Single-layer Urban Canopy Model Research Articles

Integrating CityFFD and WRF for modeling urban microclimate under heatwaves

Urban atmospheric flow is characterized by meteorological processes and street-scale perturbations of microclimate wind velocity and air temperature distributions. The Weather Research and Forecasting model (WRF) is applied to investigate the effects of meteorological processes on temperature distribution over the Greater Montreal Area during the 2017 heatwave. The single-layer Urban Canopy Model is coupled with the WRF to estimate the heat fluxes from the canopy to the atmosphere. The mesoscale simulation results provide the boundary conditions for a new city-scale microclimate LES model, CityFFD. This study first validated the WRF model through multiple weather station measurements and the CityFFD model through the literature data, then investigated the impacts of three canyon aspect ratios and three anthropogenic heat regimes, i.e., surface temperature differences, on the boundary conditions setups. The strong anthropogenic heat assumption was applied to modeling the 2017 heatwave for three consecutive days using the integrated model. The transient results show that a difference of ∼4 m/s wind speed could result in a spatial temperature variation of up to 4 °C for the area under consideration. This study shows the importance of microclimate simulations for regional climate models when studying urban heatwaves.

Uncertainty and sensitivity analysis of modeling plant CO2 exchange in the built environment

The dynamics of carbon dioxide (CO2) exchange in the built environment, coupled with local microclimate modeling, is of critical importance to the understanding of emergent patterns of longterm urban climate evolution. In addition to the complex model physics, the difficulty is outstanding to characterize uncertainties inherited in the parameter space and its impact on the model performance and predictive skills. In this study, we conducted a series of numerical simulations based on advanced Markov chain Monte Carlo algorithms to quantify the sensitivity of a recently developed modeling framework by coupling the dynamics of CO2 transport into a single-layer urban canopy model. The results show that urban morphology (canyon aspect ratio), irrigation, and the physiological properties of urban vegetation predominate the processes of plant CO2 exchange in the built environment. In contrast, the CO2 budget is relatively insensitive to material properties of urban facets in the built environment. The findings in this study can help to unravel the interplay of urban carbon dynamics and the built environment, as well as to inform researchers and policy makers for sustainable urban development towards a low carbon city.

Comparison of Urban Heat Island Intensity Estimation Methods Using Urbanized WRF in Berlin, Germany

In this study, we present a meso-scale simulation of the urban microclimate in Berlin, Germany, using the Weather Research and Forecasting (WRF) numerical weather prediction platform. The objective of the study is to derive an accurate estimate of the near-surface urban heat island (UHI) intensity. The simulation is conducted over a two-week summer period. We compare different physical schemes, different urban canopy schemes and different methods for estimating the UHI intensity. The urban fraction of each urban category is derived using the Copernicus Impervious Density data and the Corine Land Cover data. High-resolution City Geography Markup Language (CityGML) data is used to estimate the building height densities required by the multi-layer urban canopy model (UCM). Within the single-layer UCM, we implement an anthropogenic heat profile based on the large scale urban consumption of energy (LUCY) model. The optimal model configuration combines the WRF Single Moment Five-Class (WSM5) microphysics scheme, the Bougeault–Lacarrère planetary boundary layer scheme, the eta similarity (Mellor–Yamada–Janjic) surface layer scheme, the Noah Multi-Parameterization land surface model, the Dudhia and Rapid Radiative Transfer Model (RRTM) radiation schemes, and the multi-layer UCM (including the building energy model). Our simulated UHI intensity results agree well with measurements with a root mean squared error of 0.86K and a mean bias error of 0.20K. After model validation, we proceed to compare several UHI intensity calculation methods, including the ‘ring rural reference’ (RRR) method and the ‘virtual rural reference’ (VRR) method. The VRR mthod is also known as the ‘urban increment’ method. We suggest and argument that the VRR approach is superior.

