Surface reflectivity in polar regions retrieved from TDS-1 mission data

• Main Authors: Kreß, Fredrik, Semmling, Maximilian, Cardellach, Estel, Li, Weiqiang, Hoque, Mainul M., Wickert, Jens
• Format: Conference Object
• Language: unknown
• Published: 2021
• Subjects: Antarctic; Arctic; Expuesta; Antarc*; Sea ice
• Online Access: http://hdl.handle.net/10261/270336; https://doi.org/10.5194/egusphere-egu21-13036

Comunicación expuesta online en el 23rd EGU General Assembly (2021) el 26 de abril In current times of a changing global climate, a special interest is focused on thelarge-scale recording of sea ice. Among the existing remote sensing methods, bi-statically reflected signals of Global Navigation Satellite Systems (GNSS) couldplay an important role in fulfilling the task. Within this project, sensitivity ofGNSS signal reflections to sea ice properties like its occurrence, sea ice thick-ness (SIT) and sea concentration (SIC) is evaluated. When getting older, seaice tends go get thicker. Because of decreasing salinity, i.e. less permittivity,as well as relatively higher surface roughness of older ice, it can be assumedthat reflected signal strength decreases with increasing SIT. The reflection dataused were recorded in the years 2015 and 2016 by the TechDemoSat-1 (TDS-1)satellite over the Arctic and Antarctic. It includes a down-looking antenna forthe reflected as well as an up-looking antenna dedicated to receive the direct sig-nal. The raw data, provided by the manufacturer SSTL, were pre-processed byIEEC/ICE-CSIC to derive georeferenced signal power values. The reflectivitywas estimated by comparing the power of the up- and down-looking links. Theproject focuses on the signal link budget to apply necessary corrections. For thisreason, the receiver antenna gain as well as the Free-Space Path Loss (FSPL)were calculated and applied for reflectivity correction. Differences of nadir andzenith antenna FSPL and gain show influence of up to 6 dB and ‑9 dB to 9 dBrespectively on the recorded signal strength. All retrieved reflectivity values arecompared to model predictions based on Fresnel coefficients but also to avail-able ancillary truth data of other remote sensing missions to identify possiblepatterns: SIT relations are investigated using Level-2 data of the Soil Moistureand Ocean Salinity (SMOS) satellite. The SIC comparison was done with anAMSR-2 product. The results show sensitivity of the reflectivity value to ...