A New Perspective for Charactering the Spatio-temporal Patterns of Error in GPM IMERG over China Mainland in 2018

Abstract:

Precipitation is one of most important components of water cycle and Global Precipitation Measurement (GPM) Integrated Multi-satellitE Retrievals (IMERG) is the main current satellite-based global precipitation product by NASA. This study focuses on proposing a new perspective for charactering the spatio-temporal patterns of errors in GPM IMERG over China Mainland including quatitative hot cluster analusis and error featured region extraction. Besides evaluating IMERG data using China Merged Precipitation Analysis (CMPA) data during 2018 over China Mainland, we applied a quantitative cluster analysis method to analyze the characteristics of the errors in GPM IMERG based on three geographical factors including elevation (Ele), latitude (Lat) and the distance from seashore (DFS). In addition, the analysis on charactering the errors in GPM IMERG were conducted in both warm and cold seasons to capture the temporal error patterns. The results show that: (1) IMERG overall has the ability to capture spatio-temporal precipitation patterns over China Mainland, with relative overestimations; (2) geophysical factors (elevation, latitude and the distance of seashore) have strong linear relationships with the evaluation indexes on IMERG using CMPA data; and (3) the spatial patterns of errors in IMERG were automatically finalized, which have significant geographical characteristics. Results of this study would provide great potentials for improving the quality of the IMERG over the global land areas.