Impact of Urbanization on Heavy Rainfall Events: A Case Study over the Megacity of Bengaluru, India

This study is about the simulation and observational analysis of a heavy rainfall event (HRE) and its sensitivity to land-use changes. The impact of urbanization on processes and mechanisms of rainfall including cloud processes is discussed. This study is based on high-resolution (2 km), time-ensemble simulation of one of the HREs that occurred on 27 May 2017 over the city of Bengaluru in the southern part of India. The simulations are carried out using the Weather Research and Forecasting (WRF) model, which is coupled with a single-layer urban canopy model (UCM). The high-resolution (30 s) land-use data derived from the Indian Space Research Organization (ISRO) for the year 2016–2017 is shown to be realistic in representing the current land-use scenario with a threefold increase in urbanization when compared to USGS land-use data of 1991–1992. Simulation and analysis of large-scale circulation patterns revealed that the event was triggered and sustained by the low-pressure system and cyclonic circulation over the Bay of Bengal. Simulated rainfall was found to be remarkably sensitive to land-use changes as shown by control (USGS) and test (ISRO) simulations. The rainfall intensity and spatial distribution are close to observation in test simulations with relatively less error at station scale with a correlation of 0.49 (95% significance) when compared to control simulations, indicating the importance of realistic representation of land use in the model and its impact on heavy rainfall processes. The test simulation which represents the current urbanization scenario has shown a significant increase in rainfall by over 100–200%. The surface energy fluxes and thermodynamic indices as shown by test simulations are favorable to HREs, and also consistent with the current land-use scenario with increased urbanization. This study demonstrated how a realistic representation of land-use data in the model can help to improve model skill. The main limitation of this research work is that it is based on the generic parameterization of urbanization using single-layer UCM. An in-depth study based on multi-layer UCM and city-specific parameterization of urbanization using sub-kilometer-scale land-use data including buildings would further enhance our understanding on this subject.

Improving the accuracy of simplified urban canopy models for arid regions using site-specific prior information

An overly complex urban climate/energy model would not be of much practical use in a decision support setting where a large number of year-long simulations are often necessary. While detailed modeling of urban momentum/energy exchanges can be attempted via Computational Fluid Dynamics (CFD) or mesoscale modeling, conducting multiple full year simulations in a design optimization or sensitivity analysis context is practically impossible. Furthermore, CFD models often do not consider climate/building energy exchanges. To address these limitations, standalone Urban Canopy Models (UCMs) have been developed, attempting to replace the full-fledged atmospheric representation with a computationally light equivalent. In this study, we investigate the impact of several modifications to a standalone Single-Layer Urban Canopy Model (SLUCM) for an arid region based on the prior availability of site-specific information. The suggested improvements are portable to SLUCM schemes incorporated within mesoscale models. The SLUCM will undergo several improvements and each variant will be evaluated based on its ability to predict UHI intensity and air-conditioning energy demand. Three original SLUCM improvements are covered in the present study. (1) We use actual radiation parameters instead of those generated for idealized geometries. It is shown that, in the absence of this improvement, standard UCMs can underestimate the average urban heat island intensity by 5% if using the Town Energy Balance (TEB) radiation scheme or overestimate it by 7% if using the Square Prism Urban Canopy (SPUC) radiation scheme. (2) We use the results of a prior steady-state RANS (Reynolds-Averaged Numerical Simulation) simulation to replace some of the default morphological parameters of the UCM by the more accurate values derived from the RANS results. It is shown that, in the absence of this improvement, standard UCMs using default empirical relations can overestimate the average urban heat island intensity by up to 22%. (3) Instead of using the empirically calculated default value of the urban canyon wind speed, we estimate it directly from the concomitant rural value using a regression model trained by historical measurements. It is shown that, in the absence of this improvement, standard UCMs can underestimate the average canyon wind velocity by more than 12%, although the other indicators (UHI, cooling demand) are not significantly affected.

