Iceberg drift ensemble forecasting

Kielley, Evan (2020) Iceberg drift ensemble forecasting. Masters thesis, Memorial University of Newfoundland.

[img] [English] PDF - Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.

Download (9MB)

Abstract

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.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/14403
Item ID: 14403
Additional Information: Includes bibliographical references (pages 96-99).
Keywords: Iceberg, drift, ensemble, forecasting
Department(s): Science, Faculty of > Mathematics and Statistics
Date: May 2020
Date Type: Submission
Library of Congress Subject Heading: Sea ice drift--Simulation methods.

Actions (login required)

View Item View Item

Downloads

Downloads per month over the past year

View more statistics