PECA-FY4A: Precipitation Estimation using Chromatographic Analysis methodology for full-disc multispectral observations from FengYun-4A/AGRI

Abstract

Near-real-time precipitation estimates based on geostationary meteorological satellites are of great importance for monitoring hydrology-related disasters. Currently, the contributions of multispectral infrared observations to precipitation estimation have not been fully understood thus far. Motivated by estimating precipitation based on real-time data from geostationary satellites, this study proposes the Precipitation Estimation using Chromatographic Analysis (PECA) methodology based on full-disc observations from Advanced Geosynchronous Radiation Imager (AGRI) of FengYun-4A (FY-4A). Compared with PERSIANN-CCS and FY4AQPE-Official, the results of PECA (PECA-FY4A) are comprehensively evaluated against the GSOD (global gauge data), CMS (Chinese gauge data) and IMERG-LR (micro-wave precipitation products) for the period from January, 2019 to November, 2021. The findings and conclusions mainly include but are not limited to the following: (1) PECA clearly reveals that T12, ∆T10−14, ∆T7−14, and ∆T7−8 are effective for estimating precipitation volumes, with strong correlation to precipitation volumes but significantly less redundant information. (2) IR band differences are still sensitive to heavy precipitation although the abilities of single IR bands have become insufficient. For example, ∆T7−8 are sensitive to heavy precipitation in the eye walls of the typhoons. (3) The evaluation results show that PERSIANN-CCS generally outperforms FY4AQPE-Official, while PECA-FY4A features significant improvements over PERSIANN-CCS (the international benchmark of IR precipitation products) in terms of CC (∼10%, ∼100%, and ∼ 21%), RMSE (∼20%, ∼36%, and ∼ 11%), and CSI (∼25%, ∼100%, and ∼ 12%) against IMERG-LR, CMS and GSOD, respectively. The findings are expected to considerably contribute towards extending the current three-geostationary-satellite-series network (GOES, Meteosat, and Himawari) in PERSIANN-CCS to a four-geostationary-satellite-series network (by adding FY-4A and FY-4B) using PECA with higher quality, especially over the Asia-Pacific areas.