Title

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

Authors

Authors

S. Alsweiss; R. Hanna; P. Laupattarakasem; W. L. Jones; C. C. Hennon;R. Y. Chen

Comments

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Abbreviated Journal Title

Remote Sens.

Keywords

SeaWinds; conical scanning; scatterometers; wind vector retrievals; MLE; tropical cyclones; H*Wind; OCEAN; NSCAT; SYSTEM; Remote Sensing

Abstract

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.

Journal Title

Remote Sensing

Volume

6

Issue/Number

5

Publication Date

1-1-2014

Document Type

Article

Language

English

First Page

4133

Last Page

4148

WOS Identifier

WOS:000337160700029

ISSN

2072-4292

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