Application of Continuous Data Assimilation in High-Resolution Ocean Modeling

Application of Continuous Data Assimilation in High-Resolution Ocean Modeling

Year:    2024

Author:    Adam Larios, Mark Petersen, Collin Victor

Communications in Computational Physics, Vol. 35 (2024), Iss. 5 : pp. 1418–1444

Abstract

We demonstrate a formulation of the Azouani-Olson-Titi (AOT) algorithm in the MPAS-Ocean implementation of the primitive equations of the ocean, presenting global ocean simulations with realistic coastlines and bathymetry. We observe an exponentially fast decay in the error before reaching a certain error level, which depends on the terms involved and whether the AOT feedback control term was handled implicitly or explicitly. A wide range of errors was observed for both schemes, with the implicit scheme typically exhibiting lower error levels, depending on the specific physical terms included in the model. Several factors seem to be contributing to this wide range, but the vertical mixing term is demonstrated to be an especially problematic term. This study provides insight into the promises and challenges of adapting the AOT algorithm to the setting of high-resolution, realistic ocean models.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/cicp.OA-2023-0208

Communications in Computational Physics, Vol. 35 (2024), Iss. 5 : pp. 1418–1444

Published online:    2024-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    27

Keywords:    Continuous data assimilation Azouani-Olson-Titi oceanography MPAS-Ocean primitive equations nudging.

Author Details

Adam Larios

Mark Petersen

Collin Victor

  1. Continuous data assimilation for the 3D and higher-dimensional Navier–Stokes equations with higher-order fractional diffusion

    Larios, Adam

    Victor, Collin

    Journal of Mathematical Analysis and Applications, Vol. 540 (2024), Iss. 1 P.128644

    https://doi.org/10.1016/j.jmaa.2024.128644 [Citations: 1]