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Development and Assessment of the Monthly Grid Precipitation Datasets in China
Frontiers in Environmental Science ( IF 4.6 ) Pub Date : 2021-04-09 , DOI: 10.3389/fenvs.2021.656794
Jiadong Peng , Lijie Duan , Wenhui Xu , Qingxiang Li

Based on the high-quality homogenized precipitation data from all of the 2419 national weather stations in China, the climatology and the anomalies percentage fields are derived, then the Digital Elevation Model (DEM) is employed to reduce the influence of elevation on the spatial interpolation accuracy of precipitation due to the unique topography in China. Then, the gradient plus inverse distance squared (GIDS) method and the inverse distance squared method (IDS) method are used to grid the climatology field and the anomaly percentage field, respectively, and the 0.5° × 0.5° gridded data sets during 1961-2018 in China is obtained by combining them together. The evaluation shows that the mean absolute error (MAE) between the analysis value and the observation is 15.8 mm/month. The MAE in South China is generally higher than that in North China, and the MAE is obviously larger in summer than in other seasons. Specifically, 94.6%, 54.4%, 4.6% and 53.8% of the MAE are below 10 mm/month in winter (DJF), spring (MAM), summer (JJA) and autumn (SON), respectively, and 99.5%, 79.9%, 22.8% and 82.1% of them are less than 20 mm/month. The MAE over China in four seasons are 3.8 mm/month, 13.2 mm/month, 33.5 mm/month and 12.7 mm/month, respectively. This dataset has the potentials of broad application prospects in the evaluations of the weather and climate models and the satellite products.
更新日期:2021-04-09
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