A direct comparison of hydrometeor types (HMT) from state-of-the-art hydrometeor classification schemes (HMC) with modelled hydrometeors (ICOL-LAM, operational weather predictions model of the German Weather Service) is challenging, e.g. due to different HMT definitions and numbers and difficulties to identify dominant types in mixtures of hydrometeors. A comparison of published HMCs even revealed significant differences between the membership functions used for the same hydrometeor types (Figure 1), emphasizing again the high uncertainty in scattering simulations for ice hydrometeors because of their complex geometries, dielectric properties, and largely unknown size and orientation distributions. The HMCs were applied to perturbed polarimetric variables observed by the X-band Radar in Bonn (BoXPol) to test their robustness against measurement errors and show that especially in the regions with solid precipitation misclassification in hydrometeor typing occurs often. Thus, a dual strategy to evaluate the hydrometeor type representation in ICON-LAM is presented: i) Classification after clustering of the data is assumed to reduce the sensitivity of the decision to the uncertainty of scattering simulations. First an agglomerative hierarchical clustering of the radar pixels based on their similarity in multi-dimensional polarimetric signatures is applied, and afterwards for each identified cluster a comparison of the distributions of polarimetric moments with scattering simulations or membership functions for different HMT is performed. ii) A direct comparison of multivariate simulated and observed distributions of polarimetric moments. These comparisons will be performed for different heights and/or space-time subsets, and for clusters with similar HMT in the model and the observations as identified with the advanced radar-based hydrometeor classification scheme. Results for a set of case studies observed with the polarimetric X-band radar composite in Bonn, Germany, will be presented.