Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya
Approximate glacier models are routinely used to compute the future evolution of mountain glaciers under any given climate-change scenario. A majority of these models are based on statistical scaling relations between glacier volume, area, and/or length. In this paper, long-term predictions from sca...
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fttriple:oai:gotriple.eu:oai:doaj.org/article:9d2b50d271a44ca8834a124862c39e5a 2023-05-15T18:32:18+02:00 Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya A. Banerjee D. Patil A. Jadhav 2020-09-01 https://doi.org/10.5194/tc-14-3235-2020 https://tc.copernicus.org/articles/14/3235/2020/tc-14-3235-2020.pdf https://doaj.org/article/9d2b50d271a44ca8834a124862c39e5a en eng Copernicus Publications doi:10.5194/tc-14-3235-2020 1994-0416 1994-0424 https://tc.copernicus.org/articles/14/3235/2020/tc-14-3235-2020.pdf https://doaj.org/article/9d2b50d271a44ca8834a124862c39e5a undefined The Cryosphere, Vol 14, Pp 3235-3247 (2020) geo envir Journal Article https://vocabularies.coar-repositories.org/resource_types/c_6501/ 2020 fttriple https://doi.org/10.5194/tc-14-3235-2020 2023-01-22T17:32:58Z Approximate glacier models are routinely used to compute the future evolution of mountain glaciers under any given climate-change scenario. A majority of these models are based on statistical scaling relations between glacier volume, area, and/or length. In this paper, long-term predictions from scaling-based models are compared with those from a two-dimensional shallow-ice approximation (SIA) model. We derive expressions for climate sensitivity and response time of glaciers assuming a time-independent volume–area scaling. These expressions are validated using a scaling-model simulation of the response of 703 synthetic glaciers from the central Himalaya to a step change in climate. The same experiment repeated with the SIA model yields about 2 times larger climate sensitivity and response time than those predicted by the scaling model. In addition, the SIA model obtains area response time that is about 1.5 times larger than the corresponding volume response time, whereas scaling models implicitly assume the two response times to be equal to each other. These results indicate the possibility of a low bias in the scaling model estimates of the long-term loss of glacier area and volume. The SIA model outputs are used to obtain parameterisations, climate sensitivity, and response time of glaciers as functions of ablation rate near the terminus, mass-balance gradient, and mean thickness. Using a linear-response model based on these parameterisations, we find that the linear-response model outperforms the scaling model in reproducing the glacier response simulated by the SIA model. This linear-response model may be useful for predicting the evolution of mountain glaciers on a global scale. Article in Journal/Newspaper The Cryosphere Unknown The Cryosphere 14 9 3235 3247 |
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geo envir A. Banerjee D. Patil A. Jadhav Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya |
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description |
Approximate glacier models are routinely used to compute the future evolution of mountain glaciers under any given climate-change scenario. A majority of these models are based on statistical scaling relations between glacier volume, area, and/or length. In this paper, long-term predictions from scaling-based models are compared with those from a two-dimensional shallow-ice approximation (SIA) model. We derive expressions for climate sensitivity and response time of glaciers assuming a time-independent volume–area scaling. These expressions are validated using a scaling-model simulation of the response of 703 synthetic glaciers from the central Himalaya to a step change in climate. The same experiment repeated with the SIA model yields about 2 times larger climate sensitivity and response time than those predicted by the scaling model. In addition, the SIA model obtains area response time that is about 1.5 times larger than the corresponding volume response time, whereas scaling models implicitly assume the two response times to be equal to each other. These results indicate the possibility of a low bias in the scaling model estimates of the long-term loss of glacier area and volume. The SIA model outputs are used to obtain parameterisations, climate sensitivity, and response time of glaciers as functions of ablation rate near the terminus, mass-balance gradient, and mean thickness. Using a linear-response model based on these parameterisations, we find that the linear-response model outperforms the scaling model in reproducing the glacier response simulated by the SIA model. This linear-response model may be useful for predicting the evolution of mountain glaciers on a global scale. |
format |
Article in Journal/Newspaper |
author |
A. Banerjee D. Patil A. Jadhav |
author_facet |
A. Banerjee D. Patil A. Jadhav |
author_sort |
A. Banerjee |
title |
Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya |
title_short |
Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya |
title_full |
Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya |
title_fullStr |
Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya |
title_full_unstemmed |
Possible biases in scaling-based estimates of glacier change: a case study in the Himalaya |
title_sort |
possible biases in scaling-based estimates of glacier change: a case study in the himalaya |
publisher |
Copernicus Publications |
publishDate |
2020 |
url |
https://doi.org/10.5194/tc-14-3235-2020 https://tc.copernicus.org/articles/14/3235/2020/tc-14-3235-2020.pdf https://doaj.org/article/9d2b50d271a44ca8834a124862c39e5a |
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The Cryosphere |
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The Cryosphere |
op_source |
The Cryosphere, Vol 14, Pp 3235-3247 (2020) |
op_relation |
doi:10.5194/tc-14-3235-2020 1994-0416 1994-0424 https://tc.copernicus.org/articles/14/3235/2020/tc-14-3235-2020.pdf https://doaj.org/article/9d2b50d271a44ca8834a124862c39e5a |
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op_doi |
https://doi.org/10.5194/tc-14-3235-2020 |
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The Cryosphere |
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14 |
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9 |
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3235 |
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3247 |
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