Developing a new plume-based non-local turbulence closure scheme under complex oceanic forcing

ORAL

Abstract

In this study, we extend a recently developed hybrid mass-flux and high-order closure scheme to parameterize turbulent mixing in the ocean surface boundary layer (OSBL) under realistic, time-varying, and non-equilibrium surface forcing conditions. The scheme combines a plume-based, non-local formulation with the prognostic evolution of key second- and third-order turbulent moments, ensuring energetic consistency. Our previous work demonstrated its ability to capture both diffusive and non-diffusive OSBL mixing across idealized wind-, wave-, and buoyancy-driven regimes. Here, we evaluate the scheme's performance under more complex oceanic forcing by validating it against a suite of large eddy simulations (LES). The results highlight the scheme's robustness and suitability for large-scale Earth system models. In addition, the scheme is optimized for GPU acceleration, enhancing its compatibility with emerging high-performance computing architectures.

*This research was funded in part as part of the Energy Exascale Earth System Model (E3SM) and Interdisciplinary Research for Arctic Coastal Environments (InteRFACE) project through the Department of Energy, Office of Science, Biological and Environmental Research Earth and Environment Systems Sciences Division, Regional and Global Model Analysis (RGMA), Earth System Model Development (ESMD), MultiSector Dynamics (MSD), and Data Management (DM) programs and was awarded under contract Grant 89233218CNA000001 to Triad National Security, LLC ("Triad") and Department of Energy subcontract agreements #B645995 and #B663241 to Oregon State University. This research was also funded in part by the National Science Foundation grant through the REU program at Oregon State University (NSF OCE-2148655).

Presenters

  • Amrapalli Garanaik

    • Oregon State University

Authors

  • Amrapalli Garanaik

    • Oregon State University
  • Yvette Lin

    • University of California Irvine
  • Sebastian Moreno-Comstock

    • Tufts University
  • Qing Li

    • The Hong Kong University of Science and Technology (Guangzhou)
    • The Hong Kong University of Science and Technology
  • Luke van Roekel

    • Los Alamos National Laboratory
  • Brodie Pearson

    • Oregon State University