Equilibrium dynamics of ice streams: A Bayesian statistical analysis

L. M. Berliner, N. Cressie, K. Jezek, Y. Kim, C. Q. Lam, C. J. Van Der Veen

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Studies of the behaviors of glaciers, ice sheets, and ice streams rely heavily on both observations and physical models. Data acquired via remote sensing provide critical information on geometry and movement of ice over large sections of Antarctica and Greenland. However, uncertainties are present in both the observations and the models. Hence, there is a need for combining these information sources in a fashion that incorporates uncertainty and quantifies its impact on conclusions. We present a hierarchical Bayesian approach to modeling ice-stream velocities incorporating physical models and observations regarding velocity, ice thickness, and surface elevation from the North East Ice Stream in Greenland. The Bayesian model leads to interesting issues in model assessment and computation.

Original languageEnglish
Pages (from-to)145-165
Number of pages21
JournalStatistical Methods and Applications
Volume17
Issue number2
DOIs
StatePublished - May 2008

Keywords

  • Hierarchical Bayesian analysis
  • Importance sampling
  • Markov chain Monte Carlo

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