Abstract

Snow is the most reflective, and also the most insulative, natural material on Earth. Consequently, it is an integral part of the sea-ice and climate systems. However, the spatial and temporal heterogeneities of snow pose challenges for observing, understanding and modelling those systems under anthropogenic warming. Here, we survey the snow–ice system, then provide recommendations for overcoming present challenges. These include: collecting process-oriented observations for model diagnostics and understanding snow–ice feedbacks, and improving our remote sensing capabilities of snow for monitoring large-scale changes in snow on sea ice. These efforts could be achieved through stronger coordination between the observational, remote sensing and modelling communities, and would pay dividends through distinct improvements in predictions of polar environments.

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Data availability

The N-ICE2015 snow data101 are available via the Norwegian Polar Institute at https://go.nature.com/2OBliCi. The climatological snow data are available at https://doi.org/10.7265/N5MS3QNJ. The ice mass balance buoy data102 are available at: http://imb-crrel-dartmouth.org. The ERA-Interim data103 used for Fig. 2 are available at https://doi.org/10.1002/qj.828. The in situ data shown in Fig. 3a were provided by the SCAR Antarctic Sea Ice Processes and Climate (ASPeCt) programme (http://aspect.antarctica.gov.au). The Operation IceBridge snow radar data104 are available at https://doi.org/10.5067/FAZTWP500V70.

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References

  1. 1.

    Warren, S. G. Optical properties of snow. Rev. Geophys. 20, 67–89 (1982).

  2. 2.

    Perovich, D. K., Grenfell, T. C., Light, B. & Hobbs., P. V. Seasonal evolution of the albedo of multiyear Arctic sea ice. J. Geophys. Res. 107(C10), 8044 (2002).

  3. 3.

    Derksen, C. & Brown, R. Spring snow cover extent reductions in the 2008–2012 period exceeding climate model projections. Geophys. Res. Lett. 39, L19504 (2012).

  4. 4.

    IPCC Climate Change 2014: Synthesis Report (eds Core Writing Team, Pachauri, R. K. & Meyer, L. A.) (IPCC, 2014).

  5. 5.

    Mudryk, L. R., Kushner, P. J., Derksen, C. & Thackeray, C. Snow cover response to temperature in observational and climate model ensembles. Geophys. Res. Lett. 44, 919–926 (2017).

  6. 6.

    Ledley, T. S. Snow on sea ice: competing effects in shaping climate. J. Geophys. Res. 96, 17195–17208 (1991).

  7. 7.

    Sturm, M. & Massom, R. A. in Sea Ice 3rd edn (ed. Thomas, D. N.) 65–109 (Wiley and Blackwell, Oxford, 2017).The most recent review of snow on Arctic and Antarctic sea ice.

  8. 8.

    Maykut, G. A. & Untersteiner, N. Some results from a time-dependent thermodynamic model of sea ice. J. Geophys. Res. 76, 1550–1575 (1971).

  9. 9.

    Sturm, M., Perovich, D. K. & Holmgren, J. Thermal conductivity and heat transfer through the snow on the ice of the Beaufort Sea. J. Geophys. Res. 107(C21), 8043 (2002).

  10. 10.

    Sturm, M., Holmgren, J. & Perovich, D. K. Winter snow cover on the sea ice of the Arctic Ocean at the Surface Heat Budget of the Arctic Ocean (SHEBA): temporal evolution and spatial variability. J. Geophys. Res. 107(C10), 8047 (2002). An observational analysis on the evolution and spatial distribution of snow on Arctic sea ice over the seasonal cycle, which concludes with recommendations for representing snow cover variations in models.

  11. 11.

    Filhol, S. & Sturm, M. Snow bedforms: a review, new data and a formation model. J. Geophys. Res. 120, 1645–1669 (2015).

  12. 12.

    Trujillo, E., Leonard, K., Maksym, T. & Lehning, M. Changes in snow distribution and surface topography following a snowstorm on Antarctic sea ice. J. Geophys. Res. Earth Surf. 121, 2172–2191 (2016).

  13. 13.

    Leonard, K. & Maksym, T. The importance of wind-blown snow redistribution to accumulation on and mass balance of Bellingshausen Sea ice. Ann. Glaciol. 52, 271–278 (2011).This analysis uses Antarctic field observations to quantify snow accumulation on level ice and inform a modelling investigation, which showed that about half of precipitation over sea ice could be lost to leads.

  14. 14.

