A Parametric Model Incorporated with Satellite Wind for Tropical Cyclone Surface Wind Speed Assessment

The surface wind speed (SWS) structure of tropical cyclones (TCs) is essential for assessing their size and intensity, which are critical for disaster prevention. Empirical parametric wind models provide stable products for TC SWS. Although empirical profiles are beneficial for TC initialization and intensity forecast, they can be less representative due to the lack of adjustment from real-time observations. As the quality and coverage of SWS measured by satellites have increased over time, it becomes necessary to complement parametric estimation with satellite data to obtain optimal profiles in real time. This study develops a method to construct the real-time SWS profiles by integrating data from Cyclone Global Navigation Satellite System (CYGNSS) wind, Advanced Scatterometer (ASCAT) wind, and operational initial TC vitals into the parametric wind model. The newly proposed parametric wind model is constructed by quadrants with temporal continuity. Particularly, the methodology highlights and enhances the impact of limited inner-core CYGNSS observations, and it handles spatiotemporally inhomogeneous characteristics in different satellite data. The algorithm is applied to the cases during the 2018−2020 Atlantic hurricane seasons, and the results are compared with the Synthetic Aperture Radar (SAR) products and the empirical profiles. Results show that the satellite-incorporated profiles well represent the TC structure and provide continuous and realistic products with TC asymmetry. The application and detailed analysis of satellite-incorporated profiles are further demonstrated with Hurricane Florence (2018), Dorian (2019), and Teddy (2020).