GPROF-IR is a CNN-based retrieval that uses temporal context in geostationary IR observations to produce precipitation estimates with lower error than prior IR methods and climatological consistency with PMW retrievals for integration into IMERG V08.
arXiv preprint arXiv:2409.07188 (2024)
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FuXi-TC combines the FuXi global DL model with a diffusion generative framework to downscale and improve TC intensity and precipitation forecasts, matching ECMWF skill while being faster and generalizing zero-shot to North Atlantic hurricanes.
citing papers explorer
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GPROF-IR: An Improved Single-Channel Infrared Precipitation Retrieval for Merged Satellite Precipitation Products
GPROF-IR is a CNN-based retrieval that uses temporal context in geostationary IR observations to produce precipitation estimates with lower error than prior IR methods and climatological consistency with PMW retrievals for integration into IMERG V08.
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FuXi-TC: A generative framework integrating deep learning and physics-based models for improved tropical cyclone forecasts
FuXi-TC combines the FuXi global DL model with a diffusion generative framework to downscale and improve TC intensity and precipitation forecasts, matching ECMWF skill while being faster and generalizing zero-shot to North Atlantic hurricanes.