FY4QPE-MSA: An All-Day Near-Real-Time Quantitative Precipitation Estimation Framework Based on Multispectral Analysis From AGRI Onboard Chinese FY-4 Series Satellites

Accurate and near-real-time rain information at fine scales is critical for forecasting local weather and floods. Traditional classical infrared (IR) cloud-top brightness temperature data alone do not contain sufficient precipitation-related information, and the introduction of visible (VIS) observations limits their applications to daytime. Methods for the efficient and comprehensive utilization of multichannel IR observations for accurately retrieving all-day near-real-time rain rates with consistent high quality warrant further exploration. In this study, we propose an all-day near-real-time quantitative precipitation estimation framework based on multispectral analysis (MSA) from the Advanced Geosynchronous Radiation Imager (AGRI) onboard Chinese FY-4 series satellites; the proposed framework is called FY4QPE-MSA. Multiple IR bands are comprehensively and efficiently considered by adopting the principal component analysis technique to reduce the dimensionality to a few independent features while preserving most of the variations. The main conclusions include, but are not limited to, the following aspects: 1) the MSA from IR channels provides valuable information that facilitates the more accurate delineations of the precipitation occurrences; 2) FY4AQPE-MSA outperforms FY4AQPE-Offical [similar to 20% gain in the Pearson correlation coefficient (CC), similar to 25% gain in the root mean square error (RMSE), and similar to 15% gain in the critical success index (CSI)], FY4AQPE-Single (similar to 10% gain in CC, similar to 15% gain in RMSE, and similar to 15% gain in CSI), and Precipitation Estimation from Remotely Sensed Information using artificial neural network-cloud classification system (PERSIANN-CCS) (similar to 30% gain in CC, similar to 20% gain in RMSE, and similar to 25% gain in CSI); and 3) compared with the international IR-based baseline precipitation product, i.e., PERSIANN-CCS, FY4AQPE-MSA demonstrates no spatial gaps over the Tibetan Plateau. In addition, the results of this study suggest that the proposed general framework is promising and applicable for Chinese FY-4 series satellites in generating all-day near-real-time rain-rate information.