    Déry, S. J. & Tremblay, L. ‐B. Modeling the effects of wind redistribution on the snow mass budget of polar sea ice. J. Phys. Oceanogr. 34, 258–271 (2004).

  15. 15.

    Eicken, H., Lange, M. A., Hubberten, H.-W. & Wadhams, P. Characteristics and distribution patterns of snow and meteoric ice in the Weddell Sea and their contribution to the mass balance of sea ice. Ann. Geophys. 12, 80–93 (1994).

  16. 16.

    Massom, R. A., Drinkwater, M. R. & Haas, C. Winter snow cover on sea ice in the Weddell Sea. J. Geophys. Res. 102, 1101–1117 (1997).

  17. 17.

    Sturm, M., Morris, K. & Massom, R. in Antarctic Sea Ice: Physical Processes, Interactions and Variability Vol. 74 (ed. Jeffries, M. O.) 1–18 (AGU, Washington DC, 1998).

  18. 18.

    O’Brien, H. W. & Munis, R. H. Red and Near-Infrared Spectral Reflectance of Snow Report No. 332 (Cold Regions Research and Engineering Laboratory, 1975).

  19. 19.

    Colbeck, S. C. The layered character of snow covers. Rev. Geophys. 291, 81–96 (1991).

  20. 20.

    Warren, S. et al. Snow depth on Arctic sea ice. J. Clim. 12, 1814–1829 (1999).

  21. 21.

    Gerland, S. & Haas, C. Snow‐depth observations by adventurers traveling on Arctic sea ice. Ann. Glaciol. 52, 369–376 (2011).

  22. 22.

    Webster, M. A. et al. Interdecadal changes in snow depth on Arctic sea ice. J. Geophys. Res. Oceans 119, 5395–5406 (2014).

  23. 23.

    Haas, C. et al. Ice and snow depth variability and change in the high Arctic Ocean observed by in situ measurements. Geophys. Res. Lett. 44, 10462–10469 (2017).

  24. 24.

    Simmonds, I., Burke, C. & Keay, K. Arctic climate change as manifest in cyclone behavior. J. Clim. 21, 5777–5796 (2008).

  25. 25.

    Lique, C., Holland, M. M., Dibike, Y. B., Lawrence, D. M. & Screen, J. A. Modeling the Arctic freshwater system and its integration in the global system: lessons learned and future challenges. J. Geophys. Res. Biogeosci. 121, 540–566 (2016).

  26. 26.

    Boisvert, L. et al. Intercomparison of precipitation estimates over the Arctic Ocean and its peripheral seasfrom reanalyses. J. Clim. 31, 8441–8462 (2018).

  27. 27.

    Gallet, J. C. et al. Spring snow conditions on Arctic sea ice north of Svalbard during the Norwegian young sea ICE (N-ICE2015) expedition. J. Geophys. Res. Atmos. 122, 10820–10836 (2017).

  28. 28.

    Granskog, M. A. et al. Snow contribution to first-year and second-year Arctic sea ice mass balance north of Svalbard. J. Geophys. Res. Oceans 122, 2539–2549 (2017). Isotope data from sea-ice cores is used to quantify the contribution of snow-ice formation to sea ice north of Svalbard.

  29. 29.

    Merkouriadi, I., Cheng, B., Graham, R. M., Rösel, A. & Granskog, M. A. Critical role of snow on sea ice growth in the Atlantic sector of the Arctic Ocean. Geophys. Res. Lett. 44, 10479–10485 (2017).

  30. 30.

    Provost, C. et al. Observations of flooding and snow-ice formation in a thinner Arctic sea-ice regime during the N-ICE2015 campaign: influence of basal ice melt and storms. J. Geophys. Res. Oceans 122, 7115–7134 (2017). An investigation on the observed flooding and snow-ice formation north of Svalbard due to storm-induced breakup of ice floes and loss of buoyancy due to basal ice melt.

  31. 31.

    Rösel, A. et al. Thin sea ice, thick snow and widespread negative freeboard observed during N-ICE2015 north of Svalbard. J. Geophys. Res. Oceans 123, 1156–1176 (2018).

  32. 32.

    Hezel, P. J., Zhang, X., Bitz, C. M., Kelly, B. P. & Massonnet, F. Projected decline in spring snow depth on Arctic sea ice caused by progressively later autumn open ocean freeze-up this century. Geophys. Res. Lett. 39, L17505 (2012). The first analysis of snow depth on Arctic sea ice from the Coupled Model Intercomparison Project Phase 5, which showed a decline in snow depth and attributed the decline to the loss of sea-ice area in autumn and winter.

