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Evaluation of multi-source precipitation products over the Yangtze River Basin
Atmospheric Research ( IF 5.5 ) Pub Date : 2021-02-01 , DOI: 10.1016/j.atmosres.2020.105287
Wei Wang , Hui Lin , Nengcheng Chen , Zeqiang Chen

Abstract Precipitation products are good choices to complement ground observations in hydrological research, but their accuracy is uncertain in different areas. This study aims to evaluate the systematic error characteristics of four major precipitation products, namely, Climate Prediction Center MORPHing technique(CMORPH), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), Global Land Data Assimilation System (GLDAS), and Tropical Rainfall Measuring Mission(TRMM) 3B42 v7, over the Yangtze River Basin in terms of estimating precipitation amounts and detecting events. The results show that the precipitation products have high spatial and seasonal heterogeneity of error characteristics, and the capability to capture rain occurrence decreases when rainfall intensity increases. GLDAS demonstrated the poorest performance, with the lowest correlation of 0.08 and the largest relative bias of over 25% underestimation. The possibility of GLDAS missing medium and heavy rains (>15 mm/d) reached 50%, and of falsely reporting light rainfall was up to 40%, while CMORPH outperformed the others with the highest consistency (0.39) against the gauge, the smallest root-mean-square error (RMSE) (10.28 mm), and the highest scores for most subregions. Generally, in this study GLDAS proved its inferiority to satellite-based precipitation products for hydrological applications over the Yangtze River Basin.

中文翻译:

长江流域多源降水产品评价

摘要 降水产品是水文研究中补充地面观测的良好选择,但其准确性在不同领域存在不确定性。本研究旨在评估四种主要降水产品的系统误差特征,即气候预测中心 MORPHing 技术(CMORPH)、气候危害组站站红外降水(CHIRPS)、全球陆地数据同化系统(GLDAS)和热带降雨测量。 Mission(TRMM) 3B42 v7,在估计降水量和检测事件方面在长江流域上空。结果表明,降水产品具有较高的空间和季节异质性误差特征,随着降雨强度的增加,对降雨发生的捕捉能力降低。GLDAS 表现最差,0.08 的最低相关性和超过 25% 低估的最大相对偏差。GLDAS漏报中、大雨(>15mm/d)的可能性达到50%,误报小雨的可能性高达40%,而CMORPH的表现优于其他的,相对于仪表的一致性最高(0.39),最小均方根误差 (RMSE)(10.28 毫米),并且在大多数子区域中得分最高。总的来说,在这项研究中,GLDAS 证明了其在长江流域水文应用中不如卫星降水产品。而 CMORPH 的表现优于其他标准,具有最高的一致性 (0.39),最小的均方根误差 (RMSE) (10.28 mm),以及大多数子区域的最高分。总的来说,在这项研究中,GLDAS 证明了其在长江流域水文应用中不如卫星降水产品。而 CMORPH 的表现优于其他标准,具有最高的一致性 (0.39),最小的均方根误差 (RMSE) (10.28 mm),以及大多数子区域的最高分。总的来说,在这项研究中,GLDAS 证明了其在长江流域水文应用中不如卫星降水产品。
更新日期:2021-02-01
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