Theoretical and Applied Climatology

, Volume 132, Issue 1–2, pp 621–637 | Cite as

Statistical evaluation of the performance of gridded monthly precipitation products from reanalysis data, satellite estimates, and merged analyses over China

  • Xueliang Deng
  • Suping Nie
  • Weitao Deng
  • Weihua Cao
Original Paper


In this study, we compared the following four different gridded monthly precipitation products: the National Centers for Environmental Prediction version 2 (NCEP-2) reanalysis data, the satellite-based Climate Prediction Center Morphing technique (CMORPH) data, the merged satellite-gauge Global Precipitation Climatology Project (GPCP) data, and the merged satellite-gauge-model data from the Beijing Climate Center Merged Estimation of Precipitation (BMEP). We evaluated the performances of these products using monthly precipitation observations spanning the period of January 2003 to December 2013 from a dense, national, rain gauge network in China. Our assessment involved several statistical techniques, including spatial pattern, temporal variation, bias, root-mean-square error (RMSE), and correlation coefficient (CC) analysis. The results show that NCEP-2, GPCP, and BMEP generally overestimate monthly precipitation at the national scale and CMORPH underestimates it. However, all of the datasets successfully characterized the northwest to southeast increase in the monthly precipitation over China. Because they include precipitation gauge information from the Global Telecommunication System (GTS) network, GPCP and BMEP have much smaller biases, lower RMSEs, and higher CCs than NCEP-2 and CMORPH. When the seasonal and regional variations are considered, NCEP-2 has a larger error over southern China during the summer. CMORPH poorly reproduces the magnitude of the precipitation over southeastern China and the temporal correlation over western and northwestern China during all seasons. BMEP has a lower RMSE and higher CC than GPCP over eastern and southern China, where the station network is dense. In contrast, BMEP has a lower CC than GPCP over western and northwestern China, where the gauge network is relatively sparse.



This work was jointly supported by the National Natural Science Foundation of China (Grant Nos. 41275076, 40905046, 41305057, and 41175086), the Beijing Natural Science Foundation (Grant No. 8144046), the Anhui Research Project in the Public Interest (Grant No. 1604f0804003), and the China Special Fund for Meteorological Research in the Public Interest (Grant No. GYHY201406039).


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Copyright information

© Springer-Verlag Wien 2017

Authors and Affiliations

  • Xueliang Deng
    • 1
  • Suping Nie
    • 2
  • Weitao Deng
    • 3
  • Weihua Cao
    • 4
  1. 1.Key Laboratory of Atmospheric Science and Satellite Remote SensingAnhui Institute of MeteorologyHefeiChina
  2. 2.National Climate CenterChina Meteorological AdministrationBeijingChina
  3. 3.Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science and TechnologyNanjingChina
  4. 4.Institute of Urban MeteorologyChina Meteorological AdministrationBeijingChina

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