Abstract

The realistic and accurate estimation of hurricane intensity is highly desired in many scientific and operational applications. With the advance of passive microwave polarimetry, an alternative opportunity for retrieving wind speed in hurricanes has become available. A wind speed retrieval algorithm for wind speeds above 20 m/s in hurricanes has been developed by using the 6.8 and 10.7 GHz vertically and horizontally polarized brightness temperatures of WindSat. The WindSat measurements for 15 category 4 and category 5 hurricanes from 2003 to 2010 and the corresponding H*wind analysis data are used to develop and validate the retrieval model. In addition, the retrieved wind speeds are also compared to the Remote Sensing Systems (RSS) global all-weather product and stepped-frequency microwave radiometer (SFMR) measurements. The statistical results show that the mean bias and the overall root-mean-square (RMS) difference of the retrieved wind speeds with respect to the H*wind analysis data are 0.04 and 2.75 m/s, respectively, which provides an encouraging result for retrieving hurricane wind speeds over the ocean surface. The retrieved wind speeds show good agreement with the SFMR measurements. Two case studies demonstrate that the mean bias and RMS difference are 0.79 m/s and 1.79 m/s for hurricane Rita-1 and 0.63 m/s and 2.38 m/s for hurricane Rita-2, respectively. In general, the wind speed retrieval accuracy of the new model in hurricanes ranges from 2.0 m/s in light rain to 3.9 m/s in heavy rain.

Highlights

  • Passive microwave remote sensing is an important tool for studying atmospheric and oceanographic processes and can provide both daytime and nighttime observations of geophysical parameters [1], such as atmospheric water vapor, cloud liquid water, rain rate, sea surface temperature, sea surface wind, and sea ice

  • Algorithms [3,6,7,8,9] have been developed for passive microwave radiometry that are able to retrieve the wind speeds of low to moderate winds in no-rain areas with a good degree of accuracy

  • Comparing W6H with W6V, we find that W6H seems to have a better correlation than W6V

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Summary

Introduction

Passive microwave remote sensing is an important tool for studying atmospheric and oceanographic processes and can provide both daytime and nighttime observations of geophysical parameters [1], such as atmospheric water vapor, cloud liquid water, rain rate, sea surface temperature, sea surface wind, and sea ice. 1987 [2], making it possible to obtain the global ocean surface wind from a spaceborne passive microwave instrument [3]. A successive dataset of wind speed has been obtained from the passive microwave radiometry [3,4,5]. Algorithms [3,6,7,8,9] have been developed for passive microwave radiometry that are able to retrieve the wind speeds of low to moderate winds in no-rain areas with a good degree of accuracy.

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