• ACIA, 2005: Arctic Climate Impact Assessment. Cambridge University Press, 1042 pp.

  • Agnew, T., , B. Alt, , R. D. Abreu, , and S. Jeffers, 2001: The loss of decades old sea ice plugs in the Canadian Arctic Islands. Extended Abstracts, Sixth Conf. on Polar Meteorology and Oceanography, San Diego, CA, Amer. Meteor. Soc., 1.5.

  • Agnew, T., , A. Lambe, , and D. Long, 2008: Estimating sea ice area flux across the Canadian Arctic Archipelago using enhanced AMSR-E. J. Geophys. Res., 113 , C10011. doi:10.1029/2007JC004582.

    • Search Google Scholar
    • Export Citation
  • Barber, D. G., , and J. M. Hanesiak, 2004: Meteorological forcing of sea ice concentrations in the southern Beaufort Sea over the period 1979 to 2000. J. Geophys. Res., 109 , C06014. doi:10.1029/2003JC002027.

    • Search Google Scholar
    • Export Citation
  • Bourke, R. H., , and R. P. Garrett, 1987: Sea ice thickness distribution in the Arctic Ocean. Cold Reg. Sci. Technol., 13 , 259280.

  • Bromwich, D. H., , R. L. Fogt, , K. I. Hodges, , and J. E. Walsh, 2007: A tropospheric assessment of the ERA-40, NCEP, and JRA-25 global reanalyses in the polar regions. J. Geophys. Res., 112 , D10111. doi:10.1029/2006JD007859.

    • Search Google Scholar
    • Export Citation
  • Brown, R. D., , and P. Cote, 1992: Interannual variability of landfast ice thickness in the Canadian High Arctic, 1950–89. Arctic, 45 , 273284.

    • Search Google Scholar
    • Export Citation
  • Bryan, K., 1969: A numerical method for the study of the circulation of the world ocean. J. Comput. Phys., 4 , 347376.

  • CIS, 2002: Sea Ice Climatic Atlas: Northern Canadian Waters, 1971–2000. Canadian Ice Service–Environment Canada, 262 pp.

  • Curry, J. A., , J. L. Schramm, , A. Alam, , R. Reeder, , T. E. Arbetter, , and P. Guest, 2002: Evaluation of data sets used to force sea ice models in the Arctic Ocean. J. Geophys. Res., 107 , 8027. doi:10.1029/2000JC000466.

    • Search Google Scholar
    • Export Citation
  • Derocher, A., , N. Lunn, , and I. Stirling, 2004: Polar bears in a warming climate. Integr. Comput. Biol., 44 , 163176.

  • Dey, B., 1981: Monitoring winter sea ice dynamics in the Canadian Arctic with NOAA-TIR images. J. Geophys. Res., 86 , 32233235.

  • Dumas, J. A., , G. M. Flato, , and R. D. Brown, 2006: Future projections of landfast ice thickness and duration in the Canadian Arctic. J. Climate, 19 , 51755189.

    • Search Google Scholar
    • Export Citation
  • Dumas, J. A., , H. Melling, , and G. M. Flato, 2007: Late-summer pack ice in the Canadian Archipelago: Thickness observations from a ship in transit. Atmos.–Ocean, 45 , 5770.

    • Search Google Scholar
    • Export Citation
  • ESA, cited. 2007: Satellites witness lowest Arctic ice coverage in history. [Available online at http://www.esa.int/esaCP/SEMYTC13J6F_index_0.html.].

    • Search Google Scholar
    • Export Citation
  • Flato, G. M., , and R. D. Brown, 1996: Variability and climate sensitivity of landfast Arctic sea ice. J. Geophys. Res., 101 , (C10). 2576725777.

    • Search Google Scholar
    • Export Citation
  • Flato, G. M., , and G. Boer, 2001: Warming asymmetry in climate change simulations. Geophys. Res. Lett., 28 , 195198.

  • Hibler III, W. D., 1979: A dynamic thermodynamic sea ice model. J. Phys. Oceanogr., 9 , 815846.

  • Holland, D., 2000: Merged IBCAO/ETOPO5 topography (AOMIP). Center for Atmosphere–Ocean Studies (CA/OS) of the Courant Institute of Mathematical Sciences Tech. Rep. [Available online at http://efdl.cims.nyu.edu/project_aomip/forcing_data/topography/merged/overview.html.].

    • Search Google Scholar
    • Export Citation
  • Holland, D. M., cited. 2000: Merged IBCAO/ETOPO5 global topographic data product. National Geophysical Data Center (NGDC), Boulder, Colorado. [Available online at http://www.ngdc.noaa.gov/mgg/bathymetry/arctic/ibcaorelatedsites.html.].

    • Search Google Scholar
    • Export Citation
  • Holland, M. N., , and C. M. Bitz, 2003: Polar amplification of climate change in coupled models. Climate Dyn., 21 , 221232.

  • Holland, M. N., , C. M. Bitz, , and B. Tremblay, 2006: Future abrupt reductions in the summer Arctic sea ice. Geophys. Res. Lett., 33 , L23503. doi:10.1029/2006GL028024.

    • Search Google Scholar
    • Export Citation
  • Holloway, G., 1992: Representing topographic stress for large-scale ocean models. J. Phys. Oceanogr., 22 , 10331046.

  • Holloway, G., , and T. Sou, 2002: Has Arctic sea ice rapidly thinned? J. Climate, 15 , 16911701.

  • Houghton, J. T., , Y. Ding, , D. J. Griggs, , M. Noguer, , P. J. van der Linden, , X. Dai, , K. Maskell, , and C. A. Johnson, and Eds., 2001: Climate Change 2001: The Scientific Basis. Cambridge University Press, 881 pp.

    • Search Google Scholar
    • Export Citation
  • Howell, S. E. L., , A. Tivy, , J. J. Yackel, , and S. McCourt, 2008: Multi-Year Sea Ice Conditions in the Western Canadian Arctic Archipelago Region of the Northwest Passage: 1968–2006. Atmos.–Ocean, 46 , 229242. doi:10.3137/ao.460203.

    • Search Google Scholar
    • Export Citation
  • Huebert, R., 2001: Climate change and Canadian sovereignty in the Northwest Passage. Isuma: Can. J. Policy Res., 2 , 8694.

  • Hulme, M., , E. M. Barrow, , N. W. Arnell, , P. A. Harrison, , T. C. Johns, , and T. E. Downing, 1999: Relative impacts of human-induced climate change and natural climate variability. Nature, 397 , 688691.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437471.

  • Kauker, F., , R. Gerdes, , M. Karcher, , C. Köberle, , and J. L. Lieser, 2003: Variability of Arctic and North Atlantic sea ice: A combined analysis of model results and observations from 1978 to 2001. J. Geophys. Res., 108 , 3182. doi:10.1029/2002JC001573.

    • Search Google Scholar
    • Export Citation
  • Kim, S-J., , G. M. Flato, , G. J. Boer, , and N. A. McFarlane, 2002: A coupled climate model simulation of the last glacial maximum, part 1: Transient response. Climate Dyn., 19 , 515537.

    • Search Google Scholar
    • Export Citation
  • Kliem, N., , and D. A. Greenberg, 2003: Diagnostic simulations of the summer circulation in the Canadian Arctic Archipelago. Atmos.–Ocean, 41 , 273289.

    • Search Google Scholar
    • Export Citation
  • Kreyscher, M., , M. Harder, , P. Lemke, , and G. M. Flato, 2000: Results of the Sea Ice Model Intercomparison Project: Evaluation of sea ice rheology schemes for use in climate simulations. J. Geophys. Res., 105 , 1129911320.

    • Search Google Scholar
    • Export Citation
  • Kwok, R., 2005: Variability of Nares Strait ice flux. Geophys. Res. Lett., 32 , L24502. doi:10.1029/2005GL024768.

  • Kwok, R., 2006: Exchange of sea ice between the Arctic Ocean and the Canadian Arctic Archipelago. Geophys. Res. Lett., 33 , L16501. doi:10.1029/2006GL027094.

    • Search Google Scholar
    • Export Citation
  • Lammers, R. B., , A. I. Shiklomanov, , C. J. Vörösmarty, , B. M. Fekete, , and B. J. Peterson, 2001: Assessment of contemporary Arctic river runoff based on observational discharge records. J. Geophys. Res., 106 , 33213334.

    • Search Google Scholar
    • Export Citation
  • Maslowski, W., , and W. H. Lipscomb, 2003: High-resolution simulations of Arctic sea ice, 1979–1993. Polar Res., 22 , 6774.

  • Melling, H., 2000: Exchanges of freshwater through the shallow straits of the North American Arctic. The Freshwater Budget of the Arctic Ocean, E. L. Lewis et al., Eds., Kluwer Academic Publishers, 479–502.

    • Search Google Scholar
    • Export Citation
  • Melling, H., 2001: Is the extent or thickness of Arctic sea ice declining? The State of the Arctic Cryosphere during the Extreme Warm Summer of 1998: Documenting Cryospheric Variability in the Canadian Arctic, CCAF Summer 1998 Project Final Report. [Available online at http://www.socc.ca/summer/ftp/ftp/html.].

    • Search Google Scholar
    • Export Citation
  • Melling, H., 2002: Sea ice of the northern Canadian Arctic Archipelago. J. Geophys. Res., 107 , 3181. doi:10.1029/2001JC001102.

  • Nakicenovic, N., , and R. Swart, Eds. 2000: Emission Scenarios. Cambridge University Press, 570 pp.

  • Nazarenko, L., , G. Holloway, , and N. Tausnev, 1998: Dynamics of transport of “Atlantic Signature” in the Arctic Ocean. J. Geophys. Res., 103 , 3100331015.

    • Search Google Scholar
    • Export Citation
  • Pacanowski, R., 1995: MOM2 documentation, user’s guide and reference manual. Geophysical Fluid Dynamics Laboratory Ocean Group Tech. Rep. 3, NOAA/GFDL Laboratory, Princeton University, 232 pp.

    • Search Google Scholar
    • Export Citation
  • Parkinson, C. L., 2000: Recent trend reversals in Arctic sea ice extents: Possible connections to the North Atlantic Oscillation. Polar Geogr., 24 , 112.

