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Validation of the North American Ice Service Iceberg Drift Model

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Date

2022-04-13

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Université d'Ottawa / University of Ottawa

Creative Commons

Attribution-NonCommercial-NoDerivatives 4.0 International

Abstract

Icebergs calved from high-latitude glaciers and ice shelves pose a threat to vessels and offshore infrastructure at a time when Arctic shipping and resource exploration are increasing. Knowledge of the location of potential ice hazards is therefore critical to ensure safe and efficient operations in this remote region. The Canadian Ice Service (CIS; Environment and Climate Change Canada) provides information to stakeholders on the observed and predicted distribution of icebergs in Canadian waters by combining iceberg observations with forecasts from the North American Ice Service (NAIS) iceberg drift model. The NAIS model estimates the forces acting on an iceberg to predict its future position and velocity. It is widely used for the east coast of Canada but largely unproven in the Arctic and suffers from insufficient validation due to a paucity of reliable in-situ observations of iceberg drift. This study represents the first comprehensive validation of the NAIS iceberg drift model for the Canadian Arctic. A total of 133 hindcast simulations for the period 2009-2019 were performed against in-situ drift observations of 44 icebergs. These data, collated in an iceberg beacon database (compiled by Carleton University and CIS), includes observations collected by Cryologgers; novel iceberg tracking beacons designed as part of this study. Quantified comparisons of the distance error between observed and modelled drift tracks indicate that the NAIS model produces realistic simulations of iceberg drift in Baffin Bay. Root mean square error after 24-hours of simulated drift ranged from 18-22 km and increased at a daily rate of 11-13 km, which is typical of previous model verification and validation studies. Improved model performance was observed for longer (>250 m) and deeper-keeled (>100 m) icebergs, which appears to counteract the model’s tendency to overestimate drift by reducing the influence of stronger surface ocean currents acting on the iceberg. Ocean current direction, wind direction, and iceberg keel geometry were identified by a sensitivity analysis as the model parameters and environmental driving forces that have the greatest influence on modelled iceberg drift. These results emphasize the need for accurate environmental information and underscore the importance of properly representing the physical characteristics of icebergs in drift models.

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Keywords

iceberg, drift, modelling, tracking beacon

Citation