Evaluating the performance of WRF urban schemes and PBL schemes over Dallas Fort Worth during a dry summer and a wet summer

AbstractThis study evaluated the Weather Research and Forecasting (WRF) model sensitivity to different planetary boundary layer (PBL) schemes (the YSU and MYJ schemes) and urban schemes including the bulk scheme (BULK), single-layer urban canopy model (UCM), multi-layer building environment parameterization (BEP) model, and multi-layer building energy model (BEM). Daily reinitialization simulations were conducted over Dallas-Fort Worth during a dry summer month (July 2011) and a wet summer month (July 2015) with weaker (stronger) daytime (nocturnal) UHI in 2011 than 2015. All urban schemes overestimated the urban daytime 2m temperature in both summers, but BEP and BEM still reproduced the daytime urban cool island in dry summer. All urban schemes reproduced the nocturnal urban heat island, with BEP producing the weakest one due to its unrealistic urban cooling. BULK and UCM overestimated the urban canopy wind speed, while BEP and BEM underestimated it. The urban schemes showed prominent impact on daytime PBL profiles. UCM+MYJ showed a superior performance than other configurations. The relatively large (small) aspect ratio between building height and road width in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy temperature. The relatively low (high) building height in UCM (BEM) was responsible for the overprediction (underprediction) of urban canopy wind speed. Improving urban schemes and providing realistic urban parameters were critical for improving urban canopy simulation.

Modeling carbon dioxide exchange in a single-layer urban canopy model

Carbon dioxide (CO2) is the primary greenhouse gas that drives the global climate change in past centuries. Much effort of carbon mitigation as a countermeasure to global changes has focused on the urban areas – the hotspots of fossil fuel and concentrated emission and pollutants. Despite their critical role in CO2 exchange in urban ecosystem, emission from vegetation and soils are largely overlooked in existing urban land surface models. In this study, we parameterized the biogenic CO2 exchange in cities using an advanced single-layer urban canopy model, by incorporating plant physiological functions in the built environment. In addition, the proposed model also includes the anthropogenic CO2 fluxes especially that from traffic emissions based on gridded dataset. We evaluate the proposed model using field measurements from an eddy covariance flux tower located at west Phoenix, Arizona, USA. The model results are in good agreement with the observed carbon flux over the built terrain, with a root mean squared error of 0.21 mg m−2s−1. Furthermore, our simulations show that the abiotic traffic-emitted CO2 amounts the largest source in cities, as expected. Nevertheless, the biogenic carbon exchange can be significantly enhanced in the built environment, making an equally important contributor to the total carbon emission especially in sub-urban areas.

WRF‐TEB: Implementation and Evaluation of the Coupled Weather Research and Forecasting (WRF) and Town Energy Balance (TEB) Model

AbstractUrban land surface processes need to be represented to inform future urban climate and building energy projections. Here, the single layer urban canopy model Town Energy Balance (TEB) is coupled to the Weather Research and Forecasting (WRF) model to create WRF‐TEB. The coupling method is described generically, implemented into software, and the code and data are released with a Singularity image to address issues of scientific reproducibility. The coupling is implemented modularly and verified by an integration test. Results show no detectable errors in the coupling. Separately, a meteorological evaluation is undertaken using observations from Toulouse, France. The latter evaluation, during an urban canopy layer heat island episode, shows reasonable ability to estimate turbulent heat flux densities and other meteorological quantities. We conclude that new model couplings should make use of integration tests as meteorological evaluations by themselves are insufficient, given that errors are difficult to attribute because of the interplay between observational errors and multiple parameterization schemes (e.g., radiation, microphysics, and boundary layer).

