Understanding the relative influences of the metocean forcings on the drift of sea ice floes is a crucial component to the overall characterization of an ice environment and to developing an understanding of the factors controlling the ice dynamics. In addition, estimating the magnitude of the internal stress gradients on drifting sea ice floes generated by surrounding ice cover is important for modeling operations, informing the design of offshore structures and vessels in ice environments, and for the proper calibration of Discrete Element Models (DEM) of fields of drifting ice floes. In the spring of 2015 and 2016, four sea ice floes offshore Makkovik, Labrador were tagged with satellite‐linked ice tracking buoys along with one satellite‐linked weather station on each floe to transmit wind speed and direction. Twenty satellite‐linked Lagrangian surface ocean current tracking buoys were also deployed in the open water adjacent to the targeted ice floes. In this paper, the dynamics of the four ice floes are explored in terms of the relative proportions which were forced by the wind, current, sea surface topography, Coriolis, and internal stress gradients. The internal ice stress gradients are calculated as residuals between the observed accelerations of the floes as measured by the tracking buoys and the sums of the other metocean forcings. Results show that internal ice stress gradients accounted for up to 50% of the observed forcing on the floes, and may have reached up to around 0.19 kPa.

On 29 April 2015, four beacons were deployed onto an ice island in the Strait of Belle Isle to record positional data. The ice island later broke up into many fragments, four of which were tracked by the beacons. The relative influences of wind drag, current drag, Coriolis force, sea surface height gradient and sea-ice force on the drift of the tracked ice island fragments were analyzed. Using atmospheric and oceanic model outputs, the sea-ice force was calculated as the residual of the fragments' net forces and the sum of all other forces. This was compared against the force obtained through ice concentration-dependent relationships when sea ice was present. The sea-ice forces calculated from the residual approach and concentration-dependent relationships were significant only when sea ice was present at medium-high concentrations in the vicinity of the ice island fragments. The forces from ocean currents and sea surface tilt contributed the most to the drift of the ice island fragments. Wind, however, played a minimal role in the total force governing the drift of the four ice island fragments, and Coriolis force was significant when the fragments were drifting at higher speeds.

The eastern Canadian Arctic is an ice-prone environment that is a vital part of Canadian Arctic shipping lanes. A better understanding of the ice environment and ice characteristics in this region is essential for supporting safe and economical marine activities. This study presents a first analysis of the drift of ice islands that originated from the Petermann Glacier calving events in northwest Greenland between 2008 and 2012. These massive calving events generated numerous smaller ice islands and icebergs through subsequent deterioration and break-up events. Surviving ice features drifted further southward into the Baffin Bay and reached as far as offshore Newfoundland (∼47 °N) for the case of the 2010 calving event. The drift characteristics of Petermann ice islands are evaluated through the analysis of the recently developed Canadian Ice Island Drift, Deterioration and Detection (CI2D3) database. The average drift distance, speed, and directions of the ice islands that resulted from the 2008, 2010, and 2012 calving events were estimated using successive observations of the monitored ice islands in the CI2D3 database. This study also includes an assessment of fracture events, including the total number of ice island break-up events following each massive calving event and the average number of daughter ice islands resulting from each break-up event. A geographical analysis of the data was also performed to present the location of the fracture events, as well as the time series of latitude change of Petermann ice islands from their origin (northwest Greenland ice tongues) to where until they became too small (< 0.25 km2) to be delineated in the CI2D3 database. This information is of particular interest to marine activities in the eastern Canadian Arctic, and oil and gas operations offshore Newfoundland and Labrador.

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 uses the recently developed Canadian Ice Island Drift, Deterioration and Detection database to investigate the fracture events that these ice islands experienced, and it presents 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 are 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 is quantified using Bayes' theorem. Out of the seven variables analyzed in this study, water temperature and ocean current speed are identified as the most and least important contributors, respectively, to the fracture events of the Petermann ice islands. It is also revealed that the ice island fracture probability increases to 75 % as the ice islands encounter extreme (very high) atmospheric and oceanic conditions. A validation scheme is presented using the cross-validation approach and Pareto principle, and an average error of 13 %–39 % is 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 ice and risk management in the eastern Canadian Arctic. Future research, however, is necessary for model training and testing to further validate this ice island fracture model.

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