Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5031-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-18-5031-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Seasonal evolution of the sea ice floe size distribution in the Beaufort Sea from 2 decades of MODIS data
Ellen M. Buckley
Center for Fluid Mechanics, School of Engineering, Brown University, Providence, RI, USA
Leela Cañuelas
Center for Fluid Mechanics, School of Engineering, Brown University, Providence, RI, USA
Mary-Louise Timmermans
Department of Earth and Planetary Sciences, Yale University, New Haven, CT, USA
Monica M. Wilhelmus
CORRESPONDING AUTHOR
Center for Fluid Mechanics, School of Engineering, Brown University, Providence, RI, USA
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Cited articles
Alstott, J., Bullmore, E., and Plenz, D.: powerlaw: a Python package for analysis of heavy-tailed distributions, PloS one, 9, e85777, https://doi.org/10.1371/journal.pone.0095816, 2014. a
Asplin, M. G., Galley, R., Barber, D. G., and Prinsenberg, S.: Fracture of summer perennial sea ice by ocean swell as a result of Arctic storms, J. Geophys. Res.-Oceans, 117, C06025, https://doi.org/10.1029/2011JC007221, 2012. a
Birnbaum, G. and Lüpkes, C.: A new parameterization of surface drag in the marginal sea ice zone, Tellus A, 54, 107–123, https://doi.org/10.3402/tellusa.v54i1.12121, 2002. a
Buckley, E.: ellenbuckley/FSD_segmentation: FSD paper code (v1.0.1), Zenodo [code], https://doi.org/10.5281/zenodo.14010776, 2024. a
Buckley, E. and Wilhelmus, M.: Ice Floe Segmentation of MODIS imagery, Zenodo [data set], https://doi.org/10.5281/zenodo.11553700, 2024. a
Clauset, A., Shalizi, C. R., and Newman, M. E.: Power-law distributions in empirical data, SIAM review, 51, 661–703, https://doi.org/10.48550/arXiv.0706.1062, 2009. a, b
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., and Meygret, A.: Sentinel-2: ESA's optical high-resolution mission for GMES operational services, Remote Sens. Environ., 120, 25–36, https://doi.org/10.1016/j.rse.2011.11.026, 2012. a
Fetterer, F., Knowles, K., Meier, W. N., Savoie, M., and Windnagel, A. K.: Sea Ice Index, Version 3, Boulder, Colorado USA, National Snow and Ice Data Center [data set], https://doi.org/10.7265/N5K072F8, 2017. a
Galley, R. J., Babb, D., Ogi, M., Else, B., Geilfus, N.-X., Crabeck, O., Barber, D. G., and Rysgaard, S.: Replacement of multiyear sea ice and changes in the open water season duration in the Beaufort Sea since 2004, J. Geophys. Res.-Oceans, 121, 1806–1823, https://doi.org/10.1002/2015JC011583, 2016. a, b
Holt, B. and Martin, S.: The effect of a storm on the 1992 summer sea ice cover of the Beaufort, Chukchi, and East Siberian Seas, J. Geophys. Res.-Oceans, 106, 1017–1032, 2001. a
Horvat, C., Tziperman, E., and Campin, J.-M.: Interaction of sea ice floe size, ocean eddies, and sea ice melting, Geophys. Res. Lett., 43, 8083–8090, https://doi.org/10.1002/2016GL069742, 2016. a, b
Hwang, B., Wilkinson, J., Maksym, T., Graber, H. C., Schweiger, A., Horvat, C., Perovich, D. K., Arntsen, A. E., Stanton, T. P., Ren, J., and Wadhams, P.: Winter-to-summer transition of Arctic sea ice breakup and floe size distribution in the Beaufort Sea, Elementa: Science of the Anthropocene, 5, 40, 2017. a, b
Jewell, M. E., Hutchings, J. K., and Geiger, C. A.: Atmospheric highs drive asymmetric sea ice drift during lead opening from Point Barrow, The Cryosphere, 17, 3229–3250, https://doi.org/10.5194/tc-17-3229-2023, 2023. a
Klaus, A., Yu, S., and Plenz, D.: Statistical analyses support power law distributions found in neuronal avalanches, PloS one, 6, e19779, https://doi.org/10.1371/journal.pone.0019779, 2011. a
Kwok, R. and Cunningham, G.: Contribution of melt in the Beaufort Sea to the decline in Arctic multiyear sea ice coverage: 1993–2009, Geophys. Res. Lett., 37, L20501, https://doi.org/10.1029/2010GL044678, 2010. a
Lewis, B. J. and Hutchings, J. K.: Leads and associated sea ice drift in the Beaufort Sea in winter, J. Geophys. Res.-Oceans, 124, 3411–3427, https://doi.org/10.1029/2018JC014898, 2019. a
Lopez-Acosta, R., Schodlok, M., and Wilhelmus, M.: Ice Floe Tracker: An algorithm to automatically retrieve Lagrangian trajectories via feature matching from moderate-resolution visual imagery, Remote Sens. Environ., 234, 111406, https://doi.org/10.1016/j.rse.2019.111406, 2019. a, b
