WindSat Wind Vector Retrievals in the Presence of Clouds

The WindSat instrument aboard the Coriolis satellite was launched on 6th January 2003. WindSat is the first spaceborne fully polarimetric microwave radiometer specifically designed to demonstrate the capability of retrieving the ocean surface wind speed and direction from space. At 845 Km altitude in a near-polar orbit, WindSat renders fore and aft swath measurements at five frequencies: 6.8, 10.7, 18.7, 23.8 and 37 GHz. Three of them (10.7, 18.7 and 37 GHz) are fully-polarimetric, and the other two are V and H polarized channels that were included to estimate the contributions of both the atmosphere and the sea surface temperature.

Using several months of WindSat measurements, collocated NCEP Global Data Assimilation System (GDAS) model fields, Special Sensor Microwave Imager (SSM/I) measurements, and SeaWinds scatterometry measurements, we developed an empirical geophysical models that describe the radiometric Stokes vector for all WindSat channels, as a function of surface parameters (wind speed, wind direction, and sea surface temperature), as well as atmospheric parameters (water vapor and cloud liquid water). This empirical GMF, namely WindSat-1, has been used to develop an ocean surface wind vector retrieval algorithm for WindSat polarimetric measurements

The NOAA WindSat EDR retrieval algorithm is a five step algorithm. Each step is characterized by a separate retrieval algorithm specifically designed to retrieve one of the environmental parameters. Only the retrieval algorithms for the atmospheric parameters are independent algorithms. The retrieval algorithms for the total precipitable water and cloud liquid water were developed to support the wind vector retrieval algorithm, where the retrieval algorithms for the surface wind speed and direction and sea surface temperature are dependent upon the atmospheric retrievals.

A first evaluation of the current WindSat wind speed retrieval algorithms applied to tropical cyclones showed how the algorithm, originally developed for non-precipitable atmospheres and at ocean surface winds below 20 m/s, is severely affected by heavy cloud cover and precipitation. To improve performance of the wind vector retrieval algorithm we designed high-clouds wind speed and vector retrieval algorithm. We will present validation results and discuss performance of the algorithm.