The preliminary attempts to develop of the geophysical model function (GMF) for the retrieval of wind speed and wind stress in hurricanes, based on a dependency between the cross-polarized satellite SAR data from Sentinel-1 and wind speed or turbulent stress obtained from collocated NOAA GPS-dropsondes data array. Field measurements in the Atlantic Ocean during hurricane season in the period 2001-2018 were analyzed. Using the data measured by GPSdropsondes, due to the ensemble averaging, mean wind velocity profiles were obtained, and the atmospheric boundary layer parameters drag coefficient and turbulent stress (or friction velocity) were retrieved from the “wake” part of the velocity profiles taking into account a self-similarity property of the velocity profile “defect”. The parameters were retrieved for 25 major hurricanes of categories 4 and 5. The collocation of Sentinel-1 images and GPS-dropsonde data was made for the hurricanes Irma 2017/09/07, Maria 2017/09/21 and 2017/09/23, taking into account the assumption that turbulent boundary layer parameters in the hurricanes remain quasistationary. The dependencies of the cross-polarized normalized radar cross-section (NRCS) on the wind speed and wind friction velocity were obtained, the results were compared to the data for small and moderate winds, represented in [1], a good agreement is demonstrated. In the region of high wind speeds the relation between NRCS and the wind friction velocity becomes ambiguous, it may be explained by the dependency on the hurricane sector.
The research is devoted to the problem of estimations of CO2 fluxes between the hydrosphere and atmosphere. Hurricane-force winds lead to intensive wave breaking, with formation of spray in the air, and bubbles in the water. It strongly intensifies gas flux characterizing by power dependence of the transfer rate on the 10-m height wind speed used for approximation of the empirical results. But available data demonstrate wide variation which leads large confidence limits for coefficients in empirical approximations. On the other hand there is an obvious problem of obtaining reliable data on the wind speed. Widely used reanalysis data typically underestimate wind speed magnitude, due to the low spatial and temporal resolution. One of the most promising ways to measure near water wind speed is the use of the data of remote sensing. The present study used technique to achieve wind speed based on the processing sea surface images obtained in cross-polarized mode with C-band (5.4 GHz) radar with synthesized aperture (RSA) of RADARSAT satellite. To this propose geophysical model function (GMF) which binds values of wind speed and normalized radar cross section in cross-polarized mode was used. This GMF was developed in a special laboratory experiment on the wind-wave flumes for a wide range of wind speeds, including hurricanes. In turn, for parameterization of gas transfer rate results of recent laboratory experiment on high speed wind-wave flume was used.
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