Sea level rise and sea state variability due to climate change and global warming are major research topics in the scientific community. Multiple techniques have been developed to observe and monitor these phenomena with great precision on a global scale. However, these techniques present limitations in terms of spatial and temporal resolution or poor performance in coastal zones, which are highly dynamic complex areas impacted by increasing sea level and wind-wave effects represented by the sea state.
This Master’s thesis presents the possibility of using GNSS-Reflectometry (GNSS-R) to monitor sea state in coastal areas. GNSS-R is a bistatic radar-based technique that allows for retrieval of the Earth's surface properties by analyzing direct and reflected signals (once it bounces off the Earth's surface) captured by a receiver. This study relies on, first, the observed minus computed (O-C) reflected signal power from which a sea state factor (SSF) is derived, and second, analysis of the Doppler shift distribution of the reflected signal to then correlate them with ancillary date of wind speed (WS) and significant wave height (SWH) from the ERA5 model. The tracking process of the direct signal allows us to retrieve its power, and a re-tracking process, aided by a signal path model, is used to obtain the power of the reflected signal. Direct and reflected power are used to compute the observed reflectivity reduced by a modeled (computed) reflectivity to calculate the SSF. The Doppler distribution involves the computation of the mean and standard deviation of the Doppler frequency shift. The latter is retrieved from the power spectral density approach computed every minute from the in-phase (I) and quadrature (Q) components of the reflected re-tracked signal.
Results have shown a sensitivity of the sea state factor and the Doppler distribution with respect to ERA5 sea state parameters with dependency on the GNSS satellite elevation angle as well. As the increase in the roughness of the sea surface, there is a loss on the power of the reflected signal. Therefore, the SSF has a high and moderate anti-correlation with respect to WS and SWH at low elevations (E<10°), with values of, -0.73 and -0.51, respectively. The Doppler standard deviation has a high correlation with WS and SWH of 0.94 and 0.85 respectively, decreasing progressively whit the increase in elevation angle.