Articles | Volume 18, issue 1
https://doi.org/10.5194/tc-18-341-2024
© 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-18-341-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jan 2024
Research article |
| 19 Jan 2024
| 19 Jan 2024
A method for constructing directional surface wave spectra from ICESat-2 altimetry
Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI, USA
NSF National Center for Atmospheric Research, CISL/CGD, Boulder, CO, USA
Christopher Horvat
Department of Earth, Environmental and Planetary Sciences, Brown University, Providence, RI, USA
Waipapa Taumatu Rau / University of Auckland, Department of Physics, Tāmaki Makaurau / Auckland, Aotearoa / New Zealand
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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.
Sea ice is heavily impacted by waves on its margins, and we currently do not have routine...
