Urban climate simulation model to support climate-sensitive planning decision making at local scale

Abstract

Urban planning, through design and land use allocation, affects urban climate dynamics and patterns at different atmospheric layers and spatial scales. Climate sensitive planning and design draws attention to the consideration of climate parameters for decision making. Seeking to contribute to the above, this research set out to identify the effect of urban design features (e.g., vegetation cover and construction density) on air temperature behavior. We conducted a case study, selected the Renca municipality located north-west Santiago, Chile, which represents a Mediterranean urban area affected by an intense daytime and nighttime urban heat island (UHI). We developed simple linear regression models to estimate air temperature per block in four different present and future scenarios: summer and winter and for day (16:00) and night (23:00). The urban-environmental variables were evaluated with the air temperature data series, measured in 21 points in the commune which were representative of urban and natural local climatic zones (LCZ). The results were evaluated and validated. We observed that variables such as vegetation, surface temperature or relative humidity are important explanatory factors for air temperature at the block scale in Renca across all four models. Models represent a tool that allows the evaluation of different design and urban planning alternatives at the scale of a city block, providing useful information for climate-sensitive decision-making.