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Critical Southern Ocean climate model biases traced to atmospheric model cloud errors

Hyder, P., Edwards, J. M., Allan, R. P. ORCID: https://orcid.org/0000-0003-0264-9447, Hewitt, H. T., Bracegirdle, T. J., Gregory, J. M. ORCID: https://orcid.org/0000-0003-1296-8644, Wood, R. A., Meijers, A. J. S., Mulcahy, J., Field, P., Furtado, K., Bodas-Salcedo, A., Williams, K. D., Copsey, D., Josey, S. A., Liu, C., Roberts, C. D., Sanchez, C., Ridley, J., Thorpe, L. , Hardiman, S. C., Mayer, M., Berry, D. I. and Belcher, S. E. (2018) Critical Southern Ocean climate model biases traced to atmospheric model cloud errors. Nature Communications, 9 (1). 3625. ISSN 2041-1723

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To link to this item DOI: 10.1038/s41467-018-05634-2

Abstract/Summary

The Southern Ocean is a pivotal component of the global climate system yet it is poorly represented in climate models, with significant biases in upper-ocean temperatures, clouds and winds. Combining Atmospheric and Coupled Model Inter-comparison Project (AMIP5/CMIP5) simulations, with observations and equilibrium heat budget theory, we show that across the CMIP5 ensemble variations in sea surface temperature biases in the 40–60°S Southern Ocean are primarily caused by AMIP5 atmospheric model net surface flux bias variations, linked to cloud-related short-wave errors. Equilibration of the biases involves local coupled sea surface temperature bias feedbacks onto the surface heat flux components. In combination with wind feedbacks, these biases adversely modify upper-ocean thermal structure. Most AMIP5 atmospheric models that exhibit small net heat flux biases appear to achieve this through compensating errors. We demonstrate that targeted developments to cloud-related parameterisations provide a route to better represent the Southern Ocean in climate models and projections.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:78927
Publisher:Nature Publishing Group

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