*2.3. Rain Type Classification*

Rain type classification was based on an ensemble classifier to predict stratiform versus convective rain based on cloud type, rain intensity, and the standard deviation of rain intensities calculated over the span of ten minutes.

To create a training set for the machine learning model that classifies rain type into convective and stratiform, we obtained records of cloud genera from the DWD [74]. These ground observations were available between July 2013 and August 2014 at Fürstenzell and between July 2013 and January 2014 at Regensburg.

A random forest classification model was trained on the available data from the two locations in this dataset. A combination of two criteria was used for the prior classification, the observation of cloud genus, and the values of R and its standard deviation over five minutes. The model was trained based on the intervals where the prior classification was feasible. It was then used to classify rain in the whole dataset. The spatial variability in rain properties might influence the quality of our classification scheme, especially that the model was trained in only two out of the ten sites. However, the drop in quality on this scale when training in one location and testing in another was minor [28]. More details about the classification procedure are given in Ghada et al [28].
