Evaluation of precipitation forecasts by polarimetric radar

Over the last years, weather services have developed a new generation of high resolution mesoscale numerical weather prediction (NWP) models with the aim to explicitly predict convection. New methods are required to validate the representation of precipitation processes in these NWP models against observations. Polarimetric radar systems are especially suited for model validation as they provide information on the intensity and the microphysical characteristics of a precipitation event at a high temporal and spatial resolution. However, the observations can not be directly employed for model evaluation as polarimetric radar systems do not explicitly measure the parameters represented in microphysical parameterization schemes. In order to establish a relationship and allow for a direct comparison between the model parameters and the observations, the polarimetric radar forward operator SynPolRad (Synthetic Polarimetric Radar) has been developed. SynPolRad simulates synthetic polarimetric radar quantities out of model forecasts which permits an evaluation in terms of observed quantities. In a first step, the synthetic reflectivity, LDR, and ZDR are computed from predicted bulk water quantities and in a second step, the beam propagation in the model domain is simulated under consideration of refractivity and attenuation effects. In order to successfully employ SynPolRad for model evaluation purposes, the link between the forward operator and the mesoscale model has to conform as closely as possible to the model assumptions. However, in the case of a polarimetric radar forward operator not all the input parameters are defined by the model. Within this work, these free parameters are derived on theoretical terms accordingly to the model assumptions such that the polarimetric quantities match the thresholds of a hydrometeor classification scheme. Furthermore, special care is given to the representation of brightband signatures. The application of SynPolRad on two case studies proves the potential of the new method. A stratiform and a convective case study are chosen to assess the ability of mesoscale models to represent precipitation in different dynamical regimes. LMK (Lokal-Modell-Kürzestfrist) and MesoNH (Mesoscale Non-Hydrostatic Model) simulations considering different microphysical parameterization schemes are evaluated. The evaluation concentrates on the representation of life cycle, intensity, and the spatial distribution of synthetic reflectivity, LDR, and ZDR. Furthermore, hydrometeor types derived from the observed and synthetic polarimetric quantities employing a classification scheme are compared. Large discrepancies are found between the model simulations and the observations. However, the consideration of an additional ice hydrometeor category in the 3 component scheme significantly improves the performance of the LMK