Precipitation-Surface Temperature Relationship in the IPCC CMIP5 Models

Precipitation and surface temperature are two important quantities whose variations are closely related through various physical processes. In the present study, we evaluated the precipitation-surface temperature （P-T） relationship in 17 climate models involved in the Coupled Model Intercomparison P...

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Bibliographic Details
Published inAdvances in atmospheric sciences Vol. 30; no. 3; pp. 766 - 778
Main Author 吴仁广 陈洁鹏 温之平
Format Journal Article
LanguageEnglish
Published Heidelberg SP Science Press 01.05.2013
Springer Nature B.V
Institute of Space and Earth Information Science, The Chinese University of Hong Kong,Hong Kong%Center for Monsoon and Environment Research/Department of Atmospheric Sciences,Sun Yat-Sen University, Guangzhou 510275
Subjects
Assessments
Atmospheric models
Atmospheric Sciences
Climate
Climate models
Computer simulation
Correlation
Earth and Environmental Science
Earth Sciences
Geophysics/Geodesy
Intergovernmental Panel on Climate Change
Land
Latitude
Marine
Meteorology
Oceans
Precipitation
Seasons
Surface temperature
Temperature
Tropical environments
Tropics
中高纬度地区
大尺度特征
模拟分析
气候模型
相关分布
表面温度
评估报告
降水
seasonal dependence
precipitation-surface temperature relationship
CMIP5 models
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Summary:Precipitation and surface temperature are two important quantities whose variations are closely related through various physical processes. In the present study, we evaluated the precipitation-surface temperature （P-T） relationship in 17 climate models involved in the Coupled Model Intercomparison Project Phase 5 （CMIP5） for the IPCC Assessment Report version 5. Most models performed reasonably well at simulat- ing the large-scale features of the P-T correlation distribution. Based on the pattern correlation of the P-T correlation distribution, the models performed better in November-December-January-February-March （NDJFM） than in May-June-July-August-September （MJJAS） except for the mid-latitudes of the North- ern Hemisphere, and the performance was generally better over the land than over the ocean. Seasonal dependence was more obvious over the land than over the ocean and was more obvious over the mid- and high-latitudes than over the tropics. All of the models appear to have had difficulty capturing the P-T correlation distribution over the mid-latitudes of the Southern Hemisphere in MJJAS. The spatial variabil- ity of the P-T correlation in the models was overestimated compared to observations. This overestimation tended to be larger over the land than over the ocean and larger over the mid- and high-latitudes than over the tropics. Based on analyses of selected model ensemble simulations, the spread of the P-T correlation among the ensemble members appears to have been small. While the performance in the P-T correlation provides a general direction for future improvement of climate models, the specific reasons for the discrep- ancies between models and observations remain to be revealed with detailed and comprehensive evaluations in various aspects.
Bibliography:precipitation-surface temperature relationship, CMIP5 models, seasonal dependence
WU Renguang, CHEN Jiepeng, and WEN Zhiping
Precipitation and surface temperature are two important quantities whose variations are closely related through various physical processes. In the present study, we evaluated the precipitation-surface temperature （P-T） relationship in 17 climate models involved in the Coupled Model Intercomparison Project Phase 5 （CMIP5） for the IPCC Assessment Report version 5. Most models performed reasonably well at simulat- ing the large-scale features of the P-T correlation distribution. Based on the pattern correlation of the P-T correlation distribution, the models performed better in November-December-January-February-March （NDJFM） than in May-June-July-August-September （MJJAS） except for the mid-latitudes of the North- ern Hemisphere, and the performance was generally better over the land than over the ocean. Seasonal dependence was more obvious over the land than over the ocean and was more obvious over the mid- and high-latitudes than over the tropics. All of the models appear to have had difficulty capturing the P-T correlation distribution over the mid-latitudes of the Southern Hemisphere in MJJAS. The spatial variabil- ity of the P-T correlation in the models was overestimated compared to observations. This overestimation tended to be larger over the land than over the ocean and larger over the mid- and high-latitudes than over the tropics. Based on analyses of selected model ensemble simulations, the spread of the P-T correlation among the ensemble members appears to have been small. While the performance in the P-T correlation provides a general direction for future improvement of climate models, the specific reasons for the discrep- ancies between models and observations remain to be revealed with detailed and comprehensive evaluations in various aspects.
11-1925/O4
ObjectType-Article-1
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ISSN:0256-1530
1861-9533
DOI:10.1007/s00376-012-2130-8