Better constraints on the sea-ice state using global sea-ice data assimilation

摘要

Short-term and decadal sea-ice prediction systems need a realistic initialstate, generally obtained using ice–ocean model simulations with dataassimilation. However, only sea-ice concentration and velocity data arecurrently assimilated. In this work, an ensemble Kalman filter system is usedto assimilate observed ice concentration and freeboard (i.e. thickness ofemerged) data into a global coupled ocean–sea-ice model. The impact andeffectiveness of our data assimilation system is assessed in two steps:firstly, through the use of synthetic data (i.e. model-generated data), andsecondly, through the assimilation of real satellite data. While iceconcentrations are available daily, freeboard data used in this study areonly available during six one-month periods spread over 2005–2007. Ourresults show that the simulated Arctic and Antarctic sea-ice extents areimproved by the assimilation of synthetic ice concentration data.Assimilation of synthetic ice freeboard data improves the simulated sea-icethickness field. Using real ice concentration data enhances the model realismin both hemispheres. Assimilation of ice concentration data significantlyimproves the total hemispheric sea-ice extent all year long, especially insummer. Combining the assimilation of ice freeboard and concentration dataleads to better ice thickness, but does not further improve the ice extent.Moreover, the improvements in sea-ice thickness due to the assimilation ofice freeboard remain visible well beyond the assimilation periods.