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Variability of building height induces flow heterogeneity and directly controls the depth of the roughness sub-layer, the strength of mutual sheltering, and the overlapping of urban canopy flow, which poses challenges for accurate modeling. Large-eddy simulations over 96 building arrays with varying density, height variability (standard deviation of building height), and horizontal arrangements were conducted to reveal the impact on the urban flow. Results demonstrate a strong non-local building effect on the flow due to height variability, where flow around high buildings possesses high wind speed, dispersive momentum flux, and other distinctive flow patterns, whereas around low buildings, the flow pattern is less unique. The complex flow behavior is beyond the capacity of the current multi-layer urban canopy model (MLUCM) where turbulent constants and drag effects were considered in a simplified way. The increased height variability and urban density also blur the interface of urban canopy, further making MLUCM estimates model constants heavily based on a clear urban canopy inappropriate. Based on the original model, we comprehensively tested potential contributing factors such as the estimation of displacement height, height-dependent drag coefficients, and the extended roughness sublayer. The modified model provides a better overall agreement with the LES results, especially above the mean building height where the prediction of the extended urban canopy layer is largely improved.

The Mediterranean basin is expected to experience an increase in intensity and frequency of heat wave events. Additionally, heat peaks are exacerbated by the low albedo of urban materials and the heat island effect of urban areas. To reduce heat-related discomfort and health risks, urban planners aim to implement green infrastructures to regulate temperatures thanks to their transpiration cooling effect. For example, the Metropolitan Area of Barcelona (AMB) has created a metropolitan network of “climate shelters”, which are public spaces (both indoor and outdoor) where urban dwellers can find better climatic conditions. Urban parks can be considered “climate shelters” if two requirements are met: the NDVI of the vegetation is higher than 0.4 and the extension of the park is bigger than 0.5 ha. However, given the dense urban edification and space limitation, we wanted to explore the thermal regulation capacity of smaller urban parks which are easier to implement. In this study, we present the results of a micrometeorological measurement campaign to assess the temporal and spatial variations of thermal comfort in parks of different sizes in the AMB during a heatwave episode in July 2022. The goals of this study are to determine the impact on human biometeorology of urban design in the construction of urban parks for facing heatwave episodes and to check the classification requirements for the “climate shelters”.Using a mobile human-biometeorological weather station (MaRTy cart), we registered the microclimatic factors affecting thermal exposure at different points inside and outside the parks. From the microclimatic measurements we derived the Universal Thermal Climate Index (UTCI). Additional characterization of the measurement points consisted in sky-view-factor estimations and 360o vegetation and impervious view factors. Throughout the campaign period and measurement hours (14:00, 15:00 and 20:00 LT), the UTCI varied between 29.5 oC (moderate heat stress) and 41.9 oC (very strong heat stress). During the early afternoon, when air temperatures and heat stress are higher, the UTCI is lower inside of the parks, by a difference that ranges from 1.0 oC to 3.2 oC. The sky-view-factor is responsible for 43 to 58% of the observed variability in the UTCI, pointing out the importance of tree shadowing inside the parks. Air temperature has also a clear influence on thermal comfort, explaining between 17 and 50% of the UTCI variability. Although air temperature reductions in smaller parks are not as significant as in the “climate shelter” park, there are vegetation zones inside the smaller parks with comparable reductions in the UTCI. The results show that small parks can provide thermal comfort in similar capacity as bigger parks classified as “climate shelters”.

The potential for critical infrastructure failures during extreme weather events is rising. Major electrical grid failure or "blackout" events in the United States, those with a duration of at least 1 h and impacting 50,000 or more utility customers, increased by more than 60% over the most recent 5 year reporting period. When such blackout events coincide in time with heat wave conditions, population exposures to extreme heat both outside and within buildings can reach dangerously high levels as mechanical air conditioning systems become inoperable. Here, we combine the Weather Research and Forecasting regional climate model with an advanced building energy model to simulate building-interior temperatures in response to concurrent heat wave and blackout conditions for more than 2.8 million residents across Atlanta, Georgia; Detroit, Michigan; and Phoenix, Arizona. Study results find simulated compound heat wave and grid failure events of recent intensity and duration to expose between 68 and 100% of the urban population to an elevated risk of heat exhaustion and/or heat stroke.

