Innovative approach to enhancing the reliability of urban microclimate simulations

Global climate change has established a critical challenge for thermal comfort in urban public places. As urban areas expand and global temperature rises, the need for precise and reliable urban microclimate simulations becomes determinant. This research investigates innovative methodologies to improve the reliability of these simulations through a combination of temporal and spatial validation processes.

The objective is to enhance the accuracy and applicability of urban microclimate models, thereby facilitating better urban planning and design. To achieve this, the study integrates multiple data sources. First, on-site microclimate measurements are collected in Curitiba (Brazil) using high-resolution portable weather stations and fixed reference stations during 4-day periods in summer and winter. This approach ensures that a reliable dataset is available, capturing the variability in weather conditions and their impact on urban microclimates.

The use of portable weather stations allows for detailed and localized data collection along a street, park or any urban area, while fixed stations provide a stable reference point for long-term monitoring. Second, the development and simulation of Computational Fluid Dynamics (CFD) model is conducted using the ENVI-met software. ENVI-met is a widely used tool for simulating the microclimatic conditions in urban environments. It allows for the detailed modeling of interactions between buildings, vegetation, and atmospheric conditions.

Third, comprehensive evaluation using statistical metrics is performed for both temporal and spatial validation of the urban microclimate simulation model. Temporal validation involves comparing measured data at fixed points against simulated data over time to ensure consistency and accuracy. While spatial validation involves assessing the accuracy of multiple spatial points across the urban area. The findings reveal that temporal validation shows robust alignment between measured and simulated data, with minimal error margins.

However, spatial validation indicates discrepancies in areas with complex urban geometries, suggesting a need for localized model adjustments. Through the integration of advanced measurement techniques, sophisticated modeling tools, and rigorous validation processes, this research contributes to the development of more accurate and practical urban microclimate models for diverse urban settings.