Estimating iceberg paths using a wind-driven drift model

Icebergs are hazards to ship traffic and offshore operations. Their monitoring using satellite data is hence important for marine safety and for protection of the marine environment. The repeated search for smaller icebergs in a temporal sequence of satellite images, however, can be time consuming i...

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Published in:Cold Regions Science and Technology
Main Authors: Wesche, Christine, Dierking, Wolfgang
Format: Article in Journal/Newspaper
Language:unknown
Published: ELSEVIER SCIENCE BV 2016
Subjects:
Online Access:https://epic.awi.de/id/eprint/39762/
https://hdl.handle.net/10013/epic.46888
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spelling ftawi:oai:epic.awi.de:39762 2024-09-15T17:46:50+00:00 Estimating iceberg paths using a wind-driven drift model Wesche, Christine Dierking, Wolfgang 2016-05 https://epic.awi.de/id/eprint/39762/ https://hdl.handle.net/10013/epic.46888 unknown ELSEVIER SCIENCE BV Wesche, C. orcid:0000-0002-9786-4010 and Dierking, W. orcid:0000-0002-5031-648X (2016) Estimating iceberg paths using a wind-driven drift model , Cold Regions Science and Technology, 125 (1), pp. 31-39 . doi:10.1016/j.coldregions.2016.01.008 <https://doi.org/10.1016/j.coldregions.2016.01.008> , hdl:10013/epic.46888 EPIC3Cold Regions Science and Technology, ELSEVIER SCIENCE BV, 125(1), pp. 31-39, ISSN: 0165-232X Article isiRev 2016 ftawi https://doi.org/10.1016/j.coldregions.2016.01.008 2024-06-24T04:13:16Z Icebergs are hazards to ship traffic and offshore operations. Their monitoring using satellite data is hence important for marine safety and for protection of the marine environment. The repeated search for smaller icebergs in a temporal sequence of satellite images, however, can be time consuming if the expected drift path of the berg is not known. Computer simulations of iceberg drift can be applied to determine the approximate new iceberg position to narrow the search radius for icebergs. Best suited for this purpose are relatively simple, fast-running models. For three different regions of the Weddell Sea, Antarctica, we used an iceberg drift model driven by wind forecasts and analyzed predicted iceberg positions in comparison to positions retrieved from GPS buoys placed on the icebergs. As an error measure, we took the difference between the modeled and observed iceberg positions and drift angles. As the model was developed for open water regions, we added a sea-ice component. The application of the model was tested on two ENVISAT Wide Swath SAR scenes from the Weddell Sea, simulating and tracking iceberg positions for a period of five days. Although simulation results differ from direct observations of iceberg drift, they are still useful for narrowing the search area for icebergs in satellite images. We attribute the deviations between simulations and observations to the inherent large uncertainties in the input data for the model. Article in Journal/Newspaper Antarc* Antarctica Sea ice Weddell Sea Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center) Cold Regions Science and Technology 125 31 39
institution Open Polar
collection Alfred Wegener Institute for Polar- and Marine Research (AWI): ePIC (electronic Publication Information Center)
op_collection_id ftawi
language unknown
description Icebergs are hazards to ship traffic and offshore operations. Their monitoring using satellite data is hence important for marine safety and for protection of the marine environment. The repeated search for smaller icebergs in a temporal sequence of satellite images, however, can be time consuming if the expected drift path of the berg is not known. Computer simulations of iceberg drift can be applied to determine the approximate new iceberg position to narrow the search radius for icebergs. Best suited for this purpose are relatively simple, fast-running models. For three different regions of the Weddell Sea, Antarctica, we used an iceberg drift model driven by wind forecasts and analyzed predicted iceberg positions in comparison to positions retrieved from GPS buoys placed on the icebergs. As an error measure, we took the difference between the modeled and observed iceberg positions and drift angles. As the model was developed for open water regions, we added a sea-ice component. The application of the model was tested on two ENVISAT Wide Swath SAR scenes from the Weddell Sea, simulating and tracking iceberg positions for a period of five days. Although simulation results differ from direct observations of iceberg drift, they are still useful for narrowing the search area for icebergs in satellite images. We attribute the deviations between simulations and observations to the inherent large uncertainties in the input data for the model.
format Article in Journal/Newspaper
author Wesche, Christine
Dierking, Wolfgang
spellingShingle Wesche, Christine
Dierking, Wolfgang
Estimating iceberg paths using a wind-driven drift model
author_facet Wesche, Christine
Dierking, Wolfgang
author_sort Wesche, Christine
title Estimating iceberg paths using a wind-driven drift model
title_short Estimating iceberg paths using a wind-driven drift model
title_full Estimating iceberg paths using a wind-driven drift model
title_fullStr Estimating iceberg paths using a wind-driven drift model
title_full_unstemmed Estimating iceberg paths using a wind-driven drift model
title_sort estimating iceberg paths using a wind-driven drift model
publisher ELSEVIER SCIENCE BV
publishDate 2016
url https://epic.awi.de/id/eprint/39762/
https://hdl.handle.net/10013/epic.46888
genre Antarc*
Antarctica
Sea ice
Weddell Sea
genre_facet Antarc*
Antarctica
Sea ice
Weddell Sea
op_source EPIC3Cold Regions Science and Technology, ELSEVIER SCIENCE BV, 125(1), pp. 31-39, ISSN: 0165-232X
op_relation Wesche, C. orcid:0000-0002-9786-4010 and Dierking, W. orcid:0000-0002-5031-648X (2016) Estimating iceberg paths using a wind-driven drift model , Cold Regions Science and Technology, 125 (1), pp. 31-39 . doi:10.1016/j.coldregions.2016.01.008 <https://doi.org/10.1016/j.coldregions.2016.01.008> , hdl:10013/epic.46888
op_doi https://doi.org/10.1016/j.coldregions.2016.01.008
container_title Cold Regions Science and Technology
container_volume 125
container_start_page 31
op_container_end_page 39
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