Understanding Bias in the Evaporative Damping of El Niño–Southern Oscillation Events in CMIP5 Models

Author:

Ferrett Samantha1,Collins Matthew1,Ren Hong-Li2

Affiliation:

1. College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, United Kingdom

2. Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing, and Department of Atmospheric Science, School of Environmental Studies, China University of Geoscience, Wuhan, and CMA–Nanjing University Joint Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing, China

Abstract

This study examines the extent of the Pacific double–intertropical convergence zone (ITCZ) bias in an ensemble of CMIP5 coupled general circulation models and the relationship between this common bias and equatorial Pacific evaporative heat flux feedbacks involved in El Niño–Southern Oscillation (ENSO). A feedback decomposition method, based on the latent heat flux bulk formula, is implemented to enable identification of underlying causes of feedback bias and diversity from dynamical and thermodynamical processes. The magnitude of mean precipitation south of the equator in the east Pacific (an indicator of the extent of the double-ITCZ bias in a model) is linked to the mean meridional surface wind speed and direction in the region and is consequently linked to diversity in the strength of the wind speed response during the ENSO cycle. The ENSO latent heat flux damping is weak in almost all models and shows a relatively large range in strength in the CMIP5 ensemble. While both humidity gradient and wind speed feedbacks are important drivers of the damping, the wind speed feedback is an underlying cause of the overall damping bias for many models and is ultimately more dominant in driving interensemble variation. Feedback biases can also persist in atmosphere-only (AMIP) runs, suggesting that the atmosphere model plays an important role in latent heat flux damping and double-ITCZ bias and variation. Improvements to coupled model simulation of both mean precipitation and ENSO may be accelerated by focusing on the atmosphere component.

Funder

Newton Fund

Natural Environment Research Council

China Meteorological Administration

Publisher

American Meteorological Society

Subject

Atmospheric Science

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