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Using a Kalman Filter to Assimilate TRMM-Based Real-Time Satellite Precipitation Estimates over Jinghe Basin, China

机译:利用卡尔曼滤波器对基于TRMM的Jing河盆地实时卫星降水估计进行同化

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摘要

In this study, efforts are focused on the comparison and validation of standard Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products—Version-7 3B42RT estimates before and after assimilation by using a Kalman filter with independent rain gauge networks located within the Jinghe basin of China. Generally, the direct comparison of TMPA precipitation estimates to 200 collocated rain gauges from 2006 to 2008 demonstrate that the spatial and temporal rainfall characteristics over the region are well captured by the assimilation estimates. Especially, results also show that using Kalman filter to assimilate TRMM-based multi-satellite real-time precipitation estimates tends to perform well over regions, where gauge network is rather sparse. Last, this study highlights that accurate detection and estimation of precipitation in the summer season by Kalman filter, particularly for nonlinear convective precipitation events, is still a challenging task for the future development of assimilation technique for improving the satellite-based precipitation accuracy.
机译:在这项研究中,我们的工作重点是比较和验证标准的热带雨量测量任务(TRMM)多卫星降水分析(TMPA)产品-版本7 3B42RT估算的同化前后,方法是使用位于内部的独立雨量计网络的卡尔曼滤波器中国的he河盆地。通常,将2006年至2008年TMPA降水估算与200个并置的雨量计进行直接比较,结果表明,同化估算很好地反映了该地区的时空降雨特征。尤其是,结果还表明,使用卡尔曼滤波器来吸收基于TRMM的多卫星实时降水量估计值往往在仪表网络较为稀疏的区域表现良好。最后,这项研究强调,利用卡尔曼滤波器对夏季降水进行准确的检测和估算,特别是对于非线性对流降水事件,仍然是未来发展同化技术以提高卫星降水精度的一项艰巨任务。

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