利用星规合并降水定量化面平均降水的研究

B. Hieu
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引用次数: 0

摘要

卫星降水产品(GSMaP-MVK)可以可靠地估计基于“样本设计方法”(Esdd)的区域平均降水误差,从而缓解数据稀疏的问题,特别是在测量差的流域。此外,卫星与雨量计合并降水将显著减小卫星雨量估算值与雨量计数据之间的震级差距。本文研究了利用GSMaP-MVK和局地密集雨量计数据,采用偏置减少方法对星规合并降水进行AMP评价的能力。主要发现是,结合密集雨量计测量的卫星测量混合数据显示,使用Esdd指数评估AMP的能力比原始的卫星降水估计更好。然而,当混合雨量器数量不够多时,星表混合降水的Esdd量化性能不如原始的单星降水产品GSMaP-MVK。关键词:面平均降水;遥感降水产品;satellite-gauge合并;降雨径流模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study on quantification of areal mean precipitation using satellite-gauge merging precipitation
Satellite based precipitation product (GSMaP-MVK) can be reliably used to estimate the Areal Mean Precipitation error based on “Sample Design method” (Esdd) with the effort to mitigate the problem of sparse data, especially severe in poorly gauged river basins. In addition, the satellite-gauge merging precipitation would reduce significantly the magnitude gaps between the satellite rainfall estimations and the rain gauge data. In this study, the capability of satellite-gauge merging precipitation using GSMaP-MVK and local dense rain gauge data with bias reduction approach to evaluate the AMP is investigated. The main finding is that satellite-gauge blending data which incorporates a dense rain gauge measurements shows the better capability to evaluate AMP using Esdd index than the original satellite only precipitation estimations. However, Esdd quantification performances of satellite-gauge blending precipitation are inferior to the original satellite only precipitation product GSMaP-MVK when the number of blended rain gauges is not large enough. Keywords: areal mean precipitation; remote sensed precipitation product; satellite-gauge merging; rainfall runoff simulations.
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