The urban environment directly influences Urban Boundary Layer (UBL) dynamics. Commonly proposed heat adaptation strategies focused on reducing the impacts of global change and urban induced warming are also expected to decrease the intensity of convective mixing thereby reducing UBL depth, with important consequences for air pollutant dilution and dispersion. We use 20-km grid spacing Regional Climate Model decadal scale simulations that account for end of twenty-first century greenhouse gas emissions, urban development and intensive and uniform implementation of a suite of heat adaptation strategies, to investigate the individual and combined impacts of such drivers on UBL dynamics over the Continental US (CONUS). Results indicate that combined impacts of climate change and urban development are expected to increase summer (JJA) daytime UBL height in the eastern CONUS. Heat adaptation strategies lead to a summer daytime UBL depth reduction of several hundred meters across CONUS regions, primarily as a consequence of reduced surface sensible heat fluxes and associated turbulence. Our results confirm that heat adaptation is expected to increase the static stability of both daytime and nighttime UBLs and decrease the magnitude of vertical winds, inducing stronger subsidence. In addition, the large geographical scale of our analysis indicates that adaptation impacts are greater inland and smaller over coastal cities. In Southern California, the adaptation induced increase in latent heat can counterbalance the projected decrease in UBL depth. Future work addressing these projected UBL impacts with convection permitting, high-resolution coupled atmosphere-chemistry simulations is needed to explicitly determine potential unintended consequences for urban air quality.

Urban areas have complex thermal distribution. We examined the association between extreme temperature and mortality in urban Ontario, using two temperature data sources: high-resolution and weather station data. We used distributed lag non-linear Poisson models to examine census division-specific temperature–mortality associations between May and September 2005–2012. We used random-effect multivariate meta-analysis to pool results, adjusted for air pollution and temporal trends, and presented risks at the 99th percentile compared to minimum mortality temperature. As additional analyses, we varied knots, examined associations using different temperature metrics (humidex and minimum temperature), and explored relationships using different referent values (most frequent temperature, 75th percentile of temperature distribution). Weather stations yielded lower temperatures across study months. U-shaped associations between temperature and mortality were observed using both high-resolution and weather station data. Temperature–mortality relationships were not statistically significant; however, weather stations yielded estimates with wider confidence intervals. Similar findings were noted in additional analyses. In urban environmental health studies, high-resolution temperature data is ideal where station observations do not fully capture population exposure or where the magnitude of exposure at a local level is important. If focused upon temperature–mortality associations using time series, either source produces similar temperature–mortality relationships.

Effective urban planning for climate-driven risks relies on robust climate projections specific to built landscapes. Such projections are absent because of a near-universal lack of urban representation in global-scale Earth system models. Here, we combine climate modelling and data-driven approaches to provide global multi-model projections of urban climates over the twenty-first century. The results demonstrate the inter-model robustness of specific levels of urban warming over certain regions under climate change. Under a high-emissions scenario, cities in the United States, Middle East, northern Central Asia, northeastern China and inland South America and Africa are estimated to experience substantial warming of more than 4 K—larger than regional warming—by the end of the century, with high inter-model confidence. Our findings highlight the critical need for multi-model global projections of local urban climates for climate-sensitive development and support green infrastructure intervention as an effective means of reducing urban heat stress on large scales. An urban climate model emulator has been used with a multi-model archive to estimate that in a high-emissions scenario, many cities will warm by over 4 K during local summers. Near-global relative humidity decreases highlight the potential for green infrastructure and more efficient urban cooling mechanisms.

Future urban climates are likely to warm substantively in coming decades as a result of climate change, and greater heat wave severity is anticipated. Moreover, the urban heat island contributes additional heat, especially during evening and night. Infrastructure-based heat reduction strategies can reduce canopy air temperatures during daytime, and to some extent at night. These strategies also have several additional effects beyond air temperature reduction. Here, we apply an early coupling of the WRF mesoscale model with the BEP-Tree urban canopy model to simulate extreme heat events representative of both contemporary and projected future climates for the metropolitan region of Toronto, Canada. Urban and non-urban land cover is derived using the state-of-the-art LCZ Generator methodology. Subsequently, the effectiveness of heat mitigation strategies, including highly reflective surfaces and vegetation, is quantified for the future scenario in the context of the increase in heat wave intensity. Specifically, the neighbourhood- and city-scale climate impacts of street trees across the diurnal cycle are quantified, and the diurnal progression of their local climate effects is discussed with reference to their modifications to multiple physical processes in the canopy. Effects of all heat mitigation strategies on canopy climate, building energy use, and thermal comfort indices are evaluated.

The application of nature-based solutions in urban areas to mitigate the harmful effects of urban overheating and to make cities more resilient to heat waves has gained the attention of city planners and researchers in the last decades. Street trees are an important driver of street microclimate through shadowing and transpiration cooling, which are key components in the improvements of thermal comfort. While several observational campaigns have been carried out in low and medium-density residential areas, little research has been focused in highly-compact city centres, where the impact of built elements on the local climate is expected to be stronger. In this context, Urban canopy models (UCM) with integrated trees are useful tools because they represent the impact of street trees on neighbourhood-scale climate, resolving the interactions between buildings, trees and the atmosphere. These models enable the assessment of outdoor human thermal exposure for diverse urban morphologies and allow the evaluation of greening scenarios.In this study, we present the results of a micrometeorological measurement campaign inside the city of Barcelona (Spain) for two cloud-free summer days. Vehicle transects were completed along two parallel streets with different tree densities but identical street geometry, recording upward and downward radiation fluxes, air temperature and humidity. Assessment of urban tree impacts on microclimate is supplemented by meteorological simulations using the multi-layer UCM Building Effect Parameterization with Trees (BEP-Tree), which considers the vertical variation of the combined impacts of vegetation and building on urban canopy layer climate. Comparing observed pedestrian level air temperatures between the two canyons, we can see that the impact of tree densities varies with the regional weather, with air temperatures up to 2.7 oC higher in the street with low tree density compared to the one with denser trees for a day with the wind direction perpendicular to the direction of the streets. The BEP-Tree simulations demonstrate good agreement with the observations in terms of temperature and radiation, and they are able to capture the different diurnal evolution of temperature and radiation between the two streets.

