Morphology-based classification and error-controlled reduction of urban weather files with Torino as a case study

Urban morphology creates intra-urban thermal variability that a single airport EnergyPlus Weather (EPW) file cannot represent. This study develops a reproducible GIS-to-Urban Weather Generator (UWG) framework for Torino, Italy, separating morphological classification from weather-product reduction. A preliminary building-seeded cell method was audited before adopting 100 m assignment cells characterised through overlapping 500 × 500 m neighbourhood supports. Support-size (250–1000 m) and 50 m grid-shift sensitivities were tested. Building fraction, area-weighted height, facade-to-site ratio, tree cover, and grass cover were extracted for 12,997 locations; 10,593 quality-screened supports were classified using robust scaling and CLARA-style k-medoids. Seven morphology classes balanced interpretability and spatial coherence, although four ranked best statistically, and classification robustness was moderate. Under a common UWG template, four representative EPWs were retained by curve inspection and minimax selection, with a 0.10°C maximum-error screen and a diminishing-return criterion. Maximum medoid hourly dry-bulb RMSE was 0.06°C with the delivered one-decimal EPWs and 0.04°C at diagnostic three-decimal serialisation. Across 105 stratified non-medoid supports, weighted mean and 95th-percentile RMSE were 0.05 and 0.10°C, but a 1.33°C industrial-tail error required a conservative post hoc restriction, not a validated applicability boundary. Synchronised processed 2022 station comparisons improved annual RMSE relative to Caselle only at Consolata. Humidity limitations preclude interpreting temperature fidelity as complete EPW validation. The atlas links coordinates to morphology classes, UWG configurations, and candidate EPWs. The restricted library distinguishes simulator-conditional reduction fidelity from observational accuracy.