Volume 9 Issue 2
Apr.  2016
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Article Navigation >  Water Science and Engineering  > 2016  >  9(2): 87-96
Shan-hu Jiang, Meng Zhou, Li-liang Ren, Xue-rong Cheng, Peng-ju Zhang. 2016: Evaluation of latest TMPA and CMORPH satellite precipitation products for Yellow River Basin. Water Science and Engineering, 9(2): 87-96. doi: 10.1016/j.wse.2016.06.002
Citation: Shan-hu Jiang, Meng Zhou, Li-liang Ren, Xue-rong Cheng, Peng-ju Zhang. 2016: Evaluation of latest TMPA and CMORPH satellite precipitation products for Yellow River Basin. Water Science and Engineering, 9(2): 87-96. doi: 10.1016/j.wse.2016.06.002
shu

Evaluation of latest TMPA and CMORPH satellite precipitation products for Yellow River Basin

doi: 10.1016/j.wse.2016.06.002

  • a State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, PR China

  • b College of Hydrology and Water Resources, Hohai University, Nanjing 210098, PR China

Funds:  This work was supported by the Programme of Introducing Talents of Discipline to Universities (the 111 Project, Grant No. B08048), the National Natural Science Foundation of China (Grant No. 41501017), and the Natural Science Foundation of Jiangsu Province (Grant No. BK20150815).
More Information
  • Corresponding author: Li-liang Ren
  • Received Date: 2015-09-28
  • Rev Recd Date: 2016-03-17
    Abstract
  • The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products (TMPA 3B42RT, CMORPH, TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products (3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions, respectively, and CMORPH performs better than 3B42RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement (GPM) data in the future.

     

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