Graph Analysis of Arctic Ice
abstract: Polar ice masses can be valuable indicators of trends in global climate. In an effort to better understand the dynamics of Arctic ice, this project analyzes sea ice concentration anomaly data collected over gridded regions (cells) and builds graphs based upon high correlations between cell...
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ftarizonastateun:item:17042 2023-05-15T14:49:49+02:00 Graph Analysis of Arctic Ice Wallace-Patterson, Chloe Rae (Author) Syrotiuk, Violet (Thesis Director) Colbourn, Charles (Committee Member) Montgomery, Douglas (Committee Member) Barrett, The Honors College School of Mathematical and Statistical Sciences Computer Science and Engineering Program 2013-05 26 pages http://hdl.handle.net/2286/R.I.17042 eng eng Academic Year 2012-2013 http://hdl.handle.net/2286/R.I.17042 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved Climate Graphs Computer Science Text 2013 ftarizonastateun 2019-04-06T22:55:57Z abstract: Polar ice masses can be valuable indicators of trends in global climate. In an effort to better understand the dynamics of Arctic ice, this project analyzes sea ice concentration anomaly data collected over gridded regions (cells) and builds graphs based upon high correlations between cells. These graphs offer the opportunity to use metrics such as clustering coefficients and connected components to isolate representative trends in ice masses. Based upon this analysis, the structure of sea ice graphs differs at a statistically significant level from random graphs, and several regions show erratically decreasing trends in sea ice concentration. Text Arctic Sea ice Arizona State University: ASU Digital Repository Arctic |
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Open Polar |
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Arizona State University: ASU Digital Repository |
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ftarizonastateun |
language |
English |
topic |
Climate Graphs Computer Science |
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Climate Graphs Computer Science Graph Analysis of Arctic Ice |
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Climate Graphs Computer Science |
description |
abstract: Polar ice masses can be valuable indicators of trends in global climate. In an effort to better understand the dynamics of Arctic ice, this project analyzes sea ice concentration anomaly data collected over gridded regions (cells) and builds graphs based upon high correlations between cells. These graphs offer the opportunity to use metrics such as clustering coefficients and connected components to isolate representative trends in ice masses. Based upon this analysis, the structure of sea ice graphs differs at a statistically significant level from random graphs, and several regions show erratically decreasing trends in sea ice concentration. |
author2 |
Wallace-Patterson, Chloe Rae (Author) Syrotiuk, Violet (Thesis Director) Colbourn, Charles (Committee Member) Montgomery, Douglas (Committee Member) Barrett, The Honors College School of Mathematical and Statistical Sciences Computer Science and Engineering Program |
format |
Text |
title |
Graph Analysis of Arctic Ice |
title_short |
Graph Analysis of Arctic Ice |
title_full |
Graph Analysis of Arctic Ice |
title_fullStr |
Graph Analysis of Arctic Ice |
title_full_unstemmed |
Graph Analysis of Arctic Ice |
title_sort |
graph analysis of arctic ice |
publishDate |
2013 |
url |
http://hdl.handle.net/2286/R.I.17042 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Sea ice |
genre_facet |
Arctic Sea ice |
op_relation |
Academic Year 2012-2013 http://hdl.handle.net/2286/R.I.17042 |
op_rights |
http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved |
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1766320891376959488 |