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 August 2, 2021

Professor Aluie Wins NSF Award for Probing the Ocean's Multiscale Pathways

The project utilizes a somewhat novel ‘coarse-graining’ approach to analyze multiscale interactions that is more versatile and powerful than the classical ‘mean-eddy’ decomposition. It numerical models, it is almost never possible to directly resolve all motions down to the smallest scales. Instead, the influence of the smaller scales on the larger scale circulation of interest is estimated using parameterizations, whose choice typically depend on where the cut off for resolved scales are and sometimes on the particular location which may determine what physical processes are important.

This research is aligned with the search for ‘scale-aware’ and ‘location-aware’ parameterizations, which would apply universally without needing to be tuned for specific conditions. The project can have a direct bearing on a fundamental problem in climate science: the extent to which temporal variability is naturally emergent within the flow system itself or is a response to external forcing. The work also promises to offer a priori constraints on parameter tuning of current schemes, on proposed schemes that may be applied to eddy permitting ocean models, and will help in the development of a new class of ocean parameterizations that are a function of time, location, and resolution. This work will also demonstrate a self-consistent integrated methodology to analyze and model the dynamics of multiscale systems, which can have an important impact on many fields beyond climate. The multiscale analysis codes developed for this study will be made available on Github to allow for an open development approach.

The project will support two junior scientists, one at the beginning of her PhD and another at the threshold of his career. Finally, the project’s research will be integrated into outreach efforts through the Rochester Museum and Science Center.

View Award Abstract