We use a suite of decadal-length regional climate simulations to quantify potential changes in population-weighted heat and cold exposure in 47 US metropolitan regions during the 21st century. Our results show that population-weighted exposure to locally defined extreme heat (i.e., “population heat exposure”) would increase by a factor of 12.7–29.5 under a high-intensity greenhouse gas (GHG) emissions and urban development pathway. Additionally, end-of-century population cold exposure is projected to rise by a factor of 1.3–2.2, relative to start-of-century population cold exposure. We identify specific metropolitan regions in which population heat exposure would increase most markedly and characterize the relative significance of various drivers responsible for this increase. The largest absolute changes in population heat exposure during the 21st century are projected to occur in major US metropolitan regions like New York City (NY), Los Angeles (CA), Atlanta (GA), and Washington DC. The largest relative changes in population heat exposure (i.e., changes relative to start-of-century) are projected to occur in rapidly growing cities across the US Sunbelt, for example Orlando (FL), Austin (TX), Miami (FL), and Atlanta. The surge in population heat exposure across the Sunbelt is driven by concurrent GHG-induced warming and population growth which, in tandem, could strongly compound population heat exposure. Our simulations provide initial guidance to inform the prioritization of urban climate adaptation measures and policy.

As summer heat waves become the new normal worldwide, modeling human thermal exposure and comfort to assess and mitigate urban overheating is crucial to uphold livability in cities. We introduce PanoMRT, an open source human-biometeorological model to calculate Mean Radiant Temperature (T

Altres ajuts: acords transformatius de la UAB Unidad de excelencia María de Maeztu CEX2019-000940-M Street trees are an important driver of street microclimate through shading and transpirative cooling, which are key mechanisms for improving thermal comfort in urban areas. Urban canopy models (UCM) with integrated trees are useful tools because they represent the impacts of street trees on neighborhood-scale climate, resolving the interactions between buildings, trees and the atmosphere. In this study, we present the results of a measurement campaign where vehicle transects were completed along two similar parallel streets of Barcelona with different tree densities, recording upward and downward radiation fluxes, air temperature and humidity at street level. These observations are used to evaluate and improve the multi-layer UCM Building Effect Parameterization with Trees (BEP-Tree). Prior simulations of the model revealed insufficient heat exchange between the canyon surfaces and the air at the lowest vertical levels inside the deep canyons, which we solve by including turbulent buoyancy driven wind velocity in the model. Air temperatures are 2.7 o C higher in the street with fewer trees when wind direction is perpendicular to the streets. The BEP-Tree simulations demonstrate good agreement with the observations in terms of temperature and radiation, and capture the diurnal evolution of temperature and radiation between the two streets.

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...

Urban street design choices relating to tree planting, building height and spacing, ground cover, and building façade properties impact outdoor thermal exposure. However, existing tools to simulate heat exposure have limitations with regard to optimization of street design for pedestrian cooling. A microscale three-dimensional (3D) urban radiation and energy balance model, Temperatures of Urban Facets for Pedestrians (TUF-Pedestrian), was developed to simulate pedestrian radiation exposure and study heat-reducing interventions such as urban tree planting and modifications to building and paving materials. TUF-Pedestrian simulates the spatial distribution of radiation and surface temperature impacts of trees and buildings on their surroundings at the sub-facet scale. In addition, radiation absorption by a three-dimensional pedestrian is considered, permitting calculation of a summary metric of human radiation exposure: the mean radiant temperature (T

