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The M²LInES team gathered for its annual meeting, featuring discussions on climate science, AI, machine learning, emulators, and hybrid modeling.
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Invited speakers from Open Athena, AI2, and the Simons Center helped spark new ideas and strengthen partnerships with external foundations, nonprofits, and research organizations.
title: "Impact of Data-Driven Eddy Parameterization on Climate State in an Idealized Coupled CESM Model"
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heroSubHeading: 'Impact of Data-Driven Eddy Parameterization on Climate State in an Idealized Coupled CESM Model'
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thumbnail: 'images/news/2606Shi.png'
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images: ['images/news/2606Shi.png']
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link: 'https://doi.org/10.48550/arXiv.2603.25843'
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A new [study](https://doi.org/10.48550/arXiv.2603.25843) led by Jia-Rui Shi explores how a data-driven eddy parameterization influences large-scale climate dynamics in a coupled climate model. By implementing the ZB20 eddy momentum parameterization in an idealized CESM configuration with MOM6 and CAM, the team found that the parameterized backscatter increases eddy kinetic energy, strengthens poleward ocean heat transport, and intensifies the overturning circulation in the Southern Hemisphere. These ocean adjustments produce a distinct dipolar sea surface temperature pattern, with mid-latitude cooling and high-latitude warming, and also affect the atmosphere through a compensating reduction in atmospheric heat transport and an equatorward shift of the mid-latitude jet. The results show how data-driven representations of ocean eddies can shape the mean climate state and provide insight for improving future climate models.
<strong>James P. C. Duncan, Elynn Wu, Surya Dheeshjith, Adam Subel, Troy Arcomano, Spencer K. Clark, Brian Henn, Anna Kwa, Jeremy McGibbon, W. Andre Perkins, William Gregory, Carlos Fernandez-Granda, Julius Busecke, Oliver Watt-Meyer, William J. Hurlin, Alistair Adcroft, Laure Zanna, Christopher Bretherton</strong><br>
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<a href="https://doi.org/10.1029/2025GL119340" target="_blank"><strong>SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators</strong></a><br>
<strong>David Kamm, Julie Deshayes, Pavel Perezhogin, Etienne Meunier, Alexis Barge</strong><br>
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<a href="https://doi.org/10.1029/2026MS005816" target="_blank"><strong>Assessing Data-Driven Eddy-Parameterizations in an Atlantic Sector Model </strong></a><br>
<strong>Aakash Sane, Brandon G Reichl, Alistair Adcroft, Laure Zanna</strong><br>
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<a href="https://doi.org/10.1029/2026GL122106" target="_blank"><strong>Machine learned equations for vertical mixing coefficients in the ocean surface boundary layer</strong></a><br>
<strong>Jia-Rui Shi, Pavel Perezhogin, Laure Zanna, Alistair Adcroft</strong><br>
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<a href="https://doi.org/10.48550/arXiv.2603.25843" target="_blank"><strong>Impact of Data-Driven Eddy Parameterization on Climate State in an Idealized Coupled CESM Model></strong></a><br>
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<a href="https://doi.org/10.48550/arXiv.2603.25843" target="_blank"><strong>Impact of Data-Driven Eddy Parameterization on Climate State in an Idealized Coupled CESM Model</strong></a><br>
<strong>David Kamm, Julie Deshayes, Pavel Perezhogin, Etienne Meunier, Alexis Barge</strong><br>
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<a href="https://doi.org/10.22541/essoar.177100611.18240844/v1" target="_blank"><strong>Assessing Data-Driven Eddy-Parameterizations in an Atlantic Sector Model></strong></a><br>
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<i>ESS Open Archive</i> <strong>DOI</strong>: 10.22541/essoar.177100611.18240844/v1
<strong>Sara Shamekh, Pedro Angulo-Umana, Paul A O'gorman</strong><br>
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<a href="https://doi.org/10.22541/au.176185709.98292011/v1" target="_blank"><strong>Data-driven Modeling of Stratiform and Convective Rain Area</strong></a><br>
<strong>James P. C. Duncan, Elynn Wu, Surya Dheeshjith, Adam Subel, Troy Arcomano, Spencer K. Clark, Brian Henn, Anna Kwa, Jeremy McGibbon, W. Andre Perkins, William Gregory, Carlos Fernandez-Granda, Julius Busecke, Oliver Watt-Meyer, William J. Hurlin, Alistair Adcroft, Laure Zanna, Christopher Bretherton</strong><br>
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<a href="https://doi.org/10.48550/arXiv.2509.12490" target="_blank"><strong>SamudrACE: Fast and Accurate Coupled Climate Modeling with 3D Ocean and Atmosphere Emulators</strong></a><br>
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