AI for Climate Science |

Climate change is one of the most pressing global challenges, with human emissions now unanimously accepted as the key driver. However, significant scientific uncertainties remain regarding the Earth’s climate sensitivity, which directly translate into uncertainties in the remaining carbon budget on the path to achieving the targets of the Paris Agreement. Current advances in climate science are hindered by the limitations of the methodologies commonly used for scientific data analysis, some of them ill-equipped for capturing complex relationships present in the huge volumes of data now available. At the same time, the field of machine learning has seen a series of dramatic breakthroughs over the past decade, driven by the development of new data-intensive algorithms.

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