1. A Regional Ice-Ocean Simulation Of the Barents and Kara Seas W. Paul Budgell Institute of Marine Research and Bjerknes Centre for Climate Research Bergen, Norway ROMS User Meeting, Venice October 18-21, 2004 IMR

2. Outline of Talk: Background Description of ice-ocean model Model set-up Simulation results Comparison with observations

3. IMR Background Region of interest is the Barents Sea Dynamical downscaling experiments First replicate present-day climate Validate with available observations

4. IMR Model Domain

5. IMR Ocean Model Component Community Regional Ocean Modelling System (ROMS) version 2.1 Terrain-following coordinate system with generalized vertical coordinate, curvilinear coordinates in horizontal Wide variety of mixing schemes available Advanced numerics, OMP and MPI parallel.

6. IMR Ocean Model Component Used 3rd-order upwind-biased horizontal advection Used piece-wise parabolic splines in vertical, spline vertical advection, spline Jacobian baroclinic pressure gradient at topography Used GLS mixing with MY2.5 parameters No explicit horizontal viscosity or diffusivity

7. IMR Ice Dynamics Ice dynamics are based upon the elastic-viscous-plastic (EVP) rheology of Hunke and Dukowicz (1997), Hunke (1991) and Hunke and Dukowicz (1992). Under low deformation (rigid behaviour), the singularity is regularized by elastic waves. The response is very similar to viscous-plastic models in typical Arctic pack ice conditions. Numerical behaviour improved significantly by applying linearization of the viscosities at every EVP time step. The EVP model parallelizes very efficiently under both OpenMP And MPI.

8. IMR Ice Thermodynamics Ice thermodynamics are based upon those of Mellor and Kantha (1989) and Häkkinen and Mellor (1992). Main features include: Three-level, single layer ice; single snow layer Molecular sublayer under ice; Prandtl-type ice-ocean boundary layer Surface melt ponds Forcing by short and long-wave radiation, sensible and latent heat flux NCEP fluxes, corrected for model surface temperature and ice concentration, used as forcing

9. IMR Model Set-up

10. IMR Model Set-up Horizontal resolution of 7.8 to 10.5 km, average of 9.3 km 32 levels in the vertical Flather (free surface) and Chapman (momentum) open boundary conditions for 2D variables Nudging + radiation condition OBCs for 3D-mom and tracers

11. IMR Boundary and Initial Conditions Tidal forcing from AOTIM Coarse model used for initialization and boundary forcing of regional model 50 km resolution in Nordic Seas/Arctic NCEP daily mean fluxes (Bentsen and Drange, 2001) used for forcing Hindcast from 1948-2002 completed, archived 5-day mean fields

12. IMR

14. Results are shown from the first year of a1990-2002 simulation SSTSST Ice ConcentrationIce Concentration

16. IMR Comparison with observations: SST from PODAAC Pathfinder AVHRR best SST, ascending (day-time) orbit, 8-day, 9-km means Ice concentration from SSM/I passive micowave, daily means Bjørnøya-Fugløya CTD sections

17. IMR SST

18. IMR Sea Ice Concentration

19. IMR Section Locations

20. IMR T - Bjørnøya-Fugløya Section - March

21. IMR T - Bjørnøya-Fugløya Section – Sept.

22. IMR S - Bjørnøya-Fugløya Section – Sept.

23. IMR Brine Drainage Spitzbergen Section

24. IMR Brine Drainage W. Novoya Zemlya Section

25. IMR Ice Production - 1993

26. IMR Ice Melt - 1993

27. IMR Conclusions Model captures seasonal variability in the Barents Good agreement with observed ice distribution Barents inflow is too cold, too fresh – OBC issue Brine rejection from ice formation produces realistic water masses ROMS captures significant portion of mesoscale variability even with 9-km resolution