    • Search Google Scholar
    • Export Citation
  • Parkinson, C. L., , and W. M. Washington, 1979: A large-scale numerical model of sea ice. J. Geophys. Res., 84 , 311337.

  • Parkinson, C. L., , and D. J. Cavalieri, 2002: A 21 year record of Arctic sea-ice extents and their regional, seasonal and monthly variability and trends. Ann. Glaciol., 34 , 441446.

    • Search Google Scholar
    • Export Citation
  • Polyakov, I. V., and Coauthors, 2003: Long-term ice variability in Arctic marginal seas. J. Climate, 16 , 20782085.

  • Rigor, I. G., , R. L. Colony, , and S. Martin, 2000: Variations in surface air temperature observations in the Arctic, 1979–97. J. Climate, 13 , 896914.

    • Search Google Scholar
    • Export Citation
  • Rosati, A., , and K. Miyakoda, 1988: A general circulation model for upper ocean simulation. J. Phys. Oceanogr., 18 , 16011626.

  • Rothrock, D. A., , and J. Zhang, 2005: Arctic Ocean sea ice volume: What explains its recent depletion? J. Geophys. Res., 110 , C01002. doi:10.1029/2004JC002282.

    • Search Google Scholar
    • Export Citation
  • Sadler, H., 1976: Water, heat and salt transports through Nares Strait, Ellesmere Island. Fish. Res. Board Can., 33 , 22862295.

  • Serreze, M. C., , and C. M. Hurst, 2000: Representation of mean Arctic precipitation from NCEP–NCAR and ERA re-analyses. J. Climate, 13 , 182201.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., , M. P. Clark, , and D. H. Bromwich, 2003: Monitoring precipitation over the Arctic terrestrial drainage system: Data requirements, shortcomings, and applications of atmospheric reanalysis. J. Hydrometeor., 4 , 387407.

    • Search Google Scholar
    • Export Citation
  • Simmonds, M., , and S. Isaac, 2007: The impacts of climate change on marine mammals: Early signs of significant problems. Oryx, 41 , 1926.

    • Search Google Scholar
    • Export Citation
  • Solomon, S., , D. Qin, , M. Manning, , M. Marquis, , K. Averyt, , M. M. B. Tignor, , H. L. Miller Jr., , and Z. Chen, Eds. 2007: Climate Change 2007: The Physical Scientific Basis. Cambridge University Press, 996 pp.

    • Search Google Scholar
    • Export Citation
  • Sou, T. V., 2007: The flow and variability of sea-ice in the Canadian Arctic Archipelago: Modelling the past (1950–2004) and the future (2041–2060). M.S. thesis, Dept. of Earth and Ocean Sciences, University of Victoria, BC, Canada, 135 pp. [Available online at https://dspace.library.uvic.ca:8443/dspace/bitstream/1828/208/1/tessasou.pdf.].

  • Steele, M., , R. Morley, , and W. Ermold, 2001: PHC: A global ocean hydrography with a high-quality Arctic Ocean. J. Climate, 14 , 20792087.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J., , M. C. Serreze, , F. Fetterer, , T. Arbetter, , W. Meier, , and J. Maslanik, 2005: Tracking the Arctic’s shrinking ice cover: Another extreme September minimum in 2004. Geophys. Res. Lett., 32 , L04501. doi:10.1029/2004GL021810.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J., , M. M. Holland, , W. Meier, , T. Scambos, , and M. Serreze, 2007: Arctic sea ice decline: Faster than forecast. Geophys. Res. Lett., 34 , L09501. doi:10.1029/2007GL029703.

    • Search Google Scholar
    • Export Citation
  • Tivy, A., , T. Sou, , T. Carrieres, , G. Flato, , and G. Holloway, 2004: Critical aspects of changes in sea ice cover on energy production. Canadian Ice Service Tech. Rep. 04-01, 100 pp.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131 , 29613012.

  • Walsh, J. E., , and M. S. Timlin, 2003: Northern Hemisphere sea ice simulations by global climate models. Polar Res., 22 , 7582.

  • Walsh, J. E., , W. D. Hibler III, , and B. Ross, 1985: Numerical simulation of Northern Hemisphere sea ice variability, 1951–1980. J. Geophys. Res., 90 , (C3). 48474865.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., , and J. E. Walsh, 2006: Toward a seasonally ice-covered Arctic Ocean: Scenarios from the IPCC AR4 model simulations. J. Climate, 19 , 17301747.

    • Search Google Scholar
    • Export Citation
  • View in gallery

    The CAA model domain and bathymetry, as well as selected place names. The yellow line represents possible routes through the Northwest Passage.

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    Median ice concentrations for the week of (left) 15 May and (right) 2 Jul. (top) Observations from 1971 to 2000 are taken from the CIS atlas (CIS 2002); also shown are model results from (middle) 1970–89 and (bottom) 2041–60. There is very little difference in the plots of simulated median ice concentrations averaged over 1970–89 and 1971–2000 (not shown). The 10/10 category (shown in black) represents consolidated, immobile ice, defined by a median ice velocity of less than 0.005 m s−1 for the model results.

  • View in gallery

    Same as Fig. 2 but for the week of 10 Sep.

  • View in gallery

    Modeled ice thickness for the week of (left) 15 May and (right) 10 Sep. Results averaged over (upper) 1970–89 and (lower) 2041–60 are shown.

  • View in gallery

    Simulated summer duration based on different criteria: (left) summer duration is dependent on the median ice concentration of one-tenth; (right) it is dependent on the median ice velocity. Results are shown averaged over (upper) 1970–89 and (lower) 2041–60.

  • View in gallery

    Time series of normalized minimum ice coverage from 1971–2004; the dashed line is based on observations from the CIS atlas (CIS 2002, updated) and the solid line is the result of the CAA model.

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    Changes in modeled ice volume: balance between thermodynamics and advection.

  • View in gallery

    Gate locations used for model ice flux diagnostics. Gray represents the CAA study region. Additional gates within the CAA study region are used to compare ice fluxes through the CAA interior and ice fluxes from the polynyas in Lancaster Sound, Smith Sound, and Amundsen Gulf.

  • View in gallery

    Annually averaged ice volume fluxes through the gates shown in Fig. 8, (upper) the fluxes through the individual northern gates, and (lower) the fluxes through the individual southern gates. Positive values represent import and negative values represent export from the CAA study region.

  • View in gallery

    Simulated daily ice volume fluxes through selected gates from 1999 to 2004. Pink represents open water conditions.

  • View in gallery

    Comparison of observed and modeled ice area fluxes through three northern gates. The solid lines are observations and dashed lines are model results for different gates: the southern Amundsen Gulf gate is blue, the northern M’Clure Strait is green, and the Queen Elizabeth gate is red. Observations from Kwok (2006) are annual mean estimates and observations from Agnew et al. (2008) are wintertime estimates from September to June.

  • View in gallery

    Frequency of simulated accessible years with good shipping conditions, for (upper) 1970–89 and (lower) 2041–60. Good shipping conditions occur when both the ice concentration is less than 60% and the ice thickness is less than 1.0 m, for a minimum of eight weeks in the year.

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Sea Ice in the Canadian Arctic Archipelago: Modeling the Past (1950–2004) and the Future (2041–60)

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  • 1 University of Victoria, Victoria, British Columbia, Canada
  • | 2 Canadian Centre for Climate Modelling and Analysis, Victoria, British Columbia, Canada
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Abstract

Considering the recent losses observed in Arctic sea ice and the anticipated future warming due to anthropogenic greenhouse gas emissions, sea ice retreat in the Canadian Arctic Archipelago (CAA) is expected and indeed is already being observed. As most global climate models do not resolve the CAA region, a fine-resolution ice–ocean regional model is developed and used to make a projection of future changes in the CAA sea ice. Results from a historical run (1950–2004) are used to evaluate the model. The model does well in representing observed sea ice spatial and seasonal variability, but tends to underestimate summertime ice cover. The model results for the future (2041–60) show little change in wintertime ice concentrations from the past, but summertime ice concentrations decrease by 45%. The ice thickness is projected to decrease by 17% in the winter and by 36% in summer. Based on this study, a completely ice-free CAA is unlikely by the year 2050, but the simulated ice retreat suggests that the region could support some commercial shipping.

Corresponding author address: Tessa Sou, School of Earth and Ocean Sciences, University of Victoria, P.O. Box 3055 STN CSC, Victoria, BC V8W 3P6, Canada. Email: sout@uvic.ca

Abstract

Considering the recent losses observed in Arctic sea ice and the anticipated future warming due to anthropogenic greenhouse gas emissions, sea ice retreat in the Canadian Arctic Archipelago (CAA) is expected and indeed is already being observed. As most global climate models do not resolve the CAA region, a fine-resolution ice–ocean regional model is developed and used to make a projection of future changes in the CAA sea ice. Results from a historical run (1950–2004) are used to evaluate the model. The model does well in representing observed sea ice spatial and seasonal variability, but tends to underestimate summertime ice cover. The model results for the future (2041–60) show little change in wintertime ice concentrations from the past, but summertime ice concentrations decrease by 45%. The ice thickness is projected to decrease by 17% in the winter and by 36% in summer. Based on this study, a completely ice-free CAA is unlikely by the year 2050, but the simulated ice retreat suggests that the region could support some commercial shipping.

Corresponding author address: Tessa Sou, School of Earth and Ocean Sciences, University of Victoria, P.O. Box 3055 STN CSC, Victoria, BC V8W 3P6, Canada. Email: sout@uvic.ca

1. Introduction

The earth’s climate is changing, and the latest report of the Intergovernmental Panel on Climate Change (IPCC) concludes that the observed warming since the 1950s is “very likely” caused by an anthropogenically forced increase in greenhouse gases (Solomon et al. 2007). This warming is far from uniform, with the Arctic experiencing much greater warming than lower latitudes. Recent losses in Arctic ice cover are attributed to such warming (Zhang and Walsh 2006; Rothrock and Zhang 2005; Stroeve et al. 2007), replacing natural variability as the dominant force in ice cover changes (Melling 2001; Holloway and Sou 2002; Polyakov et al. 2003).

