Abstract
Abstract. Satellite sea ice concentrations (SICs), together with several ocean parameters, are assimilated into a regional Arctic coupled ocean–sea ice model covering the period of 2000–2008 using the adjoint method. There is substantial improvement in the representation of the SIC spatial distribution, in particular with respect to the position of the ice edge and to the concentrations in the central parts of the Arctic Ocean during summer months. Seasonal cycles of total Arctic sea ice area show an overall improvement. During summer months, values of sea ice extent (SIE) integrated over the model domain become underestimated compared to observations, but absolute differences of mean SIE to the data are reduced in nearly all months and years. Along with the SICs, the sea ice thickness fields also become closer to observations, providing added value by the assimilation. Very sparse ocean data in the Arctic, corresponding to a very small contribution to the cost function, prevent sizable improvements of assimilated ocean variables, with the exception of the sea surface temperature.
Highlights
The Arctic region is expected to experience a dramatic anthropogenic temperature increase over the years to come (IPCC, Stocker et al, 2014)
We show mean fluxes for AugustSeptember of year 2005 and compare them to the results of Tsubouchi et al (2012), who applied an inverse model to data obtained in summer 2005 to calculate net fluxes of volume, heat and freshwater around the Arctic Ocean boundary
Results from a multi-year data assimilation attempt based on a coupled Arctic Ocean–sea ice system were presented
Summary
The Arctic region is expected to experience a dramatic anthropogenic temperature increase over the years to come (IPCC, Stocker et al, 2014). Obtaining an improved understanding of the changing Arctic Ocean, its transport properties of heat, freshwater and carbon and nutrients, and its interaction with sea ice and the overlying atmosphere is of utmost importance. Despite recent improvements in observing capabilities (Lee et al, 2010), the Arctic Ocean remains one of the least explored areas of the world ocean. This is due both to the harsh environmental conditions of the region and logistical and political difficulties in maintaining sustained Arcticwide, ideally autonomous, ocean observations. Many polar-orbiting satellites obtain important ocean and sea ice parameters over the sub-Arctic region, such as sea surface height (SSH), sea surface temperature (SST), ocean color and sea surface salinity (SSS). To understand large-scale circulation processes in the Arctic Ocean the community will have to rely on numerical ocean circulation models due to the continued substantial undersampling of the Arctic under sea ice cover
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