Multilayer Urban Canopy Model Research Articles

Simulation of a cold spell in Guangdong-Hong Kong-Macao Greater Bay Area with WRF: Sensitivity to PBL schemes

The selection of the planetary boundary layer (PBL) parameterisation schemes is crucial for the simulation of local meteorology, especially under extreme weather events. A suitable PBL scheme is one of the key conditions to accurately reproduce the real weather conditions. In this study, the performance of all the three available PBL schemes that can be coupled with the multi-layer urban canopy model in the Weather Research and Forecasting (WRF) model: Yonsei University (YSU), Mellor-Yamada-Janjic (MYJ), and Bougeault-Lacarrere (BL), is evaluated for a cold spell event with Guangdong-Hong Kong-Macao Greater Bay Area (GBA) as the study region. It is found that accurate prediction of the strength of the vertical mixing and the change in wind speeds over the upper atmosphere is critical for reproducing the nighttime temperatures during the cold spell. The simulations of the BL scheme are consistent with observations that wind speeds do not vary much during daytime and nighttime, thus exhibiting strong vertical mixing and slowing down the near-surface temperature decrease during nighttime. The MYJ and YSU schemes cause significant underestimation of the nighttime 2-m temperature due to significant overestimation of the nighttime upper-air wind speeds, which leads to more heat transport through horizontal advection and hinders vertical mixing and convective activities. The results confirm that selection of a suitable PBL scheme can effectively reduce the uncertainty of the simulation results, and the coupling of the BL scheme with the multi-layer urban canopy model can better simulate the cold spell events occurring in the GBA, which also provides valuable references for the simulation of other similar coastal cities.

Influence of urbanization on meteorological conditions and ozone pollution in the Central Plains Urban Agglomeration, China

Changes in aerodynamic and thermal conditions caused by urbanization can impact regional meteorological conditions, subsequently affecting air quality. Updated Moderate-resolution Imaging Spectroradiometer (MODIS) land use data and coupled with the urban canopy models (UCMs) in the Weather Research and Forecasting (WRF) model. This enabled the impact of urban land expansion on meteorological conditions and ozone (O3) concentrations to be evaluated. Urban expansion increased the temperature at 2 m (T2) and the probability of precipitation in urban expansion areas, and enhanced the surface urban heat island at night. As the expansion areas became progressively larger, the increase in T2 became more pronounced. The proportions of urban surfaces in June 2016, 2018, and 2020 compared to 2001 increased by 0.69%, 0.83%, and 1.04%, respectively, while T2 increased by 0.12, 0.19, and 0.20 °C in urban areas, respectively. With urban expansion, the O3 concentration increased by 1.12, 1.37, and 0.76 μg/m3 (three-year averages) in urban, suburban, and rural areas, respectively. After coupling a multi-layer urban canopy model (building effect parameterization, BEP), or a multi-layer urban canopy model with a building energy model including anthropogenic heat due to air conditioning (BEP + BEM, abbreviated as BEM simulation), the O3 concentration changed significantly in the urban expansion area, compared to the results of a single-layer urban canopy model (UCM). O3 concentrations decreased most in the BEP simulation (−0.77 μg/m3), while O3 concentrations increased most in the BEM simulation (+1.85 μg/m3). The average observed O3 concentration was 108.35 μg/m3 (three-year average), while the simulated value was 75.65–83.72 μg/m3 (R = 0.69−0.77). The validation results in the BEM and Global Optimal Scenario (GOS) simulations were relatively good, with the GOS simulation producing slightly better results than the BEM. The simulation of O3 in urban agglomerations could be improved by integrating the results of the UCMs.

A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)

