Abstract

AbstractSubglacial topography is an important feature in numerous ice-sheet analyses and can drive the routing of water at the bed. Bed topography is primarily measured with ice-penetrating radar. Significant gaps, however, remain in data coverage that require interpolation. Topographic interpolations are typically made with kriging, as well as with mass conservation, where ice flow dynamics are used to constrain bed geometry. However, these techniques generate bed topography that is unrealistically smooth at small scales, which biases subglacial water flowpath models and makes it difficult to rigorously quantify uncertainty in subglacial drainage patterns. To address this challenge, we adapt a geostatistical simulation method with probabilistic modeling to stochastically simulate bed topography such that the interpolated topography retains the spatial statistics of the ice-penetrating radar data. We use this method to simulate subglacial topography using mass conservation topography as a secondary constraint. We apply a water routing model to each of these realizations. Our results show that many of the flowpaths significantly change with each topographic realization, demonstrating that geostatistical simulation can be useful for assessing confidence in subglacial flowpaths.

Highlights

  • The accurate representation of subglacial bed topography is important for parameterizing numerous ice-sheet models and analyses

  • Bed topography is used for calculating ice thickness and determining sea level rise contributions from ice sheets and glaciers (Fretwell and others, 2013) and has been shown to play a significant role in determining ice-sheet stability (e.g., Gudmundsson and others, 2012; Parizek and others, 2013; Docquier and others, 2014; Koellner and others, 2019), but it remains a major source of uncertainty in ice-sheet projections (e.g., Seroussi and others, 2017)

  • We investigate the sensitivity of subglacial water flow to topography by generating a water routing model for the initial, unmodified mass conservation digital elevation models (DEMs) and each topographic realization

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Summary

Introduction

The accurate representation of subglacial bed topography is important for parameterizing numerous ice-sheet models and analyses. Flight profiles are typically spaced several or tens of kilometers apart, requiring interpolation (e.g., Fretwell and others, 2013). These digital elevation models (DEMs) are commonly constructed with spline or kriging interpolation (Lythe and Vaughan, 2001; Fretwell and others, 2013). Kriging is a geostatistical technique that estimates a value by computing the weighted average of nearby points (Cressie, 1990). Because of this averaging, kriging is unable to preserve the variance of the measurements, causing the interpolated topography to be smoother than the observations

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