NEWS ARTICLE
水务学术动态：Seasonal Prediction of the Bohai Sea Ice Grade: A Multi-Model Intercomparison
论文标题：Seasonal Prediction of the Bohai Sea Ice Grade: A Multi-Model Intercomparison
发布日期：2026-05-21
作者：Donglin Guo, Xinyou Zhang, Xue Chen, Song Gao, Yiding Zhao
DOI：10.3390/w18101242
论文摘要：Even under a warming climate, winter sea ice in the Bohai Sea continues to threaten ships and offshore/coastal infrastructure. Reliable pre-season prediction of the overall wintertime sea ice condition in the Bohai Sea, as represented by the Bohai Sea Ice Grade (BSIG), is therefore important for disaster preparedness and mitigation. Based on the 1979–2024 BSIG record, this study compares seven statistical and AI-based seasonal prediction methods: analog year analysis, multiple linear regression, stepwise regression, Principal Component Regression, a cross-correlation-based regression model, support vector regression, and the Bayesian Ensemble Bohai Ice Grade Net (BE-BIGNet). As potential precursors, we considered sea ice extent in 14 Arctic regions together with 114 large-scale atmospheric and oceanic circulation indices. The results suggest substantial differences in predictive skill among the methods. Among the tested approaches, BE-BIGNet, which combines Bayesian regularization with bootstrap median ensembling, achieves strong full-period performance and stable skill during the independent test period, suggesting that it may provide a useful framework for operational BSIG forecasting in the Bohai Sea.
元数据：Crossref 收录的 MDPI Water 论文。 DOI: 10.3390/w18101242. Vol. 18, Issue 10. Authors: Donglin Guo, Xinyou Zhang, Xue Chen, Song Gao, Yiding Zhao.
开放许可：https://creativecommons.org/licenses/by/4.0/
原文链接：https://doi.org/10.3390/w18101242
PDF 链接：https://www.mdpi.com/2073-4441/18/10/1242/pdf