Ice retreat has been regional, with losses primarily concentrated in the Beaufort and East Siberian Seas (Stroeve et al. 2005). Previously, observations from 1979–99 indicated significant negative trends in sea ice extent in the eastern Arctic (e.g., Barents and Kara Sea) while the central Arctic and Canadian Arctic Archipelago (CAA) have maintained their ice cover, as demonstrated by statistically insignificant trends in ice extent (Parkinson and Cavalieri 2002). These regional differences are partially explained by atmospheric variability (Parkinson 2000). In the case of the CAA region, additional factors inhibit ice loss, such as the predominance of a continental climate, the influx of ice from the Arctic Ocean ice, and the slow response of landfast, multiyear ice to changes in wind or air temperatures.

Nevertheless, sea ice loss is expected in the CAA region. Record low ice extents have been observed in the CAA region recently (CIS 2002, updated; ESA 2007), suggesting the region’s ice climate is undergoing change. Climate models also project continued loss of ice in the Arctic when forced with sustained anthropogenic forcing and continued warming (Solomon et al. 2007). It is clearly important to better understand the local sea ice response to changing climate conditions in the CAA region in terms of adaptation planning and resource management. Predicting when and how the ice will retreat is important to local residents who depend on sea ice for transportation, hunting, and fishing. Retreating sea ice also affects wildlife, including polar bears, seals, and bowhead whales (Derocher et al. 2004; Simmonds and Isaac 2007) and the development of oil and natural gas reserves off the Canadian coast is of environmental concern. There is also strong political and economic interest in the Northwest Passage (Fig. 1); a route through the CAA for ships traveling from Asia to Europe that is half the distance of the conventional route using the Suez or Panama Canals. Possible international commercial shipping through the Northwest Passage raises issues of environmental regulation and Canadian sovereignty (Huebert 2001; Barber and Hanesiak 2004).

Currently, most global climate models do not resolve the narrow channels of the CAA, and studies using Arctic Ocean models (e.g., Maslowski and Lipscomb 2003; Kauker et al. 2003) or regional CAA models (e.g., Kliem and Greenberg 2003) with higher resolutions have not focused on the impact of climate change on sea ice in the CAA region. Modeling the region with adequate resolution would supplement the current understanding of the sea ice regime, and provide a sense of ice conditions in the future. With this in mind, a three-dimensional ice–ocean coupled model of the CAA region, spanning the Canadian Arctic islands north of 70°N (Fig. 1), is integrated for two time periods: 1950–2004, using observationally based atmospheric data and 2041–60, under atmospheric forcing that combines historical variability and a projected change in climate from a global climate model. The horizontal grid resolution of 22 km (0.2°) is a compromise between representing key channels to permit ice transport, growth, and melt, and at the same time considering the resolution limitations of available forcing data (100–200 km).

Details of this CAA model setup and forcing are provided in the next section. The model’s ability to represent the observed sea ice regime is evaluated in section 3. The last section discusses the simulated changes in sea ice between the past (1970–89) and the future (2041–60), and provides a preliminary look at possible future ice conditions in the CAA.

2. Model description and data

a. Model

The model is comprised of a sea ice component (Parkinson and Washington 1979; Hibler 1979) coupled to an ocean component. A simple snow model, similar to that described by Walsh et al. (1985), is also included. The setup for this model follows previous studies as described by Nazarenko et al. (1998), and implemented by Holloway and Sou (2002) and Tivy et al. (2004). A more extensive description of the model and forcing is provided by Sou (2007).

The ice thermodynamics, which includes sensible and latent heat fluxes, shortwave radiation, and conduction through the ice, are based on Parkinson and Washington (1979). Heat storage in the ice layer is not included in the model, so penetrating shortwave radiation either melts the ice bottom or heats the underlying ocean. The equation for net longwave radiation is taken from Rosati and Miyakoda (1988); it considers both the surface and air temperatures and is well suited for models with both ice and open water regions. The albedo is dependent on the surface type and air temperature, and it ranges from open water (0.1) to dry snow (0.8).

The sea ice thickness distribution is approximated using two categories: thin ice/open water (represented by concentration, which is the fraction of the ocean surface covered by ice) and thick ice (whose mean thickness is computed). The cutoff thickness that distinguishes between these two categories is set to 0.2 m instead of 0.5 m (Hibler 1979) and represents a faster and more realistic lead closing time (H. Melling 2002, personal communication). Ridging is represented by an increase in ice thickness when ice is advected into a cell with 100% ice concentration. An upstream advection scheme is used. The ice interaction is determined by a viscous-plastic rheology (Hibler 1979), with the ice strength parameter (P*) set to 15 000 N m−2 following Kreyscher et al. (2000).

The ocean model, Modular Ocean Model (MOM; Pacanowski 1995; Bryan 1969), is a three-dimensional primitive equation model. The tracer time step is 4 h, while the momentum time step is 15 min. The subgrid-scale mixing terms for the diffusion and viscosity are assigned constant values. Vertical diffusion is 10−6 m2 s−1, while vertical and horizontal viscosities are 10−3 and 103 m2 s−1 respectively. The explicit horizontal diffusion is set to zero for flux-corrected transport (FCT) advection scheme, which was implemented in the MOM model by Nazarenko et al. (1998). An eddy–topography interaction parameterization by Holloway (1992) is included. The parameterization depends on the bottom topography, the Coriolis parameter and an eddy length scale (set to 4 km for this application).

The coupling of the ice and ocean components occurs every time step, and includes a freshwater flux, either a positive flux during ice melt or negative flux during ice formation to represent brine rejection and a heat flux. Oceanic temperatures are kept at near-freezing temperatures under the ice, and any surplus heat melts the ice. The wind stress applied to the ocean surface is equal to the water drag on the ice underside. There is no restoring for either the surface salinities or temperatures.

The model domain is shown in Fig. 1. The model grid has a horizontal resolution of 22 km (0.2°), with 24 fixed ocean depth levels,1 and it is rotated to provide nearly equidistant grid spacing over the regional domain. The bathymetry is from the merged IBCAO_ETOPO5 (Holland 2000), and some modifications are made manually: for example, Nares Strait and the narrow straits around Ellesmere and Victoria Islands are widened or deepened to better agree with navigational topographic charts. The maximum model depth is set to 1200 m, cutting off deeper regions in the Arctic Ocean and Baffin Bay to reduce integration time.

b. Forcing data

Lateral open boundaries exist in the Beaufort Sea and Baffin Bay, and forcing data is provided from a basinwide model of the Arctic Ocean with a 0.5° horizontal resolution. The domain includes the entire Arctic Ocean and part of the North Atlantic down to 45°N. The Arctic Ocean model is set up similarly to the CAA model and is run (offline) for both the historical (1950–2004) and the future (2041–60) runs (Sou 2007). The lateral forcing taken from the Arctic Ocean model for the CAA regional model includes oceanic fields (temperature, salinity, velocity, and streamfunction); ice fields (velocity, thickness, and concentration); and snow fields (thickness). A “free outflow” condition is applied in the CAA model so that outflowing oceanic temperatures and salinities are not reset to the boundary values, and the oceanic volume transport through the CAA model is set by the monthly varying transport between Greenland and mainland Canada in the Arctic Ocean model.

For simplicity, the initial ice concentration and thickness fields for the historical and future runs are taken from the end of a five-year run (1950–54) in the Arctic Ocean model and interpolated to the CAA grid. The sensitivity of the ice model to the initial ice conditions was considered briefly: a test future run was initialized with half of the 1954 ice thicknesses and was seen to equilibrate within 2–5 yr, and then reproduce the same thicknesses and concentrations as in the original future run. The results discussed here are therefore insensitive to the choice of initial ice conditions.

The ocean temperatures and salinities are initialized with climatological December values from the Polar Science Center Hydrographic Climatology (PHC; Steele et al. 2001). The impact of the initial ocean state on the overlying ice cover was investigated in a sensitivity run by which the ocean was warmed by 0.5°C below 50 m, and the salinity adjusted to retain the density structure. The resulting ice cover was almost indistinguishable, mostly because the surface waters remain highly stratified. This is because, even under future climate conditions, both the basin-scale and regional models support a wintertime ice cover. The results discussed here are therefore insensitive to at least model uncertainty in submixed-layer ocean temperature initial conditions.

1) Historical forcing, 1950–2004

Monthly air temperature, specific humidity, and surface pressure data, as well as daily wind data, are from the National Centers for Environmental Prediction–National Center for Atmospheric Research 40-Year Reanalysis (NCEP–NCAR; Kalnay et al. 1996). The wind stress is taken directly from the reanalysis data, and is used to calculate wind speed. The NCEP–NCAR reanalysis generally agrees well with observations in the Arctic region, especially in terms of cyclonic activity (Bromwich et al. 2007). However, the reanalysis overestimates shortwave radiation and underestimates cloud cover (Curry et al. 2002; Bromwich et al. 2007). Consequently, shortwave radiation is parameterized and climatological values for cloud cover are taken from Parkinson and Washington (1979). Also, the reanalysis precipitation data rates are excessive in the CAA region (Serreze and Hurst 2000), so a climatological precipitation dataset is used (Serreze et al. 2003). Specific humidity is taken from the NCEP–NCAR reanalysis, but it is modified so that the relative humidity used in the model never exceeds 95%. Climatological monthly river runoff from the Mackenzie and Peel Rivers is included (Lammers et al. 2001).

Compared to observations, the NCEP–NCAR reanalysis air temperatures over the CAA region are too cold, especially in summer. The narrow channels of the CAA are not resolved by the NCEP–NCAR model, and temperatures better represent high-altitude glaciers of Greenland and Ellesmere Island. These cold temperatures are problematic because modeled ice thicknesses are sensitive to summers that do not warm above freezing (Flato and Brown 1996). Without adequate summertime melt, the simulated ice thickness in the CAA model is much larger than observed, exceeding 10 m in the eastern CAA region (e.g., around Ellesmere Island). This result is important to note when considering CAA sea ice results from models forced with NCEP–NCAR reanalysis temperatures. Air temperature data from the European Centre for Medium-Range Weather Forecast (ECMWF; Uppala et al. 2005) showed similar tendencies.

