based on daily precipitation maps, establishing a clear link to global warming. It shows that since 2015, daily rainfall has deviated from natural variability by at least 50% of the time due to rising temperatures. This indicates that global warming is indeed changing daily weather, leading to more variable conditions and increased occurrences of extreme wet and dry periods.
The deepseek model, developed by an international team of scientists, offers a powerful tool for predicting the effects of global warming on daily precipitation. It could potentially aid in implementing policy measures to mitigate the impacts of climate change, helping us adapt to a warming world.
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