DOI: 10.1002/2015JD024540
论文题名: Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile
作者: Yang Z. ; Hsu K. ; Sorooshian S. ; Xu X. ; Braithwaite D. ; Verbist K.M.J.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2016
卷: 121, 期: 8 起始页码: 3790
结束页码: 3806
语种: 英语
英文关键词: bias adjustment
; Chile
; Gaussian weighting interpolation
; nonparametric quantile mapping
; satellite-based precipitation estimation
Scopus关键词: interpolation
; mapping method
; observational method
; precipitation assessment
; sampling bias
; satellite data
; Chile
英文摘要: Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009-2014. The historical data (satellite and gauge) for 2009-2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide. ©2016. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62921
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: College of Water Sciences, Key Laboratory of Water and Sediment Sciences, Ministry of Education, Beijing Normal University, Beijing, China; Department of Civil and Environmental Engineering, University of California, Irvine, CA, United States; UNESCO-IHP, Hydrological Systems and Global Change Section, Santiago, Chile; International Centre for Eremology, Department of Soil Management, Ghent University, Ghent, Belgium
Recommended Citation:
Yang Z.,Hsu K.,Sorooshian S.,et al. Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile[J]. Journal of Geophysical Research: Atmospheres,2016-01-01,121(8)