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Historical ocean heat uptake in two pairs of CMIP6 models: global and regional perspectives

Kuhlbrodt, T. ORCID: https://orcid.org/0000-0003-2328-6729, Voldoire, A., Palmer, M. D., Geoffroy, O. and Killick, R. E. (2023) Historical ocean heat uptake in two pairs of CMIP6 models: global and regional perspectives. Journal of Climate, 36 (7). pp. 2183-2203. ISSN 1520-0442

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To link to this item DOI: 10.1175/JCLI-D-22-0468.1

Abstract/Summary

Ocean heat content (OHC) is one of the most relevant metrics tracking the current global heating. Therefore, simulated OHC time series are a cornerstone for assessing the scientific performance of Earth System models and global climate models. Here we present a detailed analysis of OHC change in simulations of the historical climate (1850-2014) performed with two pairs of CMIP6 (Coupled Model Intercomparison Project phase 6) models: UKESM1 and HadGEM3-GC3.1-LL; and CNRM-ESM2-1 and CNRM-CM6-1. The small number of models enables us to analyse OHC change globally and for individual ocean basins, making use of a novel ensemble of observational products. For the top 700 m of the global ocean, the two CNRM models reproduce the observed OHC change since the 1960s closely. The two UK models (UKESM1.0-LL and HadGEM3-GC3.1-LL) compensate a lack of warming in the 0-700 m layer in the 1970s and 1980s with warming below 2000 m. The observed warming between 700 and 2000 m is substantially underestimated by all models. An increased relevance for ocean heat uptake in the Atlantic after 1991 – suggested by observations – is picked up by the UK models but less so by the CNRM models, probably related to an AMOC strengthening in the UK models. The regional ocean heat uptake characteristics differ even though all four models share the same ocean component (NEMO ORCA1). Differences in the simulated global, full depth OHC time series can be attributed to differences in the models’ total effective radiative forcing.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > NCAS
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:109126
Publisher:American Meteorological Society

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