Retrieval of snow and soil properties for forward radiative transfer modeling of airborne Ku-band SAR to estimate snow water equivalent: the Trail Valley Creek 2018/19 snow experiment

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 comm...

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Bibliographic Details
Published in:The Cryosphere
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: Text
Language:English
Published: 2024
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Online Access:https://doi.org/10.5194/tc-18-3857-2024
https://tc.copernicus.org/articles/18/3857/2024/
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Summary: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 (SMRT) model, 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 were 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 ( mss soil = 0.010 ± 0.002 <svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="113pt" height="12pt" class="svg-formula" dspmath="mathimg" md5hash="fe9fff5b9121d14e87b48ff1e8015a00"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="tc-18-3857-2024-ie00001.svg" width="113pt" height="12pt" src="tc-18-3857-2024-ie00001.png"/> </svg:svg> ), and it was shown that a single value could be used for the entire domain. Microwave snow grain size polydispersity ...