Modelling urban meteorology with increasing refinements for the complex morphology of a typical Chinese city (Xi'an)

Urban areas are vulnerable to intensive heatwave periods. In order to understand heat stress in cities, the single-layer urban canopy model (SLUCM) coupled with the weather research and forecasting model (WRF) have been widely used to quantify and forecast the urban climate. However, the model performance in WRF/SLUCM is limited by the coarse classification of urban canopy parameters (UCPs), and further improvements may require great effort. Therefore, this study was a new attempt at organizing the gridded UCPs in the ‘National Urban Database and Access Portal Tool (NUDAPT) approach’ and exploring its application in the WRF/SLUCM model in four simulations with contrasting UCP configurations. The model performances were evaluated for a heatwave period in 2018 in the typical Chinese city of Xi'an, using a near-surface observational network consisting of 39 meteorological stations in various urban spatial categories. We found that the increased accuracy in UCPs brought about gradual and overall improvements in the urban heat island effect (UHI) and air temperature (Ta), and had relatively slight effects on absolute humidity (ρν) and wind speed (WP). Furthermore, the station-to-station bias analyses indicated that optimization efficiency varied among urban spatial categories. Areas with an open form or areas densely covered with vegetation showed constant sensitivity to the increasing refinements of UCPs. Input of the gridded and multi-dimensional descriptions of urban canyon geometry contributed to more accurate results in dense urban areas and areas with mixed and inhomogeneous morphology.

Enhanced software and platform for the Town Energy Balance (TEB) model

The Town Energy Balance (TEB) model (Masson, 2000) is a physically based single layer Urban Canopy Model (UCM) to calculate the urban surface energy balance at neighborhood scale assuming a simplified canyon geometry. It includes several capabilities (Table 1) that have been extensively evaluated offline with flux observations (Lemonsu, Grimmond, & Masson, 2004; Leroyer, Mailhot, Belair, Lemonsu, & Strachan, 2010; Masson, Grimmond, & Oke, 2002; Pigeon, Moscicki, Voogt, & Masson, 2008) and online coupled to atmospheric models such as ALARO (Gerard, Piriou, Brožkova, Geleyn, & Banciu, 2009) in ALARO-TEB (Hamdi, Degrauwe, & Termonia, 2012), the Global Environmental Multiscale (GEM; Cote et al. (1998)) in GEM-TEB (Lemonsu, Belair, & Mailhot, 2009), Meso-NH (Lac et al., 2018; Lafore et al., 1998) in TEB-MesoNH (Lemonsu & Masson, 2002), the Regional Atmospheric Modeling System (RAMS; Pielke et al. (1992)) in RAMS-TEB (Freitas, Rozoff, Cotton, & Dias, 2007), the Advanced Regional Prediction System (ARPS; Xue et al., (2000)) in ARPS-TEB (Rozoff, Cotton, & Adegoke, 2003), and the Weather Research and Forecasting (WRF; Skamarock et al. (2019)) in WRF-TEB (Meyer et al., 2020). Here, we present an enhanced software and platform for the TEB model to help scientists and practitioners wishing to use the TEB model in their research as a standalone software application or as a library in their own software. This includes several features such as crossplatform support for Windows, Linux, and macOS using CMake (Kitware Inc., 2020), static and dynamic library generation for integration with other software/models, namelist-based configuration, integration with MinimalDX (Meyer & Raustad, 2019) and PsychroLib (Meyer & Thevenard, 2019) to improve the modelling of air conditioners (AC) and psychrometric calculations respectively, a thin interface used in the coupling with WRF-CMake (Riechert & Meyer, 2019), helper functions for Python for pre- and post-processing inputs and outputs files, and a tutorial in Jupyter Notebook to allow users to quickly become familiar with the general TEB modeling workflow. In the new platform we implement testing at every code commit through continuous integration (CI) and automate the generation of documentation. The project is developed as a free, open source, community-driven project on GitHub (https://github.com/teb-model/teb) to support existing and new model applications with enhanced functionality. We welcome contributions and encourage users to provide feedback, bug reports and feature requests, via GitHub’s issue system at https://github.com/teb-model/teb/issues

Numerical assessment of the urban green space scenarios on urban heat island and thermal comfort level in Tehran Metropolis

