Retrieval of airborne Ku-Band SAR Using Forward Radiative Transfer Modeling to Estimate Snow Water Equivalent: The Trail Valley Creek 2018/19 Snow Experiment

• Main Authors: Montpetit, Benoit, King, Joshua, Meloche, Julien, Derksen, Chris, Siqueira, Paul, Adam, J. Max, Toose, Peter, Brady, Mike, Wendleder, Anna, Vionnet, Vincent, Leroux, Nicolas R.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2024
• Subjects: article; Verlagsveröffentlichung; Canada; Northwest Territories; Trail Valley Creek; Valley Creek; Tundra
• Online Access: https://doi.org/10.5194/egusphere-2024-651; https://noa.gwlb.de/receive/cop_mods_00072246; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00070469/egusphere-2024-651.pdf; https://egusphere.copernicus.org/preprints/2024/egusphere-2024-651/egusphere-2024-651.pdf

Accurate snow information at high spatial and temporal resolution is needed to support climate services, water resource management, and environmental prediction services. However, snow remains the only element of the water cycle without a dedicated Earth Observation mission. The snow scientific community has shown that Ku-Band radar measurements provide quality snow information with its sensitivity to snow water equivalent and the wet/dry state of snow. With recent developments of tools like the Snow MicroPenetrometer (SMP) to retrieve snow microstructure data in the field and radiative transfer models like the Snow Microwave Radiative Transfer Model (SMRT), it becomes possible to properly characterize the snow and how it translates into radar backscatter measurements. An experiment at Trail Valley Creek (TVC), Northwest Territories, Canada was conducted during the winter of 2018/19 in order to characterize the impacts of varying snow geophysical properties on Ku-Band radar backscatter at a 100-m scale. Airborne Ku-Band data was acquired using the University of Massachusetts radar instrument. This study shows that it is possible to calibrate SMP data to retrieve statistical information on snow geophysical properties and properly characterize a representative snowpack at the experiment scale. The tundra snowpack measured during the campaign can be characterize by two layers corresponding to a rounded snow grain layer and a depth hoar layer. Using Radarsat-2 and TerraSAR-X data, soil background roughness properties were retrieved (msssoil = 0.010±0.002) and it was shown that a single value could be used for the entire domain. Microwave snow grain size polydispersity values of 0.74 and 1.11 for rounded and depth hoar snow grains, respectively, was retrieved. Using the Geometrical Optics surface backscatter model, the retrieved effective soil permittivity increased from C-Band (εsoil = 2.47) to X-Band (εsoil = 2.61), to Ku-Band (εsoil = 2.77) for the TVC domain. Using SMRT and the retrieved soil and snow ...