Modeling circulation and ice in the Chukchi and Beaufort Seas

Seth Danielson, UAFEnrique Curchitser, RutgersKate Hedstrom, UAFTom Weingartner, UAF

Colors: Sea Surface TemperatureSpeckles: Ice

Outline

• Description of model• Some model-data comparisons• Ongoing development & future improvements

Model setup

• Pan-arctic domain• 50 vertical levels• 20-year hindcast

(1985-2004)• Telescoping grid

3.5-7 km resolution in Chukchi-Beaufort Seas

Seafloor Topography

Model setup

• Pan-arctic domain• 50 vertical levels• 20-year hindcast

(1985-2004)• Telescoping grid

3.5-7 km resolution in Chukchi-Beaufort Seas

Grid size (km)

Arctic ice-ocean model• Built on the Regional Ocean Modeling System (ROMS)• Oceanic boundary and initial conditions from the Simple Ocean

Data Assimilation (SODA) reanalysis• Surface forcing from Common Ocean Reference Experiment

(CORE-2)• Air-sea fluxes computed via bulk formulae• Monthly and inter-annually varying river discharge from Dai and

Trenberth (2002)• Dynamic-thermodynamic sea ice model following Budgell (2005)

Sea ice component• Dynamic-thermodynamic sea ice model implementation of Budgell

(2005)• Elastic-Viscous-Plastic (EVP) following Hunke and Dukowicz (1997)

and Hunke (2001)• Thermodynamics following Mellor and Kantha (1989) and Hakkinen

and Mellor (1992)• Frazil ice production following Steele et al., (1989)

• Imposition of landfast ice extent in the Beaufort Sea following monthly climatology of Mahoney et al. (2006; http://mms.gina.alaska.edu/)

Model-data comparisons

• SSM/I passive microwave ice concentration• ICESat sea ice thickness• Moored temperature, salinity, velocity• CTD hydrography• Satellite-tracked drifters

No data assimilation: we can use a wide variety of historical data to independently assess performance.

Sea ice concentration observed:modeled cross-correlation

1.00.80.60.40.2

-0.2-0.4-0.6-0.8-1.0

Sea ice concentration Averaged over Chukchi-Beaufort region

Modeled Observed

Timing of ice setup in fall

RMSD = 15.5 days RMSD = 6.5 days

Mid-winter ice thicknessModel – ICESat Observed (m)

• Model ice too thin in NE Chukchi • Model Ice too thick along Siberian coast

Model ice thickness (m)

Northeast Chukchi near Barrow Canyon (site MK1, 71.1°N, 159.5°W)

Northeast Chukchi Offshore (site C2, 71.3°N, 164.5°W)

Landfast Ice Open water

Nearshore Beaufort Sea (McClure site, 70.3°N, 147.5°W)

Landfast Ice

Northeast Chukchi near Barrow Canyon (site MK1, 71.1°N, 159.5°W)

Nearshore Beaufort Sea (Dinkum site, 70.4°N, 147.95°W)

ObservedRun #5 Run #7 (NEP6)

• Surface forcing from Modern-Era Retrospective Analysis for Research and Applications (MERRA)

• Northeast Pacific (NEP6) regional hindcast used for oceanic boundary conditions in Bering Strait

• Improved bathymetric Digital Elevation Models

Next Steps: model improvements underway

Alaska Region Digital Elevation Model

(ARDEM)

Help improve your region of interest!ARDEM update coming in 2012-2013 through

funding from the North Pacific Research Board.

All bathymetric sounding data welcome.sldanielson@alaska.edu

Alaska Region Digital Elevation Model

(ARDEM)

http://mather.sfos.uaf.edu/~seth/bathy/

Next steps: toward ice/ocean model improvements and operational applications

Success in many future model advances depends on field observations

• Algorithm development and testing:• Growth and breakup of landfast ice• Melt pond dynamics… ice algae?• Wind-ice-ocean-oil interactions• Merge ice/ocean components… ice shelf approach?• Surface heat flux algorithms for ice-infested waters

• Model validation through community-based ocean monitoring. • Real-time nowcast/forecast ice-ocean models could inform industry,

regulators, scientific research programs and emergency response efforts.

Summary• Model strengths include:

– Capturing seasonal changes in nearshore Beaufort Sea – Wind-driven flows– Reproduction of sea ice concentration anomalies

• Model weaknesses include:– Mid-winter ice thickness: too thin in the northeast Chukchi,

too thick along the Siberian Coast– Insufficient summer ice melt or too much winter ice growth

• The data-model comparisons continue to guide model development efforts by identifying features and sub-grid scale processes that require better parameterizations.