The impact of stochastic mesoscale weather systems on the Atlantic Ocean

Zhou, Shenjie, Renfrew, Ian A. ORCID: https://orcid.org/0000-0001-9379-8215 and Zhai, Xiaoming (2023) The impact of stochastic mesoscale weather systems on the Atlantic Ocean. Journal of Climate, 36 (3). 791–804. ISSN 0894-8755

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Abstract

The ocean is forced by the atmosphere on a range of spatial and temporal scales. In numerical models the atmospheric resolution sets a limit on these scales and for typical climate models mesoscale (,500 km) atmospheric forcing is absent or misrepresented. Previous studies have demonstrated that mesoscale forcing significantly affects key ocean circulation systems such as the North Atlantic subpolar gyre (SPG) and the Atlantic meridional overturning circulation (AMOC). Here we present ocean model simulations that demonstrate that the addition of realistic mesoscale atmospheric forcing leads to coherent patterns of change: a cooler sea surface in the tropical and subtropical Atlantic Ocean and deeper mixed layers in the subpolar North Atlantic in autumn, winter, and spring. These lead to robust statistically significant increases in the volume transport of the North Atlantic SPG by 10% and the AMOC by up to 10%. Our simulations use a novel stochastic parameterization-based on a cellular automata algorithm-to represent spatially coherent weather systems realistically over a range of scales, including down to the smallest resolvable by the ocean grid (;10 km). Convection-permitting atmospheric models predict changes in the intensity and frequency of mesoscale weather systems due to climate change, so representing them in coupled climate models would bring higher fidelity to future climate projections.

Item Type: Article
Additional Information: Acknowledgments: Our model simulations were carried out on the High-Performance Computing Cluster supported by the Research and Specialist Computing Support service at the University of East Anglia. Authors Zhou and Renfrew acknowledge partial support from the NERC Grant NE/N009754/1, a component of the Iceland Greenland Seas Project, which helped to inspire the design of this study. Zhou thanks Adrian Matthews, David Ferreira, and Xiaolong Yu for helpful discussions on this work. Data availability statement: ERA5 atmosphere reanalysis data are available at Climate Data Store (https://cds.climate.copernicus.eu/). QuikSCAT data are produced by Remote Sensing Systems and sponsored by the NASA Ocean Vector Winds Science Team; they are available online (https://www.remss.com). NBDC and PIRATA buoy wind time series are stored at National Buoy Data Center (https://www.ndbc.noaa.gov/). SIMORC buoy data are available at System of Industry Metocean data for the Offshore and Research Communities (http://www.simorc.com/) via a data request form. The raw model output examined, code of the CA algorithm, and scripts for all analysis presented in this paper are available from author Zhou upon reasonable request.
Uncontrolled Keywords: atmosphere-ocean interaction,mesoscale processes,north atlantic ocean,oceanic mixed layer,sea surface temperature,stochastic models,atmospheric science ,/dk/atira/pure/subjectarea/asjc/1900/1902
Faculty \ School: Faculty of Science > School of Environmental Sciences
Faculty of Science > School of Natural Sciences
University of East Anglia Research Groups/Centres > Theme - ClimateUEA
UEA Research Groups: Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences
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Depositing User: LivePure Connector
Date Deposited: 25 Oct 2022 11:30
Last Modified: 28 Nov 2023 02:40
URI: https://ueaeprints.uea.ac.uk/id/eprint/89339
DOI: 10.1175/JCLI-D-22-0044.1

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