Numerical sensitivity studies on the variability of climate-relevant processes in the Barents Sea

2005 
[1] The Barents Sea is a key region in the North Atlantic/Arctic Ocean climate system because of the intense ocean-atmosphere heat exchange and the formation of sea ice. The latter process is connected with salt input, so-called “brine release,” whereby water masses of Atlantic origin can be transformed into dense shelf bottom waters. To investigate the sensitivity of simulated, climate-relevant processes to different but well-established and realistic initial and boundary data, a high-resolution coupled ice-ocean model is applied to the Barents Sea. The model is based on the Hamburg Shelf Ocean Model and runs on a 7 × 7 km grid, based on the International Bathymetric Chart of the Arctic Ocean topography. The model is initialized with different temperature and salinity data from the Arctic Climate System Study BarKode data set and is forced with National Centers for Environmental Prediction atmospheric data. Eight sensitivity experiments with initial and boundary conditions in different combinations are performed over a period of 6 years (1979–1984). Results are analyzed with special emphasis on the ocean-atmosphere heat exchange, the ice extent, and the brine release. The experimental variability is compared to the interannual climatic variability in order to assess the role of different forcing terms for regional climate modeling. Our results show that the experimental variability can be partly of the same order than the interannual variability, which suggests that data uncertainties could easily bias the results of climate variability studies. Modification of the Barents Sea inflow had the strongest effect on model results. The ocean-atmosphere heat flux proved to be the most sensitive parameter to oceanic and atmospheric anomalies, whereas the ice extent and the corresponding salt input is more invariant to different boundary conditions.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    27
    References
    24
    Citations
    NaN
    KQI
    []