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TC | Volume 12, issue 6
The Cryosphere, 12, 2123–2145, 2018
https://doi.org/10.5194/tc-12-2123-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
The Cryosphere, 12, 2123–2145, 2018
https://doi.org/10.5194/tc-12-2123-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 21 Jun 2018

Research article | 21 Jun 2018

Forcing the SURFEX/Crocus snow model with combined hourly meteorological forecasts and gridded observations in southern Norway

Hanneke Luijting et al.

Related subject area

Discipline: Snow | Subject: Energy Balance Obs/Modelling
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Cited articles

Barfod, E., Müller, K., Saloranta, T., Andersen, J., Orthe, N., Wartianien, A., Humstad, T., Myrabø, S., and Engeset, R.: The expert tool XGEO and its applications in the Norwegian Avalanche Forecasting Service, in: International Snow Science Workshop Grenoble, 7–11 October 2013, Chamonix Mont-Blanc, France, 2013. a
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, http://www.sciencedirect.com/science/article/pii/S0165232X02000745, 2002. a
Bellaire, S., Jamieson, J. B., and Fierz, C.: Forcing the snow-cover model SNOWPACK with forecasted weather data, The Cryosphere, 5, 1115–1125, https://doi.org/10.5194/tc-5-1115-2011, 2011. a, b
Bellaire, S., Jamieson, J. B., and Fierz, C.: Corrigendum to “Forcing the snow-cover model SNOWPACK with forecasted weather data” published in The Cryosphere, 5, 1115–1125, 2011, The Cryosphere, 7, 511–513, https://doi.org/10.5194/tc-7-511-2013, 2013. a, b
Bergstrøm, S.: Development and application of a conceptual runoff model for Scandinavian catchments, SMHI report RH07, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden, 1976. a
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Short summary
Knowledge of the snow reservoir is important for energy production and water resource management. In this study, a detailed snow model is run over southern Norway with two different sets of forcing data. The results show that forcing data consisting of post-processed data from a numerical weather model (observations assimilated into the raw weather predictions) are most promising for snow simulations when larger regions are evaluated.
Knowledge of the snow reservoir is important for energy production and water resource...
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