A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements
Understanding changes in glacier mass balances is essential for investigating climate changes. However, glacier-wide mass balances determined from geodetic observations do not provide a relevant climatic signal as they depend on the dynamic response of the glaciers. In situ point mass balance measur...
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ftird:oai:ird.fr:fdi:010074133 2024-09-15T18:07:52+00:00 A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements Vincent, C. Soruco, A. Azam, M. F. Basantes-Serrano, R. Jackson, M. Kjollmoen, B. Thibert, E. /Wagnon, Patrick Six, D. Rabatel, A. Ramanathan, A. Berthier, E. Cusicanqui, D. /Vincent, Pierre Mandal, A. FRANCE BOLIVIE INDE NORVEGE 2018 https://www.documentation.ird.fr/hor/fdi:010074133 EN eng https://www.documentation.ird.fr/hor/fdi:010074133 oai:ird.fr:fdi:010074133 Vincent C., Soruco A., Azam M. F., Basantes-Serrano R., Jackson M., Kjollmoen B., Thibert E., Wagnon Patrick, Six D., Rabatel A., Ramanathan A., Berthier E., Cusicanqui D., Vincent Pierre, Mandal A. A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements. 2018, 123 (9), p. 2228-2242 text 2018 ftird 2024-08-15T05:57:41Z Understanding changes in glacier mass balances is essential for investigating climate changes. However, glacier-wide mass balances determined from geodetic observations do not provide a relevant climatic signal as they depend on the dynamic response of the glaciers. In situ point mass balance measurements provide a direct signal but show a strong spatial variability that is difficult to assess from heterogeneous in situ measurements over several decades. To address this issue, we propose a nonlinear statistical model that takes into account the spatial and temporal changes in point mass balances. To test this model, we selected four glaciers in different climatic regimes (France, Bolivia, India, and Norway) for which detailed point annual mass balance measurements were available over a large elevation range. The model extracted a robust and consistent signal for each glacier. We obtained explained variances of 87.5, 90.2, 91.3, and 75.5% on Argentiere, Zongo, Chhota Shigri, and Nigardsbreen glaciers, respectively. The standard deviations of the model residuals are close to measurement uncertainties. The model can also be used to detect measurement errors. Combined with geodetic data, this method can provide a consistent glacier-wide annual mass balance series from a heterogeneous network. This model, available to the whole community, can be used to assess the impact of climate change in different regions of the world from long-term mass balance series. Text glacier IRD (Institute de recherche pour le développement): Horizon |
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IRD (Institute de recherche pour le développement): Horizon |
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ftird |
language |
English |
description |
Understanding changes in glacier mass balances is essential for investigating climate changes. However, glacier-wide mass balances determined from geodetic observations do not provide a relevant climatic signal as they depend on the dynamic response of the glaciers. In situ point mass balance measurements provide a direct signal but show a strong spatial variability that is difficult to assess from heterogeneous in situ measurements over several decades. To address this issue, we propose a nonlinear statistical model that takes into account the spatial and temporal changes in point mass balances. To test this model, we selected four glaciers in different climatic regimes (France, Bolivia, India, and Norway) for which detailed point annual mass balance measurements were available over a large elevation range. The model extracted a robust and consistent signal for each glacier. We obtained explained variances of 87.5, 90.2, 91.3, and 75.5% on Argentiere, Zongo, Chhota Shigri, and Nigardsbreen glaciers, respectively. The standard deviations of the model residuals are close to measurement uncertainties. The model can also be used to detect measurement errors. Combined with geodetic data, this method can provide a consistent glacier-wide annual mass balance series from a heterogeneous network. This model, available to the whole community, can be used to assess the impact of climate change in different regions of the world from long-term mass balance series. |
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Text |
author |
Vincent, C. Soruco, A. Azam, M. F. Basantes-Serrano, R. Jackson, M. Kjollmoen, B. Thibert, E. /Wagnon, Patrick Six, D. Rabatel, A. Ramanathan, A. Berthier, E. Cusicanqui, D. /Vincent, Pierre Mandal, A. |
spellingShingle |
Vincent, C. Soruco, A. Azam, M. F. Basantes-Serrano, R. Jackson, M. Kjollmoen, B. Thibert, E. /Wagnon, Patrick Six, D. Rabatel, A. Ramanathan, A. Berthier, E. Cusicanqui, D. /Vincent, Pierre Mandal, A. A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements |
author_facet |
Vincent, C. Soruco, A. Azam, M. F. Basantes-Serrano, R. Jackson, M. Kjollmoen, B. Thibert, E. /Wagnon, Patrick Six, D. Rabatel, A. Ramanathan, A. Berthier, E. Cusicanqui, D. /Vincent, Pierre Mandal, A. |
author_sort |
Vincent, C. |
title |
A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements |
title_short |
A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements |
title_full |
A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements |
title_fullStr |
A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements |
title_full_unstemmed |
A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements |
title_sort |
nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements |
publishDate |
2018 |
url |
https://www.documentation.ird.fr/hor/fdi:010074133 |
op_coverage |
FRANCE BOLIVIE INDE NORVEGE |
genre |
glacier |
genre_facet |
glacier |
op_relation |
https://www.documentation.ird.fr/hor/fdi:010074133 oai:ird.fr:fdi:010074133 Vincent C., Soruco A., Azam M. F., Basantes-Serrano R., Jackson M., Kjollmoen B., Thibert E., Wagnon Patrick, Six D., Rabatel A., Ramanathan A., Berthier E., Cusicanqui D., Vincent Pierre, Mandal A. A nonlinear statistical model for extracting a climatic signal from glacier mass balance measurements. 2018, 123 (9), p. 2228-2242 |
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1810445227736956928 |