# Can We Improve Parametric Cyclonic Wind Fields Using Recent Satellite Remote Sensing Data?
###### Abstract  
Parametric cyclonic wind fields are widely used worldwide for insurance risk underwriting, coastal planning, and storm surge forecasts. They support high-stakes financial, development and emergency decisions. Yet, there is still no consensus on a potentially \"best\" parametric approach, nor guidance to choose among the great variety of published models. The aim of this paper is to demonstrate that recent progress in estimating extreme surface wind speeds from satellite remote sensing now makes it possible to assess the performance of existing parametric models, and select a relevant one with greater objectivity. In particular, we show that the Cyclone Global Navigation Satellite System (CYGNSS) mission of NASA, along with the Advanced Scatterometer (ASCAT), are able to capture a substantial part of the tropical cyclone structure, and to aid in characterizing the strengths and weaknesses of a number of parametric models. Our results suggest that none of the traditional empirical approaches are the best option in all cases. Rather, the choice of a parametric model depends on several criteria, such as cyclone intensity and the availability of wind radii information. The benefit of using satellite remote sensing data to select a relevant parametric model for a specific case study is tested here by simulating hurricane Maria (2017). The significant wave heights computed by a wave-current hydrodynamic coupled model are found to be in good agreement with the predictions given by the remote sensing data. The results and approach presented in this study should shed new light on how to handle parametric cyclonic wind models, and help the scientific community conduct better wind, wave, and surge analyses for tropical cyclones. CYGNSS; ASCAT; cyclones; hurricanes; parametric models; storm surges; waves; winds; remote sensing 2018 10.3390/rs10121963 1.  
wind radii, location of the cyclone center, etc.) are still widely used by the research and insurance communities, due to their simplicity, efficiency, and low-computational cost [6; 7; 8; 9; 10; 11; 12]. This is especially true for studies investigating storm surge hazards with statistical approaches, for which a large number of synthetic storms need to be represented [13; 14; 15; 16]. For a few decades (and even today), the parametric surface winds have simply been derived as the sum of an axisymmetric wind field and a uniform vector to mimic the asymmetry due to the storm's translational motion. Debates have arisen to determine the best way to estimate both components, which is a particularly relevant issue, as large discrepancies of the synthesized wind field occur depending on the chosen method [17]. This kind of approach, in which the tropical cyclone (TC) size is generally determined by a single parameter, the radius of maximum winds, presents several limitations. In particular, it does not always satisfactorily represent the TC wind asymmetry, which can be due to many factors, such as a blocking action by a neighboring anticyclone, boundary layer friction, or terrestrial effects [18]. To date, the increasing availability of satellite remote sensing data makes it possible to better depict and forecast the wind structure of TCs and its variations with azimuth. Whether based on infrared imagery and data [19; 20; 21], scatterometry [22; 23], X-band, C-band and L-band radiometry [24; 25; 26; 27; 28; 29], or global navigation satellite system-reflectometry (GNSS-R) [30; 31; 32], all these data can provide information about the 34-kt, 50-kt, and/or 64-kt wind radii in each TC quadrant. These radii are now commonly reported in advisories issued by warning centers. Yet, to our knowledge, few studies investigating TC winds, cyclonic-induced waves, or storm surges using parametric models make use of all the available information, whether for forecasts or hindcasts. Often, only the estimated radius of maximum winds or the 64-kt wind radius is used, which can lead to systematic errors in the extended wind field.