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

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