EGU24-12346, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Multi-frequency SAR measurements to advance snow water equivalent algorithm development

Chris Derksen1, Richard Kelly2, Benoit Montpetit1, Julien Meloche1, Vincent Vionnet3, Nicolas Leroux3, Courtney Bayer3, Aaron Thompson2, and Anna Wendleder4
Chris Derksen et al.
  • 1Environment and Climate Change Canada, Climate Research Division, Toronto, Canada
  • 2Department of Geography and Environmental Management, University of Waterloo, Canada
  • 3Environment and Climate Change Canada, Meteorological Research Division, Montreal, Canada
  • 4German Remote Sensing Data Center, German Aerospace Center, Oberpfaffenhofen, Germany

Snow mass (commonly expressed as snow water equivalent – SWE) is the only component of the water cycle without a dedicated Earth Observation mission. A number of missions currently under development, however, will provide previously unachieved coverage and resolution at frequencies ideal for retrieving SWE. These missions include a Ku-band synthetic aperture radar (SAR) mission (presently named the ‘Terrestrial Snow Mass Mission’ – TSMM) under development in Canada, and two Copernicus Expansion Missions: the Radar Observing System for Europe at L-band (ROSE-L) and the Copernicus Imaging Microwave Radiometer (CIMR). Airborne measurements are required to support SWE algorithm development for all three of these missions. In this presentation, we will present analysis of measurements from the ‘CryoSAR’ instrument, an InSAR capable L- (1.3 GHz) and Ku-band (13.5 GHz) SAR installed on a Cessna-208 aircraft.

A time series of CryoSAR measurements were acquired over open, forested, and lake sites in central Ontario, Canada during the 2022/23 winter season. These measurements were used to evaluate a new computationally efficient SWE retrieval technique based on the use of physical snow model simulations to initialize snow microstructure information in forward model simulations for prediction of snow volume scattering at Ku-band. A primary challenge is the treatment of different layers within the snowpack. We show that a k-means classifier based on snow layer properties can effectively reduce a complex snowpack to three ‘radar-relevant’ layers which conserve SWE but simplify calculation of the snow volume radar extinction coefficient. Estimation of the background contribution is based on soil information derived from lower frequency radar measurements (X-, C-, and L-band). Our collective analysis of satellite and airborne radar observations, snow physical modeling, and SWE retrievals is facilitated by the recently developed TSMM simulator, which incorporates outputs from the Environment and Climate Change Canada land surface prediction system to produce synthetic dual-frequency (13.5 and 17.25 GHz) Ku-band radar data products.

The acquisition of multi-frequency airborne radar measurements from the CryoSAR, and the integration of these observation into the TSMM simulator, provides a fundamental new capability to provide pre-cursor datasets to advance SWE algorithms in preparation for upcoming missions.

How to cite: Derksen, C., Kelly, R., Montpetit, B., Meloche, J., Vionnet, V., Leroux, N., Bayer, C., Thompson, A., and Wendleder, A.: Multi-frequency SAR measurements to advance snow water equivalent algorithm development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12346,, 2024.