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Cities are generally warmer than their adjacent rural land, a phenomenon known as the urban heat island (UHI). Often accompanying the UHI effect is another phenomenon called the urban dry island (UDI), whereby the humidity of urban land is lower than that of the surrounding rural land 1 – 3 . The UHI exacerbates heat stress on urban residents 4 , 5 , whereas the UDI may instead provide relief because the human body can cope with hot conditions better at lower humidity through perspiration 6 , 7 . The relative balance between the UHI and the UDI—as measured by changes in the wet-bulb temperature ( T w )—is a key yet largely unknown determinant of human heat stress in urban climates. Here we show that T w is reduced in cities in dry and moderately wet climates, where the UDI more than offsets the UHI, but increased in wet climates (summer precipitation of more than 570 millimetres). Our results arise from analysis of urban and rural weather station data across the world and calculations with an urban climate model. In wet climates, the urban daytime T w is 0.17 ± 0.14 degrees Celsius (mean ± 1 standard deviation) higher than rural T w in the summer, primarily because of a weaker dynamic mixing in urban air. This T w increment is small, but because of the high background T w in wet climates, it is enough to cause two to six extra dangerous heat-stress days per summer for urban residents under current climate conditions. The risk of extreme humid heat is projected to increase in the future, and these urban effects may further amplify the risk. An analysis of data from urban and rural areas shows that in wet climates the net effect of temperature and humidity in urban areas is an increase in heat stress.

A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed Is and Ic trends, respectively) is critical for better designing urban heat mitigation strategies. However, such a global comparison remains largely absent. Using spatially continuous land surface temperatures and surface air temperatures (2003–2020), here we find that the magnitude of the global mean Is trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six‐times the corresponding Ic trend (0.03 ± 0.002°C/decade) during the day, while the former (0.06 ± 0.004°C/decade) is double the latter (0.03 ± 0.002°C/decade) at night. Variable importance scores indicate that global daytime Is trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime Ic trend. At night, both global Is and Ic trends are mainly controlled by background climate. Plain Language Summary Surface and canopy urban heat islands (surface and canopy UHIs, termed Is and Ic) are two major UHI types. These two counterparts are both related to urban population heat exposure and have long been a focus of urban climate research. However, the differences in the trends and major determinants of Is and Ic over global cities remain largely unclear. Based on spatially continuous land surface temperature and surface air temperature observations from 2003 to 2020, we find that the global mean Is trends are about 6.3 times and 2 times the Ic trends during the day and at night, respectively. During the day, the global Is trend is more regulated by surface property than by background climate, and vice versa for global Ic trend. At night, both the global Is and Ic trends are mainly regulated by background climate. These findings are important for better understanding global urban climate change and informing heat mitigation strategies. Key Points The global Is trend is six‐fold and twofold larger than the Ic trend during the day and at night, respectively During the day, global Is trend is slightly more controlled by surface property, yet background climate plays a dominant role in Ic trend At night, both global Is and Ic trends are more regulated by background climate

Increasing urbanization is likely to intensify the urban heat island effect, decrease outdoor thermal comfort, and enhance runoff generation in cities. Urban green spaces are often proposed as a mitigation strategy to counteract these adverse effects, and many recent developments of urban climate models focus on the inclusion of green and blue infrastructure to inform urban planning. However, many models still lack the ability to account for different plant types and oversimplify the interactions between the built environment, vegetation, and hydrology. In this study, we present an urban ecohydrological model, Urban Tethys-Chloris (UT&C), that combines principles of ecosystem modelling with an urban canopy scheme accounting for the biophysical and ecophysiological characteristics of roof vegetation, ground vegetation, and urban trees. UT&C is a fully coupled energy and water balance model that calculates 2 m air temperature, 2 m humidity, and surface temperatures based on the infinite urban canyon approach. It further calculates the urban hydrological fluxes in the absence of snow, including transpiration as a function of plant photosynthesis. Hence, UT&C accounts for the effects of different plant types on the urban climate and hydrology, as well as the effects of the urban environment on plant well-being and performance. UT&C performs well when compared against energy flux measurements of eddy-covariance towers located in three cities in different climates (Singapore, Melbourne, and Phoenix). A sensitivity analysis, performed as a proof of concept for the city of Singapore, shows a mean decrease in 2 m air temperature of 1.1 ∘C for fully grass-covered ground, 0.2 ∘C for high values of leaf area index (LAI), and 0.3 ∘C for high values of Vc,max (an expression of photosynthetic capacity). These reductions in temperature were combined with a simultaneous increase in relative humidity by 6.5 %, 2.1 %, and 1.6 %, for fully grass-covered ground, high values of LAI, and high values of Vc,max, respectively. Furthermore, the increase of pervious vegetated ground is able to significantly reduce surface runoff.

