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While the primary activity of this project is organized around data collection and analyses, substantial modeling efforts are needed for better understanding the relationships between different processes. An important aspect of modeling studies is the potential to synthesize the results in terms of a dynamically consistent description of the processes and events. The model results have been used to establish the relationships between changes in the atmospheric, sea ice and oceanic conditions. To efficiently use the resources and to focus on a specific question, we have employed a hierarchy of models, ranging from a 2-D model (Proshutinsky and Johnson, 1997), to an idealized 3-D model (Proshutinsky et al., 2002) and a 3-D coupled ice-ocean model (Karcher et al., 2002, see also Arctic Ocean Model Intercomparison web site and the EOS paper by Proshutinsky et al. [2005]). The 2-D model has been used to update the Arctic Ocean Oscillation index (AOO; Proshutinsky and Johnson, 1997; Proshutinsky et al., 2015) in order to continue analyzing Beaufort Gyre (BG) circulation modes: for comparison with the AO index and to predict the location of the BG center for expedition planning (see description of Arctic Oscillation Index in section “Results”,

In order to test different ideas related to oceanic physics and interactions between sea ice and ocean we  used a version of Sirpa Häkkinen’s model (Häkkinen, 1993). A similar approach was used by Proshutinsky et al. (2002), where processes of FW accumulation and release in the BG were tested in a rectangular basin with a very simple bathymetry. The development of the three-dimensional fields in time was simulated by Hakkinen and Proshutinsky (2003) with the coupled ocean-sea ice general circulation model forced with realistic atmospheric factors over the last 50 years. We have also employed two versions of the NAOSIM (North Atlantic-Arctic Ocean-Sea Ice Model) family of models developed at the Alfred Wegener Institute. High resolution NAOSIM model results are shown in an EOS paper (Proshutinsky et al., 2005). This model provides the best results among all of the AOMIP models.

The ability of the models to synthesize greater aspects of the project depends crucially on the quality of the model results. The analysis of the hindcast simulations include but are not restricted to: detailed heat and FW balance for the BG that includes transports across the boundaries, storage of heat and salt, and local surface fluxes; water mass transformation rates inside the BG; variability of stratification and surface buoyancy fluxes; relationship of convection with the heat release to atmosphere, exchange with boundary currents, and transport rates and properties of water masses; freshwater fluxes to the rest of the Arctic Ocean and its redistribution depending on climate modes.

The most recent accomplishments in teh Beaufort Gyre modeling studies are described on the FAMOS project websites, Forum for Arctive Modeling and Synthesis and FAMOS.


Proshutinsky, A., J. Yang, R. Krishfield, R. Gerdes, M. Karcher, F. Kauker, C. Koeberle, S. Hakkinen, W. Hibler, D. Holland, M. Maqueda, G. Holloway, E. Hunke, W. Maslowski, M. Steele, and J. Zhang (2005), Arctic Ocean Study: Synthesis of Model Results and Observations, EOS, 86 (40), 368-371.
Häkkinen S., A. Proshutinsky (2004), Freshwater content variability in the Arctic Ocean, J. Geophys. Res., 109, C03051, doi:10.1029/2003JC001940.
Proshutinsky, A., R. H. Bourke, and F. A. McLaughlin (2002), The role of the Beaufort Gyre in Arctic climate variability: Seasonal to decadal climate scales, Geophys. Res. Lett., 29(23), 2100, doi:10.1029/2002GL015847.