A generalized linear observable for GNSS-R wind speed retrievals over the ocean

This paper will present a generalized linear observable which can be optimized under different cost functions for the retrieval of wind speed over ocean surfaces Global Navigation Satellite System-Reflectometry (GNSS-R). The Cyclone Global Navigation Satellite System (CYGNSS) will measure the surface winds in and near the hurricane inner core, including regions beneath the eye wall and intense inner rain bands that could not previously be measured from space. CYGNSS observatories will receive both direct and reflected signals from Global Positioning System (GPS) satellites. The direct signals pinpoint observatory positions, while the reflected signals respond to ocean surface roughness, from which wind speed is retrieved. Based on simulated Delay-Doppler Maps (DDM) over a tropical cyclone, the observable is optimized according to three different methods (maximum signal to noise ratio, minimum variance of the wind speed and principal component analysis). The performances obtained with each of these three approaches are compared to each other and that of the baseline Level 2 retrievals defined for CYGNSS.