  33. 33.

    Blanchard-Wrigglesworth, E., Webster, M. A., Farrell, S. L. & Bitz, C. M. Reconstruction of snow on Arctic sea ice. J. Geophys. Res. Oceans 123, 3588–3602 (2018).

  34. 34.

    Perovich, D. K. et al. Increasing solar heating of the Arctic Ocean and adjacent seas, 1979–2005: attribution and role in the ice-albedo feedback. Geophys. Res. Lett. 34, L19505 (2007).

  35. 35.

    Holland, M. M. & Landrum, L. Factors affecting projected Arctic surface shortwave heating and albedo change in coupled climate models. Phil. Trans. R. Soc. Lond. A 373, 20140162 (2015).A large ensemble from an Earth system model is used to quantify the simulated changes associated with changing solar radiation and ice conditions in the twentieth and twenty-first centuries.

  36. 36.

    Markus, T., Stroeve, J. C. & Miller, J. Recent changes in Arctic sea ice melt onset, freezeup, and melt season length. J. Geophys. Res. 114, C12024 (2009).

  37. 37.

    Bliss, A. C. & Anderson, M. R. Arctic sea ice melt onset timing from passive microwave- and surface air temperature-based methods. J. Geophys. Res. Atmos. 123, 9063–9080 (2018).

  38. 38.

    Eicken, H., Grenfell, T. C., Perovich, D. K., Richter-Menge, J. A. & Frey, K. Hydraulic controls of summer Arctic pack ice albedo. J. Geophys. Res. 109, C08007 (2004).

  39. 39.

    Polashenski, C. et al. Percolation blockage: a process that enables melt pond formation on first year Arctic sea ice. J. Geophys. Res. Oceans 122, 413–440 (2017).

  40. 40.

    Petrich, C. et al. Snow dunes: a controlling factor of melt pond distribution on Arctic sea ice. J. Geophys. Res. 117, C09029 (2012).

  41. 41.

    Polashenski, C., Perovich, D. K. & Courville, Z. The mechanisms of sea ice melt pond formation and evolution. J. Geophys. Res. 117, C01001 (2012).

  42. 42.

    Nghiem, S. V. et al. Rapid reduction of Arctic perennial sea ice. Geophys. Res. Lett. 34, L19504 (2007).

  43. 43.

    Maslanik, J., Stroeve, J., Fowler, C. & Emery, W. Distribution and trends in Arctic sea ice age through spring 2011. Geophys. Res. Lett. 38, L13502 (2011).

  44. 44.

    Nicolaus, M., Katlein, C., Maslanik, J. & Hendricks, S. Changes in Arctic sea ice result in increasing light transmittance and absorption. Geophys. Res. Lett. 39, L24501 (2012).

  45. 45.

    Light, B., Perovich, D. K., Webster, M., Polashenski, C. & Dadic, R. Optical properties of melting first-year Arctic sea ice. J. Geophys. Res. Oceans 120, 7657–7675 (2015).

  46. 46.

    Massom, R. A. et al. Snow on Antarctic sea ice. Rev. Geophys. 39, 413–445 (2001).

  47. 47.

    Maksym, T., Stammerjohn, S. E., Ackley, S. & Massom, R. Antarctic sea ice – a polar opposite? Oceanography 25(3), 140–151 (2012).

  48. 48.

    Kwok, R., Pang, S. S. & Kacimi, S. Sea ice drift in the Southern Ocean: regional patterns, variability, and trends. Elem. Sci. Anthrop. 5, 32 (2017).

  49. 49.

    Worby, A. P., Massom, R. A., Allison, I., Lytle, V. I. & Heil, P. in Antarctic Sea Ice: Physical Processes, Interactions and Variability Vol. 74 (ed. Jeffries, M. O.) 41–67 (AGU, Washington DC, 1998).

  50. 50.

    Simmonds, I. & Keay, K. Mean Southern Hemisphere extratropical cyclone behavior in the 40-year NCEP–NCAR reanalysis. J. Clim. 13, 873–885 (2000).

  51. 51.

    Worby, A. P. et al. Thickness distribution of Antarctic sea ice. J. Geophys. Res. 11, C05S92 (2008).

  52. 52.

    Kurtz, N. T. & Markus, T. Satellite observations of Antarctic sea ice thickness and volume. J. Geophys. Res. 117, C08025 (2012).

  53. 53.

    Lindsay, R. & Schweiger, A. Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations. Cryosphere 9, 269–283 (2015).

  54. 54.

