WindSat, a satellite-based multi-frequency polarimetric microwave radiometer developed by the Naval Research Laboratory for the U.S. Navy and the NPOESS Integrated Program Office (IPO), has collected nearly five years of fully-polarimetric microwave measurements from space since its launch in 2003. The primary WindSat mission was to demonstrate the capability to retrieve the ocean surface wind vector from a space-based microwave radiometer. The WindSat data is now being used to produce near-real-time products for the ocean surface wind vector, sea surface temperature (SST) and atmospheric columnar water vapor and cloud liquid water over the ocean at the U.S. Navy's Fleet Numerical Meteorological and Oceanographic Center (FNMOC). Several groups have worked on assimilating WindSat data products into numerical weather models with positive results.

To further exploit the unique WindSat data set, significant effort has gone into improving the spatial resolution of the WindSat ocean products. Higher spatial resolution not only better resolves the wind field, but also improves high wind speed retrievals because of the smaller spatial scales of higher winds. Furthermore, reduced spatial resolution allows for retrievals closer to coastlines. The current WindSat ground data processing software produces retrievals of sea surface wind vectors, total precipitable water, and cloud liquid water at three spatial resolutions (pixel sizes of 50x71 km; 35x53 km; and 25x35 km). We will present comparisons of retrieval products at these three resolutions.

Further improvements in forward modeling, instrument calibration, and retrieval algorithms have also led to significantly improved data products. This is true for both ocean and land, where WindSat data are being used to retrieve soil moisture and vegetation water content. The multi-frequency/multi-polarization retrieval simultaneously solves for soil and vegetation products to better separate the contributions of these two variables to the WindSat brightness temperature measurements. The algorithm is validated against soil moisture climatology; ground in-situ network data; response to precipitation; and vegetation dynamics data from Vis/IR sensors. The validation results suggest that the algorithm can, for the first time, meet the requirements of 50 km resolution soil moisture mapping under low to moderate vegetation.

In addition to discussing these latest WindSat data products, we will also discuss how WindSat is being used for risk reduction for the NPOESS MIS instrument.