To address this problem, the NCEP–NCAR reanalysis air temperatures are adjusted using the gridded International Arctic Buoy Program/ Polar Exchange at the Sea Surface (IABP/POLES) dataset (Rigor et al. 2000), which spans the period 1979–2003. The adjustment simply removes the monthly climatological difference (bias) between the reanalysis and IABP/POLES datasets. The largest difference occurs in the summer, when the adjusted temperatures are larger by 0.5° to 5.0°C depending on the location. Under the adjusted forcing, the resulting modeled ice thicknesses are similar to those observed at specific sites (Brown and Cote 1992; available at http://ice-glaces.ec.gc.ca, see under Ice Archive).

2) Future scenario forcing, 2041–60

The objective for this study is to provide an initial evaluation of the sea ice response in the CAA to a warming atmosphere. Clearly the magnitude of the response will be directly related to the projected warming. For this study, the future atmospheric data is taken from the second Coupled Global Climate Model (CGCM2; Flato and Boer 2001), run on a 3.75° horizontal grid and forced under the Special Report on Emission Scenario (SRES) A2 scenario, as defined in the Special Report on Emission Scenarios (Nakicenovic and Swart 2000). The CGCM2 projections are generally well within the range of projections from other climate models and the CGCM2 model does well in representing historical climate changes (Flato and Boer 2001). The maximum Arctic ice cover in CGCM2 is 14 × 106 km2 compared to the 15 × 106 km2 observed (Kim et al. 2002), and the amplification of future warming in the Arctic is substantial (Holland and Bitz 2003; Flato and Boer 2001).

The atmospheric forcing for the future CAA model run is calculated by adding the difference in the CGCM2 climatology between 1970–89 and 2041–60 to the observationally based historical forcing from 1970 to 1989. This method retains the variability of the historical forcing while imposing the change between the present and future CGCM2 climate, and follows the approach of Hulme et al. (1999) and Dumas et al. (2006). The resulting future atmospheric forcing has warmer winters and wetter summers, compared to the historical forcing. The CAA domain-averaged air temperature increases the most in October, November, and December, by 10°C, with the greatest warming in the central and northern CAA, as well as the Amundsen Gulf. The other atmospheric variables experience less change: the wind stress magnitude is slightly lower all year, the specific humidity is larger in winter, and shortwave radiation is slightly lower in summer.

3. Model results: Historical run, 1950–2004

An open question is whether or not a model with relatively fine horizontal resolution (22 km), forced with coarse resolution atmospheric data (200 km), can accurately reflect sea ice conditions in the CAA. The forcing is limited as the global models (i.e., CGCM2 and NCEP–NCAR reanalysis) do not resolve the topography of the CAA and associated local details, such as the strong topographically channeled wind through Nares Strait. On the other hand, wind-forced advection and seasonal variability in air temperature are important processes influencing sea ice, and their large-scale patterns are well represented in the forcing. In this section, the model results are evaluated against observations of median ice concentration and thickness, in terms of spatial, seasonal, and interannual variability. Additionally, ice fluxes and associated changes in ice volume are considered. An evaluation of the simulated ocean conditions is not included here: the focus of the paper is to assess the ice response to a change in atmospheric forcing. While the ocean processes do affect ice cover, the atmospheric forcing plays the dominant role in the CAA region. Also, there is very little observed data for comparison (as described in Sou 2007).

a. Seasonal variability

1) Concentration

Ice cover in the CAA region is poorly observed. Currently, the best data for model evaluation, in terms of spatial coverage over time, is ice concentration data. The data shows that the region is covered completely in winter with densely packed ice, which is simulated by the model. In early May, concentrations are observed to decrease, especially in polynya regions. The model simulated timing and spatial patterns of the North Water Polynya in Smith Sound, the Bathurst Polynya in the Amundsen Gulf, and the smaller polynyas in Jones Sound and Lancaster Sound, are similar to observed patterns, as is the ice retreat along the southwest coast of Greenland in May and July (Fig. 2).

From July to September, the model tends to underestimate the ice extent and concentrations (Fig. 3). The simulated ice cover retreats too quickly, so that August has the minimum monthly ice extent instead of September, which is observed for this region (Parkinson and Cavalieri 2002). The timing of the minimum is difficult to simulate as the extent during August is quite similar to September; the minimum has been observed to occur in August twice (1980 and 1997) since 1979. The model does retain dense ice in the Queen Elizabeth Islands (QEI) and the central CAA, as observed, but the southern regions of Nares Strait, Gulf of Boothia and M’Clintock channels in the model are completely ice free by September, contrary to the observed data. Additionally, the simulated ice remains too close to the Alaskan coast, possibly resulting from the wind forcing or insufficient oceanic melt.

The discrepancies in summertime cover between observations and model results are reflected during fall freezeup in October; in the model, the ice freezes too early along the Alaskan coast and ice concentrations are too low in the southern channels compared to observations. On the other hand, ice in Nares Strait freezes quickly in the model and its extent agrees well with observations. By November, both the observations and model results show dense ice concentrations covering the CAA region and northern Baffin Bay, with Coronation Gulf being the last region to freeze.

Ice plugs play an important role in ice dynamics within the CAA, restricting entry of Arctic ice into the QEI as well as contributing to ice consolidation. Although the model’s resolution is not adequate for explicit representation of the ice arching process, the observed wintertime ice plugs (arches) in Lancaster Sound and Nares Strait are evident in the modeled May ice concentrations. Ice plugs are also observed in the northern QEI region during summer, but consolidated, immobile ice is underrepresented by the model.

2) Ice thickness and velocity

Ice thickness data is very limited because measurements have to be taken in situ; estimating ice thickness within narrow channels from satellite remains a technical challenge. Based on the available data, the wintertime ice thickness along the northern CAA coast ranges from 3 m in the southern Beaufort Sea to 7–8 m north of Ellesmere Island (Bourke and Garrett 1987). The model does well in simulating these thicknesses (Fig. 4), as well as the ice thickness within the CAA region: ice in the QEI is 3–4 m on average (Melling 2000), slightly less in M’Clure Strait (Bourke and Garrett 1987; Agnew et al. 2008), and the southern channels have ice that is less than 2 m thick. Observed ice thickness in northern Nares Strait ranges from 2 to 6 m (Kwok 2006), and compared well to the modeled values of 2–5 m. Simulated ice is mostly immobile within the CAA, excepting Amundsen Gulf and Lancaster Sound, and mobile in the Beaufort Sea and Baffin Bay, as expected. The simulated movement of the Arctic ice pack pushes ice against the QEI, dividing into a southwestward flow toward Alaska and a northeastward flow toward Fram Strait.

In summer, the observed ice along the northern CAA coast is thinner than in winter, ranging from 1 m in the southern Beaufort Sea to 6 m north of Greenland (Bourke and Garrett 1987), and is well represented by the model. The north and central regions of the CAA retain simulated ice thicknesses up to 3 m, with regions of open water in the south and west, agreeing with observed regions of perennial and seasonal ice, respectively. In early September, simulated ice moves southeastward through M’Clure Strait and the western QEI, but northwestward from Amundsen Gulf, and eastern QEI. The model poorly represents the ice direction in northern Nares Strait; the model simulates an average northeastward flow of ice where a southwestward flow of ice is observed. This discrepancy is a result of the coarse wind field.

3) Summer duration

The timing of the breakup and freezeup of ice, and the associated length of summertime conditions, affects the ice-dependent activities of local people and wildlife, as well as marine activities, such as shipping. Consequently, the criteria used to define breakup and freezeup depends on the application, and impacts the length of summer duration (i.e., the length of time between breakup and freezeup).

For the Canadian Ice Service (CIS) navigational charts, the week of breakup is taken to occur when the median ice concentration drops below one-tenth, and freezeup occurs when the median ice concentration becomes greater than one-tenth. This broadly reflects the timing of ice cover for navigations purposes. The charts are compared to the model results, and the simulated patterns of breakup and freezeup agree reasonably well, especially in Amundsen Gulf, Jones Sound, and northern Baffin Bay. However, the region that does not experience breakup or freezeup in the model extends too far south along the Alaskan coast, and not far enough in the Gulf of Boothia, M’Clintock Channel, or Nares Strait (CIS 2002). The resulting simulated summer duration (Fig. 5) varies regionally, lasting for a few weeks in the northern interior, longer in the south (8–12 weeks), and longest (16–18 weeks) in the North Water Polynya (NOW) region and along the Greenland coast. Charts of observed summer duration are not available.

Two other criteria of breakup and freezeup are applied, and its impact on summer duration is considered. In the first case, breakup and freezeup is based on ice thickness of 0.5 m and roughly reflects the length of time it is safe to be on the ice. Generally, the summer duration is similar to the previous (concentration based) definition, but is longer by up to 4 weeks in the southern interior and Baffin Bay.