The growing rate of urbanization and alterations in natural land-use/land-cover properties cause many worldwide environmental issues such as Urban Heat Island (UHI), low Thermal Comfort Level (TCL) and air pollution in megacities. Development of urban green spaces is one of the most proposed measures for mitigation of UHI and improvement of thermal comfort satisfaction which causes lower cooling energy consumption and indirectly improves the urban air quality. Therefore, the efficiency of realistic and executable green scenarios in both surface and roof levels (surface vegetation, green roof, surface vegetation + green roof) on early summertime UHI and TCL are evaluated and compared in Tehran Metropolis, using coupled Weather Research and Forecasting model with Single Layer Urban Canopy Model (WRF/SLUCM). Model predefined urban parameters (the urban density and vegetation fraction) are modified before the main simulations by data of remote-sensing methods which let us define surface green spaces developmental scenarios without any change in the basic urban morphology. Results are presented for three areas with different urban morphologies (Low and High-Intensity Residential (LR and HR) and Commercial and Industrial (C/I)). Three indexes (THI, ETI and RSI) are calculated for assessing TCL variations. Generally, results show that environmental operations of selected scenarios are different over selected areas. In LR area, diurnal cooling (up to −0.86 °C in green roof approach) and improvement in thermal comfort condition are observed in all scenarios. On the other hand, in HR and C/I areas, the daytime cooling (nighttime warming) effect up to −0.85 °C (up to +0.63 °C) in the third scenario are simulated. TCL alterations show similar deteriorating nightly effects in all scenarios in selected regions. Averaged diurnal decrease in wind speed is another undesirable impact of green development scenarios due to the enhanced surface roughness that can reduce urban natural heat and pollution ventilations. Current results clarify that the adoption of efficient urban green spaces programs needs to consider different environmental concerns. By comparison between roof level and surface greenery, it can be concluded that the green roof approach with the least undesirable nightly effects is a more efficient approach than surface vegetation development in high-density Tehran megacity.

Response of Near-Surface Meteorological Conditions to Advection under Impact of the Green Roof

Due to rapid urbanization, the near-surface meteorological conditions over urban areas are greatly modulated. To capture such modulations, sophisticated urban parameterizations with enhanced hydrological processes have been developed. In this study, we use the single-layer urban canopy model (SLUCM) available within the Weather Research and Forecasting (WRF) model to assess the response of near-surface temperature, wind, and moisture to advection under the impact of the green roof. An ensemble of simulations with different planetary boundary layer (PBL) schemes is conducted in the presence (green roof (GR)) and absence (control (CTL)) of green roof systems. Our results indicate that the near-surface temperature is found to be driven primarily by the surface heat flux with a minor influence from the zonal advection of temperature. The momentum budget analysis shows that both zonal and meridional momentum advection during the evening and early nighttime plays an important role in modulating winds over urban areas. The near-surface humidity remains nearly unchanged in GR compared to CTL, although the physical processes that determine the changes in humidity were different, in particular during the evening when the GR tends to have less moisture advection due to the reduced temperature gradient between the urban areas and the surroundings. Implications of our results are discussed.

Re-Naturing Cities: Evaluating the effects on future air quality in the city of Porto

The effect of different “green” measures, such as the increase of urban green areas, the application of green roofs and the increase of surfaces albedo on urban air quality were evaluated with the WRF-CHIMERE modelling system. In order to account for the heterogeneity of urban areas, a single layer urban canopy model was coupled to the WRF model. The case study consists of a heat wave occurring in the Porto (Portugal) urban area in a future climate scenario, considering the Representative Concentration Pathway RCP8.5. The influence of the selected measures on PM10, NO2 and O3 concentrations was quantified and compared with a control run (without measures) simulation scenario. The results revealed that all the measures are able to mitigate the effects of heat waves by reducing the air temperature between −0.5 °C and −1 °C (maximum differences for the mean of the episode). Positive and negative effects were found in terms of air quality. The implementation of green roofs and the increase of surfaces albedo promoted an overall increase of PM10 (between +0.6% and +1.5%) and NO2 (between +0.8% and 3.5%) concentrations, which are closely related to a decrease of vertical mixing in the urban boundary layer. The increase of green urban areas promoted an overall decrease (on average) of both PM10 and NO2, by around −1% and −3%, respectively. The O3 levels increased with the increase of urban green areas, mostly located over the Porto urban area. Slight differences were promoted by the implementation of green roofs. For the increase of surfaces albedo, both increases and decreases of O3 concentrations were observed. The obtained results contribute to the knowledge of the chemical composition of the urban atmosphere and can be of great importance for stakeholders and decision-makers to deal with climate change impacts.