    Weeks, W. On Sea Ice (Univ. Alaska Press, Fairbanks, 2010).

  55. 55.

    Arndt, S. et al. Influence of snow depth and surface flooding on light transmission through Antarctic pack ice. J. Geophys. Res. Oceans 122, 2108–2119 (2017).

  56. 56.

    Iacozza, J. & Barber, D. G. An examination of the distribution of snow on sea-ice. Atmos. Ocean 37, 21–51 (1999).

  57. 57.

    Jeffries, M. O., Krouse, H. R., Hurst-Cushing, B. & Maksym, T. Snow-ice accretion and snow-cover depletion on Antarctic first-year sea-ice floes. Ann. Glaciol. 33, 51–60 (2001).

  58. 58.

    Toyota, T. et al. On the extraordinary snow on the sea ice off East Antarctica in late winter, 2012. Deep Sea Res. Pt II 131, 53–67 (2016).

  59. 59.

    Lecomte, O., Fichefet, T., Flocco, D., Schroeder, D. & Vancoppenolle, M. Interactions between wind-blown snow redistribution and melt ponds in a coupled ocean–sea ice model. Ocean Model. 87, 67–80 (2015).

  60. 60.

    Arndt, S., Willmes, S., Dierking, W. & Nicolaus, M. Timing and regional patterns of snowmelt on Antarctic sea ice from passive microwave satellite observations. J. Geophys. Res. Oceans 121, 5916–5930 (2016).

  61. 61.

    Massom, R. A., Lytle, V. I., Worby, A. P. & Allison, I. Winter snow cover variability on East Antarctic sea ice. J. Geophys. Res. 103, 24837–24855 (1998).

  62. 62.

    Maksym, T. & Markus, T. Antarctic sea ice thickness and snow-to-ice conversion from atmospheric reanalysis and passive microwave snow depth. J. Geophys. Res. 113, C02S12 (2008).

  63. 63.

    Haas, C., Thomas, D. N. & Bareiss, J. Surface properties and processes of perennial Antarctic sea ice in summer. J. Glaciol. 47, 613–625 (2001).

  64. 64.

    Toyota, T., Massom, R., Tateyama, K., Tamura, T. & Fraser, A. Properties of snow overlying the sea ice off East Antarctica in late winter, 2007. Deep Sea Res. Pt II 58, 1137–1148 (2011).

  65. 65.

    Lubin, D. & Massom, R. A. Polar Remote Sensing Volume 1: Atmosphere and Ocean (Springer, Chichester, 2006).

  66. 66.

    Stroeve, J. C. et al. Impact of surface roughness on AMSR-E sea ice products. IEEE Trans. Geosci. Remote Sens. 44, 3103–3117 (2006).

  67. 67.

    Worby, A. P., Markus, T., Steer, A. D., Lytle, V. I. & Massom, R. A. Evaluation of AMSR-E snow depth product over East Antarctic sea ice using in situ measurements and aerial photography. J. Geophys. Res. 113, C05S94 (2008).

  68. 68.

    Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) Ch. 9 (IPCC, Cambridge Univ. Press, 2013).

  69. 69.

    Hunke, E., Lipscomb, W. & Turner, A. Sea-ice models for climate study: retrospective and new directions. J. Glaciol. 56, 1162–1172 (2010).

  70. 70.

    Sturm, M., Holmgren, J., Koenig, M. & Morris, K. The thermal conductivity of seasonal snow. J. Glaciol. 43, 26–41 (1997).

  71. 71.

    Blazey, B. A., Holland, M. M. & Hunke, E. C. Arctic Ocean sea ice snow depth evaluation and bias sensitivity in CCSM. Cryosphere 7, 1887–1900 (2013).

  72. 72.

    Lecomte, O. et al. On the formulation of snow thermal conductivity in large-scale sea ice models. J. Adv. Model. Earth Syst. 5, 542–557 (2013).

  73. 73.

    Castro-Morales, K. et al. Sensitivity of simulated Arctic sea ice to realistic ice thickness distributions and snow parameterizations. J. Geophys. Res. Oceans 119, 559–571 (2014).

  74. 74.

    Yang, D. et al. Accuracy of Tretyakov precipitation gauge: result of WMO intercomparison. Hydrol. Proc. 9, 877–895 (1995).

  75. 75.

    Dai, A. Precipitation characteristics in eighteen coupled climate models. J. Clim. 19, 4605–4630 (2006).

  76. 76.

