Advances in altimetric snow depth estimates using bi-frequency SARAL and CryoSat-2 Ka–Ku measurements

Abstract. Although snow depth on sea ice is a key parameter for thickness (SIT) retrieval, there currently does not exist reliable estimations. In the Arctic, nearly all SIT products use climatology (the modified Warren-99 climatology, W99m) constructed from in situ data obtained prior to first significant impacts of climate change. Antarctic, lack information remains major obstacle development products. this study, we present latest version altimetric (ASD) product computed over both hemispheres difference radar penetration into pack between Ka-band frequency SARAL/Altika and Ku-band CryoSat-2. The ASD solution compared against wide range including model (Pan-Arctic Ice-Ocean Modelling Assimilation System (PIOMAS) or its equivalent Antarctic Global Modeling (GIOMAS), MERCATOR model, NASA's Eulerian Snow On Sea Ice Model (NESOSIM, only Arctic)), Advanced Microwave Scanning Radiometer-2 (AMSR2) passive radiometer data, Dual-altimeter Thickness (DuST) Ka–Ku (only Arctic). further validated Arctic mass balance (IMB) buoys, CryoSat Validation Experiment (CryoVEx) Operation Bridge's (OIB) airborne measurements. These comparisons demonstrate that relevant solution, with spatiotemporal patterns consistent those alternative DuST but mean bias about 6.5 cm. We also validation data: OIB's during period 2014–2018 show correlation 0.66 RMSE 6 Furthermore, first-guess monthly has been product, which shows good agreement OIB 2009–2012. This shown provide better than W99m when data. Finally, have characterised uncertainty due an ensemble solutions by using different previously used comparison product. During 2013–2019, found spatially averaged standard deviation 20 Deviations estimations depths can reach up 77 Using instead estimate time leads reduction average 30