While the European Space Agency (ESA) provides SAR-derived wind fields over the ocean together with Sentinel-1 SAR imagery, users have to apply their own algorithms to retrieve wind products from SAR images from other satellites. These operate at various radar frequencies, polarizations, incidence angles, etc., and each combination of radar parameters requires a specific geophysical model function for the conversion of image intensities into wind speeds. In addition, different methods can be used to extract wind directions from wind streak signatures in an images itself or adopt them from numerical forecast wind fields.
In the course of a variety of research projects in this field in the last 10-20 years, with a variety of partners, the University of Miami's Center for Southeastern Tropical Advanced Remote Sensing (CSTARS) has developed capabilities to retrieve wind fields from all types of SAR images that will be acquired for the NHCI project. In addition to a simple conversion of image intensities into wind speeds, the most advanced algorithms can apply corrections to make sure the solutions for the wind vector field and the corresponding surface level pressure (SLP) field are consistent with fundamental principles of atmospheric physics. The figure on this page shows an example based on a Sentinel-1 image of Hurricane Michael over the Gulf of Mexico on October 9, 2018, 23:44 UTC. Both parts show optimized wind speeds in color (numbers on the color legend are meters per second). The left-hand part shows black wind vectors in addition; the right-hand part shows white SLP isolines with black numbers and the track of the hurricane eye as an additional black line. For the corresponding ESA-provided wind field for this case, see our team update from July 28, 2021.