A less cloudy picture of the inter-model spread in future global warming projections

Xiaoming Hu, Hanjie Fan, Ming Cai (), Sergio A. Sejas, Patrick Taylor and Song Yang
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Xiaoming Hu: Sun Yat-sen University
Hanjie Fan: Sun Yat-sen University
Ming Cai: Florida State University
Sergio A. Sejas: Science Systems and Applications, Inc
Patrick Taylor: Climate Science Branch, NASA Langley Research Center
Song Yang: Sun Yat-sen University

Nature Communications, 2020, vol. 11, issue 1, 1-11

Abstract: Abstract Model warming projections, forced by increasing greenhouse gases, have a large inter-model spread in both their geographical warming patterns and global mean values. The inter-model warming pattern spread (WPS) limits our ability to foresee the severity of regional impacts on nature and society. This paper focuses on uncovering the feedbacks responsible for the WPS. Here, we identify two dominant WPS modes whose global mean values also explain 98.7% of the global warming spread (GWS). We show that the ice-albedo feedback spread explains uncertainties in polar regions while the water vapor feedback spread explains uncertainties elsewhere. Other processes, including the cloud feedback, contribute less to the WPS as their spreads tend to cancel each other out in a model-dependent manner. Our findings suggest that the WPS and GWS could be significantly reduced by narrowing the inter-model spreads of ice-albedo and water vapor feedbacks, and better understanding the spatial coupling between feedbacks.

Date: 2020
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DOI: 10.1038/s41467-020-18227-9

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