Establishing influence of morphological aspects on microclimatic conditions through GIS-assisted mathematical modeling and field observations

Abstract

Local climate in an area is significantly affected by the extent of urbanization. The microclimatic parameters such as wind speed (W), relative humidity (RH) and temperature (T) are affected due to modifications in natural surfaces and land use. With increasing interest in urban microclimate research, factors such as energy conversation, environmental sustainability, and urban design with thermal comfort are researched extensively. The current study attempts to model T, W and RH in an urban landscape of Nagpur City by solving the microclimate governing equations using python and ArcGIS. Numeral field measurements are carried out during summer and winter seasons for validation of modeled data. The results show a statistically positive and significant correlation between modeled and monitored data (p < 0.001 at CI 95%) for T and RH with R2 ranging from 92.5–97.7% and 82.2–88.7%, respectively. However, the model underpredicts T by an average of 4–7% in winter and summer, respectively, while RH is overpredicted by an average of 2% overall. W shows moderate correlation between modeled and monitored data with an average variation of 0.02–0.1 m/s for two seasons. Holistically, the modeled data are significantly correlated with ground data, and variations between surface points are captured well by the model, indicating that python and ArcGIS can be used for the measurement of microclimate parameters, forming the basis of sustainable urban design. Evaluating the urban microclimate parameters for both greenfield and brownfield projects can assist the landscape designers, planners to effectively control the temperature and wind conditions and improve the outdoor thermal conditions in an urban area.