A New SAR Retrieval Method for Hurricane Wind Parameters

Abstract

Thanks to the capability to image the ocean surface with a spatial resolution in the order of meters, SAR images can be used to infer information on tropical cyclone wind field structure, eye size, radius of maximum wind speed and rain band distribution independent of daylight and cloudiness.
In tropical cyclone conditions however, when using the same wind retrieval technique as used for Scatterometers, saturation of the radar backscatter and damping due to heavy rain leads to an underestimation of the maximum measured wind speed.
A new method to estimate the hurricane maximum wind speed, and thus its strength by using SAR images in combination with a parametric model is presented. The algorithm derived is based on a least square minimization of the difference between the parametric model and the SAR measurement in the range where the wind speed is below 20 m/s. The radius of maximum wind speed, required as input for the minimization procedure, is measured applying an image analysis method.
Wavelength and direction of boundary layer rolls for information on wind direction are determined performing a 2-dimensional spectral analysis of the SAR images.
The algorithm is applied on a dataset of wide swath (SAR) images (400 km x 400 km coverage), acquired by the European ENVISAT satellite.
The retrieved values of maximum wind speed and central pressure agree well with the measurements provided by the NOAA Hurricane Research Division (HRD) and the Japan Meteorological Agency.
In addition the effect of heavy rain on radar backscatter and on the retrieved wind field is investigated theoretically.
The work aims at the improvement of the prediction of cyclone intensity and track.