Assimilation of synthetic observations of radar backscatters at Ku-band improves SWE estimates

Leroux, Nicolas R.; Vionnet, Vincent; Bayer, Courtney; Meloche, Julien; Dirkson, Arlan; Lespinas, Franck; Buehner, Mark; Carrera, Marco; Montpetit, Benoit; Bilodeau, Bernard; Abrahamowicz, Maria; Derksen, Chris

doi:10.5194/tc-20-2773-2026

Articles | Volume 20, issue 5

https://doi.org/10.5194/tc-20-2773-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-20-2773-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 5

Research article

|

19 May 2026

Research article |

| 19 May 2026

Assimilation of synthetic observations of radar backscatters at Ku-band improves SWE estimates

Nicolas R. Leroux, Vincent Vionnet, Courtney Bayer, Julien Meloche, Arlan Dirkson, Franck Lespinas, Mark Buehner, Marco Carrera, Benoit Montpetit, Bernard Bilodeau, Maria Abrahamowicz, and Chris Derksen

Supplement

https://doi.org/10.5194/tc-20-2773-2026-supplement

Model code and software

Code of the Soil Vegetation and Snow version 2 (SVS2) coupled with the Snow Microwave Radiative Transfer model (SMRT) within the The Multiple Snow Data Assimilation System (MuSA) N. R. Leroux et al. https://doi.org/10.5281/zenodo.17662807

Code of the land surface scheme Soil Vegetation and Snow version 2 integrated in the MESH platform (v1.0.0) V. Vionnet et al. https://doi.org/10.5281/zenodo.14859639

Short summary

This study evaluates the assimilation of Ku-band radar backscatter into a multilayer snowpack model to support the upcoming Terrestrial Snow Mass Mission. Synthetic experiments were conducted at Arctic, continental, and alpine sites over three winters using a particle filter. Results show that assimilating backscatter improves estimates of snow water equivalent, depth, and vertical snow properties, laying the groundwork for future satellite missions focused on radar-based snow monitoring.