# Can We Improve Parametric Cyclonic Wind Fields Using Recent Satellite Remote Sensing Data?
## Data and Methods
### Parametric Wind Models  
At the location and time of each CYGNSS and ASCAT data point, we compute the corresponding parametric surface wind speeds given by each gradient wind profile. The following procedure is applied:  
1. From the NHC advisories, the surface background wind relative to the cyclone translation velocity is estimated at the time of acquisition of the CYGNSS/ASCAT data point under consideration. Following the approach of [PERSON] and [PERSON] [17], we assume that this wind is decelerated by a factor of \(\alpha\) = 0.56 and rotated counter-clockwise by an angle of \(\beta\) = 19.2\({}^{\circ}\) from the free tropospheric wind.
2. The translational portion of the wind speed is removed from the maximum observed wind velocity and the 34-, 50-, and 64-kt winds.
3. Surface velocities given by the NHC are converted to velocities at the top of the atmospheric boundary layer by applying an empirical surface wind reduction factor, SWRF [39]. In the following sections, we use SWRF = 0.9. Other values were tested, but they did not change the conclusions of this paper. For the sake of brevity, these results are not presented here.
4. The radii of maximum winds are estimated for the four quadrants, using the chosen parametric gradient wind profile, and the available wind radii information. For each quadrant, up to three radii of maximum winds are thus obtained: One estimated using the 64-kt wind radius (\(R_{m64}\)), another one from the 50-kt wind radius (\(R_{m50}\)), and a third from the 34-kt wind radius (\(R_{m34}\)).
5. Depending on the case, \(R_{m64}\), \(R_{m34}\), or all the radii of maximum winds (\(R_{m64}\), \(R_{m50}\), and \(R_{m34}\)) are computed for the data point azimuth, using a spline interpolation.
6. The parametric wind speed value at the CYGNSS/ASCAT data point is computed using the chosen parametric gradient wind profile. This step is straightforward if a single radius of maximum winds is considered. In the case where all the radii of maximum winds (\(R_{m64}\), \(R_{m50}\), and \(R_{m34}\)) are considered, the parametric wind speed is computed using a linear weighting approach similar to the one proposed by [PERSON] et al. [45]. For example, for a CYGNSS/ASCAT point located at a distance, r, from the cyclone center larger than the 64-kt wind radius (\(r64\)), but lower than the 50-kt wind radius (\(r50\)), we: * (a) Compute \(V_{Rm64}\), the parametric wind speed at the CYGNSS/ASCAT data point location obtained using \(R_{m64}\); * (b) compute \(V_{Rm50}\), the parametric wind speed at the CYGNSS/ASCAT data point location obtained using \(R_{m50}\); and * (c) compute the final parametric wind speed, \(V\), using the following equation: \[V=\frac{V_{Rm50}-V_{Rm64}}{r50-r64}(r-r64)+V_{Rm64}\] This approach ensures that all the wind radii information are satisfied.
7. The velocity, \(V\), is multiplied by SWRF to obtain the parametric wind speed at the surface.
8. The wind speed obtained in the previous step is combined with the surface background wind computed in step 1 to get the final parametric wind speed at the CYGNSS/ASCAT data point considered.  
This procedure is repeated for all the storms, gradient wind profiles, and CYGNSS/ASCAT Level 2-data points within a distance of 200 km from the cyclone center. The parametric models considered here are given in Table 2.