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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. Description of model Some model-data comparisons

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Modeling circulation and ice in the Chukchi and Beaufort Seas

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  1. 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

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

  3. 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

  4. 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

  5. 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)

  6. 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/)

  7. 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

  8. 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

  9. Sea ice concentration Averaged over Chukchi-Beaufort region Modeled Observed

  10. Timing of ice setup in fall RMSD = 15.5 days RMSD = 6.5 days

  11. 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

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

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

  14. Nearshore Beaufort Sea (McClure site, 70.3°N, 147.5°W) Landfast Ice Landfast Ice Open water

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

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

  17. 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)

  18. Alaska Region Digital Elevation Model (ARDEM)

  19. 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/

  20. 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

  21. 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.

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