Physically consistent mesoscale model evaluation in complex terrain

Abstract This study introduces a novel evaluation technique for mesoscale atmospheric models in complex terrain, addressing challenges related to grid‐point (GP) selection, model resolution, and differences in terrain and measurement heights between model and observation sites. The technique includes a pre‐evaluation step designed to enhance model evaluation accuracy by correcting for systematic biases arising from discrepancies in sensor height between surface‐layer diagnosed variables and actual measurement heights. Additionally, a lapse‐rate correction is proposed that takes into account the temporal evolution of the valley atmosphere. We select a physically consistent GP (PCGP) for the evaluation with point measurements that represents the topographic and land‐cover characteristics at the measurement site better than the nearest GP (NGP). A case study is conducted for a synoptically undisturbed valley wind day over the Inn Valley using a Weather Research and Forecasting (WRF) simulation with different grid spacings. Results show that the selection of the GP for model evaluation from the NGP and its surrounding eight GPs can have an impact on model performance similar to changing the model resolution. The proposed method shows significant potential in reducing uncertainties in the assessment of model performance, particularly for coarser domains, where a large variability occurs due to the heterogeneity of surface characteristics. While the PCGP does not show consistently better statistical agreement with observations than the NGP, it enables a physically meaningful comparison by ensuring that model terrain and land‐cover characteristics match those at the observation site. The determination of the PCGP is, however, restricted by the availability of land‐use information at the measurement sites.