Estimating precipitation errors using spaceborne surface soil moisture retrievals

被引：31
|
作者：
Crow, W. T. [1 ]
Bolten, J. D. [1 ]
机构：
[1] ARS, Hydrol & Remote Sensing Lab, USDA, Beltsville, MD 20705 USA
来源：
GEOPHYSICAL RESEARCH LETTERS | 2007年 / 34卷 / 08期
关键词：
D O I：
10.1029/2007GL029450
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Limitations in the availability of ground-based rain gauge data currently hamper our ability to quantify errors in global precipitation products over data-poor areas of the world. Over land, these limitations may be eased by approaches based on interpreting the degree of dynamic consistency existing between precipitation estimates and remotely-sensed surface soil moisture retrievals. This paper demonstrates how such an approach can be implemented using a Kalman filter tuning procedure to reliably estimate daily rainfall errors in global precipitation products without reliance on ground-based rainfall observations.
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页数：5
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