Aerosol size is a key parameter for evaluating the climate and environmental impacts of aerosols. However, when discrepancies arise between simulated and observed aerosol size-distribution parameters (e.g., number concentration, mean diameter, and standard deviation), it is often difficult to judge how critical those differences are. Here, we propose a practical recipe for evaluating 3-D aerosol models with size-resolved measurement data: the Pseudo-physical Variable Comparison (PPVC) method. PPVC compares physically meaningful variables (e.g., cloud condensation nuclei concentrations and light extinction coefficients) and processes (e.g., condensation rate and Brownian coagulation rate) that are derived from observed and simulated size distributions of aerosols, together with prescribed representative values of relevant parameters (e.g., hygroscopicity or refractive index), instead of comparing only size parameters. We applied PPVC to evaluate a regional-scale meteorology&ndash;chemistry model, NHM-Chem (versions v1.0 and v2.0), using scanning mobility particle sizer (SMPS) and aerodynamic particle sizer (APS) data measured in Tsukuba. The PPVC analysis showed that v2.0 improved the predictability of light extinction coefficients relative to v1.0. Using independent datasets, we also found that NHM-Chem v2.0 generally outperformed v1.0 not only for aerosol optical depth (AOD) but also for the predicted fine-mode fractions of inorganic species, owing to improvements in aerosol size distributions. We propose a new metric to evaluate the overall consistency of simulated aerosol physical parameters: the Distance of Deviations between simulated and observed Aerosol Physical Parameters (<em>DD</em>_AP). <em>DD</em>_AP for NHM-Chem v1.0 and v2.0 were 4.2 &times; 10^&minus;2 and 3.5 &times; 10^&minus;2, respectively, indicating that the microphysical properties and processes simulated by v2.0 were approximately 17% more consistent with observations than those of v1.0.