An Assessment on Geographically Weighted Regression-Based Merging Method of Satellite and Gauge Rainfall

Abstract:

Satellite-derived and gauge rainfall data are incompatible spatial data. Although great efforts have been devoted to their combination recently, it is still a complicated issue to be addressed. In this study, the performance of merging satellite and gauge rainfall analyses is examined over a humid region in Southeast China. Using satellite rainfall from TRMM 3B43V7 and ground rain gauge measurements, a geographically weighted regression (GWR) based statistical merging algorithm was proposed to continuously produce monthly rainfall fields at 1-km resolution during the period 2003-2009. Results indicate that the benefits of this rainfall merging approach were remarkable only when the gauge density is lower than one gauge per 1,500 km², suggesting the information provided by TRMM 3B43V7 is more useful for estimating rainfall fields when the ground measurements are rather sparse.

• Periodical: Applied Mechanics and Materials (Volumes 641-642)
• Pages: 19-24
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.641-642.19
• Online since: September 2014
• Authors: Qing Fang Hu*, Zhe Li, Yin Tang Wang, Yan Li Liu, Ting Ting Cui
• Keywords: Geographically Weighted Regression, Rain Gauge, Rainfall Merging, TRMM 3B43V7

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