Evaluation of hurricane wind speed retrieval from cross-dual-pol SAR

Abstract

ABSTRACTUnderstanding and forecasting hurricanes are important components of weather prediction and climate studies. A critical concern is accuracy in hurricane wind speed estimates, especially in areas over the ocean where in situ measurements are sparse. Moreover, for very intense hurricanes, remotely sensed ocean surface winds generally lack accuracy. Recent studies on cross-polarization RADARSAT-2 synthetic aperture radar (SAR) data show very promising capability for high wind speed retrieval. The monotonic increase of cross-pol radar backscattered intensity with wind speed, and less sensitive dependence on wind direction, makes it superior to co-pol SAR measurements for operational application. Before further application of the methodology, it is important to evaluate the capability of hurricane forced wind speed retrieval from the promising, simple cross-pol SAR data. In this study, we apply a newly developed wind retrieval model to hurricanes using VH polarization dual-pol mode (VH dual-pol) RADARSAT-2 ScanSAR images. Validation of SAR wind retrievals is via surface wind analysis data from the Hurricane Research Division (HRD) of the National Oceanic and Atmospheric Administration (NOAA) and airborne stepped frequency microwave radiometer (SFMR) measurements. We found that compared to the co-polarization RADARSAT-2 SAR measurements, retrieved wind speeds from cross-polarization mode SAR have better overall accuracy and are more consistent with expected hurricane structures. Moreover, the cross-polarization model for VH dual-pol-retrieved winds does not appear to exhibit the speed ambiguity problem, which is one of the main obstacles for co-polarization retrieval of hurricane winds. SAR-retrieved winds contain detailed wind structures of the hurricane eyewall which are potentially of value for ongoing improvements in numerical models of hurricanes, air–sea interactions, and climate change. Special attention must be paid to biases caused by precipitation in order to reduce remaining errors in SAR retrieval of hurricane winds; precipitation has not been explicitly considered by current geophysical model functions.