An Improved Convolutional Neural Network for Bias Correction of Satellite Precipitation Products: Demonstration in Complex Terrain Regions Over Taiwan (opens in new tab)

Errors in passive microwave (PMW)-based precipitation retrievals from spaceborne sensors are often propagated into downstream global blended satellite precipitation products (SPPs), such as the NOAA Climate Prediction Center (CPC) morphing technique (CMORPH) and NASA’s global precipitation measurement (GPM) Integrated MultisatellitE retrievals for GPM (IMERG). To mitigate these errors, bias-correction techniques are typically applied as a postprocessing step during the derivation of SPPs. How...