Downscaling, 2-way Nesting, and Data Assimilative Modeling in Coastal and Shelf Waters of the U.S. Mid-Atlantic Bight and Gulf of Maine
Abstract:
We describe such a system for shelf waters of the Mid-Atlantic Bight (MAB) and Gulf of Maine (GoM) where the MARACOOS and NERACOOS associations of U.S. IOOS operate coastal ocean observing systems that deliver a dense observation set using CODAR HF-radar, autonomous underwater glider vehicles (AUGV), telemetering moorings, and drifting buoys. Other U.S. national and global observing systems deliver further sustained observations from moorings, ships, profiling floats, and a constellation of satellites.
Our MAB and GoM re-analysis and forecast system uses the Regional Ocean Modeling System (ROMS; myroms.org) with 4-dimensional Variational (4D-Var) data assimilation to adjust initial conditions, boundary conditions, and surface forcing in each analysis cycle. Data routinely assimilated include CODAR velocities, altimeter satellite sea surface height (with coastal corrections), satellite temperature, in situ CTD data from AUGV and ships (NMFS Ecosystem Monitoring voyages), and all in situ data reported via the WMO GTS network. A climatological data assimilative analysis of hydrographic and long-term mean velocity observations specifies the regional Mean Dynamic Topography that augments altimeter sea level anomaly data and is also used to adjust boundary condition biases that would otherwise be introduced in the process of downscaling from global models.
System performance is described with respect to the impact of satellite, CODAR and in situ observations on analysis skill. Results from a 2-way nested modeling system that adds enhanced resolution over the NSF OOI Pioneer Array in the central MAB are also shown.