Creating accurate predictive models for drift and pack ice is crucial for a wide array of applications, from improving maritime operations to improving weather prediction and climate simulations. Traditional large‐scale sea ice dynamics models rely on phenomenological ice rheology to simulate ice movements. These models are efficient on large scales but struggle to depict smaller‐scale ice features. In our study, we use a new version of the HiDEM discrete element model software to examine the formation of drift and pack ice under various stress conditions. Our findings show that high‐resolution size distributions of ice floes are universal and multimodal, and that compression ridges form three distinct zones. Reproducing complex characteristics of this nature in a standard rheology model is challenging, suggesting that a combination of models may be necessary for more precise predictions of sea ice dynamics. We propose a potential hybrid algorithm that integrates these approaches.
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Åström et al. (2024) studied this question.
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