Location
Salt Lake Community College
Start Date
5-5-2003 2:30 PM
Description
The Sea Winds scatterometer is designed primarily to retrieve winds over the ocean. Since the deployment of Sea Winds on QuikSCAT in 1999, rain corruption in wind measurements has been recognized as one of the largest contributors to wind retrieval error. This paper presents a new estimation method that incorporates rain effects into Sea Winds wind retrieval. The new method simultaneously retrieves wind and rain, giving improved wind estimates in rain-corrupted areas and providing Sea Winds-derived estimates of the rain rate. The simultaneous wind/rain estimation method works especially well in the "sweet spot" of Sea Winds' swath. On the outer-beam edges of the swath, rain estimation is not possible. This area, however, is only a small fraction of the total data. Wind speeds from simultaneous wind/rain retrieval are nearly unbiased, while the wind-only wind speeds become increasingly biased with rain rate. A synoptic example demonstrates that the new method has the capability of visually reducing the error due to rain while producing a consistent (yet somewhat noisy) estimate of the rain rate.
Simultaneous Wind and Rain Retrieval using Seawinds Data
Salt Lake Community College
The Sea Winds scatterometer is designed primarily to retrieve winds over the ocean. Since the deployment of Sea Winds on QuikSCAT in 1999, rain corruption in wind measurements has been recognized as one of the largest contributors to wind retrieval error. This paper presents a new estimation method that incorporates rain effects into Sea Winds wind retrieval. The new method simultaneously retrieves wind and rain, giving improved wind estimates in rain-corrupted areas and providing Sea Winds-derived estimates of the rain rate. The simultaneous wind/rain estimation method works especially well in the "sweet spot" of Sea Winds' swath. On the outer-beam edges of the swath, rain estimation is not possible. This area, however, is only a small fraction of the total data. Wind speeds from simultaneous wind/rain retrieval are nearly unbiased, while the wind-only wind speeds become increasingly biased with rain rate. A synoptic example demonstrates that the new method has the capability of visually reducing the error due to rain while producing a consistent (yet somewhat noisy) estimate of the rain rate.