Monday, 11 January 2016: 2:15 PM
Room 345 ( New Orleans Ernest N. Morial Convention Center)
NASA's Surface Water and Ocean Topography (SWOT) satellite, scheduled for launch in 2020, will provide sea surface height anomaly (SSHA) observations with a wider swath width and higher spatial resolution than current satellite altimeters. It is expected that this will help to further constrain ocean models in terms of the mesoscale circulation. In this work, this expectation is investigated by way of twin data assimilation experiments using the Navy Coastal Ocean Model Four Dimensional Variational (NCOM-4DVAR) data assimilation system using a weak constraint formulation. Here, a nature run is created from which SWOT observations are sampled, as well as along-track SSHA observations from simulated Jason-2 tracks. The simulated SWOT data has appropriate spatial coverage, resolution, and noise characteristics based on an observation-simulator program provided by the SWOT science team. The experiment is run for a two-month period during which the analysis is updated every 24 hours and each analysis is used to initialize a 120 hour forecast. The forecasts of each experiment is compared to the available nature run to determine the impact of the assimilated data. It is demonstrated here that the SWOT observations help to constrain the model mesoscale in a more consistent manner than traditional altimeter observations. The findings of this study suggest that data from SWOT may have a substantial impact on improving the ocean model analysis and forecast of mesoscale features and surface ocean transport.
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