Validation of oil spill transport and fate modeling in Arctic ice

Reliability of oil spill modeling in Arctic waters for response planning and risk assessments depends on the accuracy of winds, currents, and ice data (cover and drift) used as input. We compared predicted transport in ice, using ice and ocean model results as input, with observed drifter trajectori...

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Bibliographic Details
Published in:Arctic Science
Main Authors: Deborah P. French-McCay, Tayebeh Tajalli-Bakhsh, Kathy Jayko, Malcolm L. Spaulding, Zhengkai Li
Format: Article in Journal/Newspaper
Language:English
French
Published: Canadian Science Publishing 2018
Subjects:
Online Access:https://doi.org/10.1139/as-2017-0027
https://doaj.org/article/f1b42e142a484cce9276d395d8dffda5
Description
Summary:Reliability of oil spill modeling in Arctic waters for response planning and risk assessments depends on the accuracy of winds, currents, and ice data (cover and drift) used as input. We compared predicted transport in ice, using ice and ocean model results as input, with observed drifter trajectories in the Beaufort Sea and an experimental oil release in the Barents Sea. The ice models varied in ice rheology algorithms used (i.e., Elastic–Viscous–Plastic, presently used in climate models, versus a new Elasto-Brittle approach in pack ice) and the time averaging of their outputs, which were provided as input to oil spill models. Evaluations of model performance (skill) against drifters showed improvement using Elasto-Brittle instead of Elastic–Viscous–Plastic rheology. However, model skill was degraded by time-averaging of ocean and ice model vectors before input to the oil spill model. While the accuracy of individual oil model trajectories projected weeks to months into the future is expected to be low, in the event of a spill, forecasts could be updated frequently with satellite and other observations to improve reliability. Comparisons of modeled trajectories with drifters verified that use of the ice–ocean models for ensemble modeling as part of risk assessments is reliable.