Urban Climate

Journal: Urban Climate

Publisher

Elsevier

ISSN

2212-0955

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Publications1 - 10 of 24

Mapping urban temperature using crowd-sensing data and machine learning
Zumwald, Marius; Knüsel, Benedikt; Bresch, David N.; et al. (2021)
Urban Climate
Understanding the patterns of urban temperature a high spatial and temporal resolution is of large importance for urban heat adaptation and mitigation. Machine learning offers promising tools for high-resolution modeling of urban heat, but it requires large amounts of data. Measurements from official weather stations are too sparse but could be complemented by crowd-sensed measurements from citizen weather stations (CWS). Here we present an approach to model urban temperature using the quantile regression forest algorithm and CWS, open government and remote sensing data. The analysis is based on data from 691 sensors in the city of Zurich (Switzerland) during a heat wave using data from for 25-30th June 2019. We trained the model using hourly data from for 25-29th June (n = 71,837) and evaluate the model using data from June 30th (n = 14,105). Based on the model, spatiotemporal temperature maps of 10 × 10 m resolution were produced. We demonstrate that our approach can accurately map urban heat at high spatial and temporal resolution without additional measurement infrastructure. We furthermore critically discuss and spatially map estimated prediction and extrapolation uncertainty. Our approach is able to inform highly localized urban policy and decision-making.
Fluid tunnel research for challenges of urban climate
Zhao, Yongling; Chew, Lup Wai; Fan, Yifan; et al. (2023)
Urban Climate
Experimental investigations using wind and water tunnels have long been a staple in fluid mechanics research. These experiments often choose a specific physical process to be investigated, whereas studies involving multiscale and multiphysics processes are rare. In the era of climate change, there is increasing interest in innovative experimental studies in which fluid (wind and water) tunnels are used in the modeling of multiscale, multiphysics phenomena of the urban climate. Fluid tunnel measurements of urban-physics-related phenomena are also required to facilitate the development and validation of advanced multiphysics numerical models. As a repository of knowledge for modeling these urban processes, we cover the fundamentals, experimental design guidelines, recent advances, and outlook of eight selected research areas, i.e., (i) absorption of solar radiation, (ii) inhomogeneous thermal buoyancy effects, (iii) influence of thermal stratification on land-atmosphere interactions, (iv) indoor and outdoor natural ventilation, (v) aerodynamic effects of vegetation, (vi) dispersion of pollutants, (vii) outdoor wind thermal comfort, and (viii) wind flows over complex urban sites. Three main challenges are discussed, i.e., (i) the modeling of multiphysics, (ii) the modeling of anthropogenic processes, and (iii) the combined use of fluid tunnels and scaled outdoor and field measurements for urban climate studies.
Sea surface temperature impacts on tropical urban environment: A WRF modelling investigation
Mughal, Muhammad Omer; Singh, Vivek Kumar; Martilli, Alberto; et al. (2025)
Urban Climate
In recent times urban planners in dense cities have realized the negative impact of the urban heat island (UHI) phenomenon and its strong relation with climate change. Sea Surface Temperature (SST) significantly impacts the coastal urban environment, and a systematic error may adversely impact an urban thermal assessment. This study examines the role of SST during representative months in Singapore. It is found that the reanalysis SST synthesized with satellite SST indicates an improvement in RMSE up to 0.9 °C across representative seasons at station locations within the urban canopy. The systematic SST error leads to a variation in estimated UHI intensity by up to 0.3 °C, demonstrating its non-negligible impact. The highest spatial mean UHI intensity (2.9 °C) occurs at midnight in October while the lowest UHI (1.4 °C) occurs in February. The influence of sea breezes (under weak synoptic patterns in the Inter-Monsoon seasons) is analyzed to show relevant impact in the area close to the coastline. The results provide insights into the potential future impact of global warming and rising SST on Singapore's thermal environment. Adequate urban planning can promote ventilation paths starting in the coastline to further remove urban heat in inland locations.
Model-based Climate Action Plans for ambitious local emissions reduction: A project-focused approach
Lonergan, Katherine; Köll, Josef; Sansavini, Giovanni (2025)
Urban Climate
