A Toolbox for Automated Foehn Classification based on Mixture Models¶

foehnix package provides a toolbox for automated probabilistic foehn wind classification based on two-component mixture models (foehn m**ix**ture models). foehnix models are a special case of the general flexible mixture model class ([1], [2], [3], [4]), an unsupervised statistical model to identify unobserveable clusters or components in data sets.

The application of mixture models for an automated classification of foehn winds has first been proposed by [5]. The “Community Foehn Classification Experiment” shows that the method performs similar compared to another semi-automatic classification, foehn experts, students, and weather enthusiasts (see [6])

Aim of this software package:

• provide easy-to-use functions for classification
• create probabilistic foehn classification
• easy scalability (can be applied to large data sets)
• reproducibility of the results
• create results which are comparable to other locations

git clone https://github.com/matthiasdusch/foehnix-python
cd foehnix-python
pip install -e .

Create classification¶

Once the observation data have been imported, one can start doing the classification. The foehnix package comes with two demo data sets, one for Southern California (USA) and one for Tyrol (A). The documentation provides a walk-through on how to start using foehnix:

• Demo for Ellbögen (Tyrol, A)
• Demo for Viejas (California, USA)