Analysis and Validation of the UK-DMC GPS-Reflectometry Dataset from the WaveSentry Project for Sea State Monitoring
Clarizia, Maria Paola1; Gommenginger, Christine2; Jales, Philip3; Unwin, Martin3; Robertson, Colette2; Jelenak, Zorana4; Ruf, Christopher5
1National Oceanography Centre (NOC), Southampton UK / University of Michigan Ann Arbor US, UNITED KINGDOM; 2National Oceanography Centre (NOC), Southampton, UNITED KINGDOM; 3Surrey Satellite Technology Ltd (SSTL), UNITED KINGDOM; 4National Oceanic and Atmospheric Administration (NOAA), UNITED STATES; 5Atmospheric Oceanic and Space Science (AOSS), University of Michigan, UNITED STATES
Global Navigation Satellite System-Reflectometry (GNSS-R) exploits signals of opportunity from navigation constellations (e.g. GPS, GLONASS, Galileo), scattered by the surface of the ocean, to retrieve the surface wind and wave fields. GNSS-R represents a true innovation in remote sensing, and it is receiving a growing interest from the scientific community. Its main advantages lie in the dense space-time sampling capabilities, the ability of L-band signals to penetrate well through rain, and the possibility of simple, low-cost/low-power GNSS receivers. While numerous airborne GNSS-R campaigns have been carried out in the last decade, the first and still unique proof-of-concept for spaceborne GNSS-R was first demonstrated in the pioneering GPS-R experiment carried out by Surrey Satellite Technology Ltd (SSTL), onboard the UK-Disaster Monitoring Constellation (UK-DMC) satellite. Following the successful exploitation of a small number of UK-DMC GPS-R datasets for sea surface roughness retrieval [Clarizia et al., 2009], the complete set of UK-DMC GPS-R acquisitions (including reflections from multiple specular points within a single acquisition) has been recently re-processed, with improvements in the processing chain, and made available to retrieve information about wind and waves on the surface. This reprocessing and analysis has been carried out within the WaveSentry Project, funded by the Technology Strategy Board (TSB), which aimed at harvesting, processing and validating satellite GNSS-R data, to ingest them in an integrated sea state information system, for the management of marine operations in adverse sea states. Here we present the outcome of the retrieval of sea state information (directional mean square slopes) from the entire reprocessed UK-DMC dataset, by adopting the Delay-Doppler Map (DDM) least-square fitting approach presented in Clarizia et al. . Results from GPS-R data are validated against a number of independent collocated sources of wind and wave information. These include NDBC buoys, measurements from other satellites (i.e. scatterometers, altimeters), and outputs from wave models. The results presented in this study confirm the evidence already shown in Clarizia et al.  that wind and waves can be retrieved from GPS-R data, but they also highlight the need for better statistical characterization of the retrievals, which can only be achieved if more spaceborne data are made available. Luckily, these improvements are expected to happen in the near future, as a result of two new GNSS-R satellite missions, TechDemoSat-1 and CYGNSS, which should contribute significantly to the amount of spaceborne GNSS-R data available for sea state monitoring.