Articles | Volume 14, issue 1
Geosci. Model Dev., 14, 239–258, 2021
https://doi.org/10.5194/gmd-14-239-2021
Geosci. Model Dev., 14, 239–258, 2021
https://doi.org/10.5194/gmd-14-239-2021

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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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Florian Herla on behalf of the Authors (28 Oct 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (02 Nov 2020) by Fabien Maussion
RR by Matthieu Lafaysse (12 Nov 2020)
ED: Publish as is (16 Nov 2020) by Fabien Maussion
AR by Florian Herla on behalf of the Authors (26 Nov 2020)  Author's response    Manuscript
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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.