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Coldest Canadian Arctic communities face greatest reductions in shorefast sea ice


Shorefast sea ice comprises only about 12% of global sea-ice cover, yet it has outsized importance for Arctic societies and ecosystems. Relatively little is known, however, about the dominant drivers of its breakup or how it will respond to climate warming. Here, we use 19 years of near-daily satellite imagery to document the timing of shorefast ice breakup in 28 communities in northern Canada and western Greenland that rely on shorefast ice for transportation and traditional subsistence activities. Breakup timing is strongly correlated with springtime air temperature, but the sensitivity of the relationship varies substantially among communities. We combine these observations with future warming scenarios to estimate an annual reduction of 5–44 days in the length of the springtime shorefast ice season by 2100. Paradoxically, the coldest communities are projected to experience the largest reductions in springtime ice season duration. Our results emphasize the local nature of climate change and its varied impacts on Arctic communities.

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Fig. 1: Images of shorefast sea ice.
Fig. 2: Study area map showing locations of 28 communities affected by shorefast sea ice in Nunavut and the Northwest Territories, Canada, and in western Greenland.
Fig. 3: Scatter plots of shorefast ice breakup timing (day of year) versus mean springtime air temperature (°C) for all 28 communities as calculated using ERA-Interim data.
Fig. 4: Patterns in breakup sensitivity and projected change in breakup timing by temperature and region.
Fig. 5: Projected changes in springtime air temperature and shorefast ice breakup using eight CMIP5 climate models.

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Data availability

All data needed to evaluate the conclusions of this paper are present in the paper and/or the Supplementary Information. Additional data related to the paper may be requested from the authors. All data can also be accessed online from the following data centres: MOD09GQ and MOD09GA data from, maintained by the NASA EOSDIS LP DAAC at the USGS/EROS Center, Sioux Falls, South Dakota; AWS data from (Canada) and (Greenland); ERA-Interim data from the European Centre for Medium-Range Weather Forecast at; and CMIP5 climate model outputs from

Code availability

The codes used in this study are available at:


  1. Notz, D. & Stroeve, J. Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission. Science 354, 747–750 (2016).

    Article  CAS  Google Scholar 

  2. Mouginot, J. et al. Forty-six years of Greenland Ice Sheet mass balance from 1972 to 2018. Proc. Natl Acad. Sci. USA 116, 04242 (2019).

    Article  Google Scholar 

  3. Park, T., Ganguly, S., Tømmervik, H., Euskirchen, E. S. & Høgda, K. Changes in growing season duration and productivity of northern vegetation inferred from long-term remote sensing data. Environ. Res. Lett. 11, 084001 (2016).

  4. Biskaborn, B. K. et al. Permafrost is warming at a global scale. Nat. Commun. 10, 264 (2019).

    Article  Google Scholar 

  5. Rawlins, M. A. et al. Analysis of the Arctic system for freshwater cycle intensification: observations and expectations. J. Clim. 23, 5715–5737 (2010).

    Article  Google Scholar 

  6. Gearheard, S. et al. ‘It’s Not that Simple’: a collaborative comparison of sea ice environments, their uses, observed changes, and adaptations in Barrow, Alaska, USA, and Clyde River, Nunavut, Canada. Ambio 35, 203−211 (2006).

  7. Ford, J. D. et al. Sea ice, climate change, and community vulnerability in northern Foxe Basin, Canada. Clim. Res. 38, 137–154 (2009).

    Article  Google Scholar 

  8. Mahoney, A. R. in Arctic Report Card 2018 (eds Osborne, E., Richter-Menge, J. A. & Jeffries, M. O.) 99–109 (National Oceanic and Atmospheric Administration, 2018).

  9. Overeem, I. et al. Sea ice loss enhances wave action at the Arctic coast. Geophys. Res. Lett. 38, L17503 (2011).

    Article  Google Scholar 

  10. Laidre, K. L. et al. Quantifying the sensitivity of Arctic marine mammals to climate-induced habitat change. Ecol. Appl. 18, 97–125 (2008).

