Articles | Volume 18, issue 11
https://doi.org/10.5194/tc-18-5383-2024
https://doi.org/10.5194/tc-18-5383-2024
Research article
 | 
21 Nov 2024
Research article |  | 21 Nov 2024

Unravelling the sources of uncertainty in glacier runoff projections in the Patagonian Andes (40–56° S)

Rodrigo Aguayo, Fabien Maussion, Lilian Schuster, Marius Schaefer, Alexis Caro, Patrick Schmitt, Jonathan Mackay, Lizz Ultee, Jorge Leon-Muñoz, and Mauricio Aguayo

Data sets

Glacier runoff projections and their multiple sources of uncertainty in the Patagonian Andes (40-56°S) Rodrigo Aguayo et al. https://doi.org/10.5281/zenodo.11353065

Randolph Glacier Inventory - A Dataset of Global Glacier Outlines RGI Consortium https://doi.org/10.7265/4m1f-gd79

Randolph Glacier Inventory - A Dataset of Global Glacier Outlines RGI Consortium https://doi.org/10.5067/F6JMOVY5NAVZ

NASADEM Merged DEM Global 1 arc second V001 NASA JPL https://doi.org/10.5067/MEaSUREs/NASADEM/NASADEM_HGT.001

Global mapping of surface ice flow velocity and ice thickness of glaciers around the world from Millan et al. (2022) Romain Millan et al. https://doi.org/10.6096/1007

A consensus estimate for the ice thickness distribution of all glaciers on Earth - dataset Daniel Farinotti https://doi.org/10.3929/ethz-b-000315707

PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia (v1.0) Rodrigo Aguayo et al. https://doi.org/10.5281/zenodo.7992761

CR2MET: A high-resolution precipitation and temperature dataset for the period 1960-2021 in continental Chile Juan P. Boisier https://doi.org/10.5281/zenodo.7529682

ERA5 monthly averaged data on single levels from 1940 to present H. Hersbach et al. https://doi.org/10.24381/cds.f17050d7

Model code and software

rodaguayo/Glacier_Uncertainties: v1.0.1 (v1.0.1) Rodrigo Aguayo https://doi.org/10.5281/zenodo.14177951

intake/intake-esm: v2023.11.10 Anderson Banihirwe et al. https://doi.org/10.5281/zenodo.10103723

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Short summary
Predicting how much water will come from glaciers in the future is a complex task, and there are many factors that make it uncertain. Using a glacier model, we explored 1920 scenarios for each glacier in the Patagonian Andes. We found that the choice of the historical climate data was the most important factor, while other factors such as different data sources, climate models and emission scenarios played a smaller role.