Projects per year
Abstract
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.
Original language | English |
---|---|
Article number | e2024GL110552 |
Number of pages | 10 |
Journal | Geophysical Research Letters |
Volume | 51 |
Issue number | 18 |
DOIs | |
Publication status | Published - 28 Sept 2024 |
MoE publication type | A1 Journal article-refereed |
Fingerprint
Dive into the research topics of 'High-Resolution Fracture Dynamics Simulation of Pack-Ice and Drift-Ice Formation During Sea Ice Break up Events Using the HiDEM2.0 Code'. Together they form a unique fingerprint.Projects
- 1 Active
-
WindySea: Modelling engine to design, assess environmental impacts, and operate wind farms for ice-covered waters
Polojärvi, A. (Principal investigator), Petry, A. (Project Member), Owen, C. (Project Member), Prasanna, M. (Project Member), Muchow, M. (Project Member), Puolakka, O. (Project Member) & Lehto, P. (Project Member)
EU The Recovery and Resilience Facility (RRF)
01/01/2022 → 31/12/2024
Project: Academy of Finland: Other research funding