We report the first set of urban micrometeorological measurements for assessment of pedestrian thermal exposure during extreme heat in a dry climate. Hourly measurements of air temperature, humidity, wind speed and six-directional shortwave and longwave radiation were recorded with a mobile human-biometeorological station (MaRTy) from 10:00 to 21:00 local time, June 19, 2016, at 22 sites that include diverse microscale urban land cover. Sky view factor (SVF) and 360° pervious and impervious view factors for each location were calculated from six-directional fisheye photographs. Mean radiant temperature (TMRT) was determined using the six-directional method. Three-dimensional radiation budgets were decomposed into directional weighted shortwave and longwave radiation components to create a distinct TMRT profile for each site and determine the main drivers of TMRT and thermal exposure. Air temperature peaked locally at 48.5 °C, with a maximum TMRT of 76.4 °C at 15:00 MST in an east-west building canyon. Longwave radiation measured by laterally-oriented sensors dominated the TMRT budget, suggesting the importance of cooling vertical surfaces adjacent to pedestrians. Lateral shortwave radiation contributions were most spatially and temporally variable across TMRT profiles, reflecting the diverse shade conditions. The largest radiation fluxes contributing to TMRT were particularly sensitive to shade and secondarily to ground cover. Trees reduced afternoon TMRT up to 33.4 °C but exhibited a clear TMRT increase of up to 5 °C after sunset; during daytime, trees generated ground cover-dependent longwave radiant cooling or warming. Replacement of impervious with pervious ground cover cooled TMRT at all measurement times, even under dense tree shade. While recent work has found that adaptation cannot offset projected urban air temperature increases, outdoor thermal exposure depends on additional micrometeorological variables, including shortwave and longwave radiation, indicating the need and the opportunity to create pedestrian spaces that are radiantly cool within the context of future urban heat.

Spatiotemporal variation of mean radiant temperature (Tmrt), a major driver of outdoor human thermal comfort, is driven by exposure to solar and longwave radiation, which in turn respond to local patterns of shading, wind speed, air humidity and air temperature. In this study, the SOlar and LongWave Environmental Irradiance Geometry (SOLWEIG) model was used to simulate how changes in minimum and maximum air temperature and solar radiation under Representative Concentration Pathways (RCP) 4.5 and 8.5 climate projections would change Tmrt in Vancouver over the 2070–2100 period. With micrometeorological variables representative of a changed climate, days with Tmrt above 65 °C were predicted to increase three-to five-fold under RCP 4.5 and 8.5, respectively. SOLWEIG was also used to quantify the potential of maximum feasible street tree cover to reduce Tmrt for the hottest day on record for Vancouver (July 29, 2009), and an end-of-century hot day under the two future climate scenarios. SOLWEIG simulations with maximum feasible street tree cover under RCP 4.5 demonstrated an average reduction of 1.3 °C in Tmrt, compared to the contemporary extreme heat day with current street trees. However, average Tmrt increased by 1.9 °C under the RCP 8.5 scenario even with maximum feasible street tree cover, relative to the contemporary extreme heat day. We conclude that adding street trees has the potential to offset Tmrt increases under the RCP 4.5 scenario, however this measure is insufficient to maintain contemporary Tmrt under the RCP 8.5 scenario.

Utility-scale solar power plants are a rapidly growing component of the renewable energy sector. While most agree that solar power can decrease greenhouse gas emissions, the effects of photovoltaic (PV) systems on surface energy exchanges and near-surface meteorology are not well understood. This study presents data from two eddy covariance observational towers, placed within and adjacent to a utility-scale PV array in southern Arizona. The observational period (October 2017–July 2018) includes the full range of annual temperature variation. Average daily maximum 1.5-m air temperature at the PV array was 1.3°C warmer than the reference (i.e., non-PV) site, whereas no significant difference in 1.5-m nocturnal air temperature was observed. PV modules captured the majority of solar radiation and were the primary energetically active surface during the day. Despite the removal of energy by electricity production, the modules increased daytime net radiation Q* available for partitioning by reducing surface albedo. The PV modules shift surface energy balance partitioning away from upward longwave radiation and heat storage and toward sensible heat flux QH because of their low emissivity, low heat capacity, and increased surface area and roughness, which facilitates more efficient QH from the surface. The PV modules significantly reduce ground heat flux QG storage and nocturnal release, as the soil beneath the modules is well shaded. Our work demonstrates the importance of targeted observational campaigns to inform process-based understanding associated with PV systems. It further establishes a basis for observationally based PV energy balance models that may be used to examine climatic effects due to large-scale deployment.

Extensive impervious surface cover, anthropogenic heat emissions, and lack of vegetation contribute to the formation of distinct urban microclimates where higher air and surface temperature as well as lack of shade intensify outdoor heat exposure and thermal discomfort for humans. Modifications to the thermal environment via urban design can be used to mitigate this effect. In this study, the potential for increased street tree coverage to reduce mean radiant temperature (Tmrt) 1 across six different local climate zones (LCZs) 2 in Vancouver, Canada, was examined using the Solar and LongWave Environmental Irradiance Geometry (SOLWEIG) 3 model. The radiant cooling effect of increased street tree coverage during the hottest day on record for Vancouver (July 29, 2009) was quantified by spatiotemporal changes to Tmrt. SOLWEIG was evaluated successfully prior to implementation of a street tree cover increase equivalent to 1% of plan area in each of six Vancouver LCZs investigated. Results indicate 3.2–6.3 °C reduction in spatially-averaged daytime (9:00 – 18:00) Tmrt and 3.3–7.1 °C reduction during the hottest period of day, 11:00-17:00. During the hottest period of day, the largest spatially-averaged Tmrt reduction (7.1 °C) was modelled in a low-rise residential area. Modelling suggested that a pedestrian standing directly under a tree canopy would experience Tmrt reductions of 15.5–17.3 °C in all LCZs. Also, under current conditions with no increase in tree cover, the compact high-rise and the large low-rise areas are shown to be the most and least comfortable environments regarding human thermal exposure with spatially-averaged Tmrt of 41.9 °C and 47.9 °C, respectively. We conclude that increases to Vancouver’s street tree cover by 1% of plan area can substantially reduce Tmrt during extreme hot weather. The results of this study show that the cooling potential of added street trees is greater in lower density residential neighborhoods with 1–2 storey buildings compared to higher density neighborhoods occupied by high-rise or mid-rise buildings.

