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Abstract. To evaluate the performance of the eXtensible Bremen Aerosol/cloud and surfacEparameters Retrieval (XBAER) algorithm, presented in the Part 1 companion paper to this paper, we apply the XBAER algorithm to the Sea and LandSurface Temperature Radiometer (SLSTR) instrument on board Sentinel-3. Snowproperties – snow grain size (SGS), snow particle shape (SPS) and specificsurface area (SSA) – are derived under cloud-free conditions. XBAER-derivedsnow properties are compared to other existing satellite products andvalidated by ground-based and aircraft measurements. The atmosphericcorrection is performed on SLSTR for cloud-free scenarios using Modern-EraRetrospective Analysis for Research and Applications (MERRA) aerosol opticalthickness (AOT) and the aerosol typing strategy according to the standard XBAERalgorithm. The optimal SGS and SPS are estimated iteratively utilizing alook-up-table (LUT) approach, minimizing the difference betweenSLSTR-observed and SCIATRAN-simulated surface directional reflectances at0.55 and 1.6 µm. The SSA is derived for a retrieved SGS and SPS pair.XBAER-derived SGS, SPS and SSA have been validated using in situ measurements fromthe recent campaign SnowEx17 during February 2017. The comparison shows arelative difference between the XBAER-derived SGS and SnowEx17-measured SGS ofless than 4 %. The difference between the XBAER-derived SSA and SnowEx17-measured SSA is 2.7 m2/kg. XBAER-derived SPS can bereasonably explained by the SnowEx17-observed snow particle shapes. Intensive validation shows that (1) for SGS and SSA, XBAER-derived resultsshow high correlation with field-based measurements, with correlationcoefficients higher than 0.85. The root mean square errors (RMSEs) of SGS andSSA are around 12 µm and 6 m2/kg. (2) For SPS, aggregate SPSretrieved by XBAER algorithm is likely to be matched with rounded grainswhile single SPS in XBAER is possibly linked to faceted crystals. The comparison with aircraft measurements, during the Polar AirborneMeasurements and Arctic Regional Climate Model Simulation Project(PAMARCMiP) campaign held in March 2018, also shows good agreement (withR=0.82 and R=0.81 for SGS and SSA, respectively). XBAER-derived SGS andSSA reveal the variability in the aircraft track of the PAMARCMiP campaign. Thecomparison between XBAER-derived SGS results and the Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area andGrain size (MODSCAG) product over Greenland shows similar spatialdistributions. The geographic distribution of XBAER-derived SPS overGreenland and the whole Arctic can be reasonably explained by campaign-basedand laboratory investigations, indicating a reasonable retrieval accuracy ofthe retrieved SPS. The geographic variabilities in XBAER-derived SGS and SSAboth over Greenland and Arctic-wide agree with the snow metamorphismprocess.

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