Manucharyan, G. E., Lopez-Acosta, R., and Wilhelmus, M. M.: Spinning ice floes reveal intensification of mesoscale eddies in the western Arctic Ocean, Sci. Rep., 12, 7070, https://doi.org/10.1038/s41598-022-10712-z, 2022. a
Maslanik, J., Fowler, C., Stroeve, J., Drobot, S., Zwally, J., Yi, D., and Emery, W.: A younger, thinner Arctic ice cover: Increased potential for rapid, extensive sea-ice loss, Geophys. Res. Lett., 34, L24501, https://doi.org/10.1029/2007GL032043, 2007. a
Paget, M., Worby, A., and Michael, K.: Determining the floe-size distribution of East Antarctic sea ice from digital aerial photographs, Ann. Glaciol., 33, 94–100, https://doi.org/10.3189/172756401781818473, 2001. a, b
Perovich, D. K. and Jones, K. F.: The seasonal evolution of sea ice floe size distribution, J. Geophys. Res.-Oceans, 119, 8767–8777, https://doi.org/10.1002/2014JC010136, 2014. a, b, c
Platnick, S., Meyer, K. G., King, M. D., Wind, G., Amarasinghe, N., Marchant, B., Arnold, G. T., Zhang, Z., Hubanks, P. A., Holz, R. E., and Yang, P.: The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua, IEEE T. Geosci. Remote, 55, 502–525, https://doi.org/10.1109/TGRS.2016.2610522, 2016. a
Rothrock, D. A. and Thorndike, A. S.: Measuring the sea ice floe size distribution, J. Geophys. Res.-Oceans, 89, 6477–6486, https://doi.org/10.1029/JC089iC04p06477, 1984. a, b, c
Schweiger, A. J.: Changes in seasonal cloud cover over the Arctic seas from satellite and surface observations, Geophys. Res. Lett., 31, L12207, https://doi.org/10.1029/2004GL020067, 2004. a
Squire, V. A., Dugan, J. P., Wadhams, P., Rottier, P. J., and Liu, A. K.: Of ocean waves and sea ice, Annu. Rev. Fluid Mech., 27, 115–168, https://doi.org/10.1146/annurev.fl.27.010195.000555, 1995. a
Steele, M.: Sea ice melting and floe geometry in a simple ice-ocean model, J. Geophys. Res.-Oceans, 97, 17729–17738, https://doi.org/10.1029/92JC01755, 1992. a
Steer, A., Worby, A., and Heil, P.: Observed changes in sea-ice floe size distribution during early summer in the western Weddell Sea, Deep-Sea Res. Pt. II, 55, 933–942, https://doi.org/10.3189/172756401781818473, 2008. a
Stern, H. L., Schweiger, A. J., Zhang, J., and Steele, M.: On reconciling disparate studies of the sea-ice floe size distribution, Elementa: Science of the Anthropocene, 6, 49, https://doi.org/10.1525/elementa.304, 2018b. a
Timmermans, M.-L. and Toole, J. M.: The Arctic Ocean's Beaufort Gyre, Annu. Rev. Marine Sci., 15, 223–248, https://doi.org/10.1146/annurev-marine-032122-012034, 2023. a, b
Toyota, T., Kohout, A., and Fraser, A. D.: Formation processes of sea ice floe size distribution in the interior pack and its relationship to the marginal ice zone off East Antarctica, Deep-Sea Res. Pt. II, 131, 28–40, https://doi.org/10.1016/j.dsr2.2015.10.003, 2016. a
Vermote, E.: MOD09A1 MODIS Surface Reflectance 8-Day L3 Global 500 m SIN Grid V006, NASA EOSDIS Land Processes Distributed Active Archive Center, USGS Report [data set], https://doi.org/10.5067/MODIS/MOD09A1.006, 2015. a
Wang, Y., Holt, B., Erick Rogers, W., Thomson, J., and Shen, H. H.: Wind and wave influences on sea ice floe size and leads in the Beaufort and Chukchi Seas during the summer-fall transition 2014, J. Geophys. Res.-Oceans, 121, 1502–1525, https://doi.org/10.1002/2015JC011349, 2016. a
Zhang, J., Stern, H., Hwang, B., Schweiger, A., Steele, M., Stark, M., and Graber, H. C.: Modeling the seasonal evolution of the Arctic sea ice floe size distribution, Elementa: Science of the Anthropocene, 4, 000126, https://doi.org/10.12952/journal.elementa.000126, 2016. a
Short summary
Arctic sea ice cover evolves seasonally from large plates separated by long, linear leads in the winter to a mosaic of smaller sea ice floes in the summer. Here, we present a new image segmentation algorithm applied to thousands of images and identify over 9 million individual pieces of ice. We observe the characteristics of the floes and how they evolve throughout the summer as the ice breaks up.
Arctic sea ice cover evolves seasonally from large plates separated by long, linear leads in the...