OMDP Commodore Workshop 2024

This workshop aims to create a collaborative space where experts from the ocean modeling, ocean processes, and machine learning communities can converge to discuss and review the latest developments in the field. Participants will engage in in-depth discussions on advances in dynamical cores and parameterizations, while also delving into the emerging role of data-driven methodologies and machine learning techniques in the development and analysis of numerical ocean models.

A significant focus of the workshop will be on the integration of machine learning within ocean modeling. This includes exploring various data-driven and machine-learning approaches for sub-grid scale parameterizations, assessing the use of machine learning both within and in parallel to ocean circulation models, and examining the potential opportunities and future directions that these technologies present for enhancing ocean models.

In parallel, the workshop will also concentrate on key areas within numerical modeling. Topics of interest include the latest advancements in structured and unstructured grid models, as well as numerical methods designed for a wide range of scales, from coastal to global. Discussions will cover the equations, formulations, and vertical coordinates used in these models, with a particular emphasis on how they interact with parameterizations and resolved fluid dynamics. Additionally, the workshop will address the coupling of ocean models with other components of the Earth system, the application of large-eddy simulations and non-hydrostatic modeling, and the role of process studies. Finally, the development processes behind these models, including their evaluation, testing, and the establishment of test cases, will be thoroughly examined.

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