Establishing a Reliable Model Base for Urban Climate Simulations: Data Requirements and Methodological Insights

This study investigates the challenges and requirements of modeling urban climate using two computational tools: ENVI-met and Ansys Fluent. The primary objective was to explore the necessary input data for constructing reliable simulations, including detailed descriptions of construction materials, stratification of surface and building layers, urban geometries, and boundary conditions that reflect real-world environmental settings. The process of assembling such a model base required systematic decisions about the level of detail, data sources, and parameter consistency across platforms. The importance of this research lies in demonstrating that the accuracy and applicability of urban climate models depend less on the computational tool itself than on the quality and structure of the underlying data. Establishing a consistent, well-structured model base is essential for generating reliable outputs that can inform sustainable design and planning strategies in urban contexts. Beyond its relevance to urban climate research, this work also contributes to broader discussions in applied computational modeling, where data collection, organization, and abstraction serve as the critical bridge between theoretical frameworks and practical applications. The study thus resonates with ongoing interdisciplinary efforts to advance simulation methodologies at the intersection of informatics, environmental analysis, and intelligent systems.