Bayesian hierarchical modelling of North Atlantic windiness

Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operati...

Full description

Bibliographic Details
Published in:Natural Hazards and Earth System Sciences
Main Authors: Vanem, Erik, Breivik, Olav Nikolai
Format: Article in Journal/Newspaper
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10852/53355
http://urn.nb.no/URN:NBN:no-56581
https://doi.org/10.5194/nhess-13-545-2013
id ftoslouniv:oai:www.duo.uio.no:10852/53355
record_format openpolar
spelling ftoslouniv:oai:www.duo.uio.no:10852/53355 2023-05-15T17:29:42+02:00 Bayesian hierarchical modelling of North Atlantic windiness Vanem, Erik Breivik, Olav Nikolai 2013 http://hdl.handle.net/10852/53355 http://urn.nb.no/URN:NBN:no-56581 https://doi.org/10.5194/nhess-13-545-2013 en eng Breivik, Olav Nikolai (2016) Bayesian spatio-temporal hierarchical modeling: Bycatch in the Barents Sea shrimp fishery and North Atlantic windiness. Doctoral thesis. http://urn.nb.no/URN:NBN:no-56582 http://urn.nb.no/URN:NBN:no-56582 http://urn.nb.no/URN:NBN:no-56581 http://hdl.handle.net/10852/53355 Natural Hazards and Earth System Sciences 13 545 557 http://dx.doi.org/10.5194/nhess-13-545-2013 URN:NBN:no-56581 Fulltext https://www.duo.uio.no/bitstream/handle/10852/53355/1/nhess-13-545-2013.pdf Attribution 3.0 Unported https://creativecommons.org/licenses/by/3.0/ CC-BY Journal article Tidsskriftartikkel Peer reviewed PublishedVersion 2013 ftoslouniv https://doi.org/10.5194/nhess-13-545-2013 2020-06-21T08:50:15Z Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks. Article in Journal/Newspaper North Atlantic Universitet i Oslo: Digitale utgivelser ved UiO (DUO) Natural Hazards and Earth System Sciences 13 3 545 557
institution Open Polar
collection Universitet i Oslo: Digitale utgivelser ved UiO (DUO)
op_collection_id ftoslouniv
language English
description Extreme weather conditions represent serious natural hazards to ship operations and may be the direct cause or contributing factor to maritime accidents. Such severe environmental conditions can be taken into account in ship design and operational windows can be defined that limits hazardous operations to less extreme conditions. Nevertheless, possible changes in the statistics of extreme weather conditions, possibly due to anthropogenic climate change, represent an additional hazard to ship operations that is less straightforward to account for in a consistent way. Obviously, there are large uncertainties as to how future climate change will affect the extreme weather conditions at sea and there is a need for stochastic models that can describe the variability in both space and time at various scales of the environmental conditions. Previously, Bayesian hierarchical space-time models have been developed to describe the variability and complex dependence structures of significant wave height in space and time. These models were found to perform reasonably well and provided some interesting results, in particular, pertaining to long-term trends in the wave climate. In this paper, a similar framework is applied to oceanic windiness and the spatial and temporal variability of the 10-m wind speed over an area in the North Atlantic ocean is investigated. When the results from the model for North Atlantic windiness is compared to the results for significant wave height over the same area, it is interesting to observe that whereas an increasing trend in significant wave height was identified, no statistically significant long-term trend was estimated in windiness. This may indicate that the increase in significant wave height is not due to an increase in locally generated wind waves, but rather to increased swell. This observation is also consistent with studies that have suggested a poleward shift of the main storm tracks.
format Article in Journal/Newspaper
author Vanem, Erik
Breivik, Olav Nikolai
spellingShingle Vanem, Erik
Breivik, Olav Nikolai
Bayesian hierarchical modelling of North Atlantic windiness
author_facet Vanem, Erik
Breivik, Olav Nikolai
author_sort Vanem, Erik
title Bayesian hierarchical modelling of North Atlantic windiness
title_short Bayesian hierarchical modelling of North Atlantic windiness
title_full Bayesian hierarchical modelling of North Atlantic windiness
title_fullStr Bayesian hierarchical modelling of North Atlantic windiness
title_full_unstemmed Bayesian hierarchical modelling of North Atlantic windiness
title_sort bayesian hierarchical modelling of north atlantic windiness
publishDate 2013
url http://hdl.handle.net/10852/53355
http://urn.nb.no/URN:NBN:no-56581
https://doi.org/10.5194/nhess-13-545-2013
genre North Atlantic
genre_facet North Atlantic
op_relation Breivik, Olav Nikolai (2016) Bayesian spatio-temporal hierarchical modeling: Bycatch in the Barents Sea shrimp fishery and North Atlantic windiness. Doctoral thesis. http://urn.nb.no/URN:NBN:no-56582
http://urn.nb.no/URN:NBN:no-56582
http://urn.nb.no/URN:NBN:no-56581
http://hdl.handle.net/10852/53355
Natural Hazards and Earth System Sciences
13
545
557
http://dx.doi.org/10.5194/nhess-13-545-2013
URN:NBN:no-56581
Fulltext https://www.duo.uio.no/bitstream/handle/10852/53355/1/nhess-13-545-2013.pdf
op_rights Attribution 3.0 Unported
https://creativecommons.org/licenses/by/3.0/
op_rightsnorm CC-BY
op_doi https://doi.org/10.5194/nhess-13-545-2013
container_title Natural Hazards and Earth System Sciences
container_volume 13
container_issue 3
container_start_page 545
op_container_end_page 557
_version_ 1766124477360373760