Increasing the albedo of urban surfaces, through strategies like white roof installations, has emerged as a promising approach for urban climate adaptation. Yet, modeling these strategies on a large scale is limited by the use of static urban surface albedo representations in the Earth system models. In this study, we developed a new transient urban surface albedo scheme in the Community Earth System Model and evaluated evolving adaptation strategies under varying urban surface albedo configurations. Our simulations model a gradual increase in the urban surface albedo of roofs, impervious roads, and walls from 2015 to 2099 under the SSP3‐7.0 scenario. Results highlight the cooling effects of roof albedo modifications, which reduce the annual‐mean canopy urban heat island intensity from 0.8°C in 2015 to 0.2°C by 2099. Compared to high‐density and medium‐density urban areas, higher albedo configurations are more effective in cooling environments within tall building districts. Additionally, urban surface albedo changes lead to changes in building energy consumption, where high albedo results in more indoor heating usage in urban areas located beyond 30°N and 25°S. This scheme offers potential applications like simulating natural albedo variations across urban surfaces and enables the inclusion of other urban parameters, such as surface emissivity. Plain Language Summary Higher albedo surfaces reflect more sunlight, which helps cool down cities. Yet, research into how altering the albedo of urban surfaces on a global scale can aid climate adaptation is limited. It either relies on empirical analysis, oversimplifying urban physical processes, or assumes that urban surface albedo remains constant over time. These limitations hinder our understanding of how changes in urban surfaces can impact the urban thermal environment. In this study, we developed a new option that allows urban surface albedo to vary over time within a global climate model. By gradually increasing global urban surface albedo, we quantified the cooling effects of implementing high urban albedo in a more realistic way. This new option sets the stage for future exploration of scenarios like painting roofs white or how materials age, shedding light on effective urban climate adaptation strategies. Key Points We developed a new representation scheme of transient urban surface albedo in Community Earth System Model (CESM) to improve urban climate adaptation modeling The new scheme enables CESM to assess evolving adaptation strategies for roofs, impervious roads, and walls over time Simulations show increasing roof albedo cools cities more effectively than increasing wall or impervious road albedo

If local governments reduce greenhouse gas emissions, they will not see effects unless a very large number of other actors do the same. However, reducing greenhouse gas emissions can have multiple local “co-benefits” (improved air quality, energy savings, even energy security), creating incentives for local governments to reduce emissions—if just for the local side-effects of doing so. Available empirical research yet shows a large gap between co-benefits as a rationale and an explanatory factor for climate mitigation by local governments: co-benefits are seemingly very large, but do not seem to drive local mitigation efforts. Relying on policy documents, available research, and other written sources, the present paper consists of a multiple case study addressing the link between co-benefits and climate mitigation in Moscow, Paris, and Montreal. Air quality plays a very different role in each case, ranging from a key driver of mitigation to a liability for local climate action. This heterogeneity of mechanisms in place emerges as a likely explanation for the lack of a clear empirical link between co-benefits and local mitigation in the literature. We finally discuss implications for urban climate action policy and research.