    Ricker, R., Hendricks, S., Perovich, D. K., Helm, V. & Gerdes, R. Impact of snow accumulation on CryoSat-2 range retrievals over Arctic sea ice: an observational approach with buoy data. Geophys. Res. Lett. 42, 4447–4455 (2015).

  77. 77.

    Nandan, V. et al. Effect of snow salinity on CryoSat-2 Arctic first-year sea ice freeboard measurements. Geophys. Res. Lett. 44, 10419–10426 (2017).

  78. 78.

    Goosse, H. et al. Quantifying climate feedbacks in polar regions. Nat. Commun. 9, 1919 (2018).

  79. 79.

    Massonnet, F. et al. Arctic sea-ice change tied to its mean state through thermodynamic processes. Nat. Clim. Change 8, 599–603 (2018).

  80. 80.

    Liston, G. E. Representing sub-grid snow cover heterogeneities in regional and global models. J. Clim. 17, 1381–1397 (2004).

  81. 81.

    Jordan, R., Albert, M. & Brun, E. in Snow and Climate: Physical Processes, Surface Energy Exchange and Modeling (eds Armstrong, R. L. & Brun, E.) 12–69 (Cambridge Univ. Press, Cambridge, 2008).

  82. 82.

    Liston, G. E. et al. Distributed snow evolution model for sea ice applications (SnowModel). J. Geophys. Res. Oceans 7, 1259–1276 (2018).

  83. 83.

    Giles, K. A. et al. Combined airborne laser and radar altimeter measurements over the Fram Strait in May 2002. Remote Sens. Environ. 111, 182–194 (2007).

  84. 84.

    Koenig, L., Martin, S., Studinger, M. & Sonntag, J. Polar airborne observations fill gap in satellite data. Eos 91, 333–334 (2010).

  85. 85.

    Kwok, R. et al. Airborne surveys of snow depth over Arctic sea ice. J. Geophys. Res. 116, C11018 (2011).

  86. 86.

    Kwok, R. & Maksym, T. Snow depth of the Weddell and Bellingshausen sea ice covers from IceBridge surveys in 2010 and 2011: an examination. J. Geophys. Res. Oceans 119, 41414167 (2014).

  87. 87.

    Kurtz, N. & Farrell, S. Large-scale surveys of snow depth on Arctic sea ice from Operation IceBridge. Geophys. Res. Lett. 38, L20505 (2011).

  88. 88.

    Markus, T. & Cavalieri, D. J. in Antarctic Sea Ice: Physical Processes, Interactions and Variability Vol. 74 (ed. Jeffries, M. O.) 19–39 (AGU, Washington DC, 1998).

  89. 89.

    Comiso, J. C., Cavalieri, D. J. & Markus, T. Sea ice concentration, ice temperature, and snow depth using AMSR-E data. IEEE Trans. Geosci. Remote Sens. 41, 243–252 (2003).

  90. 90.

    Brucker, L. & Markus, T. Arctic-scale assessment of satellite passive microwave-derived snow depth on sea ice using Operation IceBridge airborne data. J. Geophys. Res. Oceans 118, 2892–2905 (2013).

  91. 91.

    Willmes, S., Nicolaus, M. & Haas, C. The microwave emissivity variability of snow covered first-year sea ice from late winter to early summer: a model study. Cryosphere 8, 891–904 (2014).

  92. 92.

    Guerreiro, K., Fleury, S., Zakharova, E., Remy, F. & Kourev, A. Potential for estimation of snow depth on Arctic sea ice from CryoSat-2 and SARAL/AltiKa missions. Remote Sens. Environ. 186, 339–349 (2016).

  93. 93.

    Kwok, R. & Markus, T. Potential basin-scale estimates of Arctic snow depth with sea ice freeboards from CryoSat-2 and ICESat-2: an exploratory analysis. Adv. Space Res. 62, 1243–1250 (2018).

  94. 94.

    Holland, M. & Perovich, D. Sea ice summer camp: bringing together sea ice modelers and observers to advance polar science. Bull. Am. Meteorol. Soc. 98, 2057–2059 (2017).

  95. 95.

    Richter-Menge, J. A. et al. Ice mass balance buoys: a tool for measuring and attributing changes in the thickness of the Arctic sea ice cover. Ann. Glaciol. 44, 205–210 (2006).

  96. 96.

    Jackson, K. et al. A novel and low-cost sea ice mass balance buoy. J. Atmos. Ocean Technol. 30, 2676–2688 (2013).

  97. 97.

