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| Titel |
Results from ITMIX – the Ice Thickness Models Intercomparison eXperiment |
| VerfasserIn |
Daniel Farinotti, ITMIX Consortium |
| Konferenz |
EGU General Assembly 2017
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 19 (2017) |
| Datensatznummer |
250141014
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| Publikation (Nr.) |
 EGU/EGU2017-4475.pdf |
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| Zusammenfassung |
| Knowledge about the ice thickness distribution of a given glacier or ice cap is essential for a
number of glaciological and hydrological applications. Yet, the ice thickness of the majority
of worlds’ ice masses remains poorly constrained. Recently, significant advances have been
made in numerical methods that infer glacier ice thickness from surface characteristics, and a
number of approaches have been proposed. A comprehensive assessment of their
performance, however, is missing to date.
Here, we present results from ITMIX – the Ice Thickness Models Intercomparison
eXperiment – which was the first coordinated effort to assess the relative strengths
and weaknesses of individual approaches. Operating in a working group of the
International Association of Cryospheric Sciences, we present results from a total of 17
different models, applied over 21 test cases including glaciers, ice caps, and synthetic
geometries.
We show that the results from individual approaches can differ largely, but that combining
them into an ensemble-estimate can yield significantly improvements. Comparison against
direct ice thickness measurements reveals that ensemble solution can achieve accuracies in
the order of 10 ± 24 % of the mean ice thickness. We additionally highlight how input-data
quality can affect the estimates, and argue that better accounting for input-data uncertainty
will be a key for an improved next generation of ice thickness estimation models. |
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