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Attribution of ocean temperature change to anthropogenic and natural forcings using the temporal, vertical and geographical structure

Bilbao, R. A. F., Gregory, J. M., Bouttes, N., Palmer, M. D. and Stott, P. (2019) Attribution of ocean temperature change to anthropogenic and natural forcings using the temporal, vertical and geographical structure. Climate Dynamics, 53. pp. 5389-5413. ISSN 0930-7575

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To link to this item DOI: 10.1007/s00382-019-04910-1

Abstract/Summary

We examine whether significant changes in ocean temperatures can be detected in recent decades and if so whether they can be attributed to anthropogenic or natural factors. We compare ocean temperature changes for 1960-2005 in four observational datasets and in historical simulations by atmosphere-ocean general circulation models (AOGCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5). Observations and CMIP5 models show that the upper 2000m has warmed with a signal that has a welldefined geographical pattern that gradually propagates to deeper layers over time. Greenhouse gas forcing has contributed most to increasing the temperature of the ocean, a warming which has been offset by other anthropogenic forcing (mainly aerosols), and volcanic eruptions which cause episodic cooling. By characterizing the ocean temperature change response to these forcings we construct multi-model mean fingerprints of time-depth changes in temperature and carry out two detection and attribution analysis. We consider first a twosignal separation into anthropogenic and natural forcings. Then, for the first time, we consider a three signal separation into greenhouse gas, anthropogenic aerosols and natural forcings. We show that all three signals are simultaneously detectable. Using multiple depth levels decreases the uncertainty of the results. Limiting the observations and model fields to locations where there are observations increases the detectability of the signal.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > NCAS
Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:84559
Publisher:Springer

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