    Kwok, R. & Cunningham, G. F. ICESat over Arctic sea ice: estimation of snow depth and ice thickness. J. Geophys. Res. 113, C08010 (2008).

  98. 98.

    Maksym, T. & Jeffries, M. O. A one-dimensional percolation model of flooding and snow ice formation on Antarctic sea ice. J. Geophys. Res. 105, 26313–26332 (2000).

  99. 99.

    Wang, C., Cheng, B., Wang, K., Gerland, S. & Pavlova, O. Modelling snow ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard. Polar Res. 34, 20828 (2015).

  100. 100.

    Kwok, R. et al. Intercomparison of snow depth retrievals over Arctic sea ice from radar data acquired by Operation IceBridge. Cryosphere 11, 2571–2593 (2017).

  101. 101.

    N-ICE2015 Datasets (Norwegian Polar Institute, 2016).

  102. 102.

    Perovich, D. et al. Observing and Understanding Climate Change: Monitoring the Mass Balance, Motion, and Thickness of Arctic Sea Ice (CRREL and Univ. Dartmouth, 2017).

  103. 103.

    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).

  104. 104.

    Leuschen, C. IceBridge Snow Radar L1B Geolocated Radar Echo Strength Profiles version 2 (NASA NSIDC Distributed Active Archive Center, 2014).

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Acknowledgements

M.S. was funded by the NASA Terrestrial Hydrology Program. R.M. was supported by the Australian Antarctic Division and the Australian Government’s Cooperative Research Centres Programme through the Antarctic Climate and Ecosystems Cooperative Research Centre. M.H. was supported by the National Science Foundation. D.P. and M.W. were funded by the NASA Cryospheric Sciences Program. O.L. was supported by the Belgian Fonds National de la Recherche Scientifique and the European Commission’s Horizon 2020 projects APPLICATE (GA 727862) and PRIMAVERA (GA 641727). S.G. was supported by the project ID Arctic, funded by the Norwegian Ministries for Foreign Affairs and Climate and Environment (programme Arktis 2030). E.C.H. was supported by the Earth system modelling programme of the Department of Energy’s Biological and Environmental Research Program. R.K. was supported by the Jet Propulsion Laboratory, California Institute of Technology under contract with NASA. We thank the following investigators for the 2000–2017 spring snow depth data shown in Fig. 2a: C. Polashenski, N. Wright, G. Liston and C. Planck from the project Snow, Wind, and Time: Understanding Snow Redistribution and its Effects on Sea Ice Mass Balance (NSF Award Number: 1603361); B. Notenboom on behalf of the 2-Degree North Pole Expedition; the Norwegian Polar Institute’s long-term Arctic sea ice monitoring programme and the Norwegian Young Sea Ice Cruise (N-ICE2015); B. Ousland (and T. Ulrich in 2007) from Arctic traverses in 2001 and 2007, and A. Hubert and D. Dansercoer from the ESA-sponsored Arctic Arc expedition in 2007.

Author information

Affiliations

  1. NASA Goddard Space Flight Center, Greenbelt, MD, USA

    • Melinda Webster
  2. Norwegian Polar Institute, Tromsø, Norway

    • Sebastian Gerland
  3. National Center for Atmospheric Research, Boulder, CO, USA

    • Marika Holland
  4. Fluid Dynamics and Solid Mechanics Group T-3, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA

    • Elizabeth Hunke
  5. Jet Propulsion Laboratory, Pasadena, CA, USA

    • Ron Kwok
  6. Georges Lemaitre Centre for Earth and Climate Research, Earth and Life Institute, Université Catholique de Louvain, Louvain-la-Neuve, Belgium

    • Olivier Lecomte
  7. Australian Antarctic Division and Antarctic Climate and Ecosystems Cooperative Research Centre, Hobart, Tasmania, Australia

    • Robert Massom
  8. Thayer School of Engineering, Dartmouth College, Hanover, NH, USA

    • Don Perovich
  9. University of Alaska Fairbanks, Fairbanks, AK, USA

    • Matthew Sturm

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Contributions

M.W. carried out the data synthesis and led the writing. All authors contributed to the interpretation of the results and writing, each contributing to multiple aspects of the manuscript and its ideas. M.S. created Fig. 1. S.G. and D.P. provided in situ and buoy snow data in Fig. 2. R.K. provided snow depths derived from NASA’s Operation IceBridge snow radar data for Figs. 2 and 3, and the ERA-Interim reconstructed snow depths in Fig. 2.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to Melinda Webster.

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https://doi.org/10.1038/s41558-018-0286-7