Abstract. In recent years, urban canopy models (UCMs) have been used as fully coupled components of mesoscale atmospheric models as well as offline tools to estimate temperature and surface fluxes using atmospheric forcings. Examples include multi-layer urban canopy models (MLUCMs), where the vertical variability of turbulent fluxes is calculated by solving prognostic momentum and turbulent kinetic energy (TKE, k) using mixing length scale (l) and drag parameterizations. These parameterizations are based on the well-established 1.5-order k−l turbulence closure theory and are often informed by microscale fluid dynamics simulations. However, this approach can include simplifications such as assuming the same diffusion coefficient for momentum, TKE, and scalars. In addition, the dispersive stresses arising from spatially averaged flow properties have been parameterized together with the turbulent fluxes despite being controlled by different mechanisms. Both of these assumptions impact the quantification of the turbulent exchange of flow properties and subsequent air temperature predictions in urban canopies. To assess these assumptions and improve corresponding parameterization, we analyzed 49 large-eddy simulations (LES) for idealized urban arrays, encompassing variable building height distributions and a comprehensive range of urban densities (λp∈[0.0625,0.64]) seen in global cities. We find that the efficiency of turbulent transport (numerically described via diffusion coefficients) is similar for scalars and momentum but is 3.5 times higher for TKE. Additionally, parameterizing the dispersive momentum flux using the k−l closure was a source of error, while scaling with the pressure gradient and urban morphological parameters appears more appropriate. In response to these findings, we propose two changes to the previous version of MLUCM: (a) separate characterization for turbulent diffusion coefficient for momentum and TKE and (b) introduction of an explicit physics-based “mass-flux” term to represent the fraction of the dispersive momentum transport directly induced from buildings as an amendment to the existing “eddy-diffusivity” framework. The updated one-dimensional model, after being tuned for building height variability, is further compared against the original LES results and demonstrates improved performance in predicting vertical turbulent exchange in urban canopies.

Modelling Radiative Coolers for the Built Environment in the Urban Context

AbstractRadiative Coolers (RCs) represent an emerging technology that has the potential to significantly reduce urban heat and improve indoor/outdoor thermal comfort in the built environment. Broadband and Selective Radiative Coolers (BRCs and SRCs, respectively) are the two main types of RCs that have been proposed for application in the built environment. Being both typically characterized by high solar reflectance, the former emits thermal radiation within the overall infrared spectrum, whilst the latter emits thermal radiation mainly within the Atmospheric Window (AW) waverange. A variety of both types of RCs have been developed and tested in both in‐lab and in‐field experimental campaigns. Yet, all experiments comprise small scale specimens that do not represent real‐life scale components of the built environment. In addition, no meso scale assessments have been performed with respect to the RCs' performance at a city scale. Here, for the first time, the thermo‐optical performance of both BRCs and SRCs is introduced and investigated in a multilayer Urban Canopy Model (UCM) coupled with extended Weather Research and Forecasting model (WRF) and we simulated 20 different scenarios representing the vast majority of urban layouts. The outcomes show that both types of RCs maintain lower surface temperature and air temperature at 2 m height inside the canyon, compared to conventional roofs. In addition, a city scale application of RCs has been found capable of decreasing ambient temperature up to 1.6°C as potentially experienced by pedestrians.

Urban WRF-Chem evaluation over a high-altitude tropical city

Morphology and grid resolution are important aspects that need to be considered in urban modeling applications, since together with buildings they induce a direct effect on wind and dispersion of pollutants over urban areas. In this study, we evaluate high-resolution simulations of a multi-layer urban canopy model (UCM) based on a local climate zone (LCZ) classification coupled to the Weather Research and Forecasting model with Chemistry (WRF-Chem), in the local meteorological conditions and air quality pollutants of a highly urbanized megacity. This modeling system, known as Building Effect Parameterization (BEP) considers the effects of buildings’ vertical and horizontal surfaces on the momentum that considerably impacts the lower part of the urban boundary layer (UBL). Simulations of the urbanized model (WRFu) were compared against a Noah land surface model (Noah LSM) with no urban physics (WRF) for the same period. It was observed that the LCZ classification and urban parameterization coupled to the model have a direct influence in meteorological parameters and pollutant concentrations. Urban simulations of temperature and wind speed showed higher sensitivity to initial and boundary conditions, increasing the correlation with observations and reducing the bias error. An important observation is that emissions drive air quality concentrations despite the improvements in local meteorology.

Contrasting effects of lake breeze and urbanization on heat stress in Chicago metropolitan area

This study used the latest Weather Research and Forecasting (WRF) model coupled with multilayer urban canopy models to investigate contrasting effects from urbanization and lake breeze on summer heat stress over the Chicago metropolitan area (CMA). Comparisons between the model and in situ observations show that this coupled modeling system better captures urban locations' diurnal pattern of surface air temperature, skin temperature and relative humidity, with root mean square error reduced from 1.58 to 1.80 °C to 1.14–1.31 °C, 3.11–3.55 °C to 1.81–2.21 °C, and 10.73–11.35% to 7.84–8.60%, respectively, compared to WRF without coupling the urban canopy models. Two sensitivity experiments were conducted to isolate the influence of lake breeze and urbanization: one replaced the urban land use with cropland over the CMA, and the other filled all of Lake Michigan with cropland. Three different heat stress indices were computed to assess the uncertainties of heat stress response to changes in air temperature, relative humidity, and wind conditions. Results show that, when the lake has the largest cooling effect on air temperature, it also increases the relative humidity the most, and vice versa for urban warming and drying effects. Urbanization intensifies heat stress at night, and extends the heat caution period by up to 4 h over inland urban grids; the lake breeze relieves heat stress during afternoon (when the heat stress is the worst), and shortens the heat caution period by 1–3 h over inland urban grids and 3–4 h over coastal urban grids. The intensification of heat stress over the CMA due to urbanization is more than four times greater than the reduction from the lake breeze in the late afternoon and evening.

