1 Department of Building, Civil, and Environmental Engineering, Concordia University, Montreal H3G 1M8, Canada.
2 Kenneth Lee Research Inc, Halifax, Nova Scotia B3H 4H4, Canada.
3 Ecosystem Science, Fisheries and Oceans Canada, 200 Kent Street, Ottawa, Ontario K1C 0E6, Canada.
4 CanmetEnergy-Devon, Natural Resources Canada, 1 Oil Patch Drive, Devon, Alberta T9G 1A8, Canada.

Amid growing concerns about oil spills in vulnerable Arctic and sub-Arctic regions driven by climate-induced ice retreat, this study presents the development and validation of the OSMT-ice model, an enhanced oil spill modeling system designed to predict the movement and fate of oil in ice-covered waters. The model incorporates ice-concentration-based (ICB) constraints to improve the accuracy of oil transport and weathering simulation under varying ice conditions. Using observational data from multiscale field experiments, including the FEX2009 spill in the Barents Sea and the mesoscale experiments in Svalbard, we evaluated the model's capability to simulate oil trajectories, mass balance, and oil property evolution. A comparative hindcast analysis, with and without ice-related inputs, demonstrates that incorporating ice data significantly enhances the performance of oil transport modeling. Through multiple simulation scenarios, the effectiveness of various combinations of ICB constraints and target components was assessed to identify the optimal approach for modeling oil fate in ice-covered waters. Our findings indicate that the "30/80" rule-of-thumb, originally used to model oil movement under varying ice cover, does not apply to oil fate modeling in ice conditions. In contrast, the newly proposed quadratic reduction method provides more reliable simulations of oil behavior in icy environments. The OSMT-ice model, with its enhanced weathering algorithms, offers a robust tool for assessing oil spill impacts in ice-covered waters, improving response strategies and risk assessments. This research contributes to advancing oil spill modeling in Arctic and Sub-Arctic regions, with practical implications for oil spill contingency planning.