Summer 2011 September Arctic Sea Ice Forecast

Our forecast uses a state-of-the-art General Circulation Model (GCM) initialized with average May 2011 sea ice area and volume anomalies obtained from the Pan-arctic Ice-Ocean Modeling and Assimilation System (PIOMAS). The GCM used is the National Center for Atmospheric Research (NCAR)’s Community C...

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Main Authors: Edward Blanchard-wrigglesworth, Cecilia Bitz, Jinlun Zhang, Ron Lindsay
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 2005
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.906
http://www.arcus.org/files/search/sea-ice-outlook/2011/07/pdf/pan-arctic/blanchard_etal_panarctic_july.pdf
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spelling ftciteseerx:oai:CiteSeerX.psu:10.1.1.364.906 2023-05-15T14:21:00+02:00 Summer 2011 September Arctic Sea Ice Forecast Edward Blanchard-wrigglesworth Cecilia Bitz Jinlun Zhang Ron Lindsay The Pennsylvania State University CiteSeerX Archives 2005 application/pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.906 http://www.arcus.org/files/search/sea-ice-outlook/2011/07/pdf/pan-arctic/blanchard_etal_panarctic_july.pdf en eng http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.906 http://www.arcus.org/files/search/sea-ice-outlook/2011/07/pdf/pan-arctic/blanchard_etal_panarctic_july.pdf Metadata may be used without restrictions as long as the oai identifier remains attached to it. http://www.arcus.org/files/search/sea-ice-outlook/2011/07/pdf/pan-arctic/blanchard_etal_panarctic_july.pdf text 2005 ftciteseerx 2016-01-08T01:00:18Z Our forecast uses a state-of-the-art General Circulation Model (GCM) initialized with average May 2011 sea ice area and volume anomalies obtained from the Pan-arctic Ice-Ocean Modeling and Assimilation System (PIOMAS). The GCM used is the National Center for Atmospheric Research (NCAR)’s Community Climate System Model version 4 (CCSM4) [1] at 1 ◦ resolution in all components. Our strategy is to initialize the sea ice with anomalies with respect to the model mean that are good approximations to actual Arctic sea ice anomalies. Because our predictions are several months in the future, we make no attempt to initialize the atmosphere with true conditions. Instead we create an ensemble of predictions from integrations that begin on June 1 with identical sea ice, ocean, and land conditions but with variable atmospheric initial conditions, which are drawn from consecutive days near June 1 of an arbitrary model year. In other words, an ensemble is created by shifting the dates of the initial conditions of the atmosphere component relative to the other components. We utilize one of 6 hindcast runs with CCSM4 that have been submitted for analysis to the CMIP5 dataset for IPCC AR5. The hindcast was run with observed greenhouse gas and aerosols through the year 2005. We take 2005 as the arbitrary year, which is close enough to present to be used for seasonal prediction in 2011. At this time we only apply anomalies to the sea ice and we apply no anomalies to the ocean or land. Without ocean anomalies in the initial conditions, the full ocean GCM of the model is not needed, so we carry out our integrations with a slab ocean model whose ocean heat flux convergences is specified from the CCSM4 hindcast for the years 1995-2005. We run the hindcast with slab Text Arctic Arctic Sea ice Unknown Arctic
institution Open Polar
collection Unknown
op_collection_id ftciteseerx
language English
description Our forecast uses a state-of-the-art General Circulation Model (GCM) initialized with average May 2011 sea ice area and volume anomalies obtained from the Pan-arctic Ice-Ocean Modeling and Assimilation System (PIOMAS). The GCM used is the National Center for Atmospheric Research (NCAR)’s Community Climate System Model version 4 (CCSM4) [1] at 1 ◦ resolution in all components. Our strategy is to initialize the sea ice with anomalies with respect to the model mean that are good approximations to actual Arctic sea ice anomalies. Because our predictions are several months in the future, we make no attempt to initialize the atmosphere with true conditions. Instead we create an ensemble of predictions from integrations that begin on June 1 with identical sea ice, ocean, and land conditions but with variable atmospheric initial conditions, which are drawn from consecutive days near June 1 of an arbitrary model year. In other words, an ensemble is created by shifting the dates of the initial conditions of the atmosphere component relative to the other components. We utilize one of 6 hindcast runs with CCSM4 that have been submitted for analysis to the CMIP5 dataset for IPCC AR5. The hindcast was run with observed greenhouse gas and aerosols through the year 2005. We take 2005 as the arbitrary year, which is close enough to present to be used for seasonal prediction in 2011. At this time we only apply anomalies to the sea ice and we apply no anomalies to the ocean or land. Without ocean anomalies in the initial conditions, the full ocean GCM of the model is not needed, so we carry out our integrations with a slab ocean model whose ocean heat flux convergences is specified from the CCSM4 hindcast for the years 1995-2005. We run the hindcast with slab
author2 The Pennsylvania State University CiteSeerX Archives
format Text
author Edward Blanchard-wrigglesworth
Cecilia Bitz
Jinlun Zhang
Ron Lindsay
spellingShingle Edward Blanchard-wrigglesworth
Cecilia Bitz
Jinlun Zhang
Ron Lindsay
Summer 2011 September Arctic Sea Ice Forecast
author_facet Edward Blanchard-wrigglesworth
Cecilia Bitz
Jinlun Zhang
Ron Lindsay
author_sort Edward Blanchard-wrigglesworth
title Summer 2011 September Arctic Sea Ice Forecast
title_short Summer 2011 September Arctic Sea Ice Forecast
title_full Summer 2011 September Arctic Sea Ice Forecast
title_fullStr Summer 2011 September Arctic Sea Ice Forecast
title_full_unstemmed Summer 2011 September Arctic Sea Ice Forecast
title_sort summer 2011 september arctic sea ice forecast
publishDate 2005
url http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.906
http://www.arcus.org/files/search/sea-ice-outlook/2011/07/pdf/pan-arctic/blanchard_etal_panarctic_july.pdf
geographic Arctic
geographic_facet Arctic
genre Arctic
Arctic
Sea ice
genre_facet Arctic
Arctic
Sea ice
op_source http://www.arcus.org/files/search/sea-ice-outlook/2011/07/pdf/pan-arctic/blanchard_etal_panarctic_july.pdf
op_relation http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.906
http://www.arcus.org/files/search/sea-ice-outlook/2011/07/pdf/pan-arctic/blanchard_etal_panarctic_july.pdf
op_rights Metadata may be used without restrictions as long as the oai identifier remains attached to it.
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