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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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 https://lpdaac.usgs.gov, maintained by the NASA EOSDIS LP DAAC at the USGS/EROS Center, Sioux Falls, South Dakota; AWS data from http://climate.weather.gc.ca/ (Canada) and https://www.dmi.dk/publikationer/ (Greenland); ERA-Interim data from the European Centre for Medium-Range Weather Forecast at https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim; and CMIP5 climate model outputs from https://esgf-node.llnl.gov/projects/cmip5/.
The codes used in this study are available at: https://github.com/sarahwcooley/shorefast-sea-ice-breakup37.
Notz, D. & Stroeve, J. Observed Arctic sea-ice loss directly follows anthropogenic CO2 emission. Science 354, 747–750 (2016).
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).
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).
Biskaborn, B. K. et al. Permafrost is warming at a global scale. Nat. Commun. 10, 264 (2019).
Rawlins, M. A. et al. Analysis of the Arctic system for freshwater cycle intensification: observations and expectations. J. Clim. 23, 5715–5737 (2010).
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).
Ford, J. D. et al. Sea ice, climate change, and community vulnerability in northern Foxe Basin, Canada. Clim. Res. 38, 137–154 (2009).
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).
Overeem, I. et al. Sea ice loss enhances wave action at the Arctic coast. Geophys. Res. Lett. 38, L17503 (2011).
Laidre, K. L. et al. Quantifying the sensitivity of Arctic marine mammals to climate-induced habitat change. Ecol. Appl. 18, 97–125 (2008).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
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).
Fetterer, F., Knowles, K., Meier, W. H., Savoie, M. & Windnagel, A. K. Sea Ice Index Version 3 (National Snow and Ice Data Center, 2017); https://doi.org/10.7265/N5K072F8
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).
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).
Olonscheck, D., Mauritsen, T. & Notz, D. Arctic sea-ice variability is primarily driven by atmospheric temperature fluctuations. Nat. Geosci. 12, 430–434 (2019).
Cook, A. J. et al. Atmospheric forcing of rapid marine-terminating glacier retreat in the Canadian Arctic Archipelago. Sci. Adv. 5, eaau8507 (2019).
Pithan, F. & Mauritsen, T. Arctic amplification dominated by temperature feedbacks in contemporary climate models. Nat. Geosci. 7, 181–184 (2014).
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).
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).
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).
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).
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).
Vermote, E. F. & Wolfe, R. MOD09GQ MODIS/Terra Surface Reflectance Daily L2G Global 250m SIN Grid V006 (NASA EOSDIS Land Processes DAAC, 2015); https://doi.org/10.5067/MODIS/MOD09GQ.006
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).
Planet Application Program Interface: In Space for Life on Earth (Planet Team, 2019); https://api.planet.com
Lindsay, R., Wensnahan, M., Schweiger, A. & Zhang, J. Evaluation of seven different atmospheric reanalysis products in the Arctic. J. Clim. 27, 2588–2606 (2014).
Cooley, S. W. Shorefast Sea Ice Breakup Detection Workflow First release (2020); https://doi.org/10.5281/zenodo.3699663
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.
The authors declare no competing interests.
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 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.
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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). https://doi.org/10.1038/s41558-020-0757-5
Nature Climate Change (2021)
Climatic Change (2021)