Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization

This study involves examination of glaciological mass-balance time series, glacier and climatic descriptors, the application of machine learning methods for glaciological clustering, and computation of mass-balance time series based upon the clustering and statistical analyses relative to gridded ai...

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Main Authors: Alfonso Fernández, Marcelo Somos-Valenzuela
Format: Article
Language:English
Published: Cambridge University Press 2022-12-01
Series:Journal of Glaciology
Subjects:
Online Access:https://www.cambridge.org/core/product/identifier/S0022143022000168/type/journal_article
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author Alfonso Fernández
Marcelo Somos-Valenzuela
author_facet Alfonso Fernández
Marcelo Somos-Valenzuela
author_sort Alfonso Fernández
collection DOAJ
description This study involves examination of glaciological mass-balance time series, glacier and climatic descriptors, the application of machine learning methods for glaciological clustering, and computation of mass-balance time series based upon the clustering and statistical analyses relative to gridded air temperature datasets. Our analysis revealed an increasingly coherent mass-balance trend but a latitudinal bias of monitoring programs. The glacier classification scheme delivered three clusters, suggesting these correspond to climate-based first-order regimes, as glacier morphometric characteristics weighed little in our multivariate analysis. We combined all available surface mass-balance data from in situ monitoring programs to study temperature sensitivity for each cluster. These aggregated mass-balance time series delivered spatially different statistical relationships to temperature. Results also showed that surface mass balance tends to have a temporal self-correlation of ~20 years. Using this temporal window to analyze sensitivity since ~ 1950, we found that in all cases temperature sensitivity, while generally negative, tended to fluctuate through time, with the largest absolute magnitudes occurring in the 1980s and becoming less negative in recent years, revealing that glacier sensitivity is non-stationary. These findings point to a scenario of a coherent signal of change no matter the glacier regime. This work provides new insights into glacier–climate relationships that can guide observational and analytical strategies.
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spelling doaj.art-f74a4e03d85747a7b411df345255f8bf2023-03-09T12:41:19ZengCambridge University PressJournal of Glaciology0022-14301727-56522022-12-01681041106010.1017/jog.2022.16Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalizationAlfonso Fernández0https://orcid.org/0000-0001-6825-0426Marcelo Somos-Valenzuela1Department of Geography, Mountain Geoscience Group, Universidad de Concepción, Concepción, ChileDepartment of Forestry Sciences, Butamallin Research Center for Global Change, Universidad de La Frontera, Temuco, ChileThis study involves examination of glaciological mass-balance time series, glacier and climatic descriptors, the application of machine learning methods for glaciological clustering, and computation of mass-balance time series based upon the clustering and statistical analyses relative to gridded air temperature datasets. Our analysis revealed an increasingly coherent mass-balance trend but a latitudinal bias of monitoring programs. The glacier classification scheme delivered three clusters, suggesting these correspond to climate-based first-order regimes, as glacier morphometric characteristics weighed little in our multivariate analysis. We combined all available surface mass-balance data from in situ monitoring programs to study temperature sensitivity for each cluster. These aggregated mass-balance time series delivered spatially different statistical relationships to temperature. Results also showed that surface mass balance tends to have a temporal self-correlation of ~20 years. Using this temporal window to analyze sensitivity since ~ 1950, we found that in all cases temperature sensitivity, while generally negative, tended to fluctuate through time, with the largest absolute magnitudes occurring in the 1980s and becoming less negative in recent years, revealing that glacier sensitivity is non-stationary. These findings point to a scenario of a coherent signal of change no matter the glacier regime. This work provides new insights into glacier–climate relationships that can guide observational and analytical strategies.https://www.cambridge.org/core/product/identifier/S0022143022000168/type/journal_articleClimate changeglacier mass balanceice and climate
spellingShingle Alfonso Fernández
Marcelo Somos-Valenzuela
Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization
Journal of Glaciology
Climate change
glacier mass balance
ice and climate
title Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization
title_full Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization
title_fullStr Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization
title_full_unstemmed Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization
title_short Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization
title_sort revisiting glacier mass balance sensitivity to surface air temperature using a data driven regionalization
topic Climate change
glacier mass balance
ice and climate
url https://www.cambridge.org/core/product/identifier/S0022143022000168/type/journal_article
work_keys_str_mv AT alfonsofernandez revisitingglaciermassbalancesensitivitytosurfaceairtemperatureusingadatadrivenregionalization
AT marcelosomosvalenzuela revisitingglaciermassbalancesensitivitytosurfaceairtemperatureusingadatadrivenregionalization