Atmospheric and surface urban heat islands (UHI) originate from common energetic processes, but the status of scientific knowledge on their time evolution is highly disparate. The diurnal cycles of atmospheric UHI are well known based on years of continuous measurements in cities; the cycles of surface UHI, however, cannot be measured continuously or in situ. In this article, we aim to reconcile these differences. We begin with a synthesis of previous work on the diurnal evolution of surface UHI, which leads to a novel but historically minded approach to the research problem. The approach involves a combination of microscale and mesoscale urban climate models, each of which is forced with universally described urban and rural surface parameters and atmospheric profiles. With these models, we produce theoretical time‐temperature curves for the surface UHI that are comparable to the classic curves of atmospheric UHI. This work prompts a critical look at the use of satellite thermal imagery to assess heat islands and heat risks in cities. To that end, we recommend new and more functional definitions of surface temperature. Conceptually, these represent “incomplete” temperatures defined by specific facets of the urban environment. Plain Language Summary Urban heat islands (UHI) refer to the added warmth in cities due to the abundance of buildings, vehicles, and paved ground. However, very little is known about the hourly and daily changes in the surface temperatures of the city. This is partly due to the technological difficulties of sampling surface temperatures in urban environments, and to the myriad of surface types in cities. In this article, we aim to overcome this difficulty by using a combination of urban climate models, which can replicate daily temperature cycles for the surface UHI. With these data, we recommend new indicators of surface temperature that more accurately describe the heat risks and building energy demands in cities. Key Points Three numerical climate models are used to characterize the diurnal evolution of the surface urban heat island Diurnal evolution of surface heat islands varies with regional climate, urban morphology, rural land cover, soil moisture, and wind speed Satellite‐based observations of surface heat islands are likely to overestimate (underestimate) actual daytime (nighttime) impacts

To bridge the gaps between meteorological large‐eddy simulation (LES) models and computational fluid dynamics (CFD) models for microscale urban climate simulations, the present study has developed a meteorological LES model for urban areas. This model simulates urban climates across both mesoscale (city scale) and microscale (city‐block scale). The paper offers an overview of this LES model, which distinguishes itself from standard numerical weather prediction models by resolving buildings and trees at the microscale simulations. It also differs from standard CFD models by accounting for atmospheric stratification and physical processes. Noteworthy features of this model include: (a) the calculation of long‐ and short‐wave radiations in three dimensions, incorporating multiple reflections within urban canopy layers using the radiosity method, and accounting for building and tree shadows in the simulations; (b) the provision of various heat stress indices (Universal Thermal Climate Index, Wet Bulb Globe Temperature, MRT, THI); (c) the assessment of the efficacy of heat stress mitigation measures such as dry‐mist spraying, roadside trees, cool pavements, and green/cool roofs strategies; (d) the capability to run on supercomputers, with the code parallelized in a three‐dimensional manner, and the model can also run on a graphics processing unit cluster. Following the introduction of this model, the study confirms its basic performance through various numerical experiments, including simulations of thermals in the convective boundary layer, coherent structure of turbulence over urban canopy, and thermal environment and heat stress indices in urban districts. The model developed in this study is intended to serve as a community tool for addressing both fundamental and applied studies in urban climatology. Plain Language Summary This study introduces a new multi‐scale urban climate model, City‐LES, which is a hybrid model combining meteorological modeling and engineering computational fluid dynamics (CFD) approaches. This model simulates urban climates across both mesoscale (city scale) and microscale (city‐block scale). Developed through collaboration among urban climatologists, CFD modeling researchers, and high‐performance computing experts, City‐LES simulates airflow in urban areas, conducts three‐dimensional radiation calculations in the urban canopy, incorporates various atmospheric physics schemes, and operates on supercomputers equipped with graphics processing units, as well as CPUs. Furthermore, the model enables the assessment of the efficacy of heat stress mitigation measures such as dry‐mist spraying, roadside trees, cool pavements, and green/cool roof strategies. Validation results indicate that City‐LES accurately simulates urban atmospheric dynamics, the thermal environment, and heat stress indices. The model will serve as a valuable community tool for both fundamental and applied studies in urban climatology. Key Points This study introduces a multi‐scale urban climate model that combines meteorological and computational fluid dynamics modeling approaches The model resolves buildings, simulates 3D airflow and radiation in urban areas, and runs on supercomputers equipped with graphics processing units and/or CPUs The model accurately simulates urban atmospheric dynamics, thermal environments, and heat stress indices