The second definition of summer duration is velocity-based (Fig. 5) and reflects the duration of mobile ice. This definition may be relevant for people working or traveling on the ice. Here, an ice velocity threshold of 0.005 m s−1 (0.3 m min−1) is used.2 The simulated summer duration is very short in the northern channels of the QEI, which experience observed ice plugs, and is longer by several months in the central QEI. Ice is mobile for 12–16 weeks in Viscount Melville Sound and Nares Strait, and for half the year in the southern interior channels. Ice in the Beaufort Sea and Baffin Bay, including parts of Lancaster Sound, is mobile all year. It is clear that freezeup and breakup are somewhat ambiguous concepts and that their definition (and hence timing) depends crucially on the application.

b. Interannual variability in ice extent and concentration

In addition to seasonal and regional patterns, the model’s ability to represent interannual variability in ice cover is evaluated using the CIS minimum ice coverage dataset3 available from 1971 to 2004 (Fig. 6). There is a high correlation (0.71) between the model results and observations (statistically significant at more than the 99% level), but the simulated trend (−10.9% decade−1) is larger than observed (−3.4% decade−1); this difference is significant at the 90% confidence level. The difference is primarily a result of model underestimation after about 1995. A recently discovered problem in the NCEP–NCAR reanalysis may partially explain the model–observation disagreement: air temperatures at some polar locations were incorrectly too high from 1998 to 2004 (see NCEP–NCAR reanalysis problem list available online at http://www.cdc.noaa.gov/cdc/reanalysis/problems.shtml). Another explanation may be the anomalously large export events simulated in 1998, when the dominating factor in the annual change of ice volume is due to export, not melt (Fig. 7). Nevertheless, the model captures the range of ice coverage and the timing of extreme years (e.g., light ice years of 1998 and 1981 and heavy ice years of 1997 and 1972), albeit with a tendency to underestimate ice cover, especially in the southern channels and during anomalously warm years. Interestingly, while the CAA model overestimates the recent decrease in ice cover in the CAA, global climate models underestimate the retreat in sea ice in the Arctic (Stroeve et al. 2007).

c. Ice volume evolution: Thermodynamics and advection

Interannual variability in ice volume is also of interest in terms of assessing climate change impacts on ice. A regionwide assessment based on observations is not possible; however, the simulated contribution of advective and thermodynamic processes to changes in ice volume (Fig. 7) provides insight into the sources of ice variability within the CAA study region (shown in gray, Fig. 8). Changes from export and growth dominate, are negatively correlated, and nearly balance each other,4 with a correlation coefficient of −0.7 (statistically significant at the 99.9% level). The interdependence of growth and export exists as the export of ice results in increased growth to replace ice, while ice growth results in more ice available for export. Import and melt play a smaller role in altering ice volume in the model.

Large changes in ice volume occur during years where there is an imbalance of export and growth: export was dominant in 1998, while anomalous growth occurred in 1989. Ice volume also increases when there is net import and growth (e.g., 1974), which occurs less often. Simultaneous export and melt does not occur in this annually averaged time series. Generally, the net volume changes gradually from year to year, with the exception of the mid 1970s and the 1990s. During these times, there is higher interannual variability, with an unusual number of net “import and melt” years alternating with “export and growth” years.

d. Ice fluxes

1) Model results

Simulated ice fluxes through key channels (Fig. 8) illustrate regional variability in ice advection and associated changes in ice volume. For example, the interannual variability in ice volume caused by advection (as discussed in the previous section and shown in Fig. 7) is attributed to fluxes though the northern boundary, primarily through Amundsen Gulf (upper panel, Fig. 9).

The Amundsen Gulf gate has large annual transports compared to the other straits, but the years of export and import nearly balance in the long term (1950–2004). Consequently, the 55-yr mean transport is similar to the M’Clure Strait and the QEI gates, but of opposite sign (Table 1). The combined import into M’Clure Strait and the QEI is larger than the export from Amundsen Gulf, so there is a net influx of ice from the Arctic Ocean into the northern boundary. Robeson Channel also experiences net import, but the flux is small. The total flux through the northern boundary is 86 km3 yr−1.

In comparison, the ice volume flux through the southern gates is much larger (−206 km3 yr−1) because of large exports from Smith Sound and a consistent export of ice from the other southern gates. Consequently, as export from the domain is larger than import, the CAA is a region of net ice production. This result agrees with Agnew et al. (2008).

A main source of simulated ice generation is found within polynya regions. Three main polynyas in the CAA region are Lancaster Sound, Smith Sound (NOW polynya), and Amundsen Gulf (Bathurst polynya). In these regions, ice is continually advected away from the coast or landfast ice, resulting in open water conditions and the formation of replacement ice. Consequently, the total ice fluxes exported from these polynyas are much larger than fluxes of ice leaving the CAA interior, where ice is more likely to be landfast. For example, the flux through northern Smith Sound is −9 km3 yr−1 compared to 170 km3 yr−1 through southern Smith Sound.5 Dey (1981) also found that the polynya regions play a significant role in modifying ice fluxes, and estimated that the ice volume flux into northern Baffin Bay, via Smith, Jones, and Lancaster Sounds, was 655 km3 yr−1. This rate was much larger than the transport through the interior CAA region; his estimated net flux through Robeson Channel, Fram Sound (QEI), and Barrow Strait was 201 km3 yr−1. These results indicate that the main source of ice exported into the Beaufort Sea or Baffin Bay is generated within the nearby polynya regions. Consequently, the choice of gate location is very important in channels that have different ice regimes, such as Smith Sound. Regions where the ice conditions are more homogeneous, such as M’Clure Strait and QEI, are less sensitive to the location of the gates.

Currently, observations are limited to area fluxes as thickness data is unavailable, but volume fluxes are estimated by applying a representational thickness to the observed area flux. The skill of this method is assessed using model results, in which simulated ice volume fluxes can be used to evaluate the ice volume estimated from a representational thickness and the simulated area flux. The method works well when ice thickness and ice direction is consistent (such as the QEI) but does poorly in Amundsen Gulf, where the ice direction commonly reverses and the ice thickness is systematically thicker in the north.

Annually averaged fluxes mask the shorter term variability, especially in the southern channels. The daily fluxes throughout the CAA region in the model demonstrate an aspect of high-frequency ice behavior: advective events are sudden and intense, with many reversals in direction and seasonal variability (Fig. 10). In the simulation, the Amundsen Gulf gate has the largest transports and the most seasonal variability: it experiences perennial ice in some summers, but not others, and it is usually mobile during winter, but can be landfast in some years. M’Clure Strait experiences smaller daily transports but has a similar advective pattern (not shown). The ice fluxes through the QEI (shown), Robeson Channel, Jones Sound, and Barrow Strait gates show less variability, as the ice is consistently landfast during winter, while ice at Lancaster Sound gate (shown) remains mobile most years.

2) Comparison to observations

Compared to the observed area fluxes through the northern boundary for 1998–2004 (Kwok 2006; Agnew et al. 2008), the simulated area flux has a similar range of transport and timing of extreme years (Fig. 11). The model captures the import conditions at QEI, export conditions at Amundsen Gulf, and reversals at M’Clure Strait. It also simulates increased export in 1998 (although overestimated) and decreased export in 2000. Observed area fluxes through northern Nares Strait from 1996 to 2002 range from 16 to 48 × 103 km2 yr−1 (Kwok 2005). The simulated flux is near zero; this underestimate is attributed to the coarse wind forcing, which is mostly northward over the channel. In addition, the narrow strait is poorly resolved in the model.

Evaluating the model’s skill in representing ice fluxes through the southern CAA channels, including Smith Sound, Jones Sound, and Lancaster Sound, is difficult because there is so little data. Consequently, estimates of the total volume flux into Baffin Bay are poorly constrained, and range from 655 km3 yr−1 (Dey 1981) to 220 km3 yr−1 (Sadler 1976). For comparison, the net flux (1950–2004) in the CAA model is 206 km3 yr−1, ranging from 90 to 294 km3 yr−1. More recently, Agnew et al. (2008) estimated wintertime fluxes (September to June) during 2002–03, and the CAA model results are compared in Table 2: the simulated area flux for Lancaster Sound is nearly the same as observed, but the model overestimates the flux through northern Smith Sound and underestimates the flow through Jones Sound. Jones Sound is a very narrow channel, and simulated ice movement may be restricted by inadequate model resolution or wind forcing. As seen in the comparison with the Kwok (2006) fluxes, the CAA model results are in better agreement with the observed area fluxes than the volume fluxes, in this case partially resulting from the difference in the representational and simulated ice thicknesses.

4. Model results: Future run, 2041–60

Certain aspects of sea ice behavior in a warmer climate can be anticipated based on the current understanding of the CAA ice processes. Ice thickness and summertime ice concentrations will decrease, as will the area of wintertime landfast ice. Initially, ice plugs will likely weaken, permitting more multiyear ice to enter the CAA from the Arctic Ocean. The heavily ridged ice would transit more quickly through the QEI, resulting in less melt time and stronger, thicker ice entering Parry Channel or Jones Sound. Encounters with such ice would make navigation through the Northwest Passage (NWP) more hazardous than at present (Melling 2002), continuing until the Arctic ice retreats sufficiently and the import of ice ceases (Howell et al. 2008). However, observations of ice fluxes from 1997 to 2002 showed northern movement of ice into the Arctic from M’Clure Strait and Amundsen Gulf (Kwok 2006), suggesting that the clearing of ice channels could occur without significant ice loss in the Arctic Ocean, and would depend on the future wind regime.

The total retreat of ice from the NWP during the summer of 2007 was unprecedented and unexpected (ESA 2007). Based on the observational record of the last thirty years, sea ice in the CAA has recovered within 2–3 yr after an anomalously light ice year (Agnew et al. 2001; Dumas et al. 2007), but whether the region will recover from the light ice year of 2007 is unknown. Nevertheless, global climate simulations over the twenty-first century project continuation of summertime ice in the northern CAA and adjacent Arctic Ocean (Houghton et al. 2001; Walsh and Timlin 2003; Holland et al. 2006; Solomon et al. 2007) while other regions become free of ice. The ice is retained to the north of the CAA region because the future Arctic Ocean atmospheric circulation patterns in global climate models remain similar to present day (ACIA 2005); ice is pushed up against and into the northern CAA. Continental affects, including the predominance of land in the CAA and the nearby glaciers and ice sheets, may also play a role in retaining a cold-and-ice-favorable climate into the future.

Global models generally do not resolve the CAA region. By applying the change in atmospheric forcing between 1970–89 and 2041–60, as projected by the CGCM2 model, to the past climate (historical forcing), the simulated response on sea ice in a regional model can be investigated in terms of changes in ice concentration, thickness, and duration of ice cover.

a. Changes in ice concentration, thickness, and velocity

In terms of concentration, the model simulates little change in wintertime, but the future springtime break up occurs earlier in the Amundsen Gulf, Beaufort Sea, and Baffin Bay regions (Fig. 2). Ice concentrations are also reduced in spring and summer, with more open water in Parry Channel, around Ellesmere Island, and along the Alaskan coast in September (Fig. 3). Regions of immobile, dense ice, which represent possible ice plug conditions, still exist north of the QEI and Nares Strait in summer, but are not as widespread as in the past (1970–89).

