Location
University of Utah
Start Date
5-13-2002 11:00 AM
Description
The scatterometer Sea Winds on QuikSCAT measures ocean winds via the relationship between the wind and the normalized radar backscatter cross-section (aO) from the ocean surface. Scattering and attenuation from falling rain droplets along with ocean surface perturbations due to rain change the backscatter signature of the waves induced by near-surface winds. A simple model incorporates the effects of rain on ocean aO. Colocated data from the precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite is used to simulate the effects of rain as seen by Sea Winds. PRderived backscatter, atmospheric rain attenuation, and rain rates are averaged over the Sea Winds footprint. The enhancement in backscatter from rain striking the ocean surface is estimated as a function of rain rate using a least-squares technique. QuikSCAT aO values are simulated from the PR-derived parameters and numerical weather prediction wind data using the simple backscatter model. The simple model estimates 90% of the observed rain-contaminated QuikSCAT aO values to within 3 dB.
Simulation of Seawinds Measurements in the Presence of Rain using Collocated TRMM PR Data
University of Utah
The scatterometer Sea Winds on QuikSCAT measures ocean winds via the relationship between the wind and the normalized radar backscatter cross-section (aO) from the ocean surface. Scattering and attenuation from falling rain droplets along with ocean surface perturbations due to rain change the backscatter signature of the waves induced by near-surface winds. A simple model incorporates the effects of rain on ocean aO. Colocated data from the precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite is used to simulate the effects of rain as seen by Sea Winds. PRderived backscatter, atmospheric rain attenuation, and rain rates are averaged over the Sea Winds footprint. The enhancement in backscatter from rain striking the ocean surface is estimated as a function of rain rate using a least-squares technique. QuikSCAT aO values are simulated from the PR-derived parameters and numerical weather prediction wind data using the simple backscatter model. The simple model estimates 90% of the observed rain-contaminated QuikSCAT aO values to within 3 dB.