Theoretical and Applied Climatology

, Volume 132, Issue 1–2, pp 55–69 | Cite as

Uncertainty of global summer precipitation in the CMIP5 models: a comparison between high-resolution and low-resolution models

  • Danqing Huang
  • Peiwen Yan
  • Jian Zhu
  • Yaocun Zhang
  • Xueyuan Kuang
  • Jing Cheng
Original Paper


The uncertainty of global summer precipitation simulated by the 23 CMIP5 CGCMs and the possible impacts of model resolutions are investigated in this study. Large uncertainties exist over the tropical and subtropical regions, which can be mainly attributed to convective precipitation simulation. High-resolution models (HRMs) and low-resolution models (LRMs) are further investigated to demonstrate their different contributions to the uncertainties of the ensemble mean. It shows that the high-resolution model ensemble means (HMME) and low-resolution model ensemble mean (LMME) mitigate the biases between the MME and observation over most continents and oceans, respectively. The HMME simulates more precipitation than the LMME over most oceans, but less precipitation over some continents. The dominant precipitation category in the HRMs (LRMs) is the heavy precipitation (moderate precipitation) over the tropic regions. The combinations of convective and stratiform precipitation are also quite different: the HMME has much higher ratio of stratiform precipitation while the LMME has more convective precipitation. Finally, differences in precipitation between the HMME and LMME can be traced to their differences in the SST simulations via the local and remote air-sea interaction.



This study is jointly sponsored by the National Key Research and Development Program of China (Grant Nos. 2016YFA0602104, 2016YFA0600701, and 2016YFA0600504), the National Natural Science Foundation of China (Grant No. 41575071) and the Jiangsu Collaborative Innovation Center for Climate Change. We acknowledge the climate modeling groups (listed in Table 1) for making their model outputs available, and the World Climate Research Program’s (WCRP’s) Working Group on Coupled Modeling (WGCM) which coordinates the CMIP5 project.


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Copyright information

© Springer-Verlag Wien 2017

Authors and Affiliations

  • Danqing Huang
    • 1
  • Peiwen Yan
    • 1
  • Jian Zhu
    • 2
  • Yaocun Zhang
    • 1
  • Xueyuan Kuang
    • 1
  • Jing Cheng
    • 3
  1. 1.CMA-NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric SciencesNanjing UniversityNanjingChina
  2. 2.State Key Laboratory of Hydrology-Water Resources and Hydraulic EngineeringHohai UniversityNanjingChina
  3. 3.I.M. System Group, INC.RockvilleUSA

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