Statistical Modeling of Arctic Sea Ice Concentrations for Northern Sea Route Shipping

• Published in: Applied Sciences
• Main Authors: Da Wu, Wuliu Tian, Xiao Lang, Wengang Mao, Jinfen Zhang
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2023
• Subjects: sea ice concentration; Arctic shipping; transit navigation windows; ARIMA model; time series analysis; Technology; T; Engineering (General). Civil engineering (General); TA1-2040; Biology (General); QH301-705.5; Physics; QC1-999; Chemistry; QD1-999; Arctic; Northern Sea Route; Sea ice
• Online Access: https://doi.org/10.3390/app13074374; https://doaj.org/article/dd6ecab20f5941b48eb2c137895a2b69

The safe and efficient navigation of ships traversing the Northern Sea Route demands accurate information regarding sea ice concentration. However, the sea ice concentration forecasts employed to support such navigation are often flawed. To address this challenge, this study advances a statistical interpolation method aimed at reducing errors arising from traditional interpolation approaches. Additionally, this study introduces an autoregressive integrated moving average model, derived from ERA5 reanalysis data, for short-term sea ice concentration forecasts along the Northern Sea Route. The validity of the model has been confirmed through comparison with ensemble experiments from the Coupling Model Intercomparison Project Phase 5, yielding reliable outcomes. The route availability is assessed on the basis of the sea ice concentration forecasts, indicating that the route will be available in the upcoming years. The proposed statistical models are also shown the capacity to facilitate effective management of Arctic shipping along the Northern Sea Route.