Spatiotemporal patterns of urban heat in indoor and outdoor microclimates

As global temperatures rise due to climate change, urban heat islands have emerged as an important public health concern, significantly exacerbating heat stress in urban populations. Meteorological data is critical for assessing heat stress, and localized microclimate data provide more precise measurements of heat hazards than traditional weather station data. Our study explored microclimate patterns in space and time in tropical cities with rapidly growing urban populations and warming climates. We established a microclimate monitoring network with sensors measuring air temperature and relative humidity throughout two large cities in Gujarat, India. We collected hourly microclimate data on temperature and humidity from April 2023 to May 2024 from paired indoor/outdoor sensors at 48 homes in Ahmedabad and 45 homes in Surat. We summarized dry bulb (<i>T</i>) and wet-bulb (<i>T</i> _w) temperatures at indoor and outdoor locations, compared temporal patterns across seasons and times of the day, and investigated relationships with urban land cover. Indoor and outdoor microclimates had different diurnal variations, with distinctive patterns during the monsoon compared to other seasons. Building volume had warming effects and vegetation had cooling effects on minimum <i>T</i> and <i>T</i> _w, particularly at outdoor locations. In contrast, building volume had cooling effects and vegetation had warming effects on maximum <i>T</i> and <i>T</i> _w, particularly at indoor locations. Temperatures were consistently cooler at locations with higher albedo, and relationships with water were weaker and more variable. A model comparison found significant differences in land cover effects for indoor versus outdoor locations. Given the increasing occurrence of heat waves and climate-related health threats in western India and other tropical areas, it will be essential to account for the different spatial and temporal patterns of indoor and outdoor microclimates to more precisely identify locations and timings of temperature extremes.