Articles | Volume 15, issue 2
The Cryosphere, 15, 743–769, 2021
https://doi.org/10.5194/tc-15-743-2021
The Cryosphere, 15, 743–769, 2021
https://doi.org/10.5194/tc-15-743-2021

Research article 17 Feb 2021

Research article | 17 Feb 2021

Multi-scale snowdrift-permitting modelling of mountain snowpack

Vincent Vionnet et al.

Data sets

Time series of snow cover area products over the Kananaskis Country Simon Gascoin https://doi.org/10.5281/zenodo.3834623

Canadian Rockies Hydrological Observatory (CRHO) meteorological and snow observations GIWS (Global Institute for Water Security) http://giws.usask.ca/meta/

The Canadian Surface Prediction Archive (CaSPAr): A Platform to Enhance Environmental Modeling in Canada and Globally J. Mai, K. C. Kornelsen, B. A. Tolson, V. Fortin, N. Gasset, D. Bouhemhem, D. Schäfer, M. Leahy, F. Anctil, and P. Coulibaly https://doi.org/10.1175/BAMS-D-19-0143.1

Model code and software

The Canadian Hydrological Model (CHM) v1.0: a multi-scale, multi-extent, variable-complexity hydrological model – design and overview C. B. Marsh, J. W. Pomeroy, and H. S. Wheater https://doi.org/10.5194/gmd-13-225-2020

Multi-objective unstructured triangular mesh generation for use in hydrological and land surface models C. B. Marsh, R. J. Spiteri, J. W. Pomeroy, and H. S. Wheater https://doi.org/10.1016/j.cageo.2018.06.009

A comparison of three approaches for simulating fine-scale surface winds in support of wildland fire management. Part I. Model formulation and comparison against measurements J. M. Forthofer, B. W. Butler, and N. S. Wagenbrenner https://doi.org/10.1071/WF12089

Windmapper C. Marsh and V. Vionnet https://github.com/Chrismarsh/Windmapper

MAJA (MACCSATCOR Joint Algorithm) CNES (Centre National d’Études Spatiales) https://logiciels.cnes.fr/en/content/maja

Theia Snow collection: high-resolution operational snow cover maps from Sentinel-2 and Landsat-8 data S. Gascoin, M. Grizonnet, M. Bouchet, G. Salgues, and Hagolle, O. https://doi.org/10.5194/essd-11-493-2019

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Short summary
Mountain snow cover provides critical supplies of fresh water to downstream users. Its accurate prediction requires inclusion of often-ignored processes. A multi-scale modelling strategy is presented that efficiently accounts for snow redistribution. Model accuracy is assessed via airborne lidar and optical satellite imagery. With redistribution the model captures the elevation–snow depth relation. Redistribution processes are required to reproduce spatial variability, such as around ridges.