Cities are increasingly developing Climate Action Plans to coordinate local emissions reduction; however, planners lack methodological guidance for consolidating many individual climate projects into a single plan. To close this gap, we frame the task of developing Climate Action Plans as a scheduling problem that determines optimal start times for emissions abatement projects given a specific budget. We characterize projects from empirical European data and find that considering uncertainty in cost and emissions abatement potential supports plans that are both ambitious and less prone to budget overruns than when neglecting uncertainty. We also identify difference between popular mitigation actions and those suggested under an optimal scheduling framework, which indicates potential for higher emission abatement ambition than observed in current Climate Action Plans. Our framework builds on cities' growing interest in computational models as decision-support tools while retaining the project-specific focus prominent in current stakeholder consultation practices.
Multiscale interaction between a cluster of buildings and the ABL developing over a real terrain
Vonlanthen, Marcel; Allegrini, Jonas; Carmeliet, Jan (2017)
Urban Climate
Urban form features determine spatio-temporal variation of ambient temperature: A comparative study of three European cities
Zekar, Aicha; Milojevic-Dupont, Nikola; Zumwald, Marius; et al. (2023)
Urban Climate
Driven by ongoing urbanization and accelerated global warming, urban heat stress develops into a major threat for a large part of the world population. While the literature is clear about the relevance of urban form in modifying urban heat, the spatially explicit context of heat modifications by the built environment is insufficiently explored across cities. Here we develop a consistent methodology based on a machine learning model to determine the predictive features of urban form that shape urban ambient temperature (AT) under different urban and climate conditions. For this, we combine urban climate data at 100 m resolution from the UrbClim model with urban form features computed from different open datasets. We exemplify our innovation by evaluating summer daytime and nighttime temperature variation within three European cities that are representative of distinct geographies and climates: Berlin, Zürich, and Sevilla. Mean AT at dense urban spots was higher by 3 °C (on average) during summer compared to sub-urban sites across all cities. We find that urban form features explain around 2/3 of within-city temperature variations. Vegetation cover and water bodies are most significant in explaining spatial temperature patterns during the daytime, while the impervious land cover is most critical at nighttime. Cooling effect of water areas can accumulate to −1.5 °C, while heating effects of roads can induce +0.5 °C during daytime. The magnitude of effects varies across cities, primarily based on the climate type, altitude, and dominant land-cover. However, further testing should be conducted to develop a better understanding of impact variations. The findings of this research will provide urban planners and policymakers with crucial insights towards heat mitigation and sustainable urban developments through region-tailored modifications and replacement of land-cover.
Impact of trees with varying size on street canyon flow under isothermal and non-isothermal conditions using water channel PIV measurements
Alexandrou, Giorgos; Mouzourides, Petros; Li, Haiwei; et al. (2024)
Urban Climate
This study examines the influence of trees on urban microclimate, specifically focusing on the breathability and turbulence within urban canyons. Utilizing a simplified two-dimensional street canyon model with tree-like elements, we investigate air flow interactions influenced by both buoyancy-driven and inertial forces, using Particle Image Velocimetry (PIV) measurements. The study considers trees of varying heights (ht), relative to the urban street canyon height (H), revealing that smaller trees (ht/H=1/4) allow the establishment of stronger vortices on top of the trees, while larger trees (ht/H=1) disrupt vortex formation, leading to recirculation cells. The study also explores the impact of the heated wall surface position (i.e., leeward or windward), on vortex formation and breathability at the rooftop level. Additionally, the critical value of the buoyancy parameter B, defined as the ratio of buoyancy to inertial forces, determines whether the flow field is shear- or buoyancy-dominant. These findings highlight the importance of trees placement and heated surfaces positioning in urban canyon modeling to enhance urban microclimate and pollutant dispersion. The results provide essential data for developing simplified models of tree impacts in urban areas, crucial for integrating with larger-scale weather and climate models.
