Improving the emissivity model of rough water with GNSS-reflectometry. Correlation of L-band radiometric measurements with GPS-R data.
Examensarbete för masterexamen
Remote sensing of sea surface salinity (SSS) is a challenging task. Variations of salinity in oceans are very small, but even minor changes influence the global circulation of water, thus the environment and climate. Those variations are therefore to be monitored with the highest sensitivity possible, and one way to do this is by means of radiometry. Unfortunately, the thermal radiation that is emitted by the sea, and from the measurement of which salinity can be estimated, does not change dramatically with SSS gradients, hence the difficulty to map the global salinity distribution with high accuracy. What’s even more important is the roughness of the sea: increasing roughness leads to additional thermal radiation from the sea, but in a way that is not known and not properly accounted for. As a result, the theory used to model the emissivity of water needs empirical corrections, which can be made by investigating in which manner, and to which extent, the emission of the sea changes with geophysical parameters that characterize this roughness. Those parameters are brought by studying how the signals of the Global Navigation Satellite System (GNSS) are modified when they are reflected at the surface, and methods used to do so define the field of GNSS‐reflectometry (GNSS-R). This thesis investigates how the additional emission of the sea due to its roughness is possibly correlated to GNSS‐R observables. The data considered were collected on two different airborne campaigns, for which the instrumentation onboard was however the same (same radiometer and same GNSS reflectometer). Another campaign was organized during the thesis (different instrumentation onboard though); data of the latter will be processed in the close future, meaning that the work done during this thesis will lead to further research on the same topic. As for the results obtained from the other campaigns, they show that the emission of the sea that is due to the surface roughness is always a linear function of this roughness when correlation is observed. This observation was made for five GNSS‐R observables, out of seven investigated in total. Among those, one is computed from the combination of GNSS‐R measurements with a statistical description of the sea waves: the Mean Squared Slope (MSS). Although correlation is observed for five different observables, it turns out that it is clearest when MSS estimates are considered, indicating that the roughness of the sea is better characterized when GNSS-R measurements are combined with statistical information.
Grundläggande vetenskaper , Hållbar utveckling , Oceanografi , Elektronisk mät- och apparatteknik , Rymd- och flygteknik , Basic Sciences , Sustainable Development , Oceanography , Electronic measurement and instrumentation , Aerospace Engineering