A data-driven approach for assessing ice-sheet mass balance in space and time
Combinations of various numerical models and datasets with diverse observation characteristics have been used to assess the mass evolution of ice sheets. As a consequence, a wide range of estimates have been produced using markedly different methodologies, data, approximation methods and model assum...
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ftunivwollongong:oai:ro.uow.edu.au:eispapers-6312 2023-05-15T13:58:42+02:00 A data-driven approach for assessing ice-sheet mass balance in space and time Zammit-Mangion, Andrew Bamber, Jonathan L Schoen, Nana W Rougier, Jonathon C 2015-01-01T08:00:00Z application/pdf https://ro.uow.edu.au/eispapers/5284 https://ro.uow.edu.au/cgi/viewcontent.cgi?article=6312&context=eispapers unknown Research Online https://ro.uow.edu.au/eispapers/5284 https://ro.uow.edu.au/cgi/viewcontent.cgi?article=6312&context=eispapers Faculty of Engineering and Information Sciences - Papers: Part A Engineering Science and Technology Studies article 2015 ftunivwollongong 2020-02-25T11:25:01Z Combinations of various numerical models and datasets with diverse observation characteristics have been used to assess the mass evolution of ice sheets. As a consequence, a wide range of estimates have been produced using markedly different methodologies, data, approximation methods and model assumptions. Current attempts to reconcile these estimates using simple combination methods are unsatisfactory, as common sources of errors across different methodologies may not be accurately quantified (e.g. systematic biases in models). Here we provide a general approach which deals with this issue by considering all data sources simultaneously, and, crucially, by reducing the dependence on numerical models. The methodology is based on exploiting the different space-time characteristics of the relevant ice-sheet processes, and using statistical smoothing methods to establish the causes of the observed change. In omitting direct dependence on numerical models, the methodology provides a novel means for assessing glacio-isostatic adjustment and climate models alike, using remote-sensing datasets. This is particularly advantageous in Antarctica, where in situ measurements are difficult to obtain. We illustrate the methodology by using it to infer Antarctica's mass trend from 2003 to 2009 and produce surface mass-balance anomaly estimates to validate the RACMO2.1 regional climate model. Article in Journal/Newspaper Antarc* Antarctica Ice Sheet University of Wollongong, Australia: Research Online |
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Open Polar |
collection |
University of Wollongong, Australia: Research Online |
op_collection_id |
ftunivwollongong |
language |
unknown |
topic |
Engineering Science and Technology Studies |
spellingShingle |
Engineering Science and Technology Studies Zammit-Mangion, Andrew Bamber, Jonathan L Schoen, Nana W Rougier, Jonathon C A data-driven approach for assessing ice-sheet mass balance in space and time |
topic_facet |
Engineering Science and Technology Studies |
description |
Combinations of various numerical models and datasets with diverse observation characteristics have been used to assess the mass evolution of ice sheets. As a consequence, a wide range of estimates have been produced using markedly different methodologies, data, approximation methods and model assumptions. Current attempts to reconcile these estimates using simple combination methods are unsatisfactory, as common sources of errors across different methodologies may not be accurately quantified (e.g. systematic biases in models). Here we provide a general approach which deals with this issue by considering all data sources simultaneously, and, crucially, by reducing the dependence on numerical models. The methodology is based on exploiting the different space-time characteristics of the relevant ice-sheet processes, and using statistical smoothing methods to establish the causes of the observed change. In omitting direct dependence on numerical models, the methodology provides a novel means for assessing glacio-isostatic adjustment and climate models alike, using remote-sensing datasets. This is particularly advantageous in Antarctica, where in situ measurements are difficult to obtain. We illustrate the methodology by using it to infer Antarctica's mass trend from 2003 to 2009 and produce surface mass-balance anomaly estimates to validate the RACMO2.1 regional climate model. |
format |
Article in Journal/Newspaper |
author |
Zammit-Mangion, Andrew Bamber, Jonathan L Schoen, Nana W Rougier, Jonathon C |
author_facet |
Zammit-Mangion, Andrew Bamber, Jonathan L Schoen, Nana W Rougier, Jonathon C |
author_sort |
Zammit-Mangion, Andrew |
title |
A data-driven approach for assessing ice-sheet mass balance in space and time |
title_short |
A data-driven approach for assessing ice-sheet mass balance in space and time |
title_full |
A data-driven approach for assessing ice-sheet mass balance in space and time |
title_fullStr |
A data-driven approach for assessing ice-sheet mass balance in space and time |
title_full_unstemmed |
A data-driven approach for assessing ice-sheet mass balance in space and time |
title_sort |
data-driven approach for assessing ice-sheet mass balance in space and time |
publisher |
Research Online |
publishDate |
2015 |
url |
https://ro.uow.edu.au/eispapers/5284 https://ro.uow.edu.au/cgi/viewcontent.cgi?article=6312&context=eispapers |
genre |
Antarc* Antarctica Ice Sheet |
genre_facet |
Antarc* Antarctica Ice Sheet |
op_source |
Faculty of Engineering and Information Sciences - Papers: Part A |
op_relation |
https://ro.uow.edu.au/eispapers/5284 https://ro.uow.edu.au/cgi/viewcontent.cgi?article=6312&context=eispapers |
_version_ |
1766267049221292032 |