Accuracy and spatio-temporal variation of high resolution satellite rainfall estimate over the Ganjiang River Basin

被引:0
作者
QingFang Hu
DaWen Yang
YinTang Wang
HanBo Yang
机构
[1] Tsinghua University,Department of Hydraulic Engineering
[2] Nanjing Hydraulic Research Institute,State Key Laboratory of Hydrology
来源
Science China Technological Sciences | 2013年 / 56卷
关键词
satellite rainfall estimate; accuracy evaluation; spatio-temporal variations; TRMM; CMORPH; GSMaP; PERSIANN; Ganjiang River Basin;
D O I
暂无
中图分类号
学科分类号
摘要
Based on spatial interpolation rainfall of the ground gauge measurement, we proposed a method to comprehensively evaluate and compare the accuracy of satellite rainfall estimates (SREs) at three spatial scales: 0.25°×0.25° grid scale, sub-catchment scale and the whole basin scale. Using this method, we evaluated the accuracy of six high-resolution monthly SREs (TRMM 3B42 V6, 3B42RT V6, CMORPH, GSMaP MWR+, GSMaP MVK+ and PERSIANN) and revealed the spatio-temporal variation of the SRE accuracy based on spatial interpolated rainfall from a dense network of 325 gauges during 2003–2009 over the Ganjiang River Basin in the Southeast China. The results showed that ground gauge-calibrated 3B42 had the highest accuracy with slight overestimation, whereas the other five uncalibrated SREs had severe underestimation. The accuracy of the six SREs in wet seasons was remarkably higher than that in the dry seasons. When the time scale was expanded, the accuracy of SRE, particularly 3B42, increased. Furthermore, the accuracy of SREs was relatively low in the western mountains and northern piedmont areas, while it was relatively high in the central and southeastern hills and basins of the Ganjiang River Basin. When the space scale was expanded, the accuracy of the six SREs gradually increased. This study provided an example for of SRE accuracy validation in other regions, and a direct basis for further study of SRE-based hydrological process.
引用
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页码:853 / 865
页数:12
相关论文
共 52 条
  • [1] Liu Y(2011)Satellite retrieval of precipitation: An overview Adv Earth Sci 2611 1162-1172
  • [2] Fu Q(2007)The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales J Hydrometeorol 8 38-55
  • [3] Song P(2004)CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution J Hydrometeorol 5 487-503
  • [4] Huffman G J(2009)Verification of high-resolution satellite-based rainfall estimates around Japan using a gauge-calibrated ground-radar dataset J Meteorol Soc Jpn 87 203-222
  • [5] Bolvin D T(2011)Accuracy validation of trmm 3b43 data in lancang river basin Acta Geographica Sinica 66 994-1004
  • [6] Nelkin E J(2010)Evaluating TRMM multi-satellite precipitation analysis using gauge precipitation and MODIS snow-cover products Adv Water Sci 21 343-348
  • [7] Joyce R J(2010)Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China Water Sci Eng 3 405-417
  • [8] Janowiak J E(2009)Study on watershed hydrologic processes using TRMM satellite precipitation radar products Adv Water Sci 20 461-466
  • [9] Arkin P A(2011)A new procedure to estimate the rainfall erosivity factor based on Tropical Rainfall Measuring Mission (TRMM) data Sci China Tech Sci 54 2437-2445
  • [10] Kubota T(2011)Evaluation of satellite rainfall estimates over Ethiopian river basins Hydrol Earth Syst Sci 15 1505-1514