Evaluation of ice-stream model sensitivities for parameter estimation

Richard B. Alley, Wenjie Li, Byron Richard Parizek, Fuqing Zhang

Research output: Contribution to journalArticle

Abstract

Large-ensemble perturbed-parameter forward ice-flow modeling can provide useful insights to uncertainties in inversions for basal drag or other ice-flow parameters. Inversion and data assimilation provide estimates of poorly known parameters that are essential for accurate prognostic modeling. Because ice flow depends on many such parameters with their associated uncertainties, which may interact in nonlinear ways, full uncertainty assessment for parameter estimates is challenging. With rising computational power, it is increasingly practicable to explore co-dependencies and sensitivities. Here, we use a well-characterized higher-order flowline model configured for a well-lubricated (“shelfy”) ice stream to run large ensembles, perturbing the magnitude and spatial pattern of basal drag, basal topography, and input flux. We find for steady state that ice-stream velocity and thickness along the entire domain are especially correlated to drag at the downstream end, but with greater local correlation during transients. The modeled effects of basal topographic perturbations on velocity and ice thickness are primarily local. Perturbations of input ice fluxes interact with the others in interesting ways. These insights point to the value of inversions informed by concentrated observations during forced transients such as lake-drainage events, accumulation-rate fluctuations or ice-shelf losses, and to the care needed when interpreting local results of some inversions for basal-drag parameters.

Original languageEnglish (US)
Pages (from-to)49-55
Number of pages7
JournalEarth and Planetary Science Letters
Volume516
DOIs
StatePublished - Jun 15 2019

Fingerprint

ice stream
Ice
Parameter estimation
ice
drag
evaluation
sensitivity
ice flow
Drag
inversions
perturbation
land ice
flow modeling
ice shelf
ice thickness
Fluxes
accumulation rate
data assimilation
assimilation
estimates

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Geochemistry and Petrology
  • Earth and Planetary Sciences (miscellaneous)
  • Space and Planetary Science

Cite this

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title = "Evaluation of ice-stream model sensitivities for parameter estimation",
abstract = "Large-ensemble perturbed-parameter forward ice-flow modeling can provide useful insights to uncertainties in inversions for basal drag or other ice-flow parameters. Inversion and data assimilation provide estimates of poorly known parameters that are essential for accurate prognostic modeling. Because ice flow depends on many such parameters with their associated uncertainties, which may interact in nonlinear ways, full uncertainty assessment for parameter estimates is challenging. With rising computational power, it is increasingly practicable to explore co-dependencies and sensitivities. Here, we use a well-characterized higher-order flowline model configured for a well-lubricated (“shelfy”) ice stream to run large ensembles, perturbing the magnitude and spatial pattern of basal drag, basal topography, and input flux. We find for steady state that ice-stream velocity and thickness along the entire domain are especially correlated to drag at the downstream end, but with greater local correlation during transients. The modeled effects of basal topographic perturbations on velocity and ice thickness are primarily local. Perturbations of input ice fluxes interact with the others in interesting ways. These insights point to the value of inversions informed by concentrated observations during forced transients such as lake-drainage events, accumulation-rate fluctuations or ice-shelf losses, and to the care needed when interpreting local results of some inversions for basal-drag parameters.",
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Evaluation of ice-stream model sensitivities for parameter estimation. / Alley, Richard B.; Li, Wenjie; Parizek, Byron Richard; Zhang, Fuqing.

In: Earth and Planetary Science Letters, Vol. 516, 15.06.2019, p. 49-55.

Research output: Contribution to journalArticle

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