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IPCC第六次气候变化评估中的气候约束预估方法
引用本文:周佰铨,翟盘茂.IPCC第六次气候变化评估中的气候约束预估方法[J].气象学报,2021,79(6):1063-1070.
作者姓名:周佰铨  翟盘茂
作者单位:中国气象科学研究院灾害天气国家重点实验室,北京,100081
基金项目:国家重点研发计划项目(2018YFC1507700)、国家自然科学基金项目(41905082)
摘    要:得益于第五次评估报告(AR5)以来约束预估研究的迅速发展,观测约束成为政府间气候变化专门委员会(IPCC)第一工作组(WGI)第六次评估报告(AR6)提升对未来预估约束的证据链中的重要一环。IPCC第一工作组第六次评估报告首次利用包括根据历史模拟温度升高幅度得到的观测约束、多模式预估以及第六次评估报告中更新的气候敏感度在内的多条证据链来约束全球地表温度未来变化的预估,减小了多模式预估的不确定性。文中回顾并介绍了IPCC第一工作组第六次评估报告中涉及的几种主要观测约束方法(多模式加权方法、基于归因结论的约束方法(ASK方法)、萌现约束方法)及其应用情况。在IPCC第一工作组第六次评估报告以及很多针对不同区域不同变量的预估研究中,观测约束方法均显示出了订正模式误差、改善模式预估的潜力。相比而言,目前中国在观测约束预估方面的研究还不多,亟待加强观测约束方法研究以及在中国区域气候变化预估中的应用,为中国应对气候变化的政策制定和适应规划提供更丰富、不确定性更小的未来气候信息。 

关 键 词:气候预估    观测约束    多模式加权    ASK方法    萌现约束
收稿时间:2021/9/13 0:00:00
修稿时间:2021/10/22 0:00:00

The constraint methods for projection in the IPCC Sixth Assessment Report on climate change
ZHOU Baiquan,ZHAI Panmao.The constraint methods for projection in the IPCC Sixth Assessment Report on climate change[J].Acta Meteorologica Sinica,2021,79(6):1063-1070.
Authors:ZHOU Baiquan  ZHAI Panmao
Institution:State Key Laboratory of Severe Weather,Chinese Academy of Meteorological Sciences,China Meteorological Administration,Beijing 100081,China
Abstract:With the rapid development since the Fifth Assessment Report (AR5), observational constraints have become an important part of the lines of evidence used in the Sixth Assessment Report (AR6) of Intergovernmental Panel on Climate Change (IPCC) Working Group I (WGI) to improve the constraints on projections of future climate change. For the first time in the history of the IPCC, the WGI AR6 report uses multiple lines of evidence, including observational constraints based on past simulated warming, multi-model projections, as well as the updated climate sensitivity, to constrain the assessed future changes in global surface temperature, which reduces the uncertainty of the multi-model estimation. This paper reviews and introduces several main observational constraint methods and their applications involved in the WGI AR6 report, including model weighting, attribution-based constraint (ASK methods), and emergent constraint. No matter in AR6 or in many projection studies for different variables over various regions, observational constraints have shown the potential to correct model bias and improve model projections. In comparison, there are very few studies focusing on observational constrained projection in China. It is urgent to strengthen researches on observational constraint methods and their application in the projections of regional climate change in China, to provide more abundant climate information with narrowed uncertainty for policy formulation and adaptation planning in response to climate change.
Keywords:Climate projection  Observational constraint  Model weighting  ASK method  Emergent constraint
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