Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework

Andrew Zammit Mangion, Jonathan C Rougier, Jonathan L Bamber, Nana W Schoen

Research output: Contribution to journalArticle (Academic Journal)peer-review

17 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)245-264
Number of pages20
Issue number4
Publication statusPublished - 30 Oct 2013


  • spatial statistics
  • stochastic partial differential equations
  • remote sensing
  • source separation
  • sea-level rise


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