Evaluating the predictive performance of human avalanche forecasts and model predictions in Switzerland

DOI

This data set was used in the analysis by Techel et al. Forecasting avalanche danger: human-made forecasts vs. fully automated model-driven predictions, submitted to Natural Hazards Earth System Sciences on 20 Aug 2024. The repository contains data from two avalanche forecasting seasons (2022/2023, 2023/2024) in Switzerland.

Interpolated predictions - The .zip file contains the interpolated predictions for the three models in nowcast- and forecast- mode. This data is needed to reproduce the figures and tables in the submitted preprint.

The other data are the raw data underlying the interpolations: - Avalanche forecast by WSL Institute for Snow and Avalanche Research SLF, published at 17.00 local time, valid for the following 24 hours and relating to dry snow avalanche conditions. - Model predictions in nowcast- and forecast-mode for three models (danger level, instability, natural avalanche), valid for 12.00 local time - Subset of points extracted from GPS tracks (courtesy of Skitourenguru GmbH) - Avalanche observations - natural avalanches and human-triggered avalanches - Estimates of the snowline - Randomly chosen subset of grid points used for generating reference distributions

For details regarding the data sets refer to the publication.

Identifier
DOI https://doi.org/10.16904/envidat.535
Metadata Access https://www.envidat.ch/api/action/package_show?id=f821b651-245a-47b6-95d4-64c5497b8b21
Provenance
Publisher EnviDat
Publication Year 2024
Funding Reference WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland,
Rights cc-by-sa; Creative Commons Attribution Share-Alike (CC-BY-SA)
OpenAccess true
Contact envidat(at)wsl.ch
Representation
Resource Type Dataset
Discipline Environmental Sciences
Spatial Coverage (5.956W, 45.818S, 10.492E, 47.808N)
Temporal Coverage Begin 2022-11-01T00:00:00Z
Temporal Coverage End 2024-04-30T00:00:00Z