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Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2)

Farinotti, Daniel (författare)
Swiss Fed Inst Technol, Lab Hydraul Hydrol & Glaciol VAW, Zurich, Switzerland; Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland
Brinkerhoff, Douglas J. (författare)
Univ Montana, Dept Comp Sci, Missoula, MT 59812 USA
Fuerst, Johannes J. (författare)
‎ Friedrich Alexander Univ Erlangen Nuremberg FAU, Inst Geog, Erlangen, Germany
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Gantayat, Prateek (författare)
Indian Inst Sci, Divecha Ctr Climate Change, Bangalore, Karnataka, India
Gillet-Chaulet, Fabien (författare)
Univ Grenoble Alpes, CNRS, IRD, Inst Geosci Environm IGE,UMR 5001, Grenoble, France
Huss, Matthias (författare)
Swiss Fed Inst Technol, Lab Hydraul Hydrol & Glaciol VAW, Zurich, Switzerland; Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland; Univ Fribourg, Dept Geosci, Fribourg, Switzerland
Leclercq, Paul W. (författare)
Univ Oslo, Dept Geosci, Oslo, Norway
Maurer, Hansruedi (författare)
Swiss Fed Inst Technol, Inst Geophys, Zurich, Switzerland
Morlighem, Mathieu (författare)
Univ Calif Irvine, Dept Earth Syst Sci, Irvine, CA USA
Pandit, Ankur (författare)
Indian Inst Technol, Interdisciplinary Programme IDP Climate Studies, Mumbai, Maharashtra, India; Tata Consultancy Serv TCS Res & Innovat, Thana, India
Rabatel, Antoine (författare)
Univ Grenoble Alpes, CNRS, IRD, Inst Geosci Environm IGE,UMR 5001, Grenoble, France
Ramsankaran, R. A. A. J. (författare)
Indian Inst Technol, Dept Civil Engn, Mumbai, Maharashtra, India
Reerink, Thomas J. (författare)
Royal Netherlands Meteorol Inst KNMI, De Bilt, Netherlands
Robo, Ellen (författare)
CALTECH, Pasadena, CA 91125 USA
Rouges, Emmanuel (författare)
Swiss Fed Inst Technol, Lab Hydraul Hydrol & Glaciol VAW, Zurich, Switzerland; Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland; European Ctr Medium Range Weather Forecasts, Reading, Berks, England
Tamre, Erik (författare)
MIT, Dept Earth Atmospher & Planetary Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA
van Pelt, Ward J. J. (författare)
Uppsala universitet,Luft-, vatten- och landskapslära
Werder, Mauro A. (författare)
Swiss Fed Inst Technol, Lab Hydraul Hydrol & Glaciol VAW, Zurich, Switzerland; Swiss Fed Inst Forest Snow & Landscape Res WSL, Birmensdorf, Switzerland
Azam, Mohod Farooq (författare)
Indian Inst Technol Indore, Discipline Civil Engn, Simrol, India
Li, Huilin (författare)
Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Cryospher Sci, Tian Shan Glaciol Stn, Lanzhou, Peoples R China
Andreassen, Liss M. (författare)
Norwegian Water Resources & Energy Directorate NV, Oslo, Norway
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 (creator_code:org_t)
2021-01-21
2021
Engelska.
Ingår i: Frontiers in Earth Science. - : Frontiers Media S.A.. - 2296-6463. ; 8
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Knowing the ice thickness distribution of a glacier is of fundamental importance for a number of applications, ranging from the planning of glaciological fieldwork to the assessments of future sea-level change. Across spatial scales, however, this knowledge is limited by the paucity and discrete character of available thickness observations. To obtain a spatially coherent distribution of the glacier ice thickness, interpolation or numerical models have to be used. Whilst the first phase of the Ice Thickness Models Intercomparison eXperiment (ITMIX) focused on approaches that estimate such spatial information from characteristics of the glacier surface alone, ITMIX2 sought insights for the capability of the models to extract information from a limited number of thickness observations. The analyses were designed around 23 test cases comprising both real-world and synthetic glaciers, with each test case comprising a set of 16 different experiments mimicking possible scenarios of data availability. A total of 13 models participated in the experiments. The results show that the inter-model variability in the calculated local thickness is high, and that for unmeasured locations, deviations of 16% of the mean glacier thickness are typical (median estimate, three-quarters of the deviations within 37% of the mean glacier thickness). This notwithstanding, limited sets of ice thickness observations are shown to be effective in constraining the mean glacier thickness, demonstrating the value of even partial surveys. Whilst the results are only weakly affected by the spatial distribution of the observations, surveys that preferentially sample the lowest glacier elevations are found to cause a systematic underestimation of the thickness in several models. Conversely, a preferential sampling of the thickest glacier parts proves effective in reducing the deviations. The response to the availability of ice thickness observations is characteristic to each approach and varies across models. On average across models, the deviation between modeled and observed thickness increase by 8.5% of the mean ice thickness every time the distance to the closest observation increases by a factor of 10. No single best model emerges from the analyses, confirming the added value of using model ensembles.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Naturgeografi (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Physical Geography (hsv//eng)

Nyckelord

glaciers
ice caps
ice thickness
intercomparison
modeling

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