Articles | Volume 16, issue 8
https://doi.org/10.5194/tc-16-3393-2022
https://doi.org/10.5194/tc-16-3393-2022
Research article
 | 
29 Aug 2022
Research article |  | 29 Aug 2022

Using snow depth observations to provide insight into the quality of snowpack simulations for regional-scale avalanche forecasting

Simon Horton and Pascal Haegeli

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Cited articles

Bellaire, S. and Jamieson, B.: Forecasting the formation of critical snow layers using a coupled snow cover and weather model, Cold Reg. Sci. Technol., 94, 37–44, https://doi.org/10.1016/j.coldregions.2013.06.007, 2013. 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
Bellaire, S., van Herwijnen, A., Mitterer, C., and Schweizer, J.: On forecasting wet-snow avalanche activity using simulated snow cover data, Cold Reg. Sci. Technol., 144, 28–38, https://doi.org/10.1016/j.coldregions.2017.09.013, 2017. a
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/S0022143000009552, 1992. a
Calonne, N., Richter, B., Löwe, H., Cetti, C., ter Schure, J., Van Herwijnen, A., Fierz, C., Jaggi, M., and Schneebeli, M.: The RHOSSA campaign: multi-resolution monitoring of the seasonal evolution of the structure and mechanical stability of an alpine snowpack, The Cryosphere, 14, 1829–1848, https://doi.org/10.5194/tc-14-1829-2020, 2020. a
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Short summary
Snowpack models can help avalanche forecasters but are difficult to verify. We present a method for evaluating the accuracy of simulated snow profiles using readily available observations of snow depth. This method could be easily applied to understand the representativeness of available observations, the agreement between modelled and observed snow depths, and the implications for interpreting avalanche conditions.