## 1 Introduction
However, it does not preserve any information at the edges, thus preventing any retrievals at distances closer than 50 km from the coast. Based on this fact, the higher resolution coastal product is obtained by applying a box averaging on a 50 km by 50 km area, in order to minimize the noise while preserving \(\sigma_{0}\) measurements near the coast. The outcome is that the coastal product will have increased variability among neighbor wind vector cells since a larger number of measurements away from the center of the cell are included in the averaging. A different approach based on image reconstruction has been adopted by [PERSON] et al. [21] to create a high resolution ASCAT wind product. The reconstruction is based on the weighted average method that is weighted by the spatial response function (SRF), which corresponds to the footprint of each measurement as a function of aperture [22]. The grid is defined to be the same as the coastal product, but sub-divided into 1.25-km spacing. Leveraging wind retrievals at 12.5-km spatial resolution from the ASCAT instruments onboard the Meteorological Operational-A, -B (Metop-A, -B) satellite series, [PERSON] et al. [23] developed a new method to identify cold pools globally based on the horizontal wind gradient, termed as 'Gradient Feature' (GF). The validity of this method was evaluated with simulation of the Weather Research and Forecasting (WRF) model over the Indian Ocean during the DYNAmics of Madden-Julian Oscillation field campaign, as well as air temperature from buoys and precipitation data from the Tropical Rainfall MeasurementMission (TRMM). However, some uncertainty in the method was also identified due to the characteristics of the ASCAT and its overpass relative to the life cycle of the convective system. The former accounts for the tendency of ASCAT to overestimate (underestimate) wind speed retrievals at lower (higher) wind speeds [24; 25]. The authors suggested wind gradient to be more robust than divergence and vorticity since biases in the retrievals, especially near gust front boundaries, can complicate the interpretation between the two latter quantities. Nevertheless, [PERSON] and [PERSON] [26] demonstrated the ability of the 12.5-km ASCAT winds to detect the horizontal wind divergence associated with MCS downdrafts, whereas smaller convective-scale downdrafts were not resolved. The ability of ASCAT to detect more generalized wind patterns, such as outflow boundaries near precipitation at moderate rain rates was shown by [PERSON] et al. [27]. The authors utilized an image processing method, known as the singularity analysis to improve the quality control of wind retrievals under rain conditions. A tracking algorithm for gust fronts of convective cold pools was developed by [PERSON] and [PERSON] [28], which was based on the gradient of the radial velocity. The algorithm can be described in three phases: first a rain cell tracking is performed, followed by the calculation of the radial velocity and its gradient. The last phase includes the identification of the cold pool edges based on the minimum in the gradient of the radial velocity. Using a large eddy simulation model, the authors were able to demonstrate the efficiency of the method to identify an ensemble of cold pools in comparison to traditional thermodynamical approaches. The physical basis lies on the fact that cold pool edges can exhibit thermodynamic properties similar to the surrounding air, while new convection is triggered in regions of near-surface convergence. Gust fronts have also been studied utilizing ground-based radar systems Wakimoto [29]. Automated algorithms have been developed based on radar proxies to detect gust fronts [30; 31; 32]. The ability of the ground-based radar systems to assess the low-levels of the atmosphere that are key to the performance of the scatterometers has been demonstrated by [PERSON] et al. [33]. The authors demonstrated that quality flagging is sensitive to individual storm characteristics utilizing ground-based radar retrieved rain rate.