In May, the future ice thickness is reduced by more than 1.0 m in M’Clure Strait, Viscount Melville Sound, and the QEI regions, while ice thickness in Amundsen Gulf and Barrow Strait decreases by 0.5 m. The most dramatic loss of ice occurs north of the CAA, where ice thins by 2–4 m (Fig. 4). Regionally averaged, the maximum ice thickness drops by 17%. Most of the CAA region continues to be landfast in winter, so the ice velocity patterns are unchanged, but there is increased ice movement in Baffin Bay and the Beaufort Sea.

The simulated September ice thickness shows a pattern of thinning similar to that seen in the winter, with the greatest reduction in ice thickness occurring to the north of the CAA region and within the QEI and Parry Strait (Fig. 4). Future ice retreat is evident in Beaufort Sea, Barrow Strait, and around Ellesmere Island (also seen in ice concentrations). The regionally averaged ice thickness decreases by 36% from 1.23 to 0.77 m, and the normalized ice coverage6 drops by 46%, from 0.34 to 0.18. Also, summertime ice velocities are larger in the future, and are especially evident north of and within the QEI, suggesting an increase of ice import.

Changes in the seasonal cycle of ice coverage are also evident. While the wintertime ice extent from December to May is basically unchanged, the future ice cover retreats faster in June and remains more open in October. The summertime ice extent is also reduced, by up to 30% in August and 50% in September. Hence, the month of minimum ice cover in the model shifts from August to September.

b. Change in summer duration

Generally, the summer duration (based on median ice concentration of one-tenth) is longer in the future time period (2041–60). Regionally averaged over the CAA study region, the ice breaks up 10 days earlier and freezes up 17 days later than in the past (1970–89). The largest difference in breakup dates occurs in regions that did not open up in the past simulation but retreat as early as June in the future run, for example, the southern Beaufort Sea, northern Barrow Strait, and off the western coast of Ellesmere Island. These areas of retreated ice results in more ocean area experiencing breakup and freezeup, which increases from 61% to 77% of the CAA study region. Other regions break up earlier. Northern Baffin Bay, Nares Strait, and Amundsen Gulf open up 2–5 weeks earlier, and M’Clintock Channel and the Gulf of Boothia open up 1–2 weeks earlier. The timing of breakup in Coronation Gulf is unchanged. On the other hand, freezeup dates range from 2 to 4 weeks later, where freezeup is delayed the most in the Amundsen Gulf and the NOW region.

Consequently, summer duration7 increases the most in the southern Beaufort Sea region (5 months longer), in Amundsen Gulf (2 months longer), and around Ellesmere Island (1 month longer). The NOW region is open about 5–6 months, a month longer than in the past. The remaining regions of seasonal ice cover generally experience 3–5 more weeks of “summer” (Fig. 5), shifting from 1–3 months to 2–4 months.

Summer duration based on ice thickness less than 0.5 m has a similar pattern of change but is generally longer compared to the concentration-based definition. Changes in Baffin Bay are most dramatic, with the NOW region being open 7–8 months in the future compared to 4–5 months in the past. Also, the Greenland coast is ice-free longer. The simulated ice tends to thin faster than it retreats, so that the duration of summer, as defined by ice thickness, will be more sensitive than that based on ice concentration. Summer duration is also calculated using the length of time ice velocities are greater than 0.005 m s−1. The simulated future ice within the CAA region is generally mobile a month longer than in the past. The northern CAA region (e.g., QEI) experiences the most dramatic changes, and is mobile for up to 5 months longer (Fig. 5). Regardless of the definition used, the duration of landfast ice in the CAA region is projected to decrease substantially in the future.

Summer duration is particularly relevant in terms of accessibility for shipping. The ability to navigate through ice-covered waters depends on many factors; for example, the ship’s ability to withstand ice pressure, requirements for draft, and the experience of the crew. Although there is a wide range of allowable conditions, commercial ships can generally withstand ice concentrations up to 60% with ice thickness less than 1.0 m (H. Melling 2007, personal communication). To present a general picture of potential impacts of future climate on transportation in the region, these criteria8 are used to define good shipping conditions. Channels are considered accessible during the years these conditions exist for a minimum of 8 weeks. It is assumed that a channel would need to be consistently accessible from year to year in order to be considered commercially viable. The NWP consists of two main routes: a shallow water route through Queen Maud Gulf (south of Victoria Island), and a deep water route through Viscount Melville Sound and out through Prince of Wales Strait (north of Victoria Island). The shallow water route has several access points, for example, Prince Regent Inlet (through Bellot Sound) or Peel Sound.

A plot of the frequency of accessible years for the present (1970–89; Fig. 12), based on the model results, shows the deep water route is closed every year while the shallow water route is accessible 50%–60% of the years. Baffin Bay is completely open, but access to the Beaufort Sea is blocked by ice along the Alaskan coast, which is not observed. In the future simulation, the shallow NWP route through Prince Regent Inlet and Bellot Strait is open every year, but the passage through Peel Sound and the deep water route remains limited by ice in Barrow Strait 40% of the time. The Alaskan coast is clear of ice.

c. Ice fluxes

The future ice volume flux through the northern boundary drops by 60%, and the flux through the southern boundary decreases by 20% (Table 3). Because of the unequal change in fluxes, the net ice volume exported from the region increases (from 78 to 114 km3 yr−1). The change at the northern boundary is caused mostly by a decrease in ice thickness (from 3.3 to 1.9 m); ice area fluxes remain similar as reduced ice concentrations are compensated by faster ice velocities. In comparison, the southern boundary experiences less change in ice thickness and velocity.

Freshwater fluxes through the CAA are also considered (Table 4). The CAA experiences a net freshening from oceanic transport, which outweighs the loss of freshwater from ice transports. In the future simulation, the region is freshening at a faster rate (137 km3 yr−1) than in the past (86 km3 yr−1). These rates are small, relative to the total oceanic freshwater fluxes, but are comparable to the ice fluxes.

5. Conclusions

In the context of recently observed warmer air temperatures and exceptional summertime ice retreat in the Arctic, the fate of sea ice in the Canadian Arctic Archipelago (CAA) region is a growing concern. Although the CAA region has been maintaining its sea ice cover, and the trend over the past several decades of observed ice thickness and area are not statistically significant, the record low ice extent in the summer of 2007 hints that conditions may be changing. Ice loss in the CAA would negatively impact the culture of local people as well as the survival of many ice-dependent species.

For this study, a regional, 22-km resolution, ice–ocean coupled model is forced with observationally based historical atmospheric data (e.g., NCEP–NCAR reanalysis), and with climate change projections from a global climate model. The forcing for the lateral boundaries, which exist at the northern and southern boundaries of the model, is provided by a basinwide (Arctic Ocean) model, which was set up for this purpose and run offline using the same forcing.

In the process of setting up the models, it was found that the NCEP–NCAR air temperatures over the CAA region were systematically too cold compared to in situ observations; the resulting simulated ice thicknesses were much larger than observed (up to 10 m). In addition, air temperatures from the ECMWF reanalysis (ERA-15) project had similar problems. Therefore, the NCEP–NCAR air temperatures were adjusted to remove most of this bias.

The model does reasonably well in representing the historical sea ice from 1950 to 2004. Spatial patterns of ice thickness and area are as expected, including the polynyas in Amundsen Gulf and Smith Sound. The patterns of breakup and freezeup are similar to observations, except along the Alaskan coast and in southern channels of Gulf of Boothia and M’Clintock Channel. Compared to observations, the model retains too much ice along the Alaskan coast, and not enough ice in the southern channels. Hence, the model underestimates summertime ice cover, simulating ice-free conditions in the southern channels and lower ice concentrations in M’Clure Strait. The seasonal cycle of ice extent agrees well with observations, with the CAA region being completely covered with sea ice from November to May, but the timing of the minimum ice cover occurs several weeks too early. Even so, the model captures the interannual variability in summertime ice cover, as well as the unusually light ice year of 1998.

Simulated ice volume changes in the CAA region are mostly from net export and growth, which are found to be negatively correlated: the export of ice results in increased growth of replacement ice, and ice growth results in more ice available for export. Years of net import and melt are less common, and years of net export and melt do not occur in the model results.

Polynyas are key regions of ice generation and dominate the variability in ice advection. For example, the fluxes through Amundsen Gulf, a polynya region, control the simulated interannual variability in ice advection as well as changes in ice volume for the CAA region. In addition, most of the sea ice exported from the CAA region (to the Beaufort Sea or Baffin Bay) is generated within the polynya regions of Amundsen Gulf, Smith Sound, and Lancaster Sound. Ice fluxes within the interior CAA region are much smaller in comparison.

Simulated ice area fluxes compare well with observations, but the comparison to volume fluxes is limited by the method used to estimate ice volume flux from observations of ice area flux. Associated ice thickness data are not available, so a representational ice thickness is applied to the area flux data. This method is assessed using data from the CAA regional model and does poorly in regions of high variability (i.e., in ice direction or thickness); in fact, estimates using this method should be viewed with caution.

The future atmospheric forcing for the regional CAA model represents the projected climate during the mid-twenty-first century, under the SRES A2 scenario, and it is taken from the Canadian CGCM2 model. The forcing is specified by adding the climatological monthly change, simulated by CGCM2, between 1970–89 and 2041–60, to the historical forcing. Generally, the future forcing has higher air temperatures and precipitation than in the past.

While global climate models project an overall summertime ice retreat in the Northern Hemisphere, they imply a persistence of wintertime sea ice in the CAA region (and central Arctic). Results from this study agree: the CAA region remains ice covered by midcentury, with little change in wintertime ice extent or ice concentrations. Ice retreat is more evident in summer; ice concentrations decrease by 46%. Ice thickness is also reduced, by 17% in the winter and by 36% in the summer. In spite of this ice retreat, perennial ice is retained in the Queen Elizabeth Islands (QEI). Generally, ice is projected to be more mobile in the future, especially in the northern channels.

