期刊
JOURNAL OF HYDROLOGY
卷 605, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.jhydrol.2021.127353
关键词
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资金
- National Natural Science Foundation of China [41901343]
- Key R&D Program of Ministry of Science and Technology, China [2018YFC1506500]
- China Postdoctoral Science Foundation [2018M630037, 2019T120021]
- Open Grants of the State Key Laboratory of Severe Weather [2021LASW-B12]
- Research on Key Technologies of Early Warning and Forecast using Satellite-based and Ground-based Spatio-temporal data [RB2003]
- Open Fund of the State Key Laboratory of Remote Sensing Science, China [OFSLRSS201909]
- State Key Laboratory of Resources and Environmental Information System, China
- Research and development of real-time monitoring of water quality of large areas based on remote sensing technology [20190365]
- Guizhou Provincial Science and Technology Plan Project [[2020] 1Y155]
The study found that satellite-based precipitation products generally outperform model-based products, but the latter perform better in high-latitude regions and winter. ERA5 and ERA5-Land show similar spatio-temporal patterns and have their own advantages. Satellite products perform best in subregions of subtropical and tropical monsoon climate.
Accurate precipitation retrievals with fine spatio-temporal resolutions are critical in global and regional analyses. As an important alternative of satellite-based precipitation products, model-based precipitation estimates have undergone rapid development over the past few decades. With the recent public release of the fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts (ERA5) and ERA5-Land, it is necessary to verify whether these two latest model-based precipitation products outperform satellite-based precipitation products. This study comprehensively evaluates the performances of state-of-the-art satellite-based and model-based precipitation products, including the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG), Global Satellite Mapping of Precipitation (GSMaP), ERA5, and ERA5-Land, over mainland China from 2016 to 2019. The main findings are as follows: (1) Satellite-based products generally outperform model-based products, but the latter significantly perform better than the former over high-latitude regions and in winter. (2) ERA5 and ERA5-Land share similar spatio-temporal patterns and have their own advantages in terms of different types of metrics. (3) Satellite-based products perform best over subregions of subtropical and tropical monsoon climate (ST), whereas model-based products show highest performance over subregions of temperate monsoon climate (TM) and temperate continental climate (TC); both types of products show the poorest performance over subregions of plateau mountain climate (PM). (4) IMERG-Final performs best in terms of precipitation events, while GSMaP-Gauge tends to overestimate the duration of precipitation events, and model-based products tend to underestimate the mean precipitation rate of the events. These findings provide valuable insights into the error characteristics of state-of-the-art model-based and satellite-based precipitation products in the recent years, and will also serve as useful reference for the potential improvement of precipitation retrieval algorithms in the next generation.
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