Assimilation of radar freeboard and snow altimetry observations in the Arctic and Antarctic with a coupled ocean/sea ice modelling system

Abstract. Sea ice and snow volume are essential variables for polar predictions, but operational systems still struggle to accurately capture their evolution. Satellite measurements now provide estimates of sea ice freeboard and snow depth. The combined assimilation of sea ice concentration (SIC), along-track altimetry radar freeboard data from Cryosat-2 and observations of snow depth from Cryosat-2 and SARAL is implemented in a multivariate approach in a global ¼° ocean/sea ice coupled NEMO4.2/SI3 model. A multivariate experiment, performed on two full seasonal cycles 2017–2018, is compared to a free (no assimilation) and a SIC-only assimilation simulations. The multivariate technique increases the sea ice volume, even in the absence of freeboard and snow measurements during summer, and rapidly changes the spatial patterns of ice and snow thicknesses in both hemispheres, in accordance with the assimilated observations. The sea ice volume from the multivariate approach compares better with independent (not assimilated) estimates from IceSat-2 and CS2SMOS or SMOS in both hemispheres. The multivariate system performs better in the Arctic than in Antarctica where the ice and ocean separate analyses seem not designed to consider the strong interactions between upper oceanic layers and sea ice cover in the Southern Ocean and to prevent localised degradations. These results also confirm the importance of using variable snow and ice densities in a freeboard assimilation context. This study shows promising results for enhancing the capacity of assimilation systems to monitor the volume of sea ice and snow and paves the way for future satellite missions.