Evaluation of employing local climate zone classification for mesoscale modelling over Beijing metropolitan area

Urban land use and landscape morphology exert notable influences on local climate and its surrounding environment. Better understanding of the complex interplay between urban landscape and overlying atmosphere could contributes to decision-making related to urban planning and risk assessment. This paper classifies local climate zones (LCZs) over Beijing metropolitan area following the World Urban Database and Access Portal Tools (WUDAPT) level 0 method, and evaluates the effect of LCZ classification on mesoscale Weather Research and Forecasting (WRF) modelling over the city. Specifically, according to the method proposed by Stewart and Oke (Bull Am Meteor Soc 93(12):1879–1900, https://doi.org/10.1175/BAMS-D-11-00019.1, 2012), the LCZ classification across Beijing is created based on the Landsat imagery of the Earth’s surface. The derived LCZ system is then imported to the WRF model, and coupled to different urban canopy schemes, i.e. single-layer urban canopy model (SLUCM), multi-layer urban canopy model (BEP—building effect parameterization), and the BEP model with a simple building energy model (BEP + BEM). The performance of employing this refined land use classification scheme versus those using United States Geological Survey land use data is evaluated by comparisons with weather station observations. The results, e.g. the spatial distribution of 2-m temperature and the diurnal variation of the surface heat fluxes, indicate that the LCZ classification scheme yields better comparisons than the default land use method, especially when coupled to the SLUCM as compared to BEP and BEP + BEM. This finding qualifies the coupling scheme of LCZ and SLUCM as a promising albeit simple option for weather modelling in a finer resolution.

Numerical evaluation of urban green space scenarios effects on gaseous air pollutants in Tehran Metropolis based on WRF-Chem model

Although positive environmental aspects of increasing urban vegetative spaces are undeniable, using predefined or unmanaged long-term green programs may cause undesirable and unexpected impacts on the air quality in megacities. In this study, the mitigation potential of three green spaces development scenarios (expansion of surface vegetative area, Green Roof development and combination of surface and roof greenery) on three gaseous air pollutants (O3, SO2 and NO2) concentrations in Tehran Metropolis in an early summertime period is analyzed using coupled Weather Research and Forecasting model with chemistry (WRF/Chem), single-layer urban canopy model (SLUCM) and biogenic emission from Model of Emissions of Gases and Aerosols from Nature (MEGAN). Current results indicate that general patterns of diurnal distribution of SO2 and NO2 are totally controlled by the location of anthropogenic sources of pollutants in the south and the city center, beside the prevailing wind field over the city of Tehran. Ozone distribution follows the diurnal advection from the northern and eastern sub-urban areas and distribution of primary pollutants such as NO2. By conducting green scenarios, reduction in the wind speed, variations in pollutants dry deposition velocities which are directly affected by the boundary layer and surface properties, and pollutants deposition fluxes are observed. Alterations in deposition fluxes are not uniform across the city area and clearly conform to changes in pollutants concentrations. In addition, the shallower (deeper) boundary layer height and the buoyancy forcing due to the reduction (increase) in near-surface air temperature cause less (more) vertical mass transport during the day (night), which in both situations could have negative impacts on the air quality since under lower wind speed condition and less convective upward transfer, polluted air near the surface can be trapped. The defined scenarios have shown different impacts over the city of Tehran with the complex urban morphology so, suggestion of the most efficient summertime green policy with the minimum negative feedbacks is not conceivable.

