Using Surface Pressure to Improve Tropical Cyclone Surface Wind Retrievals form Synthetic Aperture Radar Imagery

Abstract

Abstract : The calibration and validation of surface wind and stress retrievals from oceanic synthetic aperture radar (SAR) imagery is especially difficult in tropical cyclone (TC) conditions. The geophysical model functions (GMFs) that characterize the radar backscatter in terms of the near-surface wind vector for different viewing geometries are currently poorly characterized for the very high wind and strong ocean surface wave conditions that are present in all TCs. Our long-term goal is to develop a novel methodology to use surface pressure observations and a planetary boundary (PBL) model for calibration and validation (Cal/Val) of SAR GMFs in TC conditions and to produce scene-wide wind vector retrievals that are most consistent with the image backscatter, the GMF and the PBL model. We further working toward an improved understanding of atmospheric boundary layer processes and air-sea interaction in tropical cyclones. The objectives of this research are to (1) develop the methodology for deriving TC SLP fields from first-guess surface wind vector estimates based on various GMF formulations; (2) Use these SLP fields to derive surface wind vector retrievals that are, in a least-squares sense, a scene-wide optimal surface wind retrieval that is consistent with the observable linear features in the SAR image, the GMF and the PBL model; (3) Develop an optimization scheme that seeks the minimum adjustment to the surface wind vector field that will minimize the difference between observed (e.g. via drop sondes or buoys) and SAR-derived bulk pressure gradients across the image. The optimized surface wind field can then be used either to assess or adjust the GMF.