Urban heat dome flow deflected by the Coriolis force
Zhang, Yan; Wang, Xiaoxue; Fan, Yifan; et al. (2023)
Urban Climate
An urban heat dome forms over urban areas when synoptic winds are weak, which is widely seen during heatwaves and expected to become the ‘norm’ in the future due to climate change. The spatial and aerodynamic characteristics of the urban heat dome have a direct impact on city-scale heat distribution and associated building cooling energy demand and many human-environment interaction processes. As the hydraulic diameter of a city goes beyond 20 km, the Coriolis force that can deflect the flow of the heat dome comes into play. Our large-eddy simulations of a 400 km2 idealized square city show that the flow of the heat dome is markedly deflected by the Coriolis force. In the Northern hemisphere, the near ground convergence inflow is found to be drastically deflected counter-clockwise. At higher levels above ground, deflected airflow leaving the city center emerges gradually, and an anticyclone is eventually seen. The findings imply that, when urban characteristic diameter reaches beyond 10 km, the deflection of the urban heat dome in high-latitude regions has to be considered in order to understand city-scale heat transport at high-spatial resolution and to underpin the development of fine-tuned measures for local urban heat mitigation.
The time-evolving impact of tree size on nighttime street canyon microclimate: Wind tunnel modeling of aerodynamic effects and heat removal
Zhao, Yongling; Li, Haiwei; Bardhan, Ronita; et al. (2023)
Urban Climate
Urban trees play a crucial role in urban climate in many aspects. However, existing research has not adequately explored the impact from a time-evolving perspective, that is, tree growth over time. To bridge this research gap, this study investigates in a wind tunnel the effects of tree-to-canyon foliage cover and relative height (0.32–1.1 times canyon height), mimicking growth of trees, on conditions in street canyons during moderate and extreme heat. The results reveal that trees may affect canyon-wide ventilation and heat removal in two different scenarios. First, when canyons are in isothermal conditions, medium and large trees, that fill half the canyon height or reach slightly above the canyon, decelerate the shear layer and weaken the vortical flow, as a result reducing the canyon-wide ventilation. Second, in extreme heat conditions, medium and large trees trap heat at the pedestrian level due to the blockage of air entrainment and the suppression of upward buoyancy-driven flow from the ground surface. An air temperature rise that corresponds to 1.5 °C in a full-scale urban setting is observed in measurements. These observations suggest that urban trees' foliage cover must be managed for a canyon's optimal ventilation and heat removal during nighttime.
A deep learning approach predicts O₃ increase and PM2.5 declines under high emission scenario across the Northern China urban agglomeration
Zhang, Gangfeng; Wang, Shuo; Xu, Jing; et al. (2026)
Urban Climate
Due to the complex interaction between varied pollutant emission sources and atmospheric circulation patterns, achieving reliable air quality prediction poses a formidable challenge. Consequently, the changes in PM2.5 and O₃ pollution under future climate change scenarios remain largely unknown, particularly in regions that are frequently affected by severe air pollution, such as the Northern China urban agglomeration (NCUA). Here we developed an Integrated Graph Neural Network (IGNN) model that, trained by historical meteorological and emission data, is able to predict future PM2.5 and O₃ concentrations over the NCUA. The IGNN model contains nodes and edges, with historical station observations being the graphical nodes, while spatiotemporal features of air quality variables, meteorological properties and emission information are defined as attributes of the nodes and edges. The results demonstrate that the IGNN model effectively captures the variability of historical PM2.5 and O₃, outperforming other state-of-the-art methods in accurately predicting air quality variability. In high carbon emission scenario with varying air pollutant strategies, all IGNN model simulations show a significant decrease of average concentration of PM2.5 (the rate of decline ranges from −0.14 to −0.37 μg m⁻³ year⁻¹, p < 0.05), Conversely, there is a significant increase in average concentration of O₃ (+0.07 to +0.22 μg m−3 year−1, p < 0.05). Our findings highlight the risk posed by elevated O₃ pollution levels under high carbon emission scenarios in the NCUA. This underscores the critical necessity for a coordinated approach that integrates air quality control with climate change mitigation efforts.

Publications1 - 10 of 24

Journal: Urban Climate

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