Many cities in the northern hemisphere experience both extreme heat and extreme cold weather. Pedestrians are exposed to these thermal extremes, causing bodily stress. With a growing and ageing urban population, city design that contributes to the mitigation of summer heat exposure while also reducing winter cold exposure is of increasing importance. Pedestrian thermal exposure depends on several microclimatic factors in addition to air temperature, including wind speed, humidity, as well as shortwave and longwave radiation, which can be quantified by the mean radiant temperature (Tmrt). There has been little study of the impacts on pedestrian thermal exposure in climates with high humidity during summer and snow cover in the winter. We gathered seasonal radiation data from varied urban microclimates using the six-directional Tmrt method in a Canadian city. We deployed a mobile human-biometeorological weather station (MaRTy cart), which has previously been used primarily in hot, dry climates. Tmrt profiles are decomposed into their directional components, and they demonstrate substantial differences in the drivers of thermal exposure between seasons and locations within the city.

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...

In the wake of growing concern for climate change, heat waves and their potential health effects (McGeehin and Mirabelli, 2001) [37] have become a recurring phenomenon (Beniston, 2004; Fouillet et al., 2006) [8] , [21] . Extreme heat events in the USA are responsible for more deaths as compared to other weather events such as hurricanes, lightning, tornadoes and floods (Luber and McGeehin, 2008) [33] . Heat exposure in buildings has risen due to global warming in conjunction with other factors like urbanization and associated heat island effects (Kolokotroni et al., 2012) [25] , lack of thermal mass (Lomas and Porritt, 2017a) [31] , exposure to solar insolation on higher stories, absence of window shading, overcrowding and envelope properties exacerbate the overheating inside the dwellings (Vellei et al., 2017). [45] . Stone et al. (2021) [43] provides a macro view of the indoor environments in buildings due to the concurrent event of power outage during heat wave in face of climate change. This paper builds on the previous publication and provides a detailed view of modeling methodology, building physics that explains the sources/sinks of heat and entails a detailed evaluation of the current building stock for the low to moderate income residences in the city of Phoenix, Arizona in terms of their thermal performance. Finite Element models of building stock were simulated using MATLAB for microclimate weather files of Phoenix generated by Weather Research and Forecasting (WRF) simulation. Significant differences in temperature were noted in same building archetypes in different pockets of the city indicating the role of urbanization in aggravating the impact of heat wave. Dwellings with high thermal mass are found to be much more resilient to high ambient temperatures as compared to code compliant residences with basements being the coolest zones in all prototypes.

Cities are facing the twin pressures of greenhouse gas driven climatic warming and locally induced urban heating. These pressures are threatening populations that are sensitive to extreme heat due to sociodemographic factors including economic means. Heat-reducing infrastructure adaptation measures such as reflective “cool” materials can reduce urban temperatures. Here we examine the needs-based equity implications associated with heat-reducing cool roofing in Maricopa County, Arizona through application of high-resolution urban-atmospheric simulations. We simulate heatwave conditions and evaluate the air temperature reduction arising from uniform cool roof implementation (i.e., the entire urbanized county), and contrast results against simulated cooling impacts of needs-based targeted cool roof implementation in sociodemographically heat sensitive areas. We find that installing cool roofs uniformly, rather than in a targeted fashion, provides on average 0.66 °C reduction in the highest heat sensitivity area and 0.39 °C temperature reduction in the lowest heat sensitivity area due in part to a higher roof area density in the heat sensitive area. Targeting cool roof implementation yields 0.45 °C cooling in the most sensitive areas compared to 0.22 °C cooling in the least sensitive areas, meaning that needs-based targeted cool roofs in high sensitivity areas provide more relief than cool roofs targeted at low sensitivity areas, thus providing more cooling where it is most needed. Needs-based targeted implementation has the dual benefits of concurrently producing more than twice as much cooling and reducing heat exposure for the largest absolute number of individuals in the densely populated, highly heat sensitive areas. Targeting cool roof implementation to high heat sensitivity areas, however, does not achieve thermally equal temperatures in Maricopa County because the high sensitivity areas were substantially warmer than low sensitivity areas prior to implementation. This study illustrates the utility of a new “Targeted Urban Heat Adaptation” (TUHA) framework to assess needs-based equity implications of heat-reducing strategies and underscores its importance by examining the impacts of cooling interventions across sociodemographically heterogeneous urban environments.

