Iceberg drift ensemble forecasting
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...
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Memorial University of Newfoundland
2020
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ftmemorialuniv:oai:research.library.mun.ca:14403 2023-10-01T03:54:25+02:00 Iceberg drift ensemble forecasting Kielley, Evan 2020-05 application/pdf https://research.library.mun.ca/14403/ https://research.library.mun.ca/14403/1/thesis.pdf en eng Memorial University of Newfoundland https://research.library.mun.ca/14403/1/thesis.pdf Kielley, Evan <https://research.library.mun.ca/view/creator_az/Kielley=3AEvan=3A=3A.html> (2020) Iceberg drift ensemble forecasting. Masters thesis, Memorial University of Newfoundland. thesis_license Thesis NonPeerReviewed 2020 ftmemorialuniv 2023-09-03T06:49:45Z 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. Thesis ArcticNet Memorial University of Newfoundland: Research Repository |
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Memorial University of Newfoundland: Research Repository |
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ftmemorialuniv |
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English |
description |
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. |
format |
Thesis |
author |
Kielley, Evan |
spellingShingle |
Kielley, Evan Iceberg drift ensemble forecasting |
author_facet |
Kielley, Evan |
author_sort |
Kielley, Evan |
title |
Iceberg drift ensemble forecasting |
title_short |
Iceberg drift ensemble forecasting |
title_full |
Iceberg drift ensemble forecasting |
title_fullStr |
Iceberg drift ensemble forecasting |
title_full_unstemmed |
Iceberg drift ensemble forecasting |
title_sort |
iceberg drift ensemble forecasting |
publisher |
Memorial University of Newfoundland |
publishDate |
2020 |
url |
https://research.library.mun.ca/14403/ https://research.library.mun.ca/14403/1/thesis.pdf |
genre |
ArcticNet |
genre_facet |
ArcticNet |
op_relation |
https://research.library.mun.ca/14403/1/thesis.pdf Kielley, Evan <https://research.library.mun.ca/view/creator_az/Kielley=3AEvan=3A=3A.html> (2020) Iceberg drift ensemble forecasting. Masters thesis, Memorial University of Newfoundland. |
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thesis_license |
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1778522010660372480 |