Exploring the Best-Matching Precipitation Traits in Four Long-Term Mainstream Products over China from 1981 to 2020

نویسندگان

چکیده

As a major component of water cycle, the accuracy quantification different precipitation products is critical for evaluating climate change and ecosystem functions. However, lack evidence available to choose precise product in relative applications. Here, solve this limit, we analyze spatiotemporal pattern four products, including CHIRPS V2.0, PERSIANN-CDR, ECMWF ERA5-Land, GLDAS_NOAH025_3H, over China during period 1981–2020, based on five traits (i.e., spatial multi-year average, annual trend, seasonality, frequency, intensity), meteorological gauge observations are taken as benchmark. Our results show that, compared other data has strongest ability present average precipitation, especially most parts northeastern southern China, ERA5 weakest simulate precipitation. All can accurately depict among which have highest lowest fitting ability, respectively, but poorly describe intensity frequency at daily scale. These only correctly predict interannual trend some local areas. findings provide evidences select high-quality data, could help improve geophysical models.

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ژورنال

عنوان ژورنال: Remote Sensing

سال: 2023

ISSN: ['2315-4632', '2315-4675']

DOI: https://doi.org/10.3390/rs15133355