Articles | Volume 8, issue 12
https://doi.org/10.5194/gmd-8-3867-2015
https://doi.org/10.5194/gmd-8-3867-2015
Model description paper
 | 
08 Dec 2015
Model description paper |  | 08 Dec 2015

A factorial snowpack model (FSM 1.0)

R. Essery

Related authors

Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023,https://doi.org/10.5194/essd-15-5121-2023, 2023
Short summary
Evaluating Snow Microwave Radiative Transfer (SMRT) model emissivities with 89 to 243 GHz observations of Arctic tundra snow
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
The Cryosphere, 17, 4325–4341, https://doi.org/10.5194/tc-17-4325-2023,https://doi.org/10.5194/tc-17-4325-2023, 2023
Short summary
GEMS v1.0: Generalizable empirical model of snow accumulation and melt based on daily snow mass changes in response to climate and topographic drivers
Atabek Umirbekov, Richard Essery, and Daniel Müller
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-103,https://doi.org/10.5194/gmd-2023-103, 2023
Revised manuscript under review for GMD
Short summary
Simulating net ecosystem exchange under seasonal snow cover at an Arctic tundra site
Victoria R. Dutch, Nick Rutter, Leanne Wake, Oliver Sonnentag, Gabriel Hould Gosselin, Melody Sandells, Chris Derksen, Branden Walker, Gesa Meyer, Richard Essery, Richard Kelly, Phillip Marsh, Julia Boike, and Matteo Detto
EGUsphere, https://doi.org/10.5194/egusphere-2023-772,https://doi.org/10.5194/egusphere-2023-772, 2023
Short summary
Simulation of Arctic snow microwave emission in surface-sensitive atmosphere channels
Melody Sandells, Nick Rutter, Kirsty Wivell, Richard Essery, Stuart Fox, Chawn Harlow, Ghislain Picard, Alexandre Roy, Alain Royer, and Peter Toose
EGUsphere, https://doi.org/10.5194/egusphere-2023-696,https://doi.org/10.5194/egusphere-2023-696, 2023
Short summary

Related subject area

Cryosphere
A finite-element framework to explore the numerical solution of the coupled problem of heat conduction, water vapor diffusion, and settlement in dry snow (IvoriFEM v0.1.0)
Julien Brondex, Kévin Fourteau, Marie Dumont, Pascal Hagenmuller, Neige Calonne, François Tuzet, and Henning Löwe
Geosci. Model Dev., 16, 7075–7106, https://doi.org/10.5194/gmd-16-7075-2023,https://doi.org/10.5194/gmd-16-7075-2023, 2023
Short summary
AvaFrame com1DFA (v1.3): a thickness-integrated computational avalanche module – theory, numerics, and testing
Matthias Tonnel, Anna Wirbel, Felix Oesterle, and Jan-Thomas Fischer
Geosci. Model Dev., 16, 7013–7035, https://doi.org/10.5194/gmd-16-7013-2023,https://doi.org/10.5194/gmd-16-7013-2023, 2023
Short summary
Universal differential equations for glacier ice flow modelling
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
Geosci. Model Dev., 16, 6671–6687, https://doi.org/10.5194/gmd-16-6671-2023,https://doi.org/10.5194/gmd-16-6671-2023, 2023
Short summary
A new model for supraglacial hydrology evolution and drainage for the Greenland Ice Sheet (SHED v1.0)
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023,https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Modeling sensitivities of thermally and hydraulically driven ice stream surge cycling
Kevin Hank, Lev Tarasov, and Elisa Mantelli
Geosci. Model Dev., 16, 5627–5652, https://doi.org/10.5194/gmd-16-5627-2023,https://doi.org/10.5194/gmd-16-5627-2023, 2023
Short summary

Cited articles

Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning, Part I: Numerical model, Cold Reg. Sci. Technol., 35, 123–145, https://doi.org/10.1016/S0165-232X(02)00074-5, 2002.
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R .L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011.
Boone, A. and Etchevers, P.: An intercomparison of three snow schemes of varying complexity coupled to the same land surface model: Local-scale evaluation at an alpine site, J. Hydrometeorol., 2, 374–394, 2001.
Calonne, N., Geindreau, C., and Flin, F.: Macroscopic modeling for heat and water vapor transfer in dry snow by homogenization, J. Phys. Chem. B, 118, 13393–13403, https://doi.org/10.1021/jp5052535, 2014.
Download
Short summary
Models of snow on the ground need to represent processes of solar radiation absorption, heat conduction, liquid water movement and compaction in snow and transfers of heat from the atmosphere. There are many such models in use, but their wide range in complexity makes it hard to understand how differences in process representations determine differences in predictions. Processes in the factorial snow model can be switched on or off independently, allowing highly controlled numerical experiments.