Do CMIP5 Models Show El Niño Diversity?

Author:

Feng Jie1,Lian Tao2,Ying Jun1,Li Junde1,Li Gen3

Affiliation:

1. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, China

2. State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources, Hangzhou, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

3. College of Oceanography, Hohai University, Nanjing, China

Abstract

AbstractWhether the state-of-the-art CMIP5 models have different El Niño types and how the degree of modeled El Niño diversity would be impacted by the future global warming are still heavily debated. In this study, cluster analysis is used to investigate El Niño diversity in 30 CMIP5 models. As the method does not rely on any prior knowledge of the patterns of El Niño seen in observations, it provides a practical way to identify the degree of El Niño diversity in models. Under the historical scenario, most models show a poor degree of El Niño diversity in their own model world, primarily due to the lopsided numbers of events belonging to the two modeled El Niño types and the weak compactness of events in each cluster. Four models are found showing significant El Niño diversity, yet none of them captures the longitudinal distributions of the warming centers of the two El Niño types seen in the observations. Heat budget analysis of the sea surface temperature (SST) anomaly suggests that the degree of modeled El Niño diversity is highly related to the climatological zonal SST gradient over the western-central equatorial Pacific in models. As the gradient is weakened in most models under the future high-emission scenario, the degree of modeled El Niño diversity is further reduced in the future. The results indicate that a better simulation of the SST gradient over the western-central equatorial Pacific might allow a more reliable simulation/projection of El Niño diversity in most CMIP5 models.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Henan Province

China Ocean Mineral Resources Research and Development Association program

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference81 articles.

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