Evaluation of multi-satellite precipitation products in Xinjiang, China

Abstract

ABSTRACTSatellite precipitation retrieval is a critical approach to understanding the spatial distribution of precipitation in Xinjiang, an arid area located in Northwest China, where weather stations are sparsely distributed. However, satellite precipitation retrieval in arid areas is a challenging task. The goal of this study is to evaluate the estimates of four satellite precipitation products, namely, the Global Satellite Mapping of Precipitation (GSMaP), Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis 3B42 (3B42), and Climate Prediction Center Morphing Technique (CMORPH), on half-hourly, hourly, 3-hourly, and daily scales based on rain gauge data. The findings of this study are as follows. (1) The four products generally display a declining trend from northwest to southeast. IMERG exhibits a higher accuracy than CMORPH for all indexes at the half-hourly scale, while GSMaP performs better than other products based on most indexes at hourly and daily scales. (2) In three sub-regions, i.e. Southern Xinjiang (SX), Northern Xinjiang (NX) and the Tianshan Mountains (Tianshan), these products exhibit significant regional characteristics. The precipitation in SX, where rainfall observations are scarce, is overestimated by all products; in contrast, all products underestimate precipitation in Tianshan in NX, except for the underestimation by 3B42, precipitation was overestimated by the studied products. (3) All satellite products performed better in the warm season than in the cold season at each time scale. During the warm season, apart from the apparent overestimation by CMORPH, the relative bias values of the other products are all within ±10%. During the cold season, all products underestimate precipitation mainly composed of snowfall, especially 3B42, which yields the most underestimated values. (4) IMERG performs well in the retrieval of the distribution of the probability density function (PDF) of the occurrence (PDFc) of gauge observations, especially at low precipitation intensities, and the difference between the estimated and observed precipitation volumes at the hourly scale is the smallest. However, GSMaP performed better at the daily scale according to the PDF for the volume of precipitation (PDFv). This study is the first to evaluate IMERG and CMORPH products at the half-hourly scale and is one of the few sub-daily evaluations of various satellite precipitation products in arid areas of China. Thus, our results provide a significant reference for the satellite retrieval of precipitation in arid areas.