Title :
Rain and Wind Estimation from Seawinds in Hurricanes at Ultra High Resolution
Author :
Williams, Brent A. ; Long, David G.
Author_Institution :
MERS Lab., Brigham Young Univ., Provo, UT
Abstract :
A Bayesian method for estimating wind and rain in hurricanes from SeaWinds at ultra-high resolution is developed. We use a hurricane model to generate prior distributions for the wind speed, wind direction, and rain rate. The rain prior is derived from data from the Tropical Rainfall Measuring Mission Precipitation Radar (TRMM-PR). The new method reduces the variability of the standard simultaneous wind and rain estimates while preserving meso-scale detail.
Keywords :
Bayes methods; atmospheric techniques; geophysical signal processing; rain; remote sensing by radar; storms; wind; Bayesian method; SeaWinds; TRMM-PR; Tropical Rainfall Measuring Mission Precipitation Radar; hurricanes; mesoscale event; rain rate; ultra high resolution; wind direction; wind speed; Backscatter; Bayesian methods; Geophysical measurements; Hurricanes; Maximum likelihood estimation; Polarization; Pollution measurement; Radar measurements; Rain; Wind speed;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-2807-6
Electronic_ISBN :
978-1-4244-2808-3
DOI :
10.1109/IGARSS.2008.4779080
