Articles | Volume 12, issue 6
https://doi.org/10.5194/tc-12-2123-2018
https://doi.org/10.5194/tc-12-2123-2018
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, Dagrun Vikhamar-Schuler, Trygve Aspelien, Åsmund Bakketun, and Mariken Homleid

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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.