EGU26-14014, updated on 14 Mar 2026
https://doi.org/10.5194/egusphere-egu26-14014
EGU General Assembly 2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Oral | Thursday, 07 May, 14:45–14:55 (CEST)
 
Room L3
Stochastic GM+E: An energetically-informed stochastic backscatter scheme for ocean models
Ian Grooms1, Niraj Agarwal1, Gustavo Marques2, Philip Pegion3, and Houssam Yassin1
Ian Grooms et al.
  • 1University of Colorado, Applied Mathematics, Boulder, Colorado, United States of America (ian.grooms@colorado.edu)
  • 2NSF National Center for Atmospheric Research, Climate and Global Dynamics, Boulder, Colorado, United States of America
  • 3National Oceanic and Atmospheric Administration, Physical Sciences Lab, Boulder, Colorado, United States of America

Global ocean models at resolutions that do not resolve mesoscale eddies lack variability, not just on scales that they cannot represent because they are below the grid scale, but also on resolvable scales. This research develops a backscatter parameterizations that increases variability on the resolved scales of a non-eddying model. The parameterization acts on the model's momentum equations, and sets the rate of backscatter, viz. the rate at which energy is injected to the resolved scales, proportional to the rate at which the Gent-McWilliams (GM) parameterization removes energy from the resolved scales. This models the physical process whereby mesoscales convert large-scale potential energy to kinetic energy, and then transfer that kinetic energy towards larger scales. These parameterization is implemented in the MOM6 ocean model, and results are presented on its impact in simulations at nominal 2/3-degree resolution. Stochastic GM+E acts primarily in the Southern Ocean, the North Atlantic Current, and the Kuroshio Extension, where it impacts SST variability and southern-hemisphere sea ice extent.

How to cite: Grooms, I., Agarwal, N., Marques, G., Pegion, P., and Yassin, H.: Stochastic GM+E: An energetically-informed stochastic backscatter scheme for ocean models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14014, https://doi.org/10.5194/egusphere-egu26-14014, 2026.