Assimilating satellite and in situ data into a Chesapeake Bay model using the LETKF

An advanced data assimilation system has been set up for the Chesapeake Bay using the local ensemble transform Kalman filter (LETKF) and a ROMS model of the Bay (ChesROMS). Observation system simulation experiments (OSSEs) have shown that the LETKF improves the state estimate of the system using synthetic observations that approximate the real satellite and in situ observational network. Errors in wind forcing dominate the chaotic grown of initial condition errors, but using an ensemble of forcing fields as well as adaptive inflation techniques these errors are managed. In addition to the OSSEs, we will show results from the assimilation of real SST from NOAA's AVHRR instrument and in situ temperature and salinity profiles. Performance is evaluated for the year 2003 as compared to independent in situ observations.