Abstract

Abstract. Knowledge of the ice thickness distribution of glaciers and ice caps is an important prerequisite for many glaciological and hydrological investigations. A wealth of approaches has recently been presented for inferring ice thickness from characteristics of the surface. With the Ice Thickness Models Intercomparison eXperiment (ITMIX) we performed the first coordinated assessment quantifying individual model performance. A set of 17 different models showed that individual ice thickness estimates can differ considerably – locally by a spread comparable to the observed thickness. Averaging the results of multiple models, however, significantly improved the results: on average over the 21 considered test cases, comparison against direct ice thickness measurements revealed deviations on the order of 10 ± 24 % of the mean ice thickness (1σ estimate). Models relying on multiple data sets – such as surface ice velocity fields, surface mass balance, or rates of ice thickness change – showed high sensitivity to input data quality. Together with the requirement of being able to handle large regions in an automated fashion, the capacity of better accounting for uncertainties in the input data will be a key for an improved next generation of ice thickness estimation approaches.

Highlights

  • The ice thickness distribution of a glacier, ice cap, or ice sheet is a fundamental parameter for many glaciological applications

  • It determines the total volume of the ice body, which is crucial to quantify water availability or sea-level change, and provides the link between surface and subglacial topography, which is a prerequisite for ice flow modelling studies

  • 189 different solutions were submitted to Intercomparison eXperiment (ITMIX) (Table 2)

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Summary

Introduction

The ice thickness distribution of a glacier, ice cap, or ice sheet is a fundamental parameter for many glaciological applications. Chen and Ohmura, 1990; Bahr et al, 1997), partially including other characteristics such as glacier length or surface slope (e.g. Lüthi, 2009; Radicand Hock, 2011; Grinsted, 2013) Such approaches, yield estimates of the mean ice thickness and total volume of a glacier only. Approaches that take into account mass conservation and ice flow dynamics go back to Budd and Allison (1975) and Rasmussen (1988), whose ideas were further developed by Fastook et al (1995) and Farinotti et al (2009) The latter approach was successively extended by Huss and Farinotti (2012), who presented the first globally complete estimate for the ice thickness distribution of individual glaciers. Oping a new generation of improved ice thickness estimation approaches

Experimental set-up
Considered test cases and data
Participating models
Brinkerhoff
Minimization approaches
Mass conserving approaches
Shear-stress-based approaches
Velocity-based approaches
Other approaches
Results and discussion
Between-model comparison
Comparison to ice thickness measurements
Individual model performance
GCneuralnet
Conclusions
VanPeltLeclercq 10
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