A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023
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 observation...
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2024-12-01
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| Online Access: | https://doi.org/10.1038/s41597-024-04281-1 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Jean Rabault |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-202e683b25374500a951c5b4ac386890 |
| institution | DOAJ |
| issn | 2052-4463 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj-art-202e683b25374500a951c5b4ac3868902025-08-20T02:39:38ZengNature PortfolioScientific Data2052-44632024-12-0111111010.1038/s41597-024-04281-1A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023Jean Rabault0Catherine Taelman1Martina Idžanović2Gaute Hope3Takehiko Nose4Yngve Kristoffersen5Atle Jensen6Øyvind Breivik7Helge Thomas Bryhni8Mario Hoppmann9Denis Demchev10Anton Korosov11Malin Johansson12Torbørn Eltoft13Knut-Frode Dagestad14Johannes Röhrs15Leif Eriksson16Marina Durán Moro17Edel S. U. Rikardsen18Takuji Waseda19Tsubasa Kodaira20Johannes Lohse21Thibault Desjonquères22Sveinung Olsen23Olav Gundersen24Victor Cesar Martins de Aguiar25Truls Karlsen26Alexander Babanin27Joey Voermans28Jeong-Won Park29Malte Müller30Norwegian Meteorological Institute, IT DepartmentUiT The Arctic University of Norway, Dept. of Physics and TechnologyNorwegian Meteorological Institute, Division for Ocean and IceNorwegian Meteorological Institute, Division for Oceanography and Marine MeteorologyThe University of Tokyo, Graduate School of Frontier SciencesUniversity of Bergen, Department of Earth ScienceUniversity of Oslo, Department of MathematicsNorwegian Meteorological Institute, Division for Oceanography and Marine MeteorologyNorwegian Meteorological Institute, Division for Oceanography and Marine MeteorologyAlfred-Wegener-Institut, Helmholtz-Zentrum fuer Polar- und MeeresforschungDepartment of Space, Earth and Environment, Chalmers University of TechnologyOcean and Sea Ice Remote Sensing Group, Nansen Environmental and Remote Sensing CenterUiT The Arctic University of Norway, Dept. of Physics and TechnologyUiT The Arctic University of Norway, Dept. of Physics and TechnologyNorwegian Meteorological Institute, Division for Oceanography and Marine MeteorologyNorwegian Meteorological Institute, Division for Ocean and IceDepartment of Space, Earth and Environment, Chalmers University of TechnologyNorwegian Meteorological Institute, Remote sensing and data management divisionNorwegian Meteorological Institute, Division for Ocean and IceThe University of Tokyo, Graduate School of Frontier SciencesThe University of Tokyo, Graduate School of Frontier SciencesUiT The Arctic University of Norway, Dept. of Physics and TechnologyGothenburg UniversityUiT The Arctic University of Norway, Dept. of Physics and TechnologyUniversity of Oslo, Department of MathematicsUiT The Arctic University of Norway, Dept. of Physics and TechnologyUiT The Arctic University of Norway, Dept. of Physics and TechnologyDepartment of Infrastructure Engineering, University of MelbourneDepartment of Infrastructure Engineering, University of MelbourneCenter of Remote Sensing and GIS, Korea Polar Research InstituteUniversity of Oslo, Department of GeosciencesAbstract 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.https://doi.org/10.1038/s41597-024-04281-1 |
| spellingShingle | 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 A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023 Scientific Data |
| title | A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023 |
| title_full | A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023 |
| title_fullStr | A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023 |
| title_full_unstemmed | A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023 |
| title_short | A position and wave spectra dataset of Marginal Ice Zone dynamics collected around Svalbard in 2022 and 2023 |
| title_sort | position and wave spectra dataset of marginal ice zone dynamics collected around svalbard in 2022 and 2023 |
| url | https://doi.org/10.1038/s41597-024-04281-1 |
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