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CMIP6与CMIP5多模式集合中极端气候的区域气候敏感性

Regional Climate Sensitivity of Climate Extremes in CMIP6 Versus CMIP5 Multimodel Ensembles.

作者信息

Seneviratne Sonia I, Hauser Mathias

机构信息

Institute for Atmospheric and Climate Science, Department of Environmental Systems Science ETH Zurich Zurich Switzerland.

出版信息

Earths Future. 2020 Sep;8(9):e2019EF001474. doi: 10.1029/2019EF001474. Epub 2020 Sep 20.

Abstract

We analyze projected changes in climate extremes (extreme temperatures and heavy precipitation) in the multimodel ensembles of the fifth and sixth Coupled Model Intercomparison Projects (CMIP5 and CMIP6). The results reveal close similarity between both ensembles in the regional climate sensitivity of the projected multimodel mean changes in climate extremes, that is, their projected changes as a function of global warming. This stands in contrast to widely reported divergences in global (transient and equilibrium) climate sensitivity in the two multimodel ensembles. Some exceptions include higher warming in the South America monsoon region, lower warming in Southern Asia and Central Africa, and higher increases in heavy precipitation in Western Africa and the Sahel region in the CMIP6 ensemble. The multimodel spread in regional climate sensitivity is found to be large in both ensembles. In particular, it contributes more to intermodel spread in projected regional climate extremes compared with the intermodel spread in global climate sensitivity in CMIP6. Our results highlight the need to consider regional climate sensitivity as a distinct feature of Earth system models and a key determinant of projected regional impacts, which is largely independent of the models' response in global climate sensitivity.

摘要

我们分析了第五次和第六次耦合模式比较计划(CMIP5和CMIP6)多模式集合中极端气候(极端温度和强降水)的预估变化。结果显示,两个集合在极端气候预估多模式平均变化的区域气候敏感性方面极为相似,即它们作为全球变暖函数的预估变化。这与广泛报道的两个多模式集合在全球(瞬态和平衡)气候敏感性方面的差异形成对比。一些例外情况包括,CMIP6集合中南美季风区变暖幅度更大,南亚和中非变暖幅度更小,西非和萨赫勒地区强降水增加幅度更大。在两个集合中,区域气候敏感性的多模式离散度都很大。特别是,与CMIP6中全球气候敏感性的模式间离散度相比,它对预估区域极端气候的模式间离散度贡献更大。我们的结果强调,需要将区域气候敏感性视为地球系统模式的一个独特特征以及预估区域影响的关键决定因素,这在很大程度上独立于模式在全球气候敏感性方面的响应。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca10/7539979/3929cb084ea8/EFT2-8-e2019EF001474-g001.jpg

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