4.7 Article

Extreme Precipitation Indices over China in CMIP5 Models. Part I: Model Evaluation

Journal

JOURNAL OF CLIMATE
Volume 28, Issue 21, Pages 8603-8619

Publisher

AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-15-0099.1

Keywords

Geographic location; entity; Asia; Atm; Ocean Structure; Phenomena; Extreme events; Physical Meteorology and Climatology; Climate change; Models and modeling; Model evaluation; performance; Variability; Interannual variability

Funding

  1. State Key Program of National Natural Science Foundation of China [41230528]
  2. National Basic Research Program 973 [2012CB955204]
  3. Special Research Program for Public Welfare (Meteorology) of China [GYHY201306024]
  4. Research and Innovation Project for College Graduates of Jiangsu Province [KYLX_0843]
  5. Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions

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Compared to precipitation extremes calculated from a high-resolution daily observational dataset in China during 1960-2005, simulations in 31 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) have been quantitatively assessed using skill-score metrics. Four extreme precipitation indices, including the total precipitation (PRCPTOT), maximum consecutive dry days (CDD), precipitation intensity (SDII), and fraction of total rainfall from heavy events (R95T) are analyzed. Results show that CMIP5 models still have wet biases in western and northern China. Especially in western China, the models' median relative error is about 120% for PRCPTOT; the 25th and 75th percentile errors are of 70% and 220%, respectively. However, there are dry biases in southeastern China, where the underestimation of PRCPTOT reach 200 mm. The performance of CMIP5 models is quite different between western and eastern China. The simulations are more reliable in the east than in the west in terms of spatial pattern and interannual variability. In the east, precipitation indices are more consistent with observations, and the spread among models is smaller. The multimodel ensemble constructed from a selection of the most skillful models shows improved behavior compared to the all-model ensemble. The wet bias in western and northern China and dry bias over southeastern China are all decreased. The median of errors for PRCPTOT has a decrease of 69% and 17% in the west and east, respectively. The good reproduction of the southwesterlies along the east coast of the Arabian Peninsula is revealed to be the main factor explaining the improvement of precipitation patterns and extreme events.

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