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An operational synoptic-scale sea ice forecasting system for the Southern Ocean, namely Southern Ocean Ice Prediction System (SOIPS), has been developed to support ship navigation in the Antarctic sea ice zone. Practical application of the SOIPS forecasts had been implemented for the 38th Chinese National Antarctic Research Expedition for the first time. The SOIPS is configured on an Antarctic regional sea-ice‒ocean‒ice-shelf coupled model and an ensemble-based Localized Error Subspace Transform Kalman Filter data assimilation model. Daily near-real-time satellite sea ice concentration observations are assimilated into the SOIPS to update sea ice concentration and thickness in the 12 ensemble members of model state. By evaluating the SOIPS performance on forecasting sea ice metrics in a complete melt-freeze cycle from October 1, 2021 to September 30, 2022, this study shows that the SOIPS can provide reliable Antarctic sea ice forecasts. In comparison with the OSISAF data, annual mean root mean square errors of the sea ice concentration forecasts at leading time of up to 168-hour are lower than 0.19, and the integrated ice-edge errors of sea ice forecasts in most freezing months at leading times of 24-hour and 72-hour maintain around 0.5 × 106 km2 and below 1.0 × 106 km2, respectively. With respect to the scarce ICESat-2 observations, the mean absolute errors of the sea ice thickness forecasts at leading time of 24-hour are lower than 0.3 m, which is in range of the ICESat-2 uncertainties. Specifically, the SOIPS has a promised capacity in forecasting sea ice drift, both in magnitude and direction. The derived sea ice convergence rate forecasts have a high potential in supporting ship navigation on local fine scale. [ABSTRACT FROM AUTHOR]

• Energetic sea ice drift occurs under negative phase of Arctic Oscillation with positive phase of Arctic Dipole. • Wind-ice stress dominates ice floes away from islands and continents. • Balance exists between internal ice stress and sea surface height gradient in thick multiyear ice zone. By analyzing an Arctic ice-ocean coupled simulation, we study the linkage between wintertime sea ice drift and atmospheric circulation, and interpret the driving force terms in the sea ice dynamic equation. Sea ice drift anomaly is featured by an anticyclonic (cyclonic) gyre when regulated by negative (positive) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole, and a quasi-meridional stream from Chukchi-Beaufort (Barents-Kara) Seas to Barents-Kara (Chukchi-Beaufort) Seas when regulated by positive (negative) phase of Arctic Oscillation with positive (negative) phase of Arctic Dipole. Sea ice drift anomaly, when regulated by the mode alone, resembles spatial pattern of leading atmospheric mode. Decomposing sea ice dynamical equation shows that wind-ice stress dominates sea ice drift in areas away from islands and continental coastlines, ocean-ice stress acts as a resistant power to partly cancel the wind-ice stress in these areas, while in the coastal areas such as the thick multiyear ice zone north of the Canadian Arctic Archipelago, the wind-ice and ocean-ice stresses are small, the balance exists between sea surface height potential gradient and internal ice stress divergence. Developing more sophisticated internal ice stress expression in ice model is of great important to correctly project future sea ice change for the ice modeling community. [ABSTRACT FROM AUTHOR]