Using MODAS to derive subsurface sound speed estimates from satellite observations

Abstract

The Modular Ocean Data Assimilation System (MODAS) provides a set of tools for analysis and manipulation of ocean data. One of its functions is the estimation of subsurface temperature and salinity fields from satellite observations of height deviation and temperature. A two-dimensional optimal interpolation of the satellite data produces fields of surface height anomaly and temperature. These data are provided to the MODAS synthetic profile routine to predict subsurface temperature and salinity fields compatible with the surface observations and local climatological statistics. Available in situ measurements may be assimilated at this stage. A sound speed field calculated from the temperature and salinity estimates provides the basis for additional acoustical applications. MODAS products, evaluated by comparison with finely sampled surveys, show significant improvement over estimates from static climatologies. [This work was funded by the Space and Naval Warfare Systems Command (SPAWAR) and the ONR through the Advanced Data Fusion Center Support and the On-Scene Tactical Ocean Forecast Capability projects (SPAWAR, Program Element 603207N) and the MODAS Improvements and the Prediction of Coastal Buoyancy Jets projects (ONR, Program Element 602435N).]