Despite recent advances in the development of detailed plant radiative transfer models, large-scale canopy models generally still rely on simplified one-dimensional (1-D) radiation models based on assumptions of horizontal homogeneity, including dynamic ecosystem models, crop models, and global circulation models. In an attempt to incorporate the effects of vegetation heterogeneity or “clumping” within these simple models, an empirical clumping factor, commonly denoted by the symbol Ω, is often used to effectively reduce the overall leaf area density and/or index value that is fed into the model. While the simplicity of this approach makes it attractive, Ω cannot in general be readily estimated for a particular canopy architecture and instead requires radiation interception data in order to invert for Ω. Numerous simplified geometric models have been previously proposed, but their inherent assumptions are difficult to evaluate due to the challenge of validating heterogeneous canopy models based on field data because of the high uncertainty in radiative flux measurements and geometric inputs. This work provides a critical review of the origin and theory of models for radiation interception in heterogeneous canopies and an objective comparison of their performance. Rather than evaluating their performance using field data, where uncertainty in the measured model inputs and outputs can be comparable to the uncertainty in the model itself, the models were evaluated by comparing against simulated data generated by a three-dimensional leaf-resolving model in which the exact inputs are known. A new model is proposed that generalizes existing theory and is shown to perform very well across a wide range of canopy types and ground cover fractions.

This is a comment to the paper "Magnitude of urban heat islands largely explained by climate and population" by Manoli et al. (2019, Nature 573 p. 55-60; https://doi.org/10.1038/s41586-019-1512-9)

Street trees are more and more regarded as a potential measure to mitigate the excessive heat in urban areas resulting from climate change and the urban heat island. However, the current knowledge of the cooling effect of street trees relies on studies at the micro-scale while potential interactions at the city-scale are yet to be understood. In fact, the vast majority of large-scale modelling studies only represent street trees outside the street canyon, neglecting important effects such as the shading and sheltering.In order to explicitly represent street trees in coupled urban climate simulation, the multi-layer urban canopy model BEP-Tree was coupled with the regional weather and climate model COSMO-CLM. The coupled model, named COSMO-BEP-Tree, enabled simulating the radiative, flow and energy interactions between street trees, canyon surfaces and the atmosphere during weather and climate simulations. In this study, COSMO-BEP-Tree is used to model the cooling potential of street trees during a heatwave event in Basel, Switzerland. The impact of street trees is explored in terms of near-surface air temperature and thermal comfort. The impact of greening scenarios is simulated and compared with other heat mitigation strategies.The results highlight contrasting urban climate effects of street trees during daytime and night-time, where different processes become dominant. The daytime cooling was primarily a local effect and proportional to the local density of street trees. In contrast, the impact was more widespread at night, where city-scale interactions become important. Beside air temperature, the model results suggest a significant impact of street trees on wind speed and canyon surface temperature. Owing to these effects, street trees produced a larger impact on thermal comfort than on air temperature. Finally, the need for further model development with respect to urban hydrology is outlined.

In mesoscale climate models, urban canopy flow is typically parameterized in terms of the horizontally averaged (1-D) flow and scalar transport, and these parameterizations can be informed by computational fluid dynamics (CFD) simulations of the urban climate at the microscale. Reynolds averaged Navier–Stokes simulation (RANS) models have previously been employed to derive vertical profiles of turbulent length scale and drag coefficient for such parameterization. However, there is substantial evidence that RANS models fall short in accurately representing turbulent flow fields in the urban roughness sublayer. When compared with more accurate flow modeling such as large-eddy simulations (LES), we observed that vertical profiles of turbulent kinetic energy and associated turbulent length scales obtained from RANS models are substantially smaller specifically in the urban canopy. Accordingly, using LES results, we revisited the urban canopy parameterizations employed in the one-dimensional model of turbulent flow through urban areas and updated the parameterization of turbulent length scale and drag coefficient. Additionally, we included the parameterization of the dispersive stress, previously neglected in the 1-D column model. For this objective, the PArallelized Large-Eddy Simulation Model (PALM) is used and a series of simulations in an idealized urban configuration with aligned and staggered arrays are considered. The plan area density (λp) is varied from 0.0625 to 0.44 to span a wide range of urban density (from sparsely developed to compact midrise neighborhoods, respectively). In order to ensure the accuracy of the simulation results, we rigorously evaluated the PALM results by comparing the vertical profiles of turbulent kinetic energy and Reynolds stresses with wind tunnel measurements, as well as other available LES and direct numerical simulation (DNS) studies. After implementing the updated drag coefficients and turbulent length scales in the 1-D model of urban canopy flow, we evaluated the results by (a) testing the 1-D model against the original LES results and demonstrating the differences in predictions between new (derived from LES) and old (derived from RANS) versions of the 1-D model, and (b) testing the 1-D model against LES results for a test case with realistic geometries. Results suggest a more accurate prediction of vertical turbulent exchange in urban canopies, which can consequently lead to an improved prediction of urban heat and pollutant dispersion at the mesoscale.

