Objectives

SUPSAR-Snow

Preparing Europe’s next SAR missions to better measure snow

Seasonal snow is changing fast. SUPSAR-Snow develops and validates multi-frequency SAR methods, enabling future missions like ROSE-L and Sentinel-1 FG/NG to deliver reliable snow information, including changes in snow water equivalent (ΔSWE), SWE itself, snow depth (SD), and melt/refreeze phases. We fuse C and L band (with support from X/Ku) and package the results into open software and datasets that missions and services can use right away.

What we deliver

  • ΔSWE from multi-channel InSAR (C+L): combining interferometric measurements to reduce the impact of phase wraps and decorrelation.
  • SWE from backscatter (X/Ku): SMRT-based forward modeling constrained by SVS-2/Crocus and multi-frequency decoupling of soil and snow signals.
  • Snow depth from DEM differencing: precise mutual calibration of bistatic/repeat-pass InSAR DEMs and deep-learning compensation for radar penetration bias (TanDEM-X → transfer to C/L).
  • Melt / refreeze mapping: C-band wet-snow detection plus multi-frequency refreezing-depth retrieval refined using tower radar data.
  • Open outputs: a Python Algorithm Software Package, an Input Reference Dataset Collection, experimental products, validation reports, and a Scientific Roadmap with acquisition/phase recommendations.

Why it matters

  • Water & hazards: sharper streamflow and flood outlooks from improved snow mass estimates.
  • Weather & climate: better initial snow states for models and assimilation.
  • Mission readiness: practical guidance for Sentinel & ROSE-L tasking and higher-level product design.

How it works (in brief)

  1. Consolidate science requirements & sites across tundra, alpine, boreal and agricultural snow.
  2. Build a shared dataset from towers (SodSAR, WBSCAT), airborne (CryoSAR, UAVSAR, F-SAR), and spaceborne (Sentinel-1, ALOS-2/4, TanDEM-X, RCM…).
  3. Develop & validate algorithms for ΔSWE (InSAR), SWE (backscatter), SD (DEM differencing), and melt/refreeze depth; quantify uncertainties.
  4. Deliver software & products and compare against state-of-the-art.
  5. Publish, demonstrate, recommend: roadmap for future Sentinel/ROSE-L snow products and acquisitions.

Where we work

Antarctic Peninsula & ice shelves — homogeneous areas for refreezing depth tests.

Sodankylä, Finland — dense in-situ snow & tower radars.

Austrian Alps — complex terrain testbed.

Trail Valley Creek (NWT, Canada), Powassan (ON, Canada) — varied snow/soil regimes.