The NASA Earth Venture Cyclone Global Navigation Satellite System (CYGNSS) is a spaceborne mission scheduled to launch in October 2016 that is focused on tropical cyclone (TC) inner core process studies. CYGNSS attempts to resolve one of the principle deficiencies with current TC intensity forecasts, which lies in inadequate observations and modeling of the inner core. CYGNSS is specifically designed to address these two limitations by combining the all-weather performance of GNSS bistatic ocean surface scatterometry with the sampling properties of a constellation of satellites. CYGNSS measurements of bistatic radar cross section of the ocean can be directly related to the near surface wind speed, in a manner roughly analogous to that of conventional ocean wind scatterometers. The technique has been demonstrated previously from space by the UK-DMC mission in 2005-6.
Using several months of WindSat measurements collocated with the NCEP Global Data Assimilation System model field, the Special Sensor Microwave Imager (SSM/I) measurements and QuikScat scatterometry measurements, we have derived an empirical geophysical model that describes radiometric vector for all WindSat channels, as a function of surface parameters: wind speed, wind direction and sea surface temperature, and atmospheric parameters: total precipitable water and cloud liquid water.
This model function was then used to develop an ocean surface wind vector retrieval algorithm from WindSat polarimetric measurements.
The accuracy of the retrieved wind vectors was quantified using several months of WindSat measurements collocated with the Special Sensor Microwave Imager (SSM/I) measurements and QuikSCAT scatterometry measurements.
Collocation of WindSat brightness temperatures and retrieved windspeeds with Stepped Frequency Microwave Radiometer (SFMR) on board NOAA WP-3D Orion aircraft are used to analyze and validate WindSat data under extreme wind conditions. For this study, the data presented are from September 2003 during Hurricane Fabian (03 September 2003). Temporal and spatial variability within the SFMR data stream are discussed in relation to both the WindSat brightness temperatures and derived windspeeds.