王予,李惠心,王会军,孙博,陈活泼. 2021. CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较[J]. 气象学报, (0):-, doi:10.11676/qxxb2021.031
CMIP6全球气候模式对中国极端降水模拟能力的评估及其与CMIP5的比较
Evaluation of CMIP6 for Extreme Precipitation in China and Its Comparison with CMIP5
投稿时间:2020-12-26  修订日期:2021-02-20
DOI:10.11676/qxxb2021.031
中文关键词:  CMIP6,CMIP5,极端降水,模拟评估
英文关键词:CMIP6, CMIP5, Extreme precipitation, Model evaluation
基金项目:国家自然科学基金(42005015;42088101;41991283);江苏省自然科学基金资助项目(SBK2020040311);江苏省高等学校自然科学研究面上项目(20KJB170001)
作者单位邮编
王予 南京信息工程大学 气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心 210044
李惠心 南京信息工程大学 气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心 210044
王会军 南京信息工程大学 气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心 210044
孙博 南京信息工程大学 气象灾害教育部重点实验室/气象灾害预报预警与评估协同创新中心 210044
陈活泼 竺可桢-南森国际研究中心中国科学院大气物理研究所 100029
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中文摘要:
      基于CN05.1观测数据集,本文对32个CMIP6全球气候模式在中国地区极端降水的模拟能力进行评估。研究结果表明,在极端降水的气候平均态方面,CMIP6多模式集合对1961—2005年中国地区区域平均的8个极端降水指数模拟的平均相对误差为29.94%,相较于CMIP5减少2.95%。在极端降水的气候变率方面,CMIP6多模式集合对区域平均的8个极端降水指数模拟的平均相对误差为10.10%,相较于CMIP5减小5.45%。此外,利用TS评分进行模式间比较时,CMIP6的平均分(0.78)高于CMIP5(0.75),且模拟能力排名前五的模式中CMIP6占四个。对比14个同源模式的TS评分可以发现,CMIP6(0.91分)相对于CMIP5(0.68分)的模拟能力显著提高。进一步研究发现,CMIP6相对于CMIP5对不同区域极端降水模拟能力的改进有所区别:CMIP6对干旱区区域平均的气候态和变率方面改进明显,而关于湿润区的改进主要表现在对极端降水空间相关模拟能力的提高。
英文摘要:
      Based on the 32 global climate models in phase 6 of the Coupled Model Intercomparison Project (CMIP6), 27 global climate models in CMIP5, and the observational dataset CN05.1, this study evaluates the performances of CMIP6 and CMIP5 in simulating extreme precipitation index over China during 1961—2005. Eight extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) are applied to represent extreme precipitation events. Results indicate that the multi-model ensemble (MME) median of CMIP6 has overall lower relative errors in China for both climatological mean (with an average of 29.94%, reduced by 2.95%) and relative variability (with an average of 10.10%, reduced by 5.45%), compared with those of CMIP5. Generally, CMIP6 performs better than CMIP5 in simulating the climatological condition, especially over the arid region (reduced by 12.15% when compared with CMIP5). Further analyses suggest that the MME median of CMIP6 has large spatial correlation coefficients and small root-mean-square errors. Based on the Taylor skill (TS) score, the models in both CMIP6 and CMIP5 are ranked to evaluate the relative model performances. The models in CMIP6 have higher ranks than those in CMIP5, with an averaged TS score of 0.78 (0.75) for CMIP6 (CMIP5), and four out of the five highest-scored models are from CMIP6 models. When it comes to the homologous models, the TS scores from CMIP6 (an average of 0.91) are larger than their earlier versions in CMIP5 (an average of 0.68), suggesting a prominent improvement in CMIP6. Further analyses indicate that the performances of CMIP6 differ when simulating extreme precipitation in different regions over China.
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