Tropical Cyclone Wind Direction Retrieval From Dual-Polarized SAR Imagery Using Histogram of Oriented Gradients and Hann Window Function

Accurate knowledge of wind directions plays a critical role in ocean surface wind retrieval and tropical cyclone (TC) research. Under TC conditions, apparent wind streaks induced by marine atmospheric boundary layer rolls can be detected in VV- and VH-polarized synthetic aperture radar (SAR) images. It suggests that though relatively noisy, VH signals may help enhance wind streak orientation magnitudes contained in VV signals and thus to achieve a more accurate wind direction estimation. The study proposes a new method for wind direction retrieval from TC SAR images. Unlike conventional approaches, which calculate wind directions from single-polarization imagery, the method combines VV and VH signals to obtain continuous wind direction maps across moderate and extreme wind speed regimes. The technique is developed based on the histogram of oriented gradient descriptor and Hann window function, accounting for the contribution of neighboring wind streak information (weighted by separation distances). As a case study, the wind directions over four TCs (Karl, Maria, Douglas, and Larry) are derived and verified by estimates from simultaneous dropsonde, ASCAT and ECMWF winds, showing a promising consistency. Furthermore, a more comprehensive statistical analysis is carried out with 14 SAR images, revealing that obtained wind directions have a correlation coefficient of 0.98, a bias of −6.07
$^{\circ }$
and a RMSD of 20.24
$^{\circ }$
, superior to estimates from VV (0.97, −7.84
$^{\circ }$
, and 24.23
$^{\circ }$
, resp.) and VH signals (0.96, −10.46
$^{\circ }$
, and 29.53
$^{\circ }$
, resp.). The encouraging results prove the feasibility of the technique in SAR wind direction retrieval.