Urban climate models can predict the environmental impacts of urban development by simulating the exchange processes between the atmosphere and urban surfaces. A comprehensive simulation of urban climate requires adequate representation of the exchanges of momentum, heat, and water between the atmosphere and the impervious, vegetated, or soil surfaces. This study presents the inclusion of hydrological processes in a computationally-efficient urban micro-climate model, the Vertical City Weather Generator (VCWG v2.0.0). VCWG v2.0.0 accounts for not only the interaction between indoor and outdoor environments through parameterizations including building energy, surface energy balance, radiation, and vertical diffusion models, but also the biophysical and ecophysiological behavior of urban vegetation via an advanced hydrology model. VCWG v2.0.0 is evaluated against field measurements from Basel, Switzerland, in 2002, and Vancouver, Canada, in 2008. The model outperforms the previous version by reducing the RMSE of potential temperature, wind speed, and specific humidity by 0.5 K, 0.52 m s−1, and 0.001 kg kg−1, respectively. Inclusion of the hydrology model also improves prediction of sensible/latent heat fluxes with RMSE of 18.1/27.7 W m−2 for the Vancouver case. VCWG v2.0.0 is further assessed by explorations related to seasonal variations, modification of ground vegetation, green and cool roofs, and changes in the Local Climate Zone (LCZ), which are all in reasonable agreement with models and observations in previous studies. VCWG v2.0.0 can be used as a design, prediction, or investigation tool to understand how urban climate variables are influenced as a function of forcing environmental conditions and urban configurations.

Climate change and urban development are projected to substantially warm US cities, yet dynamic interaction between these two drivers of urban heat may modify the warming. Here, we show that business-as-usual GHG-induced warming and corresponding urban expansion would interact nonlinearly, reducing summer night-time warming by 0.5 K over the twenty-first century in most US regions. Nevertheless, large projected warming remains, particularly at night when the degree of urban expansion warming approaches that of climate change. Joint, high-intensity implementation of adaptation strategies, including cool and evaporative roofs and street trees, decreases projected daytime mean and extreme heat, but region- and emissions scenario-dependent nocturnal warming of 2–7 K persists. A novel adaptation strategy—lightweight urban materials—yields ~1 K night-time cooling and minor daytime warming in denser areas. Our findings highlight the diurnal interplay of urban warming and adaptation cooling, and underscore the inability of infrastructure-based adaptation to offset projected night-time warming, and the consequent necessity for simultaneous emissions reductions.

We introduce a multilayer model to estimate mean radiant temperature (MRT) and evaluate the pedestrian thermal comfort in a street canyon. This multilayer MRT model (MMRT) is suitable for urban streets with varying building and tree heights. The model simulates shortwave and longwave radiation exchange for each urban element and area-weighted view factors, then finally obtains MRT of pedestrians on the sidewalk. Probability density profiles of buildings and trees enable the consideration of urban vertical heterogeneity. Furthermore, Monte Carlo ray tracing (MCRT) allows the model to evaluate the radiation transfer in complex urban areas. We verify the effectiveness of MCRT and the probabilistic density profile approach. A sensitivity test conducted in Seoul on September 1, 2017 using the MMRT reveals that MRT can be reduced by 23 °C as the tree leaf area density increases from 0 to 1, and by 18 °C as the tree height increases from 0 m to 12 m in 1300 LST. The model controls urban form and pavement parameters as well as tree parameters. We aim to use this model to compare diverse MRT mitigation strategies and confirm the best strategy for thermal-friendly street design.

The influence of roof-edge roughness elements on airflow, heat transfer, and street-level pollutant transport inside and above a two-dimensional urban canyon is analyzed using an urban energy balance model coupled to a large-eddy simulation model. Simulations are performed for cold (early morning) and hot (mid afternoon) periods during the hottest month of the year (August) for the climate of Abu Dhabi, United Arab Emirates. The analysis suggests that early in the morning, and when the tallest roughness elements are implemented, the temperature above the street level increases on average by 0.5 K, while the pollutant concentration decreases by 2% of the street-level concentration. For the same conditions in mid afternoon, the temperature decreases conservatively by 1 K, while the pollutant concentration increases by 7% of the street-level concentration. As a passive or active architectural solution, the roof roughness element shows promise for improving thermal comfort and air quality in the canyon for specific times, but this should be further verified experimentally. The results also warrant a closer look at the effects of mid-range roughness elements in the urban morphology on atmospheric dynamics so as to improve parametrizations in mesoscale modelling.