The accessibility of the Northwest Passage for commercial shipping is of major interest. A simple index is used to estimate the frequency of accessible years.9 Based on the model results for the past (1970–89) time period, the shallow water route through the Queen Maud Gulf is accessible 50%–60% of the years, and the deep water route through Viscount Melville Sound is closed. In the future simulation, the shallow water route is accessible every year, while the deep water route is accessible 30%–50% of the time. Results from this model suggest that a completely ice-free CAA is unlikely by midcentury, but the Northwest Passage will be accessible for commercial shipping. In view of the extreme retreat of summertime ice in 2007, such a projection seems plausible.

Acknowledgments

This research was supported by the ArcticNet NCE and the Polar Climate Stability Network, funded by the Canadian Foundation for Climate and Atmospheric Sciences. We thank Andrew Weaver, Humfrey Melling, Greg Holloway, and Nadja Steiner for their contributions to this project, and we appreciate the helpful comments from the reviewers.

REFERENCES

  • ACIA, 2005: Arctic Climate Impact Assessment. Cambridge University Press, 1042 pp.

  • Agnew, T., , B. Alt, , R. D. Abreu, , and S. Jeffers, 2001: The loss of decades old sea ice plugs in the Canadian Arctic Islands. Extended Abstracts, Sixth Conf. on Polar Meteorology and Oceanography, San Diego, CA, Amer. Meteor. Soc., 1.5.

  • Agnew, T., , A. Lambe, , and D. Long, 2008: Estimating sea ice area flux across the Canadian Arctic Archipelago using enhanced AMSR-E. J. Geophys. Res., 113 , C10011. doi:10.1029/2007JC004582.

    • Search Google Scholar
    • Export Citation
  • Barber, D. G., , and J. M. Hanesiak, 2004: Meteorological forcing of sea ice concentrations in the southern Beaufort Sea over the period 1979 to 2000. J. Geophys. Res., 109 , C06014. doi:10.1029/2003JC002027.

    • Search Google Scholar
    • Export Citation
  • Bourke, R. H., , and R. P. Garrett, 1987: Sea ice thickness distribution in the Arctic Ocean. Cold Reg. Sci. Technol., 13 , 259280.

  • Bromwich, D. H., , R. L. Fogt, , K. I. Hodges, , and J. E. Walsh, 2007: A tropospheric assessment of the ERA-40, NCEP, and JRA-25 global reanalyses in the polar regions. J. Geophys. Res., 112 , D10111. doi:10.1029/2006JD007859.

    • Search Google Scholar
    • Export Citation
  • Brown, R. D., , and P. Cote, 1992: Interannual variability of landfast ice thickness in the Canadian High Arctic, 1950–89. Arctic, 45 , 273284.

    • Search Google Scholar
    • Export Citation
  • Bryan, K., 1969: A numerical method for the study of the circulation of the world ocean. J. Comput. Phys., 4 , 347376.

  • CIS, 2002: Sea Ice Climatic Atlas: Northern Canadian Waters, 1971–2000. Canadian Ice Service–Environment Canada, 262 pp.

  • Curry, J. A., , J. L. Schramm, , A. Alam, , R. Reeder, , T. E. Arbetter, , and P. Guest, 2002: Evaluation of data sets used to force sea ice models in the Arctic Ocean. J. Geophys. Res., 107 , 8027. doi:10.1029/2000JC000466.

    • Search Google Scholar
    • Export Citation
  • Derocher, A., , N. Lunn, , and I. Stirling, 2004: Polar bears in a warming climate. Integr. Comput. Biol., 44 , 163176.

  • Dey, B., 1981: Monitoring winter sea ice dynamics in the Canadian Arctic with NOAA-TIR images. J. Geophys. Res., 86 , 32233235.

  • Dumas, J. A., , G. M. Flato, , and R. D. Brown, 2006: Future projections of landfast ice thickness and duration in the Canadian Arctic. J. Climate, 19 , 51755189.

    • Search Google Scholar
    • Export Citation
  • Dumas, J. A., , H. Melling, , and G. M. Flato, 2007: Late-summer pack ice in the Canadian Archipelago: Thickness observations from a ship in transit. Atmos.–Ocean, 45 , 5770.

    • Search Google Scholar
    • Export Citation
  • ESA, cited. 2007: Satellites witness lowest Arctic ice coverage in history. [Available online at http://www.esa.int/esaCP/SEMYTC13J6F_index_0.html.].

    • Search Google Scholar
    • Export Citation
  • Flato, G. M., , and R. D. Brown, 1996: Variability and climate sensitivity of landfast Arctic sea ice. J. Geophys. Res., 101 , (C10). 2576725777.

    • Search Google Scholar
    • Export Citation
  • Flato, G. M., , and G. Boer, 2001: Warming asymmetry in climate change simulations. Geophys. Res. Lett., 28 , 195198.

  • Hibler III, W. D., 1979: A dynamic thermodynamic sea ice model. J. Phys. Oceanogr., 9 , 815846.

  • Holland, D., 2000: Merged IBCAO/ETOPO5 topography (AOMIP). Center for Atmosphere–Ocean Studies (CA/OS) of the Courant Institute of Mathematical Sciences Tech. Rep. [Available online at http://efdl.cims.nyu.edu/project_aomip/forcing_data/topography/merged/overview.html.].

    • Search Google Scholar
    • Export Citation
  • Holland, D. M., cited. 2000: Merged IBCAO/ETOPO5 global topographic data product. National Geophysical Data Center (NGDC), Boulder, Colorado. [Available online at http://www.ngdc.noaa.gov/mgg/bathymetry/arctic/ibcaorelatedsites.html.].

    • Search Google Scholar
    • Export Citation
  • Holland, M. N., , and C. M. Bitz, 2003: Polar amplification of climate change in coupled models. Climate Dyn., 21 , 221232.

  • Holland, M. N., , C. M. Bitz, , and B. Tremblay, 2006: Future abrupt reductions in the summer Arctic sea ice. Geophys. Res. Lett., 33 , L23503. doi:10.1029/2006GL028024.

    • Search Google Scholar
    • Export Citation
  • Holloway, G., 1992: Representing topographic stress for large-scale ocean models. J. Phys. Oceanogr., 22 , 10331046.

  • Holloway, G., , and T. Sou, 2002: Has Arctic sea ice rapidly thinned? J. Climate, 15 , 16911701.

  • Houghton, J. T., , Y. Ding, , D. J. Griggs, , M. Noguer, , P. J. van der Linden, , X. Dai, , K. Maskell, , and C. A. Johnson, and Eds., 2001: Climate Change 2001: The Scientific Basis. Cambridge University Press, 881 pp.

    • Search Google Scholar
    • Export Citation
  • Howell, S. E. L., , A. Tivy, , J. J. Yackel, , and S. McCourt, 2008: Multi-Year Sea Ice Conditions in the Western Canadian Arctic Archipelago Region of the Northwest Passage: 1968–2006. Atmos.–Ocean, 46 , 229242. doi:10.3137/ao.460203.

    • Search Google Scholar
    • Export Citation
  • Huebert, R., 2001: Climate change and Canadian sovereignty in the Northwest Passage. Isuma: Can. J. Policy Res., 2 , 8694.

  • Hulme, M., , E. M. Barrow, , N. W. Arnell, , P. A. Harrison, , T. C. Johns, , and T. E. Downing, 1999: Relative impacts of human-induced climate change and natural climate variability. Nature, 397 , 688691.

    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437471.

  • Kauker, F., , R. Gerdes, , M. Karcher, , C. Köberle, , and J. L. Lieser, 2003: Variability of Arctic and North Atlantic sea ice: A combined analysis of model results and observations from 1978 to 2001. J. Geophys. Res., 108 , 3182. doi:10.1029/2002JC001573.

    • Search Google Scholar
    • Export Citation
  • Kim, S-J., , G. M. Flato, , G. J. Boer, , and N. A. McFarlane, 2002: A coupled climate model simulation of the last glacial maximum, part 1: Transient response. Climate Dyn., 19 , 515537.

    • Search Google Scholar
    • Export Citation
  • Kliem, N., , and D. A. Greenberg, 2003: Diagnostic simulations of the summer circulation in the Canadian Arctic Archipelago. Atmos.–Ocean, 41 , 273289.

    • Search Google Scholar
    • Export Citation
  • Kreyscher, M., , M. Harder, , P. Lemke, , and G. M. Flato, 2000: Results of the Sea Ice Model Intercomparison Project: Evaluation of sea ice rheology schemes for use in climate simulations. J. Geophys. Res., 105 , 1129911320.

    • Search Google Scholar
    • Export Citation
  • Kwok, R., 2005: Variability of Nares Strait ice flux. Geophys. Res. Lett., 32 , L24502. doi:10.1029/2005GL024768.

  • Kwok, R., 2006: Exchange of sea ice between the Arctic Ocean and the Canadian Arctic Archipelago. Geophys. Res. Lett., 33 , L16501. doi:10.1029/2006GL027094.

    • Search Google Scholar
    • Export Citation
  • Lammers, R. B., , A. I. Shiklomanov, , C. J. Vörösmarty, , B. M. Fekete, , and B. J. Peterson, 2001: Assessment of contemporary Arctic river runoff based on observational discharge records. J. Geophys. Res., 106 , 33213334.

    • Search Google Scholar
    • Export Citation
  • Maslowski, W., , and W. H. Lipscomb, 2003: High-resolution simulations of Arctic sea ice, 1979–1993. Polar Res., 22 , 6774.

  • Melling, H., 2000: Exchanges of freshwater through the shallow straits of the North American Arctic. The Freshwater Budget of the Arctic Ocean, E. L. Lewis et al., Eds., Kluwer Academic Publishers, 479–502.

    • Search Google Scholar
    • Export Citation
  • Melling, H., 2001: Is the extent or thickness of Arctic sea ice declining? The State of the Arctic Cryosphere during the Extreme Warm Summer of 1998: Documenting Cryospheric Variability in the Canadian Arctic, CCAF Summer 1998 Project Final Report. [Available online at http://www.socc.ca/summer/ftp/ftp/html.].

    • Search Google Scholar
    • Export Citation
  • Melling, H., 2002: Sea ice of the northern Canadian Arctic Archipelago. J. Geophys. Res., 107 , 3181. doi:10.1029/2001JC001102.

