Object-Based Comparison of Data-Driven and Physics-Driven Satellite Estimates of Extreme Rainfall.

ABSTRACT: The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conv

SUBMITTER: Li Z 

PROVIDER: S-EPMC8216224 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature