Representativeness of Two Global Gridded Precipitation Data Sets in the Intensity of Surface Short-Term Precipitation over China

Abstract

This study evaluates the representativeness of two widely used next-generation global satellite precipitation estimates data for short-term precipitation over China, namely the satellite data from the Climate Prediction Center morphing (CMORPH) and the satellite data from the Global Precipitation Measurement (GPM) mission. These two satellite precipitation data sets were compared with the hourly liquid in-situ precipitation from China national surface stations from 2016 to 2020. The results showed that the GPM precipitation data has better representativeness of surface short-term precipitation than that of the CMORPH data, and these two quantitative precipitation estimate (QPE) data sets underestimated extreme precipitation. Moreover, we analyzed the influence of the error between two QPE data sets and the in-situ precipitation on the classification of short-term precipitation intensity. China uses 8.1–16 mm/h as the definition of heavy precipitation, but the accuracy of the satellite QPE product was different due to the different lowest threshold of heavy rain (more than 8.1 mm/h or more than 16 mm/h). Increasing the threshold value of the QPE data for short-term strong precipitation resulted in lower accuracy for detecting such events, but higher accuracy for detecting moderate intensity rainfall. When studying short-term strong precipitation over China using precipitation grade, selecting an appropriate threshold was important to ensure accurate judgments. Additionally, it is important to account for errors caused by QPE data, which can significantly affect the accuracy of precipitation grading.

Evaluating the Performance and Applicability of Satellite Precipitation Products over the Rio Grande–San Juan Basin in Northeast Mexico

“…The ranking of errors, mostly between 10 and 100 mm, is consistent in this study following previous monthly analyses [2,17,56]. However, these are deemed insignificant, as the monthly precipitation average is at least 300 mm.…”

“…Some studies suggest CMORPH is the best product over mountainous regions with tropical weather. On the other hand, IMERG has obtained good correlation and performance over arid and semiarid regions but has problems over mountainous regions [2,[16][17][18][19].…”