Urban climate model evaluation often remains limited by a lack of trusted urban weather observations. The increasing density of personal weather stations (PWS) make them a potential rich source of data for urban climate studies that address the lack of representative urban weather observations. In our study, we demonstrate that PWS data not only improve urban climate models’ evaluation, but can also serve for bias-correcting their output prior to any urban climate impact studies. After simulating near-surface air temperatures over London and south-east England during the hot summer of 2018 with the Weather Research Forecast (WRF) model and its Building Effect Parameterization with the Building Energy Model (BEP-BEM) activated, we evaluated the modelled temperatures against 402 urban PWS and showcased a heterogeneous spatial distribution of the model’s cool bias that was not captured using official weather stations only. This finding indicated a need for spatially-explicit urban bias corrections of air temperatures, which we performed using an innovative method using machine learning to predict the models’ biases in each urban grid cell. Our technique is the first to consider that urban temperatures are heterogeneously accurate in space and that this accuracy is not linearly correlated to the urban fraction. Our results showed that the bias-correction was beneficial to bias-correct daily-minimum, -mean, and -maximum temperatures in the cities. We recommend that urban climate modellers further investigate the use of PWS for model evaluation and derive a framework for bias-correction of urban climate simulations that can serve urban climate impact studies.

Urban overheating, driven by global climate change and urban development, is a major contemporary challenge which substantially impacts urban livability and sustainability. Overheating represents a multi-faceted threat to well-being, performance, and health of individuals as well as the energy efficiency and economy of cities, and it is influenced by complex interactions between building, city, and global scale climates. In recent decades, extensive discipline-specific research has characterized urban heat and assessed its implications on human life, including ongoing efforts to bridge neighboring disciplines. The research horizon now encompasses complex problems involving a wide range of disciplines, and therefore comprehensive and integrated assessments are needed that address such interdisciplinarity. Here, the objective is to go beyond a review of existing literature and provide a broad overview and future outlook for integrated assessments of urban overheating, defining holistic pathways for addressing the impacts on human life. We (i) detail the characterization of heat exposure across different scales and in various disciplines, (ii) identify individual sensitivities to urban overheating that increase vulnerability and cause adverse impacts in different populations, (iii) elaborate on adaptive capacities that individuals and cities can adopt, (iv) document the impacts of urban overheating on health and energy, and (v) discuss frontiers of theoretical and applied urban climatology, built environment design, and governance toward reduction of heat exposure and vulnerability at various scales. The most critical challenges in future research and application are identified, targeting both the gaps and the need for greater integration in overheating assessments.

The urban environment directly influences the evolution of the Urban Boundary Layer (UBL). Heat adaptation strategies proposed to help cities respond to global change and urban induced warming, are also expected to reduce the intensity of convective mixing and decrease UBL depth, thereby reducing the volume of air available to pollutant dilution and dispersion. We use 20 km resolution WRF-ARW decadal scale simulations that account for end of 21st century greenhouse gas emissions, urban expansion and intensive and uniform implementation of cool roofs, green roofs and street trees to investigate the individual and combined impacts of these drivers on the dynamics of the UBL over the Conterminous US (CONUS). Results indicate that combined impacts of climate change and urban expansion are expected to increase summer (JJA) daytime UBL depth in the eastern regions of CONUS (peak value: Δh ≅ 80 m over Atlanta metro area). When adaptation strategies are applied, summer daytime UBL depth is reduced by a few hundred meters (peak value: Δh ≅ -310 m over Dallas and Fort Worth metro areas) in all CONUS regions as a consequence of decreased surface sensible heat fluxes. Adaptation impacts are greater inland and smaller over coastal cities. In arid regions, the adaptation induced increase in latent heat fluxes can counterbalance the projected decrease in UBL depth. Furthermore, adaptation strategies are expected to increase the static stability of both daytime and nighttime UBLs and decrease the magnitude of vertical winds, inducing earlier and stronger subsidence (peak value: Δm/s ≅ -0.05 m over Phoenix and Tucson metro areas). In light of these findings, ongoing work addressing these aspects with convection resolving, high-resolution simulations is needed to determine whether the widespread implementation of urban adaptation measures could have deleterious effects for urban air quality in the cities of the future Contiguous US.