Global Navigation Satellite System Reflectometry (GNSS-R) has come of age. Two decades after the first spaceborne demonstrations, and almost a decade into the CYGNSS mission, GNSS-R has moved to a established source of Earth observation, with a growing constellation of missions delivering frequent and all-weather observations of ocean winds and sea state, soil moisture, freeze/thaw, inundation and wetlands, snow and sea ice, and vegetation. The recent launch of HydroGNSS, ESA's first Scout mission and the first GNSS-R mission dedicated to the terrestrial water cycle, marks the start of a new phase in which GNSS-R can address Earth system science questions at the scale, quality, and continuity required for operational monitoring and modeling.
Until now, GNSS-R contributions at EGU have been distributed across sessions. This session, the first at EGU dedicated to GNSS-R, brings this community together in one place and shifts the emphasis from the technique to its use. Its focus is on how GNSS-R observations, alone and in combination with other satellite and ground-based data, advance understanding of the hydrosphere, cryosphere, atmosphere, biosphere, and ocean, and how they are integrated into Earth system models to constrain water, energy, and carbon exchanges and to improve weather, hydrological, and climate prediction.
We welcome, but do not limit, contributions on:
• First results, validation, and early science from HydroGNSS
• Monitoring of soil moisture, floods and wetlands, snow, sea ice, freeze-thaw, permafrost, and vegetation with GNSS-R
• Ocean surface winds, sea state, and extreme events such as tropical cyclones observed with GNSS-R
• Assimilation of GNSS-R products into land surface, hydrological, ocean, weather, and climate models
• AI-based data fusion, gap filling, and emulation of forward models, as well as integration of GNSS-R into AI-based weather and Earth system models
• Use of GNSS-R for model evaluation, parameter calibration, and process understanding
• Synergy of GNSS-R with passive microwave, SAR, altimetry, optical, and in-situ observations
• Long-term records, product intercomparison, and machine learning approaches bridging observations and models
• Airborne GNSS-R supporting Earth system applications
• Perspectives on future GNSS-R missions and the role of GNSS-R in the multi-mission Earth observing system