Multi-scale temporal and spatial data-assimilative modeling for improving bathymetry information
Abstract
An iterative ensemble Kalman filter data assimilation scheme analogous to the outer loop of the 4DVAR variational data assimilation method was implemented. It utilizes remotely sensed observations and provides estimation of bathymetry in a nested tidal inlet, nearshore, and coastal region around the New River Inlet, NC. We employed the Regional Ocean Modeling System (ROMS) and the Simulating WAves Nearshore (SWAN) models as the hydrodynamic and wave components of the assimilative modeling framework. In the tidal inlet case, O(1 km), the data were surface velocity components derived from short-dwell airborne synthetic aperture radar (SAR) and wavenumber-frequency pairs derived from long-dwell tower-mounted X-band radar. Extension into the nearshore zone, O(10 km), involved assimilation of short-dwell satellite data to enhance bathymetry information in larger spatial scales. Assimilation of the dominant wavenumber of surface waves derived from satellite mounted SAR for depth information in the nearshore region is tested. At the coastal ocean scale, O(100 km), experiments with assimilation of water surface elevation data derived from satellite altimeters will be presented, with the aim of reducing systematic slope errors in bathymetry.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFMOS23A2000M
- Keywords:
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- 4544 Internal and inertial waves;
- OCEANOGRAPHY: PHYSICALDE: 4546 Nearshore processes;
- OCEANOGRAPHY: PHYSICALDE: 4558 Sediment transport;
- OCEANOGRAPHY: PHYSICALDE: 4560 Surface waves and tides;
- OCEANOGRAPHY: PHYSICAL