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Generative Modeling of High-resolution Global Precipitation Forecasts. (arXiv:2210.12504v1 [cs.LG])
Oct. 25, 2022, 1:12 a.m. | James Duncan, Shashank Subramanian, Peter Harrington
cs.LG updates on arXiv.org arxiv.org
Forecasting global precipitation patterns and, in particular, extreme
precipitation events is of critical importance to preparing for and adapting to
climate change. Making accurate high-resolution precipitation forecasts using
traditional physical models remains a major challenge in operational weather
forecasting as they incur substantial computational costs and struggle to
achieve sufficient forecast skill. Recently, deep-learning-based models have
shown great promise in closing the gap with numerical weather prediction (NWP)
models in terms of precipitation forecast skill, opening up exciting new
avenues …
More from arxiv.org / cs.LG updates on arXiv.org
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