How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment
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...
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Language: | English |
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Copernicus Publications
2017-04-01
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Series: | The Cryosphere |
Online Access: | http://www.the-cryosphere.net/11/949/2017/tc-11-949-2017.pdf |
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doaj-7b92c212db514fef88bb497f2d0997d7 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
D. Farinotti D. J. Brinkerhoff G. K. C. Clarke J. J. Fürst H. Frey P. Gantayat F. Gillet-Chaulet C. Girard M. Huss P. W. Leclercq A. Linsbauer H. Machguth C. Martin F. Maussion M. Morlighem C. Mosbeux A. Pandit A. Portmann A. Rabatel R. Ramsankaran T. J. Reerink O. Sanchez P. A. Stentoft S. Singh Kumari W. J. J. van Pelt B. Anderson T. Benham D. Binder J. A. Dowdeswell A. Fischer K. Helfricht S. Kutuzov I. Lavrentiev R. McNabb G. H. Gudmundsson H. Li L. M. Andreassen |
spellingShingle |
D. Farinotti D. J. Brinkerhoff G. K. C. Clarke J. J. Fürst H. Frey P. Gantayat F. Gillet-Chaulet C. Girard M. Huss P. W. Leclercq A. Linsbauer H. Machguth C. Martin F. Maussion M. Morlighem C. Mosbeux A. Pandit A. Portmann A. Rabatel R. Ramsankaran T. J. Reerink O. Sanchez P. A. Stentoft S. Singh Kumari W. J. J. van Pelt B. Anderson T. Benham D. Binder J. A. Dowdeswell A. Fischer K. Helfricht S. Kutuzov I. Lavrentiev R. McNabb G. H. Gudmundsson H. Li L. M. Andreassen How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment The Cryosphere |
author_facet |
D. Farinotti D. J. Brinkerhoff G. K. C. Clarke J. J. Fürst H. Frey P. Gantayat F. Gillet-Chaulet C. Girard M. Huss P. W. Leclercq A. Linsbauer H. Machguth C. Martin F. Maussion M. Morlighem C. Mosbeux A. Pandit A. Portmann A. Rabatel R. Ramsankaran T. J. Reerink O. Sanchez P. A. Stentoft S. Singh Kumari W. J. J. van Pelt B. Anderson T. Benham D. Binder J. A. Dowdeswell A. Fischer K. Helfricht S. Kutuzov I. Lavrentiev R. McNabb G. H. Gudmundsson H. Li L. M. Andreassen |
author_sort |
D. Farinotti |
title |
How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment |
title_short |
How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment |
title_full |
How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment |
title_fullStr |
How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment |
title_full_unstemmed |
How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperiment |
title_sort |
how accurate are estimates of glacier ice thickness? results from itmix, the ice thickness models intercomparison experiment |
publisher |
Copernicus Publications |
series |
The Cryosphere |
issn |
1994-0416 1994-0424 |
publishDate |
2017-04-01 |
description |
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 (1<i>σ</i> 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. |
url |
http://www.the-cryosphere.net/11/949/2017/tc-11-949-2017.pdf |
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doaj-7b92c212db514fef88bb497f2d0997d72020-11-24T21:33:42ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242017-04-0111294997010.5194/tc-11-949-2017How accurate are estimates of glacier ice thickness? Results from ITMIX, the Ice Thickness Models Intercomparison eXperimentD. Farinotti0D. J. Brinkerhoff1G. K. C. Clarke2J. J. Fürst3H. Frey4P. Gantayat5F. Gillet-Chaulet6C. Girard7M. Huss8P. W. Leclercq9A. Linsbauer10H. Machguth11C. Martin12F. Maussion13M. Morlighem14C. Mosbeux15A. Pandit16A. Portmann17A. Rabatel18R. Ramsankaran19T. J. Reerink20O. Sanchez21P. A. Stentoft22S. Singh Kumari23W. J. J. van Pelt24B. Anderson25T. Benham26D. Binder27J. A. Dowdeswell28A. Fischer29K. Helfricht30S. Kutuzov31I. Lavrentiev32R. McNabb33G. H. Gudmundsson34H. Li35L. M. Andreassen36Laboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, SwitzerlandGeophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USADepartment of Earth, Ocean and Atmospheric Sciences, University of British Columbia, Vancouver, BC, CanadaInstitute of Geography, Friedrich Alexander University of Erlangen-Nuremberg (FAU), Erlangen, GermanyDepartment of Geography, University of Zurich, Zurich, SwitzerlandDivecha Centre for Climate Change, Indian Institute of Science, Bangalore, IndiaInstitut des Géosciences de l'Environnement (IGE), Université Grenoble Alpes, CNRS, IRD, Grenoble, FranceDepartment of Earth System Science, University of California Irvine, Irvine, CA, USALaboratory of Hydraulics, Hydrology and Glaciology (VAW), ETH Zurich, Zurich, SwitzerlandDepartment of Geosciences, University of Oslo, Oslo, NorwayDepartment of Geography, University of Zurich, Zurich, SwitzerlandDepartment of Geography, University of Zurich, Zurich, SwitzerlandBritish Antarctic Survey, Natural Environment Research Council, Cambridge, UKInstitute of Atmospheric and Cryospheric Sciences, University of Innsbruck, Innsbruck, AustriaDepartment of Earth System Science, University of California Irvine, Irvine, CA, USAInstitut des Géosciences de l'Environnement (IGE), Université Grenoble Alpes, CNRS, IRD, Grenoble, FranceDepartment of Civil Engineering, Indian Institute of Technology, Bombay, IndiaSwiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf, SwitzerlandInstitut des Géosciences de l'Environnement (IGE), Université Grenoble Alpes, CNRS, IRD, Grenoble, FranceDepartment of Civil Engineering, Indian Institute of Technology, Bombay, IndiaInstitute for Marine and Atmospheric Research (IMAU), Utrecht University, Utrecht, the NetherlandsInstitut des Géosciences de l'Environnement (IGE), Université Grenoble Alpes, CNRS, IRD, Grenoble, FranceArctic Technology Centre ARTEK, Technical University of Denmark, Kongens Lyngby, DenmarkDepartment of Civil Engineering, Indian Institute of Technology, Bombay, IndiaDepartment of Earth Sciences, Uppsala University, Uppsala, SwedenAntarctic Research Centre, Victoria University of Wellington, Wellington, New ZealandScott Polar Research Institute, University of Cambridge, Cambridge, UKCentral Institute for Meteorology and Geodynamics (ZAMG), Vienna, AustriaScott Polar Research Institute, University of Cambridge, Cambridge, UKInstitute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Innsbruck, AustriaInstitute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Innsbruck, AustriaLaboratory of Glaciology, Institute of Geography, Russian Academy of Science, Moscow, RussiaLaboratory of Glaciology, Institute of Geography, Russian Academy of Science, Moscow, RussiaGeophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USABritish Antarctic Survey, Natural Environment Research Council, Cambridge, UKState Key Laboratory of Cryospheric Sciences, Tian Shan Glaciological Station, CAREERI, CAS, Lanzhou, ChinaNorwegian Water Resources and Energy Directorate (NVE), Oslo, NorwayKnowledge 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 (1<i>σ</i> 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.http://www.the-cryosphere.net/11/949/2017/tc-11-949-2017.pdf |