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Machine Learning and PDEs to predict rainfall in Ghana

Work done at the FORMES research group under Dr. Yves Atchadé at Boston University, which has resulted in the following pre-print paper: https://arxiv.org/abs/2410.14062

References:

Bézenac, Emmanuel de, Arthur Pajot, and Patrick Gallinari. “Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge.” Journal of Statistical Mechanics: Theory and Experiment 2019, no. 12 (December 20, 2019): 124009. https://doi.org/10.1088/1742-5468/ab3195.

Copernicus Climate Change Service (C3S) (2017): ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate . Copernicus Climate Change Service Climate Data Store (CDS), May 2024. https://cds.climate.copernicus.eu/cdsapp#!/home

Vitart et al.,The Sub-seasonal to Seasonal (S2S) Prediction Project Database. Bull. Amer. Meteor. Soc., 98(1), 163-176. doi: http://dx.doi.org/10.1175/BAMS-D-16-0017.1.

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