Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013

Abstract Since 2008, the Study of Environmental Arctic Change Sea Ice Outlook has solicited predictions of September sea-ice extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as month...

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Main Authors: Stroeve, Julienne, Hamilton, Lawrence C., Bitz, Cecilia M, Blanchard-Wrigglesworth, Edward
Format: Text
Language:unknown
Published: University of New Hampshire Scholars' Repository 2014
Subjects:
Online Access:https://scholars.unh.edu/soc_facpub/196
https://scholars.unh.edu/cgi/viewcontent.cgi?article=1195&context=soc_facpub
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spelling ftuninhampshire:oai:scholars.unh.edu:soc_facpub-1195 2023-05-15T14:51:36+02:00 Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013 Stroeve, Julienne Hamilton, Lawrence C. Bitz, Cecilia M Blanchard-Wrigglesworth, Edward 2014-04-01T07:00:00Z application/pdf https://scholars.unh.edu/soc_facpub/196 https://scholars.unh.edu/cgi/viewcontent.cgi?article=1195&context=soc_facpub unknown University of New Hampshire Scholars' Repository https://scholars.unh.edu/soc_facpub/196 https://scholars.unh.edu/cgi/viewcontent.cgi?article=1195&context=soc_facpub © 2014. American Geophysical Union. All Rights Reserved. Sociology Scholarship Arctic ensemble prediction sea ice Sociology text 2014 ftuninhampshire 2023-01-30T21:30:22Z Abstract Since 2008, the Study of Environmental Arctic Change Sea Ice Outlook has solicited predictions of September sea-ice extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed ice extent is near its trend, the median predictions tend to be accurate. In years when the observed extent is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial ice, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea-ice prediction. Key Points Analysis of Sea Ice Outlook contributions 2008-2013 shows bimodal success Years when observations depart from trend are hard to predict despite preconditioning Yearly conditions dominate variations in ensemble prediction success. Text Arctic Sea ice Study of Environmental Arctic Change University of New Hampshire: Scholars Repository Arctic
institution Open Polar
collection University of New Hampshire: Scholars Repository
op_collection_id ftuninhampshire
language unknown
topic Arctic
ensemble
prediction
sea ice
Sociology
spellingShingle Arctic
ensemble
prediction
sea ice
Sociology
Stroeve, Julienne
Hamilton, Lawrence C.
Bitz, Cecilia M
Blanchard-Wrigglesworth, Edward
Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
topic_facet Arctic
ensemble
prediction
sea ice
Sociology
description Abstract Since 2008, the Study of Environmental Arctic Change Sea Ice Outlook has solicited predictions of September sea-ice extent from the Arctic research community. Individuals and teams employ a variety of modeling, statistical, and heuristic approaches to make these predictions. Viewed as monthly ensembles each with one or two dozen individual predictions, they display a bimodal pattern of success. In years when observed ice extent is near its trend, the median predictions tend to be accurate. In years when the observed extent is anomalous, the median and most individual predictions are less accurate. Statistical analysis suggests that year-to-year variability, rather than methods, dominate the variation in ensemble prediction success. Furthermore, ensemble predictions do not improve as the season evolves. We consider the role of initial ice, atmosphere and ocean conditions, and summer storms and weather in contributing to the challenge of sea-ice prediction. Key Points Analysis of Sea Ice Outlook contributions 2008-2013 shows bimodal success Years when observations depart from trend are hard to predict despite preconditioning Yearly conditions dominate variations in ensemble prediction success.
format Text
author Stroeve, Julienne
Hamilton, Lawrence C.
Bitz, Cecilia M
Blanchard-Wrigglesworth, Edward
author_facet Stroeve, Julienne
Hamilton, Lawrence C.
Bitz, Cecilia M
Blanchard-Wrigglesworth, Edward
author_sort Stroeve, Julienne
title Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
title_short Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
title_full Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
title_fullStr Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
title_full_unstemmed Predicting September sea ice: Ensemble skill of the SEARCH Sea Ice Outlook 2008-2013
title_sort predicting september sea ice: ensemble skill of the search sea ice outlook 2008-2013
publisher University of New Hampshire Scholars' Repository
publishDate 2014
url https://scholars.unh.edu/soc_facpub/196
https://scholars.unh.edu/cgi/viewcontent.cgi?article=1195&context=soc_facpub
geographic Arctic
geographic_facet Arctic
genre Arctic
Sea ice
Study of Environmental Arctic Change
genre_facet Arctic
Sea ice
Study of Environmental Arctic Change
op_source Sociology Scholarship
op_relation https://scholars.unh.edu/soc_facpub/196
https://scholars.unh.edu/cgi/viewcontent.cgi?article=1195&context=soc_facpub
op_rights © 2014. American Geophysical Union. All Rights Reserved.
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