Snow and Ice Thickness Retrievals Using GNSS-R: Preliminary Results of the MOSAiC Experiment

• Published in: Remote Sensing
• Main Authors: Joan Francesc Munoz-Martin, Adrian Perez, Adriano Camps, Serni Ribó, Estel Cardellach, Julienne Stroeve, Vishnu Nandan, Polona Itkin, Rasmus Tonboe, Stefan Hendricks, Marcus Huntemann, Gunnar Spreen, Massimiliano Pastena
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2020
• Subjects: GNSS-R; sea-ice; arctic; snow; Arctic; Arctic Ocean; Alfred Wegener Institute; Climate change; Sea ice
• Online Access: https://doi.org/10.3390/rs12244038

The FSSCat mission was the 2017 ESA Sentinel Small Satellite (S⌃3) Challenge winner and the Copernicus Masters competition overall winner. It was successfully launched on 3 September 2020 onboard the VEGA SSMS PoC (VV16). FSSCat aims to provide coarse and downscaled soil moisture data and over polar regions, sea ice cover, and coarse resolution ice thickness using a combined L-band microwave radiometer and GNSS-Reflectometry payload. As part of the calibration and validation activities of FSSCat, a GNSS-R instrument was deployed as part of the MOSAiC polar expedition. The Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition was an international one-year-long field experiment led by the Alfred Wegener Institute to study the climate system and the impact of climate change in the Arctic Ocean. This paper presents the first results of the PYCARO-2 instrument, focused on the GNSS-R techniques used to measure snow and ice thickness of an ice floe. The Interference Pattern produced by the combination of the GNSS direct and reflected signals over the sea-ice has been modeled using a four-layer model. The different thicknesses of the substrate layers (i.e., snow and ice) are linked to the position of the fringes of the interference pattern. Data collected by MOSAiC GNSS-R instrument between December 2019 and January 2020 for different GNSS constellations and frequencies are presented and analyzed, showing that under general conditions, sea ice and snow thickness can be retrieved using multiangular and multifrequency data.