Spatiotemporal Prediction of Arctic Sea
We study the prediction of spatial and temporal changes in Arctic sea ice and the likelihood of ice opening, based on its physical and thermodynamic properties.
Spatiotemporal Prediction of Arctic Sea
Members: Wonhyung Shin, 윤예진, 채용
Methods: Spatiotemporal AI
We develop an Arctic Sea Ice Index that comprehensively reflects the physical and thermodynamic changes in Arctic sea ice, and use it to predict spatial and temporal changes and the likelihood of ice opening. We analyze large Arctic sea-ice datasets and examine melting from multiple perspectives. Using SAR data to extract detailed information and combining heterogeneous data, we forecast the timing and patterns of complete Arctic sea-ice opening. This research is conducted with the Cryosphere Research Center at the Korea Polar Research Institute.
Funding: Korea Polar Research Institute (KOPRI)
Leader: Wonhyung Shin