  • Nakicenovic, N., , and R. Swart, Eds. 2000: Emission Scenarios. Cambridge University Press, 570 pp.

  • Nazarenko, L., , G. Holloway, , and N. Tausnev, 1998: Dynamics of transport of “Atlantic Signature” in the Arctic Ocean. J. Geophys. Res., 103 , 3100331015.

    • Search Google Scholar
    • Export Citation
  • Pacanowski, R., 1995: MOM2 documentation, user’s guide and reference manual. Geophysical Fluid Dynamics Laboratory Ocean Group Tech. Rep. 3, NOAA/GFDL Laboratory, Princeton University, 232 pp.

    • Search Google Scholar
    • Export Citation
  • Parkinson, C. L., 2000: Recent trend reversals in Arctic sea ice extents: Possible connections to the North Atlantic Oscillation. Polar Geogr., 24 , 112.

    • Search Google Scholar
    • Export Citation
  • Parkinson, C. L., , and W. M. Washington, 1979: A large-scale numerical model of sea ice. J. Geophys. Res., 84 , 311337.

  • Parkinson, C. L., , and D. J. Cavalieri, 2002: A 21 year record of Arctic sea-ice extents and their regional, seasonal and monthly variability and trends. Ann. Glaciol., 34 , 441446.

    • Search Google Scholar
    • Export Citation
  • Polyakov, I. V., and Coauthors, 2003: Long-term ice variability in Arctic marginal seas. J. Climate, 16 , 20782085.

  • Rigor, I. G., , R. L. Colony, , and S. Martin, 2000: Variations in surface air temperature observations in the Arctic, 1979–97. J. Climate, 13 , 896914.

    • Search Google Scholar
    • Export Citation
  • Rosati, A., , and K. Miyakoda, 1988: A general circulation model for upper ocean simulation. J. Phys. Oceanogr., 18 , 16011626.

  • Rothrock, D. A., , and J. Zhang, 2005: Arctic Ocean sea ice volume: What explains its recent depletion? J. Geophys. Res., 110 , C01002. doi:10.1029/2004JC002282.

    • Search Google Scholar
    • Export Citation
  • Sadler, H., 1976: Water, heat and salt transports through Nares Strait, Ellesmere Island. Fish. Res. Board Can., 33 , 22862295.

  • Serreze, M. C., , and C. M. Hurst, 2000: Representation of mean Arctic precipitation from NCEP–NCAR and ERA re-analyses. J. Climate, 13 , 182201.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., , M. P. Clark, , and D. H. Bromwich, 2003: Monitoring precipitation over the Arctic terrestrial drainage system: Data requirements, shortcomings, and applications of atmospheric reanalysis. J. Hydrometeor., 4 , 387407.

    • Search Google Scholar
    • Export Citation
  • Simmonds, M., , and S. Isaac, 2007: The impacts of climate change on marine mammals: Early signs of significant problems. Oryx, 41 , 1926.

    • Search Google Scholar
    • Export Citation
  • Solomon, S., , D. Qin, , M. Manning, , M. Marquis, , K. Averyt, , M. M. B. Tignor, , H. L. Miller Jr., , and Z. Chen, Eds. 2007: Climate Change 2007: The Physical Scientific Basis. Cambridge University Press, 996 pp.

    • Search Google Scholar
    • Export Citation
  • Sou, T. V., 2007: The flow and variability of sea-ice in the Canadian Arctic Archipelago: Modelling the past (1950–2004) and the future (2041–2060). M.S. thesis, Dept. of Earth and Ocean Sciences, University of Victoria, BC, Canada, 135 pp. [Available online at https://dspace.library.uvic.ca:8443/dspace/bitstream/1828/208/1/tessasou.pdf.].

  • Steele, M., , R. Morley, , and W. Ermold, 2001: PHC: A global ocean hydrography with a high-quality Arctic Ocean. J. Climate, 14 , 20792087.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J., , M. C. Serreze, , F. Fetterer, , T. Arbetter, , W. Meier, , and J. Maslanik, 2005: Tracking the Arctic’s shrinking ice cover: Another extreme September minimum in 2004. Geophys. Res. Lett., 32 , L04501. doi:10.1029/2004GL021810.

    • Search Google Scholar
    • Export Citation
  • Stroeve, J., , M. M. Holland, , W. Meier, , T. Scambos, , and M. Serreze, 2007: Arctic sea ice decline: Faster than forecast. Geophys. Res. Lett., 34 , L09501. doi:10.1029/2007GL029703.

    • Search Google Scholar
    • Export Citation
  • Tivy, A., , T. Sou, , T. Carrieres, , G. Flato, , and G. Holloway, 2004: Critical aspects of changes in sea ice cover on energy production. Canadian Ice Service Tech. Rep. 04-01, 100 pp.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131 , 29613012.

  • Walsh, J. E., , and M. S. Timlin, 2003: Northern Hemisphere sea ice simulations by global climate models. Polar Res., 22 , 7582.

  • Walsh, J. E., , W. D. Hibler III, , and B. Ross, 1985: Numerical simulation of Northern Hemisphere sea ice variability, 1951–1980. J. Geophys. Res., 90 , (C3). 48474865.

    • Search Google Scholar
    • Export Citation
  • Zhang, X., , and J. E. Walsh, 2006: Toward a seasonally ice-covered Arctic Ocean: Scenarios from the IPCC AR4 model simulations. J. Climate, 19 , 17301747.

    • Search Google Scholar
    • Export Citation

Fig. 1.
Fig. 1.

The CAA model domain and bathymetry, as well as selected place names. The yellow line represents possible routes through the Northwest Passage.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 2.
Fig. 2.

Median ice concentrations for the week of (left) 15 May and (right) 2 Jul. (top) Observations from 1971 to 2000 are taken from the CIS atlas (CIS 2002); also shown are model results from (middle) 1970–89 and (bottom) 2041–60. There is very little difference in the plots of simulated median ice concentrations averaged over 1970–89 and 1971–2000 (not shown). The 10/10 category (shown in black) represents consolidated, immobile ice, defined by a median ice velocity of less than 0.005 m s−1 for the model results.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 3.
Fig. 3.

Same as Fig. 2 but for the week of 10 Sep.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 4.
Fig. 4.

Modeled ice thickness for the week of (left) 15 May and (right) 10 Sep. Results averaged over (upper) 1970–89 and (lower) 2041–60 are shown.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 5.
Fig. 5.

Simulated summer duration based on different criteria: (left) summer duration is dependent on the median ice concentration of one-tenth; (right) it is dependent on the median ice velocity. Results are shown averaged over (upper) 1970–89 and (lower) 2041–60.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 6.
Fig. 6.

Time series of normalized minimum ice coverage from 1971–2004; the dashed line is based on observations from the CIS atlas (CIS 2002, updated) and the solid line is the result of the CAA model.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 7.
Fig. 7.

Changes in modeled ice volume: balance between thermodynamics and advection.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 8.
Fig. 8.

Gate locations used for model ice flux diagnostics. Gray represents the CAA study region. Additional gates within the CAA study region are used to compare ice fluxes through the CAA interior and ice fluxes from the polynyas in Lancaster Sound, Smith Sound, and Amundsen Gulf.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 9.
Fig. 9.

Annually averaged ice volume fluxes through the gates shown in Fig. 8, (upper) the fluxes through the individual northern gates, and (lower) the fluxes through the individual southern gates. Positive values represent import and negative values represent export from the CAA study region.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 10.
Fig. 10.

Simulated daily ice volume fluxes through selected gates from 1999 to 2004. Pink represents open water conditions.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 11.
Fig. 11.

Comparison of observed and modeled ice area fluxes through three northern gates. The solid lines are observations and dashed lines are model results for different gates: the southern Amundsen Gulf gate is blue, the northern M’Clure Strait is green, and the Queen Elizabeth gate is red. Observations from Kwok (2006) are annual mean estimates and observations from Agnew et al. (2008) are wintertime estimates from September to June.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Fig. 12.
Fig. 12.

Frequency of simulated accessible years with good shipping conditions, for (upper) 1970–89 and (lower) 2041–60. Good shipping conditions occur when both the ice concentration is less than 60% and the ice thickness is less than 1.0 m, for a minimum of eight weeks in the year.

Citation: Journal of Climate 22, 8; 10.1175/2008JCLI2335.1

Table 1.

Simulated 55-yr annually averaged ice volume and area fluxes through gates shown in Fig. 8, as well as associated simulated ice thickness and velocity. Positive (negative) values indicate import (export) into the CAA region.

Table 1.
Table 2.

Observed and modeled ice fluxes through southern gates, 2002–03. Observations (Agnew et al. 2008) represent wintertime estimates from June to September. Modeled data are from the CAA model.

Table 2.
Table 3.

Simulated ice fluxes through gates for the past (1970–89) and future (2041–60) time periods, including ice volume and area fluxes, as well as average thickness and velocity.

Table 3.
Table 4.

Simulated net freshwater fluxes (km3 yr−1) from oceanic and ice transports for the past (1970–89) and future (2041–60) time periods, assuming ice salinity of 4.0 ppt and ocean salinity of 34.80 ppt.

Table 4.

1

The bottom of the levels are as follows: 5, 10, 15, 20, 25, 30, 40, 55, 75, 100, 130, 165, 205, 250, 300, 360, 430, 510, 600, 700, 810, 930, 1060, and 1200 m.

2

Breakup occurs when ice velocity becomes greater than 0.005 m s−1, and freezeup occurs when ice velocities become less than 0.005 m s−1.

3

The week of 10 September represents the climatological yearly minimum.

4

The simulated annual mean export for 1950–2004 is 116 km3 yr−1 and for growth is 108 km3 yr−1.

5

For further comparison, fluxes through Barrow Strait and southern Amundsen Gulf are also provided in Table 1.

6

Normalized ice coverage is the ice area divided by the regional area.

7

Summer duration is the period of median ice concentration less than one-tenth.

8

Strength of the ice is also important, but is not considered here.

9

An accessible year is defined as having ice with less than 60% concentration and 1.0-m thickness for a minimum of 8 weeks.

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