Supplementary material to "Advances in altimetric snow depth estimates using bi-frequency SARAL/CryoSat-2 Ka/Ku measurements"

Abstract. Although snow depth on sea ice is a key parameter for Sea Ice Thickness (SIT), there currently does not exist reliable estimations. In Arctic, nearly all SIT products use a snow depth climatology (the Warren-99 modified climatology, W99m) constructed from in-situ data obtained prior to the first significant impacts of climate change. In Antarctica, the lack of information on snow depth remains a major obstacle in the development of reliable SIT products. In this study, we present the latest version of the Altimetric Snow Depth (ASD) product computed over both hemispheres from the difference of the radar penetration into the snow pack between the CryoSat-2 Ku-band and the SARAL Ka-band frequency radars. The ASD solution is compared against a wide range of snow depth products including model data (Pan-Arctic Ice-Ocean Modeling and Assimilation System (PIOMAS) or its equivalent in Antarctica the Global Ice-Ocean Modeling and Assimilation System (GIOMAS), the MERCATOR model and NASA's Eulerian Snow On Sea Ice Model (NESOSIM, only in Arctic)), the Advanced Microwave Scanning Radiometer 2 (AMSR-2) passive radiometer data, and the Dual-altimeter Snow Thickness (DuST) Ka-Ku product (only in Arctic). It is validated in the Arctic against in-situ and airborne validation data. These comparisons demonstrate that ASD provide a consistent snow depth solution, with space and time patterns comparable with those of the alternative Ka-Ku DuST product, but with a mean bias of about 6.5 cm. We also demonstrate that ASD is consistent with the validation data. Comparisons with Operation Ice Bridge's (OIB) airborne snow radar in Arctic during the period of 2014–2018 show a correlation of 0.66 and a RMSE of about 6 cm. Furthermore, a first-guess monthly climatology has been constructed in Arctic from the ASD product, which shows a good agreement with OIB during 2009–2012. This climatology is shown to provide a better solution than the W99m climatology when compared with validation data. Finally, we have characterised the SIT uncertainty due to the snow depth from an ensemble of SIT solutions computed for the Arctic by using the different snow depth products previously used in the comparison with the ASD product. During the period of 2013–2019, we found a spatially averaged SIT mean standard deviation of 20 cm. Deviations between SIT estimations due to different snow depths can reach up to 77 cm. Using the ASD data instead of W99m to estimate SIT over this time period leads to a reduction of the average SIT of about 30 cm.