Effectiveness of vegetated patches as Green Infrastructure in mitigating Urban Heat Island effects during a heatwave event in the city of Melbourne

The city of Melbourne in southeast Australia experiences frequent heatwaves and their frequency, intensity and duration are expected to increase in the future. In addition, Melbourne is the fastest growing city in Australia and experiencing rapid urban expansion. Heatwaves and urbanization contribute in intensifying the Urban Heat Island (UHI) effect, i.e., higher temperatures in urban areas as compared to surrounding rural areas. The combined effects of UHI and heatwaves have substantial impacts on the urban environment, meteorology and human health, and there is, therefore, a pressing need to investigate the effectiveness of different mitigation options. This study evaluates the effectiveness of urban vegetation patches such as mixed forest (MF), combination of mixed forest and grasslands (MFAG), and combination of mixed shrublands and grasslands (MSAG) in reducing UHI effects in the city of Melbourne during one of the most severe heatwave events. Simulations are carried out by using the Weather Research and Forecasting (WRF) model coupled with the Single Layer Urban Canopy Model (SLUCM). The fractions of vegetated patches per grid cell are increased by 20%, 30%, 40% and 50% using the mosaic method of the WRF model. Results show that by increasing fractions from 20 to 50%, MF reduces near surface (2 m) UHI (UHI2) by 0.6–3.4 °C, MSAG by 0.4–3.0 °C, and MFAG by 0.6–3.7 °C during the night, but there was no cooling effect for near surface temperature during the hottest part of the day. The night-time cooling was driven by a reduction in storage heat. Vegetated patches partitioned more net radiation into latent heat flux via evapotranspiration, with little to no change in sensible heat flux, but rather, a reduction in the storage heat flux during the day. Since the UHI is driven by the release of stored heat during the night, the reduced storage heat flux results in reductions in the UHI. The reductions of the UHI2 varied non-linearly with the increasing vegetated fractions, with lager fractions of up to 50% resulting in substantially larger reductions. MF and MFAG were more effective in reducing UHI2 as compared to MSAG. Vegetated patches were not effective in improving HTC during the day, but a substantial improvement of HTC was obtained between the evening and early morning particularly at 2100 local time, when the thermal stress changes from strong to moderate. Although limited to a single heatwave event and city, this study highlights the maximum potential benefits of using vegetated patches in mitigating the UHI during heatwaves and the overall principles are applicable elsewhere.

Evaluation of urban surface parameterizations in WRF model using energy fluxes measurements in Portugal

The performance of WRF model was investigated for the simulation of urban microclimate, with particular focus on energy fluxes, using different urban surface parameterizations. The model performance was evaluated using measurements carried out between August and December 2014 in Portugal. Several simulations were performed over two different areas, Porto urban area and Aveiro suburban area, for the entire measurement period. Distinct simulations were performed using different urban parametrizations: (i) the Noah Land Surface Model (LSM); (ii) a single-layer urban canopy model (UCM); and (iii) a modelling system composed by WRF and SUEWS models (WRF-SUEWS).The results showed that both UCM and SUEWS are able to simulate the energy partitioning over the low and high intensity residential. At the low intensity residential area, the majority of energy is partitioned to latent heat flux, accounting on average for 47% and 49% of the daytime available energy, for UCM and SUEWS, respectively. At the high intensity residential area, the greatest share of energy goes to sensible heat flux (42% [UCM] and 50% [SUEWS]), followed by the storage heat flux (33% [UCM] and 43% [SUEWS]). For both areas, a completely different energy partitioning was obtained when the LSM was used. The analysis performed showed that the UCM are able to provide a more accurate turbulent energy partitioning (sensible and latent heat), which contribute to enhance the urban microclimate simulation results; the systematic model biases in the LSM simulation was reduced by 1–2 °C in air temperature and by 0.5–1 m s−1 in wind speeds at near surface layer, on average, depending on the urban density. The overall results suggest that an appropriate representation of urban physical processes are crucial to improve numerical tools suited for the modelling of the urban atmospheric boundary layer.

