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Wind, Sun, Surface Temperature, and Heat Island: Critical Variables for High-Resolution Outdoor Thermal Comfort

As interest in comfortable outdoor spaces grows, the demand to simulate, map, and understand these microclimates has also grown. However, such mapping rarely occurs in practice, as it requires the modelling of several complex factors: wind, sun, surface temperature, and urban heat island. At present, it is clear that a workflow to map outdoor comfort cannot include all of these factors without requiring months to compute. Accordingly, this study attempts to simulate the most accurate map of outdoor thermal comfort currently possible for a 3-block urban setting in Singapore. Next, the contributing factors are systematically removed to deduce the minimum needed to create a sufficiently accurate map. Findings indicate that, on average, the comfort conditions reported on meteorological weather networks are ~2.4oC different from a given microclimate within the urban test site. The diversity of direct sun and sky heat exchange can account for a little over a third of this discrepancy. Wind patterns similarly account for a significant fraction of this difference but results suggest that a small number wind simulations are needed to appropriately account for such patterns. Surface temperatures and heat island effect each account for a smaller ~0.5oC difference. Strategies for generating faster microclimate maps are discussed and recommendations for meteorological reporting methods are proposed.