Inferring ice thickness from a glacier dynamics model and multiple surface data sets

Research output: Contribution to journalArticle

Abstract

The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major impact on future climate. For instance, ice sheet melt may contribute significantly to global sea-level rise. Understanding the current state of the WAIS is therefore of great interest. The WAIS is drained by fast-flowing glaciers, which are major contributors to ice loss. Hence, understanding the stability and dynamics of glaciers is critical for predicting the future of the ice sheet. Glacier dynamics are driven by the interplay between the topography, temperature, and basal conditions beneath the ice. A glacier dynamics model describes the interactions between these processes. We develop a hierarchical Bayesian model that integrates multiple ice-sheet surface data sets with a glacier dynamics model. Our approach allows us to (a) infer important parameters describing the glacier dynamics, (b) learn about ice sheet thickness, and (c) account for errors in the observations and the model. Because we have relatively dense and accurate ice thickness data from the Thwaites Glacier in West Antarctica, we use these data to validate the proposed approach. The long-term goal of this work is to have a general model that may be used to study multiple glaciers in the Antarctic.

Original languageEnglish (US)
Article numbere2460
JournalEnvironmetrics
Volume29
Issue number5-6
DOIs
StatePublished - Aug 1 2018

Fingerprint

glacier dynamics
ice thickness
ice sheet
Dynamic Model
glacier
ice
Hierarchical Bayesian Model
Antarctica
Topography
melt
topography
Climate
climate
Integrate

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Ecological Modeling

Cite this

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title = "Inferring ice thickness from a glacier dynamics model and multiple surface data sets",
abstract = "The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major impact on future climate. For instance, ice sheet melt may contribute significantly to global sea-level rise. Understanding the current state of the WAIS is therefore of great interest. The WAIS is drained by fast-flowing glaciers, which are major contributors to ice loss. Hence, understanding the stability and dynamics of glaciers is critical for predicting the future of the ice sheet. Glacier dynamics are driven by the interplay between the topography, temperature, and basal conditions beneath the ice. A glacier dynamics model describes the interactions between these processes. We develop a hierarchical Bayesian model that integrates multiple ice-sheet surface data sets with a glacier dynamics model. Our approach allows us to (a) infer important parameters describing the glacier dynamics, (b) learn about ice sheet thickness, and (c) account for errors in the observations and the model. Because we have relatively dense and accurate ice thickness data from the Thwaites Glacier in West Antarctica, we use these data to validate the proposed approach. The long-term goal of this work is to have a general model that may be used to study multiple glaciers in the Antarctic.",
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Inferring ice thickness from a glacier dynamics model and multiple surface data sets. / Guan, Yawen; Haran, Murali; Pollard, David.

In: Environmetrics, Vol. 29, No. 5-6, e2460, 01.08.2018.

Research output: Contribution to journalArticle

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