Iceberg drift ensemble forecasting

• Main Author: Kielley, Evan
• Format: Text
• Language: English
• Published: Memorial University of Newfoundland 2020
• Subjects: ArcticNet
• Online Access: https://dx.doi.org/10.48336/tgm0-cv07; https://research.library.mun.ca/14403/

The goal of this thesis is to investigate whether ensemble modeling in iceberg drift forecasting improves predictions of an iceberg's trajectory. To do this, we have used a dynamic iceberg drift model and created an ensemble of realizations by applying stochastic perturbations to ocean current and wind reanalysis data, drawing from distributions of the ocean current and wind measured with ship-based instruments. In this study, we focus on simulating trajectories for two icebergs observed during the 2015 Statoil-ArcticNet research expedition. To conduct simulations, we initialized our model with observations of each iceberg at a particular time and location, then simulated a day of drift for each iceberg and compared the ensemble of simulation results to their actual known trajectories. In this comparison, we found inconsistent results. For one iceberg, the mean of the modelled trajectories was consistent with the observations but, for the other, none of the modelled trajectories were close. Overall, we conclude that ensemble modelling for iceberg drift forecasting is a useful technique only when the wind and current data driving the prediction is sufficiently accurate.