A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones

Remote Sensing

Suleiman Alsweiss¹  Rafik Hanna²  Peth Laupattarakasem²  W. Linwood Jones²  Christopher C. Hennon³ 

[1] Global Science & Technology Inc., 7855 Walker Drive, Suite 200, Greenbelt 20770, MD, USA;Central Florida Remote Sensing Laboratory, Department of Electrical Engineering and Computer Science, University of Central Florida, Orlando 32816-2450, FL, USA; E-Mails:;Department of Atmospheric Sciences, University of North Carolina at Asheville, One University Heights, Asheville 28804, NC, USA; E-Mail:

关键词: SeaWinds;    conical scanning;    scatterometers;    wind vector retrievals;    MLE;    tropical cyclones;    H*Wind;   

DOI  :  10.3390/rs6054133

来源: mdpi

【 摘 要 】

Satellite microwave scatterometers are the principal source of global synoptic-scale ocean vector wind (OVW) measurements for a number of scientific and operational oceanic wind applications. However, for extreme wind events such as tropical cyclones, their performance is significantly degraded. This paper presents a novel OVW retrieval algorithm for tropical cyclones which improves the accuracy of scatterometer based ocean surface winds when compared to low-flying aircraft with in-situ and remotely sensed observations. Unlike the traditional maximum likelihood estimation (MLE) wind vector retrieval technique, this new approach sequentially estimates scalar wind directions and wind speeds. A detailed description of the algorithm is provided along with results for ten QuikSCAT hurricane overpasses (from 2003–2008) to evaluate the performance of the new algorithm. Results are compared with independent surface wind analyses from the National Oceanic and Atmospheric Administration (NOAA) Hurricane Research Division’s H*Wind surface analyses and with the corresponding SeaWinds Project’s L2B-12.5 km OVW products. They demonstrate that the proposed algorithm extends the SeaWinds capability to retrieve wind speeds beyond the current range of approximately 35 m/s (minimal hurricane category-1) with improved wind direction accuracy, making this new approach a potential candidate for current and future conically scanning scatterometer wind retrieval algorithms.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland