Assimilation of SMOS sea ice thickness in the regional ice prediction system

摘要

Sea ice thickness (SIT) is an under-represented essential climate variable in most regional and global climate models even today. This paper presents the assimilation of SIT observations from the Soil Moisture and Ocean Salinity (SMOS) mission in the Regional Ice Prediction System in a three-dimensional variational data assimilation system. For the first time, the model uses 10 sea ice categories and SIT redistribution within the model grid. A new SIT redistribution algorithm overcomes difficulties related to grids with partial ice and water, and high SIT values. The assimilation leads to a small improvement in the background state; however, the regions dominated by thick ice did not suggest satisfactory assimilation results attributed to several factors associated with the SIT retrieval techniques from the SMOS observations. The averaged analysis minus the observed root mean square error of all assimilation cycles, 0.11 m, i.e. about 20% of the maximum retrievable SMOS SIT looks reasonable.