Scientific Data (Dec 2024)
A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023
- Jean Rabault,
- Catherine Taelman,
- Martina Idžanović,
- Gaute Hope,
- Takehiko Nose,
- Yngve Kristoffersen,
- Atle Jensen,
- Øyvind Breivik,
- Helge Thomas Bryhni,
- Mario Hoppmann,
- Denis Demchev,
- Anton Korosov,
- Malin Johansson,
- Torbørn Eltoft,
- Knut-Frode Dagestad,
- Johannes Röhrs,
- Leif Eriksson,
- Marina Durán Moro,
- Edel S. U. Rikardsen,
- Takuji Waseda,
- Tsubasa Kodaira,
- Johannes Lohse,
- Thibault Desjonquères,
- Sveinung Olsen,
- Olav Gundersen,
- Victor Cesar Martins de Aguiar,
- Truls Karlsen,
- Alexander Babanin,
- Joey Voermans,
- Jeong-Won Park,
- Malte Müller
Affiliations
- Jean Rabault
- Norwegian Meteorological Institute, IT Department
- Catherine Taelman
- UiT The Arctic University of Norway, Dept. of Physics and Technology
- Martina Idžanović
- Norwegian Meteorological Institute, Division for Ocean and Ice
- Gaute Hope
- Norwegian Meteorological Institute, Division for Oceanography and Marine Meteorology
- Takehiko Nose
- The University of Tokyo, Graduate School of Frontier Sciences
- Yngve Kristoffersen
- University of Bergen, Department of Earth Science
- Atle Jensen
- University of Oslo, Department of Mathematics
- Øyvind Breivik
- Norwegian Meteorological Institute, Division for Oceanography and Marine Meteorology
- Helge Thomas Bryhni
- Norwegian Meteorological Institute, Division for Oceanography and Marine Meteorology
- Mario Hoppmann
- Alfred-Wegener-Institut, Helmholtz-Zentrum fuer Polar- und Meeresforschung
- Denis Demchev
- Department of Space, Earth and Environment, Chalmers University of Technology
- Anton Korosov
- Ocean and Sea Ice Remote Sensing Group, Nansen Environmental and Remote Sensing Center
- Malin Johansson
- UiT The Arctic University of Norway, Dept. of Physics and Technology
- Torbørn Eltoft
- UiT The Arctic University of Norway, Dept. of Physics and Technology
- Knut-Frode Dagestad
- Norwegian Meteorological Institute, Division for Oceanography and Marine Meteorology
- Johannes Röhrs
- Norwegian Meteorological Institute, Division for Ocean and Ice
- Leif Eriksson
- Department of Space, Earth and Environment, Chalmers University of Technology
- Marina Durán Moro
- Norwegian Meteorological Institute, Remote sensing and data management division
- Edel S. U. Rikardsen
- Norwegian Meteorological Institute, Division for Ocean and Ice
- Takuji Waseda
- The University of Tokyo, Graduate School of Frontier Sciences
- Tsubasa Kodaira
- The University of Tokyo, Graduate School of Frontier Sciences
- Johannes Lohse
- UiT The Arctic University of Norway, Dept. of Physics and Technology
- Thibault Desjonquères
- Gothenburg University
- Sveinung Olsen
- UiT The Arctic University of Norway, Dept. of Physics and Technology
- Olav Gundersen
- University of Oslo, Department of Mathematics
- Victor Cesar Martins de Aguiar
- UiT The Arctic University of Norway, Dept. of Physics and Technology
- Truls Karlsen
- UiT The Arctic University of Norway, Dept. of Physics and Technology
- Alexander Babanin
- Department of Infrastructure Engineering, University of Melbourne
- Joey Voermans
- Department of Infrastructure Engineering, University of Melbourne
- Jeong-Won Park
- Center of Remote Sensing and GIS, Korea Polar Research Institute
- Malte Müller
- University of Oslo, Department of Geosciences
- DOI
- https://doi.org/10.1038/s41597-024-04281-1
- Journal volume & issue
-
Vol. 11,
no. 1
pp. 1 – 10
Abstract
Abstract Sea ice is a key element of the global Earth system, with a major impact on global climate and regional weather. Unfortunately, accurate sea ice modeling is challenging due to the diversity and complexity of underlying physics happening there, and a relative lack of ground truth observations. This is especially true for the Marginal Ice Zone (MIZ), which is the area where sea ice is affected by incoming ocean waves. Waves contribute to making the area dynamic, and due to the low survival time of the buoys deployed there, the MIZ is challenging to monitor. In 2022-2023, we released 79 OpenMetBuoys (OMBs) around Svalbard, both in the MIZ and the ocean immediately outside of it. OMBs are affordable enough to be deployed in large number, and gather information about drift (GNSS position) and waves (1-dimensional elevation spectrum). This provides data focusing on the area around Svalbard with unprecedented spatial and temporal resolution. We expect that this will allow to perform validation and calibration of ice models and remote sensing algorithms.
