A Statistical Arima Model to Predict Arctic Environment for NSR Shipping

• Published in: Volume 7: Polar and Arctic Sciences and Technology
• Main Authors: Wu, Da, Lang, Xiao, Zhang, Di, Eriksson, Leif, Mao, Wengang
• Language: unknown
• Published: 2021
• Subjects: Oceanography; Hydrology; Water Resources; Probability Theory and Statistics; Computer Science; Other Electrical Engineering; Electronic Engineering; Information Engineering; time series analysis; ARIMA model; Sea ice concentration; Arctic shipping; Northern Sea Route; Sea ice
• Online Access: https://doi.org/10.1115/OMAE2021-62783; https://research.chalmers.se/en/publication/7f722760-d295-490f-b538-43315748c03e

Safe and energy-efficient ship navigation along the Northern Sea Route (NSR) requires reliable sea ice concentration (SIC) information. However, the SIC forecast used to assist NSR shipping is often inaccurate. This study proposes a statistical interpolation method to reduce the errors induced by the traditional nearest grid point interpolation method. An auto-regressive integrated moving average (ARIMA) model is developed based on ERA5 reanalysis data. The ARIMA model can be used for short-term SIC forecasts along the NSR. Model validation has been conducted to compare the SIC forecast with ensemble experiments from the Coupled Model Intercomparison Project Phase 5 (CMIP5), achieving good agreements. The route availability is estimated according to the SIC forecast. The results indicate that the specified NSR will be open for shipping from 2021 to 2025. The work also indicates the feasibility of the proposed statistical models to assist NSR shipping management.