Evaluation of a novel WRF/PALM-4U coupling scheme incorporating a roughness-corrected surface layer representation

In this study we conduct realistic urban microclimate simulations using a multiscale approach that couples the PALM-4U microscale model to the WRF mesoscale model. The coupling is achieved by a one-way forcing of the initial and boundary conditions of the microscale model with data interpolated from the mesoscale model. To improve upon similar studies, our approach applies the roughness-corrected Monin–Obukhov similarity theory to fill the gap in the mesoscale results between the first model level and the ground. To assess the improvements of the coupled approach, we compare it to the standalone mesoscale simulation as well as to DWD measurements. Furthermore, the impact of the mesoscale model setup is investigated by comparing different inner domain grid sizes, coupling time steps, and urban parameterizations in an urban district of Berlin for a total of six different mesoscale setups. The comparison of the WRF mesoscale and PALM-4U microscale results indicate that the microscale results, in most cases, follow the mesoscale forcing and hence the microscale accuracy depends on the mesoscale setup. A comparison of simulations to measurements shows that the PALM-4U results tend to have a better agreement with measured data than the WRF results, in most but not all cases. It is also found that one mesoscale forcing setup may lead to better temperature accuracy of PALM-4U results while another one leads to better wind accuracy of PALM-4U results. However, the best overall results for temperature, mixing ratio and wind speed are achieved when forcing PALM-4U by the WRF multi-layer urban canopy model setup. Finally, decreasing the coupling time step from 1 h to 10 min or refining the WRF horizontal grid from 2 km down to 0.4 km do not lead to a significant improvement of PALM-4U simulation results. In all of the investigated cases, the PALM-4U results were sufficiently close to measurements to validate the coupled model approach.

How do street trees affect urban temperatures and radiation exchange? Observations and numerical evaluation in a highly compact city

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 on average 1.3 °C higher in the street with sparser 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.

Evaluation of Urban Canopy Models against Near-Surface Measurements in Houston during a Strong Frontal Passage

Urban canopy models (UCMs) in mesoscale numerical weather prediction models need evaluation to understand biases in urban environments under a range of conditions. The authors evaluate a new drag formula in the Weather Research and Forecasting (WRF) model’s multilayer UCM, the Building Effect Parameterization combined with the Building Energy Model (BEP+BEM), against both in-situ measurements in the urban environment as well as simulations with a simple bulk scheme and BEP+BEM using the old drag formula. The new drag formula varies with building packing density, while the old drag formula is constant. The case study is a strong cold frontal passage that occurred in Houston during the winter of 2017, causing high winds. It is found that both BEP+BEM simulations have lower peak wind speeds, consistent with near-surface measurements, while the bulk simulation has winds that are too strong. The constant-drag BEP+BEM simulation has a near-zero wind speed bias, while the new-drag simulation has a negative bias. Although the focus is on the impact of drag on the urban wind speeds, both BEP+BEM simulations have larger negative biases in the near-surface temperature than the bulk-scheme simulation. Reasons for the different performances are discussed.

On the Influences of Urbanization on the Extreme Rainfall over Zhengzhou on 20 July 2021: A Convection-Permitting Ensemble Modeling Study

This study investigates the influences of urban land cover on the extreme rainfall event over the Zhengzhou city in central China on 20 July 2021 using the Weather Research and Forecasting model at a convection-permitting scale [1-km resolution in the innermost domain (d3)]. Two ensembles of simulation (CTRL, NURB), each consisting of 11 members with a multi-layer urban canopy model and various combinations of physics schemes, were conducted using different land cover scenarios: (i) the real urban land cover, (ii) all cities in d3 being replaced with natural land cover. The results suggest that CTRL reasonably reproduces the spatiotemporal evolution of rainstorms and the 24-h rainfall accumulation over the key region, although the maximum hourly rainfall is underestimated and displaced to the west or southwest by most members. The ensemble mean 24-h rainfall accumulation over the key region of heavy rainfall is reduced by 