Revisiting glacier mass-balance sensitivity to surface air temperature using a data-driven regionalization
We are funded by the Chilean Science Council (ANID): FONDECYT Regular grant No1201429 and Anillo ACT210080. We also acknowledge all the open databases developed by the WGMS. This work is also a tribute to the hundreds of groups gathering, curating and sharing mass-balance and inventory data for more...
| Published in: | Journal of Glaciology |
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| Format: | Article in Journal/Newspaper |
| Language: | English |
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2024
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| Online Access: | https://hdl.handle.net/10533/78854 https://doi.org/10.1017/jog.2022.16 https://repositorio.ufro.cl/s/repositorio-ufro/item/7162 |
| Summary: | We are funded by the Chilean Science Council (ANID): FONDECYT Regular grant No1201429 and Anillo ACT210080. We also acknowledge all the open databases developed by the WGMS. This work is also a tribute to the hundreds of groups gathering, curating and sharing mass-balance and inventory data for more than a century. We are grateful to Mario Pino for early discussions on this work, Bryan Mark for last-minute revisions of the language style, and to the editors and reviewers. Contamos con financiamiento del Consejo Científico de Chile (ANID): FONDECYT Beca Regular No1201429 y Anillo ACT210080. También reconocemos todas las bases de datos abiertas desarrolladas por el WGMS. Este trabajo es también un tributo a los cientos de grupos que recopilan, curan y comparten datos de inventario y balance de masas durante más de un siglo. Agradecemos a Mario Pino por las primeras discusiones sobre este trabajo, a Bryan Mark por las revisiones de último momento del estilo del lenguaje, y a los editores y revisores. 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 similar to 20 years. Using this temporal ... |
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