1. 2005 ROMS Users Meeting Monday, October 24, 2005 Coupled sea-ice/ocean numerical simulations of the Bering Sea for the period 1996-present Enrique Curchitser Lamont Doherty Earth Observatory of Columbia U. Al Hermann NOAA Pacific Marine Environmental Laboratory Kate Hedstrom University of Alaska, Fairbanks Paul Budgell Institute for Marine Research, Bergen, Norway Institute for Marine Research, Bergen, Norway

2. Outline Motivation and background Motivation and background Ocean and sea-ice model descriptions Ocean and sea-ice model descriptions Bering sea model implementation Bering sea model implementation Results: Results: –Circulation –Sea-ice cover and thickness –Interannual variability and trends –Comparison to Barents Conclusions and future work Conclusions and future work

4. Motivation A yardstick for climate change (sea ice) A yardstick for climate change (sea ice) High primary productivity High primary productivity Significant commercial fisheries (Pollock) Significant commercial fisheries (Pollock) Comparison with other sub-Arctic seas (e.g., Barents) Comparison with other sub-Arctic seas (e.g., Barents)

6. Ocean model: ROMS Hydrostatic, free surface primitive equation model Hydrostatic, free surface primitive equation model Generalized terrain-following vertical coordinates Generalized terrain-following vertical coordinates Boundary-fitted, orthogonal curvilinear horizontal coordinates on an Arakawa C-grid Boundary-fitted, orthogonal curvilinear horizontal coordinates on an Arakawa C-grid Non-homogenous time-stepping algorithm Non-homogenous time-stepping algorithm High-order advection schemes High-order advection schemes Accurate baroclinic pressure gradient Accurate baroclinic pressure gradient Continuous, monotonic reconstruction of vertical gradients Continuous, monotonic reconstruction of vertical gradients

7. Sea-ice model Dynamics (Hunke and Duckowicz): Dynamics (Hunke and Duckowicz): – Elastic-viscous-plastic (EVP) rheology. Viscosities are linearized at every EVP time step. EVP parallelizes very efficiently Thermodynamics (Mellor and Kantha; Hakkinen and Mellor): Thermodynamics (Mellor and Kantha; Hakkinen and Mellor): –Three-level, single layer ice; single snow layer –Molecular sub-layer under ice; Prandtl-type ice-ocean boundary layer –Forcing by short- and long-wave radiation, sensible and latent heat fluxes

8. NEP Implementation: 10 km average horizontal resolution 10 km average horizontal resolution 30 vertical layers 30 vertical layers KPP vertical mixing KPP vertical mixing IC’s and BC’s from NPac IC’s and BC’s from NPac NCEP daily mean fluxes corrected for model surface temperature and ice concentration NCEP daily mean fluxes corrected for model surface temperature and ice concentration Modified short-wave radiation flux (important!) Modified short-wave radiation flux (important!)

9. Surface velocities

10. Transport in the passages Unimak—Amukta--Bering

11. Sea ice concentration: January 1997 ROMSSSM/I+

12. Sea ice concentration: January 1998 ROMSSSM/I+

13. Sea ice concentration: January 2000 ROMSSSM/I+

14. Sea ice concentration: January 2001 ROMS

15. Sea ice concentration: March 1997/1998 19971998

16. Bering/Barents comparison of total ice cover BarentsBering Model “Data”

17. Sea ice thickness: January 1996/1997 19961997

18. Lessons from a “bad” simulation: The global warming scenario NCEP (tweaked)NCEP

19. What is causing the variability in the sea ice in the (Southeastern) Bering Sea? Late formation (and early retreat) of ice in the Arctic Late formation (and early retreat) of ice in the Arctic Wind direction change Wind direction change Changes in Shortwave radiation Changes in Shortwave radiation Extra heat content on the shelf – e.g., more flow through Unimak pass Extra heat content on the shelf – e.g., more flow through Unimak pass

20. Final remarks and further work We implemented a coupled ocean/sea-ice regional model for the Bering sea We implemented a coupled ocean/sea-ice regional model for the Bering sea The model reproduces the seasonal and interannual variability in the sea-ice conditions as well as the major circulation features The model reproduces the seasonal and interannual variability in the sea-ice conditions as well as the major circulation features The Bering sea shows similar ice trends as the Barents The Bering sea shows similar ice trends as the Barents Future plans: Future plans: –Analyze the current simulation more carefully and… –Higher resolution (~3km) implementation—important for a better representation of the bathymetry and the Aleutian passages –Tides –Couple an ecosystem model

22. Sea ice concentration: January 1996 ROMS SSM/I+