    Article  Google Scholar 

  11. Mundy, C. J. et al. Contribution of under-ice primary production to an ice-edge upwelling phytoplankton bloom in the Canadian Beaufort Sea. Geophys. Res. Lett. 36, L17601 (2009).

    Article  Google Scholar 

  12. Eicken, H., Lovecraft, A. L. & Druckenmiller, M. L. Sea-Ice System Services: a framework to help identify and meet information needs relevant for Arctic observing networks. Arctic 62, 119–136 (2009).

    Article  Google Scholar 

  13. Laidler, G. J. et al. Travelling and hunting in a changing Arctic: assessing Inuit vulnerability to sea ice change in Igloolik, Nunavut. Clim. Change 94, 363–397 (2009).

    Article  CAS  Google Scholar 

  14. Meier, W. N., Stroeve, J. & Gearheard, S. Bridging perspectives from remote sensing and Inuit communities on changing sea-ice cover in the Baffin Bay region. Ann. Glaciol. 44, 433–438 (2006).

  15. Baztan, J., Cordier, M., Huctin, J. & Zhu, Z. Life on thin ice: insights from Uummannaq, Greenland for connecting climate science with Arctic communities. Polar Sci. 13, 100–108 (2017).

    Article  Google Scholar 

  16. Pearce, T., Smit, B. & Ford, J. D. Inuit vulnerability and adaptive capacity to climate change in Ulukhaktok, Northwest Territories, Canada. Polar Rec. 46, 157–177 (2010).

    Article  Google Scholar 

  17. Mahoney, A., Eicken, H., Gaylord, A. G. & Shapiro, L. Alaska landfast sea ice: Links with bathymetry and atmospheric circulation. J. Geophys. Res. 112, C02001 (2007).

    Article  Google Scholar 

  18. Mahoney, A. R., Eicken, H., Gaylord, A. G. & Gens, R. Landfast sea ice extent in the Chukchi and Beaufort Seas: the annual cycle and decadal variability. Cold Reg. Sci. Technol. 103, 41–56 (2014).

    Article  Google Scholar 

  19. Petrich, C. et al. Coastal landfast sea ice decay and breakup in northern Alaska: key processes and seasonal prediction. J. Geophys. Res. 117, C02003 (2012).

    Google Scholar 

  20. Howell, S. E. L., Laliberté, F., Kwok, R., Derksen, C. & King, J. Landfast ice thickness in the Canadian Arctic Archipelago from observations and models. Cryosphere 10, 1463–1475 (2016).

    Article  Google Scholar 

  21. Galley, R. J., Else, B. G. T., Howell, S. E. L., Lukovich, J. V. & Barber, D. G. Landfast sea ice conditions in the Canadian Arctic: 1983-2009. Arctic 65, 133–144 (2012).

    Google Scholar 

  22. Fetterer, F., Knowles, K., Meier, W. H., Savoie, M. & Windnagel, A. K. Sea Ice Index Version 3 (National Snow and Ice Data Center, 2017);

  23. Dee, D. P. et al. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597 (2011).

    Article  Google Scholar 

  24. Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

  25. Olonscheck, D., Mauritsen, T. & Notz, D. Arctic sea-ice variability is primarily driven by atmospheric temperature fluctuations. Nat. Geosci. 12, 430–434 (2019).

    Article  CAS  Google Scholar 

  26. Cook, A. J. et al. Atmospheric forcing of rapid marine-terminating glacier retreat in the Canadian Arctic Archipelago. Sci. Adv. 5, eaau8507 (2019).

  27. Pithan, F. & Mauritsen, T. Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nat. Geosci. 7, 181–184 (2014).

    Article  CAS  Google Scholar 

  28. Stewart, E. J., Howell, S. E. L., Draper, D., Yackel, J. & Tivy, A. Sea ice in Canada’s arctic: implications for cruise tourism. Arctic 60, 370–380 (2007).

    Google Scholar 

  29. Bennett, M. M. From state-initiated to Indigenous-driven infrastructure: the Inuvialuit and Canada’s first highway to the Arctic Ocean. World Dev. 109, 134–148 (2018).

