Water Science and Engineering (Dec 2010)

Evaluation of high-resolution satellite precipitation products with surface rain gauge observations from Laohahe Basin in northern China

  • Shan-hu Jiang,
  • Li-liang Ren,
  • Bin Yong,
  • Xiao-li Yang,
  • Lin Shi

DOI
https://doi.org/10.3882/j.issn.1674-2370.2010.04.004
Journal volume & issue
Vol. 3, no. 4
pp. 405 – 417

Abstract

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Three high-resolution satellite precipitation products, the Tropical Rainfall Measuring Mission (TRMM) standard precipitation products 3B42V6 and 3B42RT and the Climate Precipitation Center's (CPC) morphing technique precipitation product (CMORPH), were evaluated against surface rain gauge observations from the Laohahe Basin in northern China. Widely used statistical validation indices and categorical statistics were adopted. The evaluations were performed at multiple time scales, ranging from daily to yearly, for the years from 2003 to 2008. The results show that all three satellite precipitation products perform very well in detecting the occurrence of precipitation events, but there are some different biases in the amount of precipitation. 3B42V6, which has a bias of 21%, fits best with the surface rain gauge observations at both daily and monthly scales, while the biases of 3B42RT and CMORPH, with values of 81% and 67%, respectively, are much higher than a normal receivable threshold. The quality of the satellite precipitation products also shows monthly and yearly variation: 3B42RT has a large positive bias in the cold season from September to April, while CMORPH has a large positive bias in the warm season from May to August, and they all attained their best values in 2006 (with 10%, 50%, and −5% biases for 3B42V6, 3B42RT, and CMORPH, respectively). Our evaluation shows that, for the Laohahe Basin, 3B42V6 has the best correspondence with the surface observations, and CMORPH performs much better than 3B42RT. The large errors of 3B42RT and CMORPH remind us of the need for new improvements to satellite precipitation retrieval algorithms or feasible bias adjusting methods.

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