Editorial Type:
Article
Article Type:
Research Article

Intermodel Uncertainty in ENSO Amplitude Change Tied to Pacific Ocean Warming Pattern

Xiao-Tong Zheng Physical Oceanography Laboratory/CIMST, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, and Key Laboratory of Ocean–Atmosphere Interaction and Climate in Universities of Shandong, Ocean University of China, Qingdao, China

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Shang-Ping Xie Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, and Physical Oceanography Laboratory/CIMST, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Liang-Hong Lv Physical Oceanography Laboratory/CIMST, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, and Key Laboratory of Ocean–Atmosphere Interaction and Climate in Universities of Shandong, Ocean University of China, Qingdao, China

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Zhen-Qiang Zhou Physical Oceanography Laboratory/CIMST, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, China

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Print Publication:
15 Oct 2016
DOI:
https://doi.org/10.1175/JCLI-D-16-0039.1
Page(s):
7265–7279
Restricted access

Abstract

How El Niño–Southern Oscillation (ENSO) will change under global warming affects changes in extreme events around the world. The change of ENSO amplitude is investigated based on the historical simulations and representative concentration pathway (RCP) 8.5 experiments in phase 5 of the Coupled Model Intercomparison Project (CMIP5). The projected change in ENSO amplitude is highly uncertain with large intermodel uncertainty. By using the relative sea surface temperature (SST) as a measure of convective instability, this study finds that the spatial pattern of tropical Pacific surface warming is the major source of intermodel uncertainty in ENSO amplitude change. In models with an enhanced mean warming in the eastern equatorial Pacific, the barrier to deep convection is reduced, and the intensified rainfall anomalies of ENSO amplify the wind response and hence SST variability. In models with a reduced eastern Pacific warming, conversely, ENSO amplitude decreases. Corroborating the mean SST pattern effect, intermodel uncertainty in changes of ENSO-induced rainfall variability decreases substantially in atmospheric simulations forced by a common ocean warming pattern. Thus, reducing the uncertainty in the Pacific surface warming pattern helps improve the reliability of ENSO projections. To the extent that correcting model biases favors an El Niño–like mean warming pattern, this study suggests an increase in ENSO-related SST variance likely under global warming.

Corresponding author address: Xiao-Tong Zheng, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China. E-mail: zhengxt@ouc.edu.cn

Abstract

How El Niño–Southern Oscillation (ENSO) will change under global warming affects changes in extreme events around the world. The change of ENSO amplitude is investigated based on the historical simulations and representative concentration pathway (RCP) 8.5 experiments in phase 5 of the Coupled Model Intercomparison Project (CMIP5). The projected change in ENSO amplitude is highly uncertain with large intermodel uncertainty. By using the relative sea surface temperature (SST) as a measure of convective instability, this study finds that the spatial pattern of tropical Pacific surface warming is the major source of intermodel uncertainty in ENSO amplitude change. In models with an enhanced mean warming in the eastern equatorial Pacific, the barrier to deep convection is reduced, and the intensified rainfall anomalies of ENSO amplify the wind response and hence SST variability. In models with a reduced eastern Pacific warming, conversely, ENSO amplitude decreases. Corroborating the mean SST pattern effect, intermodel uncertainty in changes of ENSO-induced rainfall variability decreases substantially in atmospheric simulations forced by a common ocean warming pattern. Thus, reducing the uncertainty in the Pacific surface warming pattern helps improve the reliability of ENSO projections. To the extent that correcting model biases favors an El Niño–like mean warming pattern, this study suggests an increase in ENSO-related SST variance likely under global warming.

Corresponding author address: Xiao-Tong Zheng, College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China. E-mail: zhengxt@ouc.edu.cn
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