Whitecap and Wind Stress Observations by Microwave Radiometers: Global Coverage and Extreme Conditions

Type Article
Date 2019-09
Language English
Author(s) Hwang Paul A.1, Reul NicolasORCID2, Meissner Thomas3, Yueh Simon H.4
Affiliation(s) 1 : Remote Sensing Division, U. S. Naval Research Laboratory, Washington, DC 20375 ,USA
2 : Laboratoire d’Océanographie Physique et Spatial (LOPS), Institut Français de Recherche pour l’Exploitation de la Mer (IFREMER), Univ. Brest, CNRS, IRD, Brest, France
3 : Remote Sensing Systems, Santa Rosa, CA 94501, USA
4 : Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91125, USA
Source Journal Of Physical Oceanography (0022-3670) (American Meteorological Society), 2019-09 , Vol. 49 , N. 9 , P. 2291-2307
DOI 10.1175/JPO-D-19-0061.1
WOS© Times Cited 15
Keyword(s) Wave breaking, Wind stress, Wind waves, Severe storms, Microwave observations, Satellite observations

Whitecaps manifest surface wave breaking that impacts many ocean processes, of which surface wind stress is the driving force. For close to a half century of quantitative whitecap reporting, only a small number of observations are obtained under conditions with wind speed exceeding 25 m/s. Whitecap contribution is a critical component of ocean surface microwave thermal emission. In the forward solution of microwave thermal emission, the input forcing parameter is wind speed, which is used to generate the modeled surface wind stress, surface wave spectrum, and whitecap coverage necessary for the subsequent electromagnetic (EM) computation. In this respect, microwave radiometer data can be used to evaluate various formulations of the drag coefficient, whitecap coverage, and surface wave spectrum. In reverse, whitecap coverage and surface wind stress can be retrieved from microwave radiometer data by employing pre-calculated solutions of an analytical microwave thermal emission model that yields good agreement with field measurements. There are many published microwave radiometer datasets covering a wide range of frequency, incidence angle, and both vertical and horizontal polarizations, with maximum wind speed exceeding 90 m/s. These datasets provide information of whitecap coverage and surface wind stress from global oceans and in extreme wind conditions. Breaking wave energy dissipation rate per unit surface area can be estimated also by making use of its linear relationship with whitecap coverage derived from earlier studies.

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