    Article  Google Scholar 

  30. Dumas, J. A., Flato, G. M. & Brown, R. D. Future projections of landfast ice thickness and duration in the Canadian Arctic. J. Clim. 19, 5175–5189 (2006).

    Article  Google Scholar 

  31. Dammann, D. O., Eriksson, L. E. B., Mahoney, A. R., Eicken, H. & Meyer, F. J. Mapping pan-Arctic landfast sea ice stability using Sentinel-1 interferometry. Cryosphere 13, 557–577 (2019).

  32. Yu, Y., Stern, H., Fowler, C., Fetterer, F. & Maslanik, J. Interannual variability of Arctic landfast ice between 1976 and 2007. J. Clim. 27, 227–243 (2014).

    Article  Google Scholar 

  33. Vermote, E. F. & Wolfe, R. MOD09GQ MODIS/Terra Surface Reflectance Daily L2G Global 250m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015);

  34. Cooley, S. W. & Pavelsky, T. M. Spatial and temporal patterns in Arctic river ice breakup revealed by automated ice detection from MODIS imagery. Remote Sens. Environ. 175, 310–322 (2016).

    Article  Google Scholar 

  35. Planet Application Program Interface: In Space for Life on Earth (Planet Team, 2019);

  36. Lindsay, R., Wensnahan, M., Schweiger, A. & Zhang, J. Evaluation of seven different atmospheric reanalysis products in the Arctic. J. Clim. 27, 2588–2606 (2014).

    Article  Google Scholar 

  37. Cooley, S. W. Shorefast Sea Ice Breakup Detection Workflow First release (2020);

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This research was funded by an NSF Navigating the New Arctic (NNA) grant (no. 1836473) managed by R. Delgado. S.W.C. acknowledges funding from an NSF Graduate Research Fellowship and from a Geological Society of America Student Research Grant. J.C.R. acknowledges funding from a Voss Postdoctoral Fellowship. We gratefully acknowledge A. Andreasen, the Uummannaq Polar Institute and the Uummannaq Children’s Home for providing lodging and fieldwork support. We thank P. Kreutzmann and M. Johansen for sharing knowledge and for their assistance in the field. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modelling groups listed in the Methods for producing and making available their model output.

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Authors and Affiliations



S.W.C. and J.C.R. conceived the project. S.W.C. developed the methodology, carried out the data analysis and wrote the manuscript. J.C.R. acquired the funding and co-wrote the manuscript. L.C.S. provided supervision and co-wrote the manuscript. B.P. and C.H. assisted with the development of the methodology and edited the manuscript. B.D. and A.H.L. edited the manuscript.

Corresponding author

Correspondence to Sarah W. Cooley.

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The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Walter Meier and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 Scatter plots of shorefast ice breakup timing (day of year) versus mean springtime air temperature (°C) for all 28 communities as calculated using AWS data.

Each row shows communities from the same sub-region as defined in Fig. 1. Black lines show the linear regressions between shorefast ice breakup timing and springtime air temperature, with grey shading indicating the uncertainty in this regression. Single asterisk after community name indicates communities where breakup timing and mean springtime air temperature are uncorrelated at p < 0.05; double asterisk after community name indicates communities with less than 10 years of AWS data. The x and y axes are standardized by range to illustrate the variability in slope.

Extended Data Fig. 2 Example of MODIS-derived percentage water time series for grid cells located near four communities in 2006.

The blue circles represent the MODIS time series after cloud removal and median filtering. The red line represents the detected breakup date, defined as the mid-point of the first day when the grid cell contains greater than 90% water and the previous observation. The grey-shaded region represents the uncertainty due to cloud cover.

Supplementary information

Supplementary Information

Supplementary Text, Supplementary Figs. 1–3 and Supplementary Table 1.

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Cooley, S.W., Ryan, J.C., Smith, L.C. et al. Coldest Canadian Arctic communities face greatest reductions in shorefast sea ice. Nat. Clim. Chang. 10, 533–538 (2020).

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