235 Such a dependence leads to the situation that the training dataset used for developing the machine learning model does not cover the product of the supports of the respective marginal distributions, but only a subset of it. Meteorological normalization, however, evaluates this model on the product of supports of these marginal distributions -and hence for inputs for which the machine learning model was not trained. This extrapolation setting, which we investigated in Section 3.3, was already discussed as being critical in . A similar extrapolation setting appears when meteorological 240 normalization is used for forecasting (cf. Section 3.2). We thus agree with ; and call for caution when using meteorological normalization (if it must be used at all).