As cities and their population are subjected to climate change and urban heat islands, it is paramount to have the means to understand the local urban climate and propose mitigation measures, especially at neighbourhood, local and building scales. A framework is presented, where the urban climate is studied by coupling a meteorological model to a building-resolved local urban climate model, and where an urban climate model is coupled to a building energy simulation model. The urban climate model allows for studies at local scale, combining modelling of wind and buoyancy with computational fluid dynamics, radiative exchange and heat and mass transport in porous materials including evaporative cooling at street canyon and neighbourhood scale. This coupled model takes into account the hygrothermal behaviour of porous materials and vegetation subjected to variations of wetting, sun, wind, humidity and temperature. The model is driven by climate predictions from a mesoscale meteorological model including urban parametrisation. Building energy demand, such as cooling demand during heat waves, can be evaluated. This integrated approach not only allows for the design of adapted buildings, but also urban environments that can mitigate the negative effects of future climate change and increased urban heat islands. Mitigation solutions for urban heat island effect and heat waves, including vegetation, evaporative cooling pavements and neighbourhood morphology, are assessed in terms of pedestrian comfort and building (cooling) energy consumption.

Rapid and uncontrolled urbanization in tropical Africa is increasingly leading to unprecedented socio-economical and environmental challenges in cities, particularly urban heat and climate change. The latter calls for a better representation of tropical African cities’ properties relevant for urban climate studies. Here, we demonstrate the possibility of collecting urban canopy parameters during a field campaign in the boreal summer months of 2018 for deriving a Local Climate Zone (LCZ) map and for improving the physical representation of climate-relevant urban morphological, thermal and radiative characteristics. The comparison of the resulting field-derived LCZ map with an existing map obtained from the World Urban Data and Access Portal Tool framework shows large differences. In particular, our map results in more vegetated open low-rise classes. In addition, site-specific fieldwork-derived urban characteristics are compared against the LCZ universal parameters. The latter shows that our fieldwork adds important information to the universal parameters by more specifically considering the presence of corrugated metal in the city of Kampala. This material is a typical roofing material found in densely built environments and informal settlements. It leads to lower thermal emissivity but higher thermal conductivity and capacity of buildings. To illustrate the importance of site-specific urban parameters, the newly derived site-specific urban characteristics are used as input fields to an urban parametrization scheme embedded in the regional climate model COSMO-CLM. This implementations decreases the surface temperature bias from 5.34 to 3.97 K. Based on our results, we recommend future research on tropical African cities to focus on a detailed representation of cities, with particular attention to impervious surface fraction and building materials.

Comprehensive studies comparing impacts of building and street levels interventions on air temperature at metropolitan scales are still lacking despite increased urban heat‐related mortality and morbidity. We therefore model the impact of 9 interventions on air temperatures at 2 m during 2 hot days from the summer 2018 in the Greater London Authority area using the WRF BEP‐BEM climate model. We find that on average cool roofs most effectively reduce temperatures (∼−1.2°C), outperforming green roofs (∼0°C), solar panels (∼−0.5°C) and street level vegetation (∼−0.3°C). Application of air conditioning across London (United Kingdom) increases air temperatures by ∼+0.15°C. A practicable deployment of solar panels could cover its related energetic consumption. Current practicable deployments of green roofs and solar panels are ineffective at large scale reduction of temperatures. We provide a detailed decomposition of the surface energy balance to explain changes in air temperature and guide future decision‐making. Plain Language Summary Multiple common city scale passive and active interventions exist to reduce urban population's exposure to extreme heat during hot spells. Nonetheless, a proper comparison of the effect that each of these interventions may have on the temperatures experienced within large cities is missing. Additionally, the radiative and thermal mechanisms that lead to outdoor temperature changes are often not detailed and could lead to detrimental effects for local populations, such as indirect increase of water vapor or reflection of solar radiation. Our study, focusing over London, compares several common interventions through a modeling experiment and finds that cool roofs largely outperform other interventions during the two hottest days of the summer 2018. We also find that green roofs are ineffective on average and that solar panels and tree vegetation would only marginally change temperature exposures. Large scale deployment of air conditioning would lead to increased temperature in the core of London. Solar panels could potentially provide sufficient energy for running air conditioning all over London, creating comfortable indoor environments, and green roofs could reduce temperatures during the day. We argue that such inter‐comparisons should guide future decision making. Key Points City scale deployment of cool roofs leads to the greatest reduction in 2 m air temperature Green roofs do not decrease daily average temperature but have a daytime cooling effect Solar photovoltaic panels can reduce temperatures in London by capturing sensible heat flux and generate electrical power