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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Rochester |
| Country | United States |
| Start Date | Sep 01, 2021 |
| End Date | Aug 31, 2026 |
| Duration | 1,825 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2123496 |
Oceanic flow is a quintessentially multiscale system, involving processes and structures over an entire continuum of spatial lengths and time periods. The nonlinear coupling between scales ranging from the many thousands of kilometers of basin-wide circulation down to the millimeter size of turbulent eddies presents a major difficulty in understanding and modeling oceanic circulation and mixing, and also in limiting our predictive ability to forecast climate.
The main objective of this project is to probe the energy cycle coupling different scales from the order of 10000 km down to around 10 km in the global ocean, using data from satellites and high-resolution models. 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.
Coarse-graining has a rigorous mathematical foundation and is closely related to well-established physics techniques, including macroscopic electromagnetism, renormalization group, and large eddy simulation. Moreover, unlike the classical decomposition, coarse-graining is consistent with the parameterization requirements of coarse-resolution climate simulations.
Equations governing the dynamics of different scales on the sphere can be derived relatively easily, opening up a new and potentially transformative way to studying multiscale pathways in oceanic flows, including the transfer of energy, transport of momentum and tracers, and forcing at different scales — all of which can be probed both geographically and temporally. This project will analyze the geographic and temporal correlations between different pathways and processes, including their amplitude and frequency response to changes in atmospheric forcing.
The physical processes that require parametrization in climate models depend on the grid resolution and also on an understanding and quantification of the dominant processes at any given length-scale. In this respect, the project is ideally aligned to advancing a new systematic approach to ‘scale-aware’ and ‘location-aware’ parameterizations that reflect the latent subgrid physics, along with a deeper understanding of the amplitude and frequency responses of different length-scales and processes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
University of Rochester
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