The retrieval of snow properties from SLSTR Sentinel-3 – Part 2: Results and validation

Abstract. To evaluate the performance of eXtensible Bremen Aerosol/cloud and surfacE parameters Retrieval (XBAER) algorithm, presented in Part 1 companion paper to this paper, we apply XBAER algorithm Sea Land Surface Temperature Radiometer (SLSTR) instrument on board Sentinel-3. Snow properties – snow grain size (SGS), particle shape (SPS) specific surface area (SSA) are derived under cloud-free conditions. XBAER-derived compared other existing satellite products validated by ground-based aircraft measurements. The atmospheric correction is performed SLSTR for scenarios using Modern-Era Retrospective Analysis Research Applications (MERRA) aerosol optical thickness (AOT) typing strategy according standard algorithm. optimal SGS SPS estimated iteratively utilizing a look-up-table (LUT) approach, minimizing difference between SLSTR-observed SCIATRAN-simulated directional reflectances at 0.55 1.6 µm. SSA retrieved pair. SGS, have been situ measurements from recent campaign SnowEx17 during February 2017. comparison shows relative SnowEx17-measured less than 4 %. 2.7 m2/kg. can be reasonably explained SnowEx17-observed shapes. Intensive validation that (1) SSA, results show high correlation with field-based measurements, coefficients higher 0.85. root mean square errors (RMSEs) around 12 µm 6 (2) For SPS, aggregate likely matched rounded grains while single possibly linked faceted crystals. Polar Airborne Measurements Arctic Regional Climate Model Simulation Project (PAMARCMiP) held March 2018, also good agreement (with R=0.82 R=0.81 respectively). reveal variability track PAMARCMiP campaign. Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area Grain (MODSCAG) product over Greenland similar spatial distributions. geographic distribution whole campaign-based laboratory investigations, indicating reasonable retrieval accuracy SPS. variabilities both Arctic-wide agree metamorphism process.