Articles | Volume 12, issue 7
https://doi.org/10.5194/tc-12-2229-2018
https://doi.org/10.5194/tc-12-2229-2018
Research article
 | 
11 Jul 2018
Research article |  | 11 Jul 2018

A Bayesian hierarchical model for glacial dynamics based on the shallow ice approximation and its evaluation using analytical solutions

Giri Gopalan, Birgir Hrafnkelsson, Guðfinna Aðalgeirsdóttir, Alexander H. Jarosch, and Finnur Pálsson

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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Giri Gopalan on behalf of the Authors (20 Jun 2018)  Manuscript 
ED: Publish as is (23 Jun 2018) by Eric Larour
AR by Giri Gopalan on behalf of the Authors (27 Jun 2018)  Manuscript 
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Short summary
Geophysical systems can often contain scientific parameters whose values are uncertain, complex underlying dynamics, and field measurements with errors. These components are naturally modeled together within what is known as a Bayesian hierarchical model (BHM). This paper constructs such a model for shallow glaciers based on an approximation of the underlying dynamics. The evaluation of this model is aided by the use of exact analytical solutions from the literature.