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Modeling circulation and ice in the Chukchi and Beaufort Seas. Seth Danielson, UAF Enrique Curchitser, Rutgers Kate Hedstrom , UAF Tom Weingartner, UAF. Colors: Sea Surface Temperature Speckles: Ice. Outline. Description of model Some model-data comparisons

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modeling circulation and ice in the chukchi and beaufort seas

Modeling circulation and ice in the Chukchi and Beaufort Seas

Seth Danielson, UAF

Enrique Curchitser, Rutgers

Kate Hedstrom, UAF

Tom Weingartner, UAF

Colors: Sea Surface Temperature

Speckles: Ice

outline
Outline
  • Description of model
  • Some model-data comparisons
  • Ongoing development & future improvements
model setup
Model setup

Seafloor Topography

  • Pan-arctic domain
  • 50 vertical levels
  • 20-year hindcast (1985-2004)
  • Telescoping grid

3.5-7 km resolution in Chukchi-Beaufort Seas

model setup1
Model setup

Grid size (km)

  • Pan-arctic domain
  • 50 vertical levels
  • 20-year hindcast (1985-2004)
  • Telescoping grid

3.5-7 km resolution in Chukchi-Beaufort Seas

arctic ice ocean model
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
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
Model-data comparisons

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

  • SSM/I passive microwave ice concentration
  • ICESat sea ice thickness
  • Moored temperature, salinity, velocity
  • CTD hydrography
  • Satellite-tracked drifters
slide8

Sea ice concentration

observed:modeled cross-correlation

1.0

0.8

0.6

0.4

0.2

-0.2

-0.4

-0.6

-0.8

-1.0

slide9

Sea ice concentration

Averaged over Chukchi-Beaufort region

Modeled

Observed

timing of ice setup in fall
Timing of ice setup in fall

RMSD = 15.5 days

RMSD = 6.5 days

mid winter ice thickness
Mid-winter ice thickness

Model ice thickness (m)

Model – ICESat Observed (m)

  • Model ice too thin in NE Chukchi
  • Model Ice too thick along Siberian coast
slide12

Northeast Chukchi near Barrow Canyon

(site MK1, 71.1°N, 159.5°W)

slide15

Northeast Chukchi near Barrow Canyon

(site MK1, 71.1°N, 159.5°W)

next steps model improvements underway
Next Steps: model improvements underway
  • Surface forcing fromModern-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

Observed

Run #5

Run #7 (NEP6)

alaska region digital elevation model ardem1
Alaska Region Digital Elevation Model (ARDEM)

Help improve your region of interest!

ARDEM update coming in 2012-2013throughfunding from the North Pacific Research Board.

All bathymetric sounding data welcome.

sldanielson@alaska.edu

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

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

Success in many future model advances

depends on field observations

summary
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.