Bridging Local Knowledge and Microclimate Modeling: A Co-Produced Approach to Assess Heat Exposure Across Citizen Activity Patterns and Adaptation Strategies

As urban overheating intensifies under climate change, cities are urgently seeking strategies to reduce heat-related risks. While fixed weather stations provide regional data, they often fail to capture the localized heat exposure in daily urban life. In this study, we adopt a co-production approach to assess real-world heat exposure among urban residents in Suwon, a highly urbanized city in South Korea, with the aim of informing the selection of effective adaptation strategies.First, we integrate transportation big data with citizen participation to identify key activity patterns such as commuting and leisure walking. Next, we use the SOLWEIG micro-climate model to simulate Mean Radiant Temperature (MRT) across diverse urban settings. We propose two cumulative heat exposure indicators: time spent above a temperature threshold and total temperature accumulation. These metrics are then used to compare model outputs with in situ data collected through low-cost sensors carried by participating citizens. Additionally, we evaluate the effectiveness of urban adaptation strategies such as green infrastructure for cooling and behavioral measures in reducing heat exposure.Our findings suggest that reliance on fixed weather stations alone may underestimate the heat exposure of urban residents, particularly due to localized overheating and behavioral patterns that amplify risk. Furthermore, the effectiveness of adaptation measures varies significantly depending on residents’ activity patterns and exposure duration, highlighting the need for behavior-sensitive adaptation planning.By demonstrating the potential of a co-production approach that integrates local knowledge and modeling to capture residents’ heat exposure characteristics, this study advances knowledge by enhancing the actionability of climate information. Identifying when and where urban residents are most vulnerable allows for the development of more targeted and equitable adaptation strategies. Our findings also emphasize the importance of integrating local knowledge with scientific modeling to bridge gaps in urban climate risk assessment, ultimately supporting more effective, evidence-based decision-making.