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Abstract: A Statistical Approach to Monthly Arctic Sea Ice Prediction Based on Spatiotemporal Anomaly Persistence (AGU25)

A Statistical Approach to Monthly Arctic Sea Ice Prediction Based on Spatiotemporal Anomaly Persistence

Gyuri Lee1, Sung-Ho Woo2, Joo-Hong Kim3 and Jee-Hoon Jeong2, (1)Sejong University, Seoul, Korea, Republic of (South), (2)Sejong University, Seoul, South Korea, (3)Korea Polar Research Institute, Division of Ocean and Atmosphere Sciences, Incheon, South Korea
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