Advances in Machine Learning Techniques Can Assist Across a Variety of Stages in Sea Ice Applications

Clare Eayrs; Won Sang Lee; Emilia Jin; Jean-François Lemieux; François Massonnet; M. Vancoppenolle; Lorenzo Zampieri; Luke Bennetts; Ed Blockley; Eui-Seok Chung; Alexander Fraser; Yoo-Geun Ham; Jungho Im; Baek-Min Kim; Beong-Hoon Kim; Jinsuk Kim; Joo-Hong Kim; Seong-Joong Kim; Seung Hee Kim; Anton Korosov; Choon-Ki Lee; Donghyuck Lee; Hyun-Ju Lee; Jeong-Gil Lee; Jiyeon Lee; Jisung Na; In-Woo Park; Jikang Park; Xianwei Wang; Shiming Xu; Sukyoung Yun

doi:10.1175/bams-d-23-0332.1

Journal Articles Bulletin of the American Meteorological Society Year : 2024

Advances in Machine Learning Techniques Can Assist Across a Variety of Stages in Sea Ice Applications

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Clare Eayrs

Function : Author
PersonId : 1298181
ORCID : 0000-0003-3129-7604

Korea Polar Research Institute

Won Sang Lee

Function : Author

Korea Polar Research Institute

Emilia Jin

Function : Author

Korea Polar Research Institute

Jean-François Lemieux

Function : Author

Recherche en Prevision Numerique

François Massonnet

Function : Author

Centre Georges Lemaître for Earth and Climate Research [Louvain]

M. Vancoppenolle

Function : Author
PersonId : 739706
IdHAL : martin-vancoppenolle
ORCID : 0000-0002-7573-8582
IdRef : 250728508

Nucleus for European Modeling of the Ocean

Lorenzo Zampieri

Function : Author

Centro Euro-Mediterraneo per i Cambiamenti Climatici [Bologna]

Luke Bennetts

Function : Author

University of Adelaide

Ed Blockley

Function : Author

Met Office Hadley Centre

Eui-Seok Chung

Function : Author

Korea Polar Research Institute

Alexander Fraser

Function : Author

Institute for Marine and Antarctic Studies [Hobart]

Yoo-Geun Ham

Function : Author

Chonnam National University [Gwangju]

Jungho Im

Function : Author

Ulsan National Institute of Science and Technology

Baek-Min Kim

Function : Author

Pukyong National University

Beong-Hoon Kim

Function : Author

Korea Polar Research Institute

Jinsuk Kim

Function : Author

Korea Polar Research Institute

Joo-Hong Kim

Function : Author

Korea Polar Research Institute

Seong-Joong Kim

Function : Author

Korea Polar Research Institute

Seung Hee Kim

Function : Author

Korea Polar Research Institute

Anton Korosov

Function : Author

Nansen Environmental and Remote Sensing Center [Bergen]

Choon-Ki Lee

Function : Author

Korea Polar Research Institute

Donghyuck Lee

Function : Author

Korea Polar Research Institute

Hyun-Ju Lee

Function : Author

Korea Polar Research Institute

Jeong-Gil Lee

Function : Author

Korea Polar Research Institute

Jiyeon Lee

Function : Author

Korea Polar Research Institute

Jisung Na

Function : Author

Korea Polar Research Institute

In-Woo Park

Function : Author

Seoul National University [Seoul]

Jikang Park

Function : Author

Korea Polar Research Institute

Xianwei Wang

Function : Author

Shanghai Jiao Tong University [Shanghai]

Shiming Xu

Function : Author

Korea Polar Research Institute

Sukyoung Yun

Function : Author

Korea Polar Research Institute

Keywords

Antarctica Arctic Sea ice Forecasting Artificial intelligence Machine learning

Domains

Sciences of the Universe [physics]

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Avant la publication
Saturday, September 13, 2025

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https://hal.science/hal-04588974

Submitted on : Friday, September 13, 2024-4:46:34 PM

Last modification on : Wednesday, September 25, 2024-4:12:05 PM

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hal-04588974 , version 1 (13-09-2024)

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HAL Id : hal-04588974 , version 1
DOI : 10.1175/bams-d-23-0332.1
WOS : 001185919200002

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Clare Eayrs, Won Sang Lee, Emilia Jin, Jean-François Lemieux, François Massonnet, et al.. Advances in Machine Learning Techniques Can Assist Across a Variety of Stages in Sea Ice Applications. Bulletin of the American Meteorological Society, 2024, 105 (3), pp.E527-E531. ⟨10.1175/bams-d-23-0332.1⟩. ⟨hal-04588974⟩

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Advances in Machine Learning Techniques Can Assist Across a Variety of Stages in Sea Ice Applications

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