Articles | Volume 18, issue 1
https://doi.org/10.5194/tc-18-341-2024
https://doi.org/10.5194/tc-18-341-2024
Research article
 | 
19 Jan 2024
Research article |  | 19 Jan 2024

A method for constructing directional surface wave spectra from ICESat-2 altimetry

Momme C. Hell and Christopher Horvat

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Cited articles

Alberello, A., Bennetts, L. G., Onorato, M., Vichi, M., MacHutchon, K., Eayrs, C., Ntamba, B. N., Benetazzo, A., Bergamasco, F., Nelli, F., Pattani, R., Clarke, H., Tersigni, I., and Toffoli, A.: Three-Dimensional Imaging of Waves and Floes in the Marginal Ice Zone during a Cyclone, Nat. Commun., 13, 4590, https://doi.org/10.1038/s41467-022-32036-2, 2022. a, b, c
Ardhuin, F., Hanafin, J., Quilfen, Y., Chapron, B., Queffeulou, P., Obrebski, M., Sienkiewicz, J., and Vandemark, D.: Calibration of the “IOWAGA” Global Wave Hindcast (1991–2011) Using ECMWF and CFSR Winds, https://tds3.ifremer.fr/thredds/catalog.html (last access: 19 November 2021), 2011. a
Ardhuin, F., Stopa, J., Chapron, B., Collard, F., Smith, M., Thomson, J., Doble, M., Blomquist, B., Persson, O., Collins, C. O., and Wadhams, P.: Measuring ocean waves in sea ice using SAR imagery: A quasi-deterministic approach evaluated with Sentinel-1 and in situ data, Remote Sens. Environ., 189, 211–222, https://doi.org/10.1016/j.rse.2016.11.024, 2017. a
Belmonte Rivas, M. and Stoffelen, A.: Characterizing ERA-Interim and ERA5 surface wind biases using ASCAT, Ocean Sci., 15, 831–852, https://doi.org/10.5194/os-15-831-2019, 2019. a, b
Brouwer, J., Fraser, A. D., Murphy, D. J., Wongpan, P., Alberello, A., Kohout, A., Horvat, C., Wotherspoon, S., Massom, R. A., Cartwright, J., and Williams, G. D.: Altimetric observation of wave attenuation through the Antarctic marginal ice zone using ICESat-2, The Cryosphere, 16, 2325–2353, https://doi.org/10.5194/tc-16-2325-2022, 2022. a, b
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Short summary
Sea ice is heavily impacted by waves on its margins, and we currently do not have routine observations of waves in sea ice. Here we propose two methods to separate the surface waves from the sea-ice height observations along each ICESat-2 track using machine learning. Both methods together allow us to follow changes in the wave height through the sea ice.