Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns

Barrow, Alaska is a coastal community that is vulnerable to coastal flooding and structural damage from local high-wind events during the "ice-free" season from late summer through autumn. Historically, high latitude cyclonic storms with high-winds rarely have affected Barrow, however, wit...

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Main Authors: Kahn-Thornbrugh, Casey, Lynch, Amanda, Cassano, Liz
Format: Text
Language:unknown
Published: University Corporation For Atmospheric Research (UCAR) 2003
Subjects:
Online Access:https://dx.doi.org/10.5065/ybbw-ba96
https://opensky.ucar.edu/islandora/object/manuscripts:541
id ftdatacite:10.5065/ybbw-ba96
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spelling ftdatacite:10.5065/ybbw-ba96 2023-05-15T15:10:37+02:00 Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns Kahn-Thornbrugh, Casey Lynch, Amanda Cassano, Liz 2003 https://dx.doi.org/10.5065/ybbw-ba96 https://opensky.ucar.edu/islandora/object/manuscripts:541 unknown University Corporation For Atmospheric Research (UCAR) manuscript Text article-journal ScholarlyArticle 2003 ftdatacite https://doi.org/10.5065/ybbw-ba96 2021-11-05T12:55:41Z Barrow, Alaska is a coastal community that is vulnerable to coastal flooding and structural damage from local high-wind events during the "ice-free" season from late summer through autumn. Historically, high latitude cyclonic storms with high-winds rarely have affected Barrow, however, with the current warming trend in the Arctic, these storms with high-winds may become more intense. This project intended to identify regional sea-level pressure (SLP) patterns associated with high-wind events in Barrow. This was done with the use of the Self Organizing Map (SOM) algorithm, which identifies frequently occurring spatial patterns within a large data set. The regional of interest encompasses Alaska, eastern Siberia, the Chukchi Sea, the Bearing Sea, and the Beaufort Sea. The 12-hourly SLP input data was obtained from the NCEP/NCAR Reanalysis for the period August 1 to November 30 from 1948 to 2001. This data was run through the SOM software, which was configured to identify 48 distinct SLP patterns. The 48 SLP output patterns were compared to actual SLP patterns from 14 high-wind events in Barrow from 1950 to 2000. Seventy-two percent of the 12-hourly SLP patterns from the 14 storms were similar to one or more of the 48 SLP output patterns. With the identification of specific types of SLP patterns that have the potential to be destructive to Barrow, local weather forecasters can relay the information to Barrow residents so they are provided with enough time to prepare for these high-wind events. Text Arctic Barrow Beaufort Sea Chukchi Chukchi Sea Alaska Siberia DataCite Metadata Store (German National Library of Science and Technology) Arctic Chukchi Sea
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language unknown
description Barrow, Alaska is a coastal community that is vulnerable to coastal flooding and structural damage from local high-wind events during the "ice-free" season from late summer through autumn. Historically, high latitude cyclonic storms with high-winds rarely have affected Barrow, however, with the current warming trend in the Arctic, these storms with high-winds may become more intense. This project intended to identify regional sea-level pressure (SLP) patterns associated with high-wind events in Barrow. This was done with the use of the Self Organizing Map (SOM) algorithm, which identifies frequently occurring spatial patterns within a large data set. The regional of interest encompasses Alaska, eastern Siberia, the Chukchi Sea, the Bearing Sea, and the Beaufort Sea. The 12-hourly SLP input data was obtained from the NCEP/NCAR Reanalysis for the period August 1 to November 30 from 1948 to 2001. This data was run through the SOM software, which was configured to identify 48 distinct SLP patterns. The 48 SLP output patterns were compared to actual SLP patterns from 14 high-wind events in Barrow from 1950 to 2000. Seventy-two percent of the 12-hourly SLP patterns from the 14 storms were similar to one or more of the 48 SLP output patterns. With the identification of specific types of SLP patterns that have the potential to be destructive to Barrow, local weather forecasters can relay the information to Barrow residents so they are provided with enough time to prepare for these high-wind events.
format Text
author Kahn-Thornbrugh, Casey
Lynch, Amanda
Cassano, Liz
spellingShingle Kahn-Thornbrugh, Casey
Lynch, Amanda
Cassano, Liz
Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns
author_facet Kahn-Thornbrugh, Casey
Lynch, Amanda
Cassano, Liz
author_sort Kahn-Thornbrugh, Casey
title Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns
title_short Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns
title_full Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns
title_fullStr Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns
title_full_unstemmed Predicting high-wind events impacting Barrow, Alaska through analysis of past regional sea-level pressure patterns
title_sort predicting high-wind events impacting barrow, alaska through analysis of past regional sea-level pressure patterns
publisher University Corporation For Atmospheric Research (UCAR)
publishDate 2003
url https://dx.doi.org/10.5065/ybbw-ba96
https://opensky.ucar.edu/islandora/object/manuscripts:541
geographic Arctic
Chukchi Sea
geographic_facet Arctic
Chukchi Sea
genre Arctic
Barrow
Beaufort Sea
Chukchi
Chukchi Sea
Alaska
Siberia
genre_facet Arctic
Barrow
Beaufort Sea
Chukchi
Chukchi Sea
Alaska
Siberia
op_doi https://doi.org/10.5065/ybbw-ba96
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