Articles | Volume 14, issue 1
Geosci. Model Dev., 14, 239–258, 2021
Geosci. Model Dev., 14, 239–258, 2021
Methods for assessment of models
15 Jan 2021
Methods for assessment of models | 15 Jan 2021

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting

Florian Herla et al.

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Cited articles

Bartelt, P., Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part I: Numerical model, Cold Reg. Sci. Technol., 35, 123–145,, 2002. a
Bellaire, S. and Jamieson, J. B.: On estimating avalanche danger from simulated snow profiles, in: Proceedings of the International Snow Science Workshop, Grenoble–Chamonix Mont-Blanc, 7–11, 2013a. a
Bellaire, S. and Jamieson, J. B.: Forecasting the formation of critical snow layers using a coupled snow cover and weather model, Cold Reg. Sci. Technol., 94, 37–44,, 2013b. a
Bellaire, S., Jamieson, J. B., and Fierz, C.: Forcing the snow-cover model SNOWPACK with forecasted weather data, The Cryosphere, 5, 1115–1125,, 2011. a
Berndt, D. J. and Clifford, J.: Using dynamic time warping to find patterns in time series, in: KDD workshop, Seattle, WA, 10, 359–370, 1994. a
Short summary
The adoption of snowpack models in support of avalanche forecasting has been limited. To promote their operational application, we present a numerical method for processing multivariate snow stratigraphy profiles of mixed data types. Our algorithm enables applications like dynamical grouping and summarizing of model simulations, model evaluation, and data assimilation. By emulating the human analysis process, our approach will allow forecasters to familiarly interact with snowpack simulations.