Background Mobile air temperature monitoring is a promising method to better understand temperature distributions at fine spatial resolutions across urban areas. The study objectives were to collect microscale measurements for evaluate different data sources used to assess heat exposure in greater Vancouver, Canada. Methods Mobile air temperature monitoring was conducted on foot at least twice for each of 20 routes. First, the mobile data were compared with 1-minute measurements from the nearest fixed site. Second, the mobile data from runs corresponding with Landsat overpass days were compared with satellite-derived land surface temperature (LST). Third, the mobile data were compared with estimates from a previously developed heat map for the region. Results Mobile measurements were typically higher and more variable than simultaneous fixed site measurements. Correlations between mobile measurements and LST were weak and highly variable (r 2 = 0.04–0.38). The z-score differentials between mobile measurements and the heat map suggested that spatial variability in temperatures is captured by the heat map. Conclusion Microscale measurements confirm that fixed sites do not characterize the variability in thermal conditions within nearby streetscapes. Microscale monitoring of air temperatures is a valuable tool for temporally and spatially evaluating other high resolution temperature data within small areas.

This study aims to evaluate the effects of urban geometry on retrieval of emissivity and surface temperature in urban areas. An improved urban emissivity model based on sky view factor (IUEM-SVF) was further enhanced to consider all radiance contributions leaving the urban canopy, including (i) emission by all facets within an instantaneous field of view (IFOV); (ii) reflection by all facets of emission from surrounding facets; and (iii) propagation of emitted and reflected radiation with multiple reflections (scattering) within a complex 3D array of urban objects. The effective emissivity derived from IUEM-SVF was evaluated with a microscale radiative transfer and energy balance model: Temperatures of Urban Facets in 3-D (TUF-3D). IUEM-SVF performs well when urban facets have uniform emissivity and temperature; e.g., root mean square deviations (RMSD) are less than 0.005 when material emissivity is larger than 0.80 (ɛ ⩾ 0.80). However, when material emissivities are variable within the observed target, differences of effective emissivity between IUEM-SVF and TUF-3D become larger, e.g., RMSD of 0.010. When the effect of geometry is not considered and a mixed pixel emissivity is defined, the difference is even much larger (i.e. 0.02) and this difference increases with the decrease of sky view factor. Thus, the geometry effect should be considered in the determination of effective emissivity. Effective emissivity derived from IUEM-SVF was used to retrieve urban surface temperature from a nighttime ASTER thermal infrared image. Promising results were achieved in comparison with standard LST products retrieved with the Temperature and Emissivity Separation (TES) algorithm. IUEM-SVF shows promise as a means to improve the accuracy of urban surface temperature retrieval. The effect of thermal heterogeneity on the effective emissivity was also evaluated by TUF-3D, and results show that the thermal heterogeneity cannot be neglected since the RMSD between the effective emissivity based on TUF-3D and IUEM-SVF is relatively large.

In mesoscale climate models, urban canopy flow is typically parameterized in terms of the horizontally-averaged (1-D) flow and scalar transport, and these parameterizations can be informed by Computational Fluid Dynamics (CFD) simulations of the urban climate at the microscale. Reynolds Averaged Navier-Stokes Simulation (RANS) models have been previously employed to derive vertical profiles of turbulent length scale and drag coefficient for such parameterization. However, there is substantial evidence that RANS models fall short in accurately representing turbulent flow fields in the urban roughness sublayer. When compared with more accurate flow modeling such as Large Eddy Simulations (LES), we observed that vertical profiles of turbulent kinetic energy and associated turbulent length scales obtained from RANS models are substantially smaller specifically in the urban canopy. Accordingly, using LES results, we revisited the urban canopy parameterizations employed in the one-dimensional model of turbulent flow through urban areas, and updated the parameterization of turbulent length scale and drag coefficient. Additionally, we included the parameterization of the dispersive stress, previously neglected in the 1-D column model. For this objective, the PArallelized Large-Eddy Simulation Model (PALM) is used and a series of simulations in an idealized urban configuration with aligned and staggered arrays are considered. The plan area density is varied from 0.0625 to 0.44 to span a wide range of urban density (from sparsely developed to compact midrise neighborhoods, respectively). To ensure the accuracy of the simulation results, we rigorously evaluated the PALM results by comparing the vertical profiles of turbulent kinetic energy and Reynolds stresses with wind tunnel measurements, as well as other available LES and DNS studies. After implementing the updated drag coefficients and turbulent length scales in the 1-D model of urban canopy flow, we evaluated the results by a) testing the 1-D model against the original LES results, and demonstrating the differences in predictions between new (derived from LES) and old (derived from RANS) versions of the 1-D model, and b) testing the 1-D model against LES results for a test-case with realistic geometries. Results suggest a more accurate prediction of vertical turbulent exchange in urban canopies, which can consequently lead to an improved prediction of urban heat and pollutant dispersion at the mesoscale.