Assessment of evolving TRMM-based multisatellite real-time precipitation estimation methods and their impacts on hydrologic prediction in a high latitude basin

Assessment of evolving TRMM-based multisatellite real-time precipitation estimation methods and their impacts on hydrologic prediction in a high latitude basin
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基于 TRMM 的多卫星实时降水估算方法的发展及其对高纬度盆地水文预测的影响评估

DOI:
10.1029/2011jd017069
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发表时间:
2012-05
影响因子:
--
通讯作者:
Khan, Sadiq I.
Khan, Sadiq I.
中科院分区:
--
文献类型:
--
作者:
Yong, Bin;Hong, Yang;Ren, Li-Liang;Gourley, Jonathan J.;Huffman, George J.;Chen, Xi;Wang, Wen;Khan, Sadiq I.

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卫星降水估算的真实的实时可用性为水文学家提供了一个机会,以提高当前大中型流域的水文预测能力。由于新的卫星数据的可用性和降水算法的升级,热带降雨测量使命(TRMM)多卫星降水分析真实的时间估计(TMPA-RT)在过去十年中经历了几次重要的修订。在这项研究中,TMPA-RT估计的相对精度和水文潜力的变化,在其三个主要的演变时期进行了评估和相互比较,在日常,每月和季节尺度在中国高纬度老哈河流域。评估结果显示,TMPA-RT在2005年2月3日之后,在降水估算和径流模拟方面的性能得到了显著改善。在冬季几个月的高估是值得注意的和一致的,这是建议的被动微波反演的积雪干扰的后果。从2008年10月1日开始至今,TMPA-RT新版本6的降水估计与独立的仪器观测具有更高的相关性,并且与以前的时期相比,在检测降水方面表现更好,尽管它具有更大的平均误差和相对偏差。经过简单的偏差校正后,TMPA-RT的最新数据集在三个测试期内表现出最佳的水文响应捕获能力。总之,这项研究表明,在三个算法升级期间,TMPA‐RT在水文径流模拟中的应用潜力越来越大,但在冬季降雪事件中仍然存在重大挑战。
The real‐time availability of satellite‐derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis real‐time estimates (TMPA‐RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA‐RT estimates over its three major evolving periods were evaluated and inter‐compared at daily, monthly and seasonal scales in the high‐latitude Laohahe basin in China. Assessment results show that the performance of TMPA‐RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA‐RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest data set of TMPA‐RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA‐RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.
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