Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework†
Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to...
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ftpubmed:oai:pubmedcentral.nih.gov:4253324 2023-05-15T13:57:15+02:00 Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework† Zammit-Mangion, Andrew Rougier, Jonathan Bamber, Jonathan Schön, Nana 2014-06 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4253324 https://doi.org/10.1002/env.2247 en eng BlackWell Publishing Ltd http://www.ncbi.nlm.nih.gov/pmc/articles/PMC http://dx.doi.org/10.1002/env.2247 Copyright © 2014 John Wiley & Sons, Ltd. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. CC-BY Special Issue Papers Text 2014 ftpubmed https://doi.org/10.1002/env.2247 2014-12-14T00:56:56Z Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd. Text Antarc* Antarctic PubMed Central (PMC) Antarctic The Antarctic Environmetrics 25 4 245 264 |
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Special Issue Papers Zammit-Mangion, Andrew Rougier, Jonathan Bamber, Jonathan Schön, Nana Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework† |
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Special Issue Papers |
description |
Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd. |
format |
Text |
author |
Zammit-Mangion, Andrew Rougier, Jonathan Bamber, Jonathan Schön, Nana |
author_facet |
Zammit-Mangion, Andrew Rougier, Jonathan Bamber, Jonathan Schön, Nana |
author_sort |
Zammit-Mangion, Andrew |
title |
Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework† |
title_short |
Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework† |
title_full |
Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework† |
title_fullStr |
Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework† |
title_full_unstemmed |
Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework† |
title_sort |
resolving the antarctic contribution to sea-level rise: a hierarchical modelling framework† |
publisher |
BlackWell Publishing Ltd |
publishDate |
2014 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4253324 https://doi.org/10.1002/env.2247 |
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Antarctic The Antarctic |
geographic_facet |
Antarctic The Antarctic |
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Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC http://dx.doi.org/10.1002/env.2247 |
op_rights |
Copyright © 2014 John Wiley & Sons, Ltd. http://creativecommons.org/licenses/by/3.0/ This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
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CC-BY |
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https://doi.org/10.1002/env.2247 |
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Environmetrics |
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25 |
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245 |
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264 |
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