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arXiv 2409.04151physics.ao-ph
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2022年和2023年在斯瓦尔巴群岛周围采集的边缘冰区动力学 OpenMetBuoy 数据集

An OpenMetBuoy 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 Hopp… 展开作者

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, Torbjørn 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

AI总结:

本文介绍在斯瓦尔巴群岛周边 MIZ 及邻近海域布放79个 OMB 所形成的数据集,用于高分辨率观测漂移与波浪并支撑海冰模型和遥感算法验证校准。

摘要:

海冰是全球地球系统的关键要素,对全球气候和区域天气具有重大影响。遗憾的是,由于其中发生的底层物理过程多样且复杂,并且相对缺乏地面真值观测,准确的海冰建模颇具挑战。边缘冰区(MIZ)尤其如此,该区域是海冰受到传入的海洋波浪影响的区域。波浪促使该区域具有动态特征,而且由于布放在那里的浮标存活时间较短,MIZ 的监测颇具挑战。2022—2023年,我们在斯瓦尔巴群岛周围的 MIZ 及其紧邻外侧海域布放了79个 OpenMetBuoys(OMBs)。OMB 成本足够低廉,可大量部署,并收集有关漂移(GPS位置)和波浪(一维高程谱)的信息。这以前所未有的空间和时间分辨率提供了聚焦斯瓦尔巴群岛周边区域的数据。我们预计,这将使冰模型和遥感算法的验证与校准成为可能。

英文摘要:

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 (GPS 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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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