Underestimated MJO Variability in CMIP6 Models

Underestimated MJO Variability in CMIP6 Models
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CMIP6 模型中低估的 MJO 变异性

DOI:
10.1029/2020gl092244
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发表时间:
2021
影响因子:
5.2
通讯作者:
Foufoula‐Georgiou, Efi
Foufoula‐Georgiou, Efi
中科院分区:
地球科学1区
文献类型:
--
作者:
Le, Phong V. V.;Guilloteau, Clément;Mamalakis, Antonios;Foufoula‐Georgiou, Efi

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马登-朱利安振荡(MJO)是季节内气候变化的主要模式,对广泛的天气和气候现象产生了深远的影响。在这里,我们使用基于小波的频谱主成分分析(WsPCA)来评估20个最先进的CMIP6模型在捕捉MJO的幅度和动力学方面的技能。通过构造,wsPCA具有聚焦于期望频率并用一个主分量(PC)捕获每个传播物理模式的能力。我们表明,在大多数CMIP6模式中,MJO对总的季节内气候变率的贡献被大大低估。利用与MJO相关的小波PC序列的模和角频率的联合分布,通过Wasserstein距离对模型相对于观测值进行排序。使用Hovmöler相经图,我们还表明,在大多数亚马逊、西南部非洲和海洋大陆的CMIP6模式中,与MJO相关的降水变率被低估了。
The Madden‐Julian Oscillation (MJO) is the leading mode of intraseasonal climate variability, having profound impacts on a wide range of weather and climate phenomena. Here, we use a wavelet‐based spectral Principal Component Analysis (wsPCA) to evaluate the skill of 20 state‐of‐the‐art CMIP6 models in capturing the magnitude and dynamics of the MJO. By construction, wsPCA has the ability to focus on desired frequencies and capture each propagative physical mode with one principal component (PC). We show that the MJO contribution to the total intraseasonal climate variability is substantially underestimated in most CMIP6 models. The joint distribution of the modulus and angular frequency of the wavelet PC series associated with MJO is used to rank models relatively to the observations through the Wasserstein distance. Using Hovmöller phase‐longitude diagrams, we also show that precipitation variability associated with MJO is underestimated in most CMIP6 models for the Amazonia, Southwest Africa, and Maritime Continent.
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