Surface to boundary layer coupling in the urban area of Lisbon comparing different urban canopy models in WRF

This work presents a sensitivity study to evaluate different Urban Canopy Models (UCM) existing within the Weather Research and Forecasting Model (WRF) in the urban area of Lisbon, Portugal. Several hind-cast simulations were carried out for a selected period in July 2010, in which synoptic conditions favoured urban heat island formation. We aim to gain knowledge on the feedback of modified urban canopy representation in WRF on local scale meteorology and the boundary-layer dynamics over the urban area, by comparing a single layer urban canopy model (SLUCM) and a more sophisticated multi-layer building effect parametrisation (BEP). We find significant differences in the characteristics of the urban boundary layer between BEP and SLUCM, manifested through changes in turbulent kinetic energy (TKE) and urban boundary layer (UBL) height over the urban centre. Compared to ground observations and radiosonde data retrieved within the core urban area, both variables are better represented by BEP compared to SLUCM. Simulating perturbations of vertical wind components and temperature we can show a general amplification and displacement of modelled gravity waves over the central urban area under the prevailing synoptic conditions when a multi-layer canopy model is used instead of a single-layer model or a bulk approach.

Effects of urbanization on regional meteorology and air quality in Southern California

Abstract. Urbanization has a profound influence on regional meteorology and air quality in megapolitan Southern California. The influence of urbanization on meteorology is driven by changes in land surface physical properties and land surface processes. These changes in meteorology in turn influence air quality by changing temperature-dependent chemical reactions and emissions, gas–particle phase partitioning, and ventilation of pollutants. In this study we characterize the influence of land surface changes via historical urbanization from before human settlement to the present day on meteorology and air quality in Southern California using the Weather Research and Forecasting Model coupled to chemistry and the single-layer urban canopy model (WRF–UCM–Chem). We assume identical anthropogenic emissions for the simulations carried out and thus focus on the effect of changes in land surface physical properties and land surface processes on air quality. Historical urbanization has led to daytime air temperature decreases of up to 1.4 K and evening temperature increases of up to 1.7 K. Ventilation of air in the LA basin has decreased up to 36.6 % during daytime and increased up to 27.0 % during nighttime. These changes in meteorology are mainly attributable to higher evaporative fluxes and thermal inertia of soil from irrigation and increased surface roughness and thermal inertia from buildings. Changes in ventilation drive changes in hourly NOx concentrations with increases of up to 2.7 ppb during daytime and decreases of up to 4.7 ppb at night. Hourly O3 concentrations decrease by up to 0.94 ppb in the morning and increase by up to 5.6 ppb at other times of day. Changes in O3 concentrations are driven by the competing effects of changes in ventilation and precursor NOx concentrations. PM2.5 concentrations show slight increases during the day and decreases of up to 2.5 µg m−3 at night. Process drivers for changes in PM2.5 include modifications to atmospheric ventilation and temperature, which impact gas–particle phase partitioning for semi-volatile compounds and chemical reactions. Understanding process drivers related to how land surface changes effect regional meteorology and air quality is crucial for decision-making on urban planning in megapolitan Southern California to achieve regional climate adaptation and air quality improvements.

On‐ and off‐line evaluation of the single‐layer urban canopy model in London summertime conditions

Urban canopy models are essential tools for forecasting weather and air quality in cities. However, they require many surface parameters, which are uncertain and can reduce model performance if inappropriately prescribed. Here, we evaluate the model sensitivity of the single‐layer urban canopy model (SLUCM) in the Weather Research and Forecasting (WRF) model to surface parameters in two different configurations, one coupled to the overlying atmosphere (on‐line) in a 1D configuration and one without coupling (off‐line). A two‐day summertime period in London is used as a case study, with clear skies and low wind speeds. Our sensitivity tests indicate that the SLUCM reacts differently when coupled to the atmosphere. For certain surface parameters, atmospheric feedback effects can outweigh the variations caused by surface parameter settings. Hence, in order to fully understand the model sensitivity, atmospheric feedback should be considered.