18 May 2021

18 May 2021

Review status: this preprint is currently under review for the journal TC.

A probabilistic model for fracture events of Petermann ice islands under the influence of atmospheric and oceanic conditions

Reza Zeinali-Torbati1, Ian D. Turnbull2, Rocky S. Taylor1, and Derek Mueller3 Reza Zeinali-Torbati et al.
  • 1Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada
  • 2Ice Engineering, C-CORE, St. John’s, NL A1B 3X5, Canada
  • 3Department of Geography and Environmental Studies, Carleton University, Ottawa, ON K1S 5B6, Canada

Abstract. Four calving events of Petermann Glacier happened in 2008, 2010, 2011, and 2012, which resulted in the drift and deterioration of numerous ice islands, some reaching as far as offshore Newfoundland. The presence of these ice islands in the eastern Canadian Arctic increases the risk of interaction with offshore operations and shipping activities. This study used the recently developed Canadian Ice Island Drift, Deterioration and Detection database to investigate the fracture events that these ice islands experienced, and presented a probabilistic model for the conditional occurrence of such events by analyzing the atmospheric and oceanic conditions that drive the causes behind the ice island fracture events. Variables representing the atmospheric and oceanic conditions that the ice islands were subjected to were extracted from reanalysis datasets and then interpolated to evaluate their distributions for both fracture and non-fracture events. The probability of fracture event occurrence for different combinations of input variable conditions were quantified using Bayes theorem. Out of the seven variables analyzed in this study, water temperature and ocean current speed were identified as the most and least important contributors, respectively, to the fracture events of the Petermann ice islands. It was also revealed that the ice island fracture probability increased to 75 % as the ice islands encountered extreme (very high) atmospheric and oceanic conditions. A validation scheme was presented using cross-validation approach and Pareto principle, and an average error of 13–39 % was reported in the fracture probability estimations. The presented probabilistic model has a predictive capability for future fracture events of ice islands and could be of particular interest to offshore and marine activities in the eastern Canadian Arctic. Future research, however, is necessary for model training and testing to further validate the presented ice island fracture model.

Reza Zeinali-Torbati et al.

Status: open (until 13 Jul 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Reza Zeinali-Torbati et al.

Data sets

Canadian Ice Island Drift, Deterioration, and Detection (CI2D3) Database Desjardins, L., Crawford, A., Mueller, D., Saper, R., Schaad, C., Stewart-Jones, E., and Shepherd, J.

Reza Zeinali-Torbati et al.


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Short summary
Using the reanalysis datasets and the Canadian Ice Island Drift, Deterioration and Detection database, a probabilistic model was developed to quantify ice island fracture probability under various atmospheric and oceanic conditions. The model identified water temperature as the most dominant variable behind ice island fracture events, while ocean currents played a minor role. The developed model offers a predictive capability and could be of particular interest to offshore and marine activities.