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

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

doi:https://doi.org/10.5194/tc-12-2229-2018

Articles | Volume 12, issue 7

https://doi.org/10.5194/tc-12-2229-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-12-2229-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 12, issue 7

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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Final revised paper (published on 11 Jul 2018)
Supplement to the final revised paper
Preprint (discussion started on 15 Mar 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Peer review of "A Bayesian Hierarchical Model for Glacial Dynamics Based on the Shallow Ice Approximation and its Evaluation Using Analytical Solutions" by Gopalan et al.', Lambert Caron, 17 Apr 2018
RC2: 'Review of A Bayesian Hierarchical Model for Glacial Dynamics Based on the Shallow Ice Approximation and its Evaluation Using Analytical Solutions by Giri Gopalan, Birgir Hrafnkelsson, Guðfinna Aðalgeirsdóttir, Alexander H. Jarosch, and Finnur Pálsson', Anonymous Referee #2, 06 Jun 2018
AC1: 'Author Response', Giri Gopalan, 20 Jun 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Anna Wenzel on behalf of the Authors (21 Jun 2018) Author's response

ED: Publish as is (23 Jun 2018) by Eric Larour

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.