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.
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.
WindSat is a satellite-based multi-frequency polarimetric microwave radiometer designed to measure the fully polarimetric radiometric brightness temperature (TB) at 10.7, 18.7, and 37.0 GHz, and linearly polarized TB at 6.8 and 23.8 GHz. The primary goal of WindSat is to demonstrate the capability of polarimetric microwave radiometry in remote sensing of the ocean surface wind vector. Sea surface temperature, water vapor, and cloud liquid water, are among some of the other geophysical parameters that can also be measured. Solution of an inverse method to retrieve these environmental parameters from the polarimetric radiometer measurements requires a forward model that characterizes the measured brightness temperature due to emission from the surface and the intervening atmosphere, and its transmission through the atmosphere.
This paper concentrates predominantly on the atmospheric component of the Windsat forward model. This includes two separate but related algorithms. We have developed a complete radiative transfer model that calculates the upward and downward atmospheric radiation, including attenuation effects due to clear air (both resonant and continuum absorption by water vapor and molecular oxygen) and non-precipitating clouds. From calculations and analysis of using this full forward model and an extensive match-up dataset a computationally efficient one-layer parameterized model has been developed for use in the physically-based Windsat retrieval algorithm. A performance assessment of forward models which utilize surface and atmospheric models, NWP model data assimilation profiles, and environmental measurements from other satellites, by comparison with WindSat measurements, is presented.
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