Abstract
This dataset provides urban climate data collected from seven weather stations in Torino, Italy, spanning the years 2014 to 2023. The weather stations, operated by ARPA Piemonte, measure key meteorological variables, including air temperature, relative humidity, wind speed and direction, atmospheric pressure, and solar radiation. The data, initially in CSV format, were processed using Python to clean and merge the variables, computing missing parameters such as splitting global irradiation into its components and generating an hourly dataset for each year. Subsequently, a Typical Meteorological Year (TMY) was generated following the ISO 15927-4 standard. Missing data points were estimated using various interpolation and statistical methods to ensure data completeness. Finally, the data were converted into EnergyPlus Weather (EPW) format using custom Python scripts. This dataset serves as a crucial resource for urban climate studies and building energy simulations. It is especially valuable for assessing urban heat island (UHI) effects, supporting the generation of accurate weather files for simulation purposes, and enabling the refinement of design choices in urban planning. The data pipeline can be applied to other cities with weather stations and can also be used in future updates for Torino.