An upper-bound estimate for the accuracy of glacier volume–area scaling
Volume–area scaling is the most popular method for estimating the ice volume of large glacier samples. Here, a series of resampling experiments based on different sets of synthetic data is presented in order to derive an upper-bound estimate (i.e. a level achieved only within ideal conditions) for i...
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Copernicus Publications
2013
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Online Access: | https://doi.org/10.5194/tc-7-1707-2013 http://www.the-cryosphere.net/7/1707/2013/tc-7-1707-2013.pdf https://doaj.org/article/e80cc7bbf2d54106bdf7d19a83bbd1d7 |
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fttriple:oai:gotriple.eu:oai:doaj.org/article:e80cc7bbf2d54106bdf7d19a83bbd1d7 2023-05-15T18:32:20+02:00 An upper-bound estimate for the accuracy of glacier volume–area scaling D. Farinotti M. Huss 2013-11-01 https://doi.org/10.5194/tc-7-1707-2013 http://www.the-cryosphere.net/7/1707/2013/tc-7-1707-2013.pdf https://doaj.org/article/e80cc7bbf2d54106bdf7d19a83bbd1d7 en eng Copernicus Publications 1994-0416 1994-0424 doi:10.5194/tc-7-1707-2013 http://www.the-cryosphere.net/7/1707/2013/tc-7-1707-2013.pdf https://doaj.org/article/e80cc7bbf2d54106bdf7d19a83bbd1d7 undefined The Cryosphere, Vol 7, Iss 6, Pp 1707-1720 (2013) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2013 fttriple https://doi.org/10.5194/tc-7-1707-2013 2023-01-22T19:30:42Z Volume–area scaling is the most popular method for estimating the ice volume of large glacier samples. Here, a series of resampling experiments based on different sets of synthetic data is presented in order to derive an upper-bound estimate (i.e. a level achieved only within ideal conditions) for its accuracy. For real-world applications, a lower accuracy has to be expected. We also quantify the maximum accuracy expected when scaling is used for determining the glacier volume change, and area change of a given glacier population. A comprehensive set of measured glacier areas, volumes, area and volume changes is evaluated to investigate the impact of real-world data quality on the so-assessed accuracies. For populations larger than a few thousand glaciers, the total ice volume can be recovered within 30% if all data currently available worldwide are used for estimating the scaling parameters. Assuming no systematic bias in ice volume measurements, their uncertainty is of secondary importance. Knowing the individual areas of a glacier sample for two points in time allows recovering the corresponding ice volume change within 40% for populations larger than a few hundred glaciers, both for steady-state and transient geometries. If ice volume changes can be estimated without bias, glacier area changes derived from volume–area scaling show similar uncertainties to those of the volume changes. This paper does not aim at making a final judgement on the suitability of volume–area scaling as such, but provides the means for assessing the accuracy expected from its application. Article in Journal/Newspaper The Cryosphere Unknown The Cryosphere 7 6 1707 1720 |
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English |
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geo envir D. Farinotti M. Huss An upper-bound estimate for the accuracy of glacier volume–area scaling |
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geo envir |
description |
Volume–area scaling is the most popular method for estimating the ice volume of large glacier samples. Here, a series of resampling experiments based on different sets of synthetic data is presented in order to derive an upper-bound estimate (i.e. a level achieved only within ideal conditions) for its accuracy. For real-world applications, a lower accuracy has to be expected. We also quantify the maximum accuracy expected when scaling is used for determining the glacier volume change, and area change of a given glacier population. A comprehensive set of measured glacier areas, volumes, area and volume changes is evaluated to investigate the impact of real-world data quality on the so-assessed accuracies. For populations larger than a few thousand glaciers, the total ice volume can be recovered within 30% if all data currently available worldwide are used for estimating the scaling parameters. Assuming no systematic bias in ice volume measurements, their uncertainty is of secondary importance. Knowing the individual areas of a glacier sample for two points in time allows recovering the corresponding ice volume change within 40% for populations larger than a few hundred glaciers, both for steady-state and transient geometries. If ice volume changes can be estimated without bias, glacier area changes derived from volume–area scaling show similar uncertainties to those of the volume changes. This paper does not aim at making a final judgement on the suitability of volume–area scaling as such, but provides the means for assessing the accuracy expected from its application. |
format |
Article in Journal/Newspaper |
author |
D. Farinotti M. Huss |
author_facet |
D. Farinotti M. Huss |
author_sort |
D. Farinotti |
title |
An upper-bound estimate for the accuracy of glacier volume–area scaling |
title_short |
An upper-bound estimate for the accuracy of glacier volume–area scaling |
title_full |
An upper-bound estimate for the accuracy of glacier volume–area scaling |
title_fullStr |
An upper-bound estimate for the accuracy of glacier volume–area scaling |
title_full_unstemmed |
An upper-bound estimate for the accuracy of glacier volume–area scaling |
title_sort |
upper-bound estimate for the accuracy of glacier volume–area scaling |
publisher |
Copernicus Publications |
publishDate |
2013 |
url |
https://doi.org/10.5194/tc-7-1707-2013 http://www.the-cryosphere.net/7/1707/2013/tc-7-1707-2013.pdf https://doaj.org/article/e80cc7bbf2d54106bdf7d19a83bbd1d7 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 7, Iss 6, Pp 1707-1720 (2013) |
op_relation |
1994-0416 1994-0424 doi:10.5194/tc-7-1707-2013 http://www.the-cryosphere.net/7/1707/2013/tc-7-1707-2013.pdf https://doaj.org/article/e80cc7bbf2d54106bdf7d19a83bbd1d7 |
op_rights |
undefined |
op_doi |
https://doi.org/10.5194/tc-7-1707-2013 |
container_title |
The Cryosphere |
container_volume |
7 |
container_issue |
6 |
container_start_page |
1707 |
op_container_end_page |
1720 |
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1766216448416415744 |