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The Performance of CMIP6 Versus CMIP5 in Simulating Temperature Extremes Over the Global Land Surface
Journal of Geophysical Research: Atmospheres ( IF 3.8 ) Pub Date : 2020-09-11 , DOI: 10.1029/2020jd033031
Xuewei Fan 1 , Chiyuan Miao 1 , Qingyun Duan 1, 2 , Chenwei Shen 1 , Yi Wu 1
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Simulations from the models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6), which represent the most recent generation of climate models, are now available. Understanding the performance of these models in simulating historical climate extremes can provide a basis for producing reliable future climate projections. Here, we assess the simulation of 16 indices of temperature extremes defined by the Expert Team on Climate Change Detection and Indices using results from 24 CMIP6 models as compared with results from CMIP5. Comparisons with observations and reanalyses indicate that the CMIP6 models could capture the spatial patterns and temporal variations of the observed temperature extremes well for some indices, although less well for others. Based on spatial and temporal skill scores, CMIP6 ensemble means were more skillful in simulating absolute and threshold indices of extreme temperature than CMIP5 ensemble means were, but the performances of both the CMIP5 and CMIP6 ensemble means in simulating the spatial patterns for duration and percentile indices were relatively unsatisfactory (spatial skill scores S < 0.3). Furthermore, our results suggest that there have been improvements in spatial pattern skill scores in some individual CMIP6 models relative to CMIP5 model scores for summer days, tropical nights, cold spell duration, and diurnal temperature range.

中文翻译:

CMIP6和CMIP5在模拟全球陆地表面极端温度方面的性能

现在可以使用代表了最新一代气候模型的耦合模型比较项目(CMIP6)第六阶段的模型进行的模拟。了解这些模型在模拟历史极端气候条件下的性能可以为产生可靠的未来气候预测提供基础。在这里,我们使用24个CMIP6模型的结果与CMIP5的结果进行比较,评估了由气候变化检测和指数专家组定义的16个极端温度指数的模拟。与观察结果和再分析的比较表明,CMIP6模型可以很好地捕获某些指标观测到的极端温度的空间格局和时间变化,而对其他指标则不太好。根据时空技能得分,S  <0.3)。此外,我们的结果表明,相对于夏季,热带夜晚,寒冷季节持续时间和昼夜温度范围内的CMIP5模型得分,某些个体CMIP6模型的空间模式技能得分有所提高。
更新日期:2020-09-20
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