Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2)
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 cha...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:84655e55520d42acb0c23ce3615c0c642021-11-08T09:25:40ZResults from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2)2296-646310.3389/feart.2020.571923https://doaj.org/article/84655e55520d42acb0c23ce3615c0c642021-01-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/feart.2020.571923/fullhttps://doaj.org/toc/2296-6463Knowing 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.Daniel FarinottiDaniel FarinottiDouglas J. BrinkerhoffJohannes J. FürstPrateek GantayatFabien Gillet-ChauletMatthias HussMatthias HussMatthias HussPaul W. LeclercqHansruedi MaurerMathieu MorlighemAnkur PanditAnkur PanditAntoine RabatelRAAJ RamsankaranThomas J. ReerinkEllen RoboEllen RoboEmmanuel RougesEmmanuel RougesErik TamreWard J. J. van PeltMauro A. WerderMauro A. WerderMohod Farooq AzamHuilin LiLiss M. AndreassenFrontiers Media S.A.articleglaciersice capsice thicknessmodelingintercomparisonScienceQENFrontiers in Earth Science, Vol 8 (2021) |
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glaciers ice caps ice thickness modeling intercomparison Science Q |
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glaciers ice caps ice thickness modeling intercomparison Science Q Daniel Farinotti Daniel Farinotti Douglas J. Brinkerhoff Johannes J. Fürst Prateek Gantayat Fabien Gillet-Chaulet Matthias Huss Matthias Huss Matthias Huss Paul W. Leclercq Hansruedi Maurer Mathieu Morlighem Ankur Pandit Ankur Pandit Antoine Rabatel RAAJ Ramsankaran Thomas J. Reerink Ellen Robo Ellen Robo Emmanuel Rouges Emmanuel Rouges Erik Tamre Ward J. J. van Pelt Mauro A. Werder Mauro A. Werder Mohod Farooq Azam Huilin Li Liss M. Andreassen Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2) |
| description |
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. |
| format |
article |
| author |
Daniel Farinotti Daniel Farinotti Douglas J. Brinkerhoff Johannes J. Fürst Prateek Gantayat Fabien Gillet-Chaulet Matthias Huss Matthias Huss Matthias Huss Paul W. Leclercq Hansruedi Maurer Mathieu Morlighem Ankur Pandit Ankur Pandit Antoine Rabatel RAAJ Ramsankaran Thomas J. Reerink Ellen Robo Ellen Robo Emmanuel Rouges Emmanuel Rouges Erik Tamre Ward J. J. van Pelt Mauro A. Werder Mauro A. Werder Mohod Farooq Azam Huilin Li Liss M. Andreassen |
| author_facet |
Daniel Farinotti Daniel Farinotti Douglas J. Brinkerhoff Johannes J. Fürst Prateek Gantayat Fabien Gillet-Chaulet Matthias Huss Matthias Huss Matthias Huss Paul W. Leclercq Hansruedi Maurer Mathieu Morlighem Ankur Pandit Ankur Pandit Antoine Rabatel RAAJ Ramsankaran Thomas J. Reerink Ellen Robo Ellen Robo Emmanuel Rouges Emmanuel Rouges Erik Tamre Ward J. J. van Pelt Mauro A. Werder Mauro A. Werder Mohod Farooq Azam Huilin Li Liss M. Andreassen |
| author_sort |
Daniel Farinotti |
| title |
Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2) |
| title_short |
Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2) |
| title_full |
Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2) |
| title_fullStr |
Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2) |
| title_full_unstemmed |
Results from the Ice Thickness Models Intercomparison eXperiment Phase 2 (ITMIX2) |
| title_sort |
results from the ice thickness models intercomparison experiment phase 2 (itmix2) |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/84655e55520d42acb0c23ce3615c0c64 |
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