CoAuthors

Wang Jinbo (JPL, United States); Archer matthew (JPL, United States); Fu Lee-Lueng (JPL, United States)

We examine the impact of assimilating multi-satellite altimetry data into a model that resolves submesoscale ocean circulation of order 10 km. To resolve submesoscales, the model must have a horizontal grid spacing of about 1 km. To maximize the impact of the satellite altimetry data on the model, we need to deal with a particular set of challenges: (1) map the model solution to altimetry measurements according to the footprint size; (2) retain the high resolution along track information and spread it across tracks; (3) deal with internal tide and gravity wave signals; and (4) incorporate multiscale dynamics. Using a multiscale three-dimensional variational data assimilation (MS-3DVAR) and forecasting system for the California Current System, we illustrate these challenges, address methodologies and formulations to deal with them, and characterize the impact that multi-satellite altimetry data has on the model representation of flows down into the submesoscale.