OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD
Maritime shipping and natural resource development in the Arctic are projected to increase as sea ice coverage decreases, resulting in a greater probability of more and larger oil spills. The increasing risk of Arctic spills emphasizes the need to identify the state-of-the-art oil trajectory and sea...
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ftuninhampshire:oai:scholars.unh.edu:thesis-2534 2023-05-15T14:35:36+02:00 OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD Verfaillie, Megan Patricia 2021-05-01T07:00:00Z application/pdf https://scholars.unh.edu/thesis/1495 https://scholars.unh.edu/cgi/viewcontent.cgi?article=2534&context=thesis unknown University of New Hampshire Scholars' Repository https://scholars.unh.edu/thesis/1495 https://scholars.unh.edu/cgi/viewcontent.cgi?article=2534&context=thesis Master's Theses and Capstones Arctic modeling oil spill text 2021 ftuninhampshire 2023-01-30T22:03:57Z Maritime shipping and natural resource development in the Arctic are projected to increase as sea ice coverage decreases, resulting in a greater probability of more and larger oil spills. The increasing risk of Arctic spills emphasizes the need to identify the state-of-the-art oil trajectory and sea ice models and the potential for their integration. The Oil Spill Modeling for Improved Response to Arctic Maritime Spills: The Path Forward (AMSM) project, funded by the Arctic Domain Awareness Center (ADAC), provides a structured approach to gather expert advice to address U.S. Coast Guard (USCG) Federal On-Scene Coordinator (FOSC) core needs for decision-making. The National Oceanic & Atmospheric Administration (NOAA) Office of Response & Restoration (OR&R) provides scientific support to the USCG FOSC during oil spill response. As part of this scientific support, NOAA OR&R supplies decision support models that predict the fate (including chemical and physical weathering) and transport of spilled oil. Oil spill modeling in the Arctic faces many unique challenges including limited availability of environmental data (e.g., currents, wind, ice characteristics) at fine spatial and temporal resolution to feed models. Despite these challenges, OR&R’s modeling products must provide adequate spill trajectory predictions, so that response efforts minimize economic, cultural and environmental impacts, including those to species, habitats and food supplies. The AMSM project addressed the unique needs and challenges associated with Arctic spill response by: (1) identifying state-of-the-art oil spill and sea ice models, (2) recommending new components and algorithms for oil and ice interactions, (3) proposing methods for improving communication of model output uncertainty, and (4) developing methods for coordinating oil and ice modeling efforts. Text Arctic Sea ice University of New Hampshire: Scholars Repository Arctic |
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Arctic modeling oil spill Verfaillie, Megan Patricia OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD |
topic_facet |
Arctic modeling oil spill |
description |
Maritime shipping and natural resource development in the Arctic are projected to increase as sea ice coverage decreases, resulting in a greater probability of more and larger oil spills. The increasing risk of Arctic spills emphasizes the need to identify the state-of-the-art oil trajectory and sea ice models and the potential for their integration. The Oil Spill Modeling for Improved Response to Arctic Maritime Spills: The Path Forward (AMSM) project, funded by the Arctic Domain Awareness Center (ADAC), provides a structured approach to gather expert advice to address U.S. Coast Guard (USCG) Federal On-Scene Coordinator (FOSC) core needs for decision-making. The National Oceanic & Atmospheric Administration (NOAA) Office of Response & Restoration (OR&R) provides scientific support to the USCG FOSC during oil spill response. As part of this scientific support, NOAA OR&R supplies decision support models that predict the fate (including chemical and physical weathering) and transport of spilled oil. Oil spill modeling in the Arctic faces many unique challenges including limited availability of environmental data (e.g., currents, wind, ice characteristics) at fine spatial and temporal resolution to feed models. Despite these challenges, OR&R’s modeling products must provide adequate spill trajectory predictions, so that response efforts minimize economic, cultural and environmental impacts, including those to species, habitats and food supplies. The AMSM project addressed the unique needs and challenges associated with Arctic spill response by: (1) identifying state-of-the-art oil spill and sea ice models, (2) recommending new components and algorithms for oil and ice interactions, (3) proposing methods for improving communication of model output uncertainty, and (4) developing methods for coordinating oil and ice modeling efforts. |
format |
Text |
author |
Verfaillie, Megan Patricia |
author_facet |
Verfaillie, Megan Patricia |
author_sort |
Verfaillie, Megan Patricia |
title |
OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD |
title_short |
OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD |
title_full |
OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD |
title_fullStr |
OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD |
title_full_unstemmed |
OIL SPILL MODELING FOR IMPROVED RESPONSE TO ARCTIC MARITIME SPILLS: THE PATH FORWARD |
title_sort |
oil spill modeling for improved response to arctic maritime spills: the path forward |
publisher |
University of New Hampshire Scholars' Repository |
publishDate |
2021 |
url |
https://scholars.unh.edu/thesis/1495 https://scholars.unh.edu/cgi/viewcontent.cgi?article=2534&context=thesis |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_source |
Master's Theses and Capstones |
op_relation |
https://scholars.unh.edu/thesis/1495 https://scholars.unh.edu/cgi/viewcontent.cgi?article=2534&context=thesis |
_version_ |
1766308388796366848 |