Articles | Volume 18, issue 12
https://doi.org/10.5194/gmd-18-3583-2025
https://doi.org/10.5194/gmd-18-3583-2025
Model description paper
 | 
18 Jun 2025
Model description paper |  | 18 Jun 2025

A Flexible Snow Model (FSM 2.1.1) including a forest canopy

Richard Essery, Giulia Mazzotti, Sarah Barr, Tobias Jonas, Tristan Quaife, and Nick Rutter

Related authors

Simulating snow properties and Ku-band backscatter across the forest-tundra ecotone
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Julien Meloche, Benoit Montpetit, Nicolas R. Leroux, Richard Essery, Gabriel Hould Gosselin, and Philip Marsh
EGUsphere, https://doi.org/10.5194/egusphere-2025-1498,https://doi.org/10.5194/egusphere-2025-1498, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Multi-physics ensemble modelling of Arctic tundra snowpack properties
Georgina J. Woolley, Nick Rutter, Leanne Wake, Vincent Vionnet, Chris Derksen, Richard Essery, Philip Marsh, Rosamond Tutton, Branden Walker, Matthieu Lafaysse, and David Pritchard
The Cryosphere, 18, 5685–5711, https://doi.org/10.5194/tc-18-5685-2024,https://doi.org/10.5194/tc-18-5685-2024, 2024
Short summary
Exploring the decision-making process in model development: focus on the Arctic snowpack
Cecile B. Menard, Sirpa Rasmus, Ioanna Merkouriadi, Gianpaolo Balsamo, Annett Bartsch, Chris Derksen, Florent Domine, Marie Dumont, Dorothee Ehrich, Richard Essery, Bruce C. Forbes, Gerhard Krinner, David Lawrence, Glen Liston, Heidrun Matthes, Nick Rutter, Melody Sandells, Martin Schneebeli, and Sari Stark
The Cryosphere, 18, 4671–4686, https://doi.org/10.5194/tc-18-4671-2024,https://doi.org/10.5194/tc-18-4671-2024, 2024
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
The Cryosphere, 18, 3971–3990, https://doi.org/10.5194/tc-18-3971-2024,https://doi.org/10.5194/tc-18-3971-2024, 2024
Short summary
Altimetric Ku-band Radar Observations of Snow on Sea Ice Simulated with SMRT
Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Richard Essery, Ghislain Picard, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Jérôme Bouffard, Alessandro Di Bella, and Michele Scagliola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1583,https://doi.org/10.5194/egusphere-2024-1583, 2024
Preprint archived
Short summary

Related subject area

Cryosphere
Computationally efficient subglacial drainage modelling using Gaussian process emulators: GlaDS-GP v1.0
Tim Hill, Derek Bingham, Gwenn E. Flowers, and Matthew J. Hoffman
Geosci. Model Dev., 18, 4045–4074, https://doi.org/10.5194/gmd-18-4045-2025,https://doi.org/10.5194/gmd-18-4045-2025, 2025
Short summary
Anisotropic metric-based mesh adaptation for ice flow modelling in Firedrake
Davor Dundovic, Joseph G. Wallwork, Stephan C. Kramer, Fabien Gillet-Chaulet, Regine Hock, and Matthew D. Piggott
Geosci. Model Dev., 18, 4023–4044, https://doi.org/10.5194/gmd-18-4023-2025,https://doi.org/10.5194/gmd-18-4023-2025, 2025
Short summary
Description and validation of the ice-sheet model Nix v1.0
Daniel Moreno-Parada, Alexander Robinson, Marisa Montoya, and Jorge Alvarez-Solas
Geosci. Model Dev., 18, 3895–3919, https://doi.org/10.5194/gmd-18-3895-2025,https://doi.org/10.5194/gmd-18-3895-2025, 2025
Short summary
The Utrecht Finite Volume Ice-Sheet Model (UFEMISM) version 2.0 – Part 1: Description and idealised experiments
Constantijn J. Berends, Victor Azizi, Jorge A. Bernales, and Roderik S. W. van de Wal
Geosci. Model Dev., 18, 3635–3659, https://doi.org/10.5194/gmd-18-3635-2025,https://doi.org/10.5194/gmd-18-3635-2025, 2025
Short summary
CMIP6 models overestimate sea ice melt, growth and conduction relative to ice mass balance buoy estimates
Alex E. West and Edward W. Blockley
Geosci. Model Dev., 18, 3041–3064, https://doi.org/10.5194/gmd-18-3041-2025,https://doi.org/10.5194/gmd-18-3041-2025, 2025
Short summary

Cited articles

Alonso-González, E., López-Moreno, J. I., Gascoin, S., García-Valdecasas Ojeda, M., Sanmiguel-Vallelado, A., Navarro-Serrano, F., Revuelto, J., Ceballos, A., Esteban-Parra, M. J., and Essery, R.: Daily gridded datasets of snow depth and snow water equivalent for the Iberian Peninsula from 1980 to 2014, Earth Syst. Sci. Data, 10, 303–315, https://doi.org/10.5194/essd-10-303-2018, 2018. a
Alonso-González, E., Aalstad, K., Baba, M. W., Revuelto, J., López-Moreno, J. I., Fiddes, J., Essery, R., and Gascoin, S.: The Multiple Snow Data Assimilation System (MuSA v1.0), Geosci. Model Dev., 15, 9127–9155, https://doi.org/10.5194/gmd-15-9127-2022, 2022. a, b
Bartlett, P. A. and Verseghy, D. L.: Modified treatment of intercepted snow improves the simulated forest albedo in the Canadian Land Surface Scheme, Hydrol. Process., 29, 3208–3226, https://doi.org/10.1002/hyp.10431, 2015. a, b
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. a
Blyth, E. M., Harding, R. J., and Essery, R.: A coupled dual source GCM SVAT, Hydrol. Earth Syst. Sci., 3, 71–84, https://doi.org/10.5194/hess-3-71-1999, 1999. a, b
Download
Short summary
How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.
Share