The impact of stochastic mesoscale weather systems on the Atlantic Ocean
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 mes...
| Published in: | Journal of Climate |
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| Main Authors: | , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://ueaeprints.uea.ac.uk/id/eprint/89339/ https://ueaeprints.uea.ac.uk/id/eprint/89339/7/1520_0442_JCLI_D_22_0044.1.pdf https://doi.org/10.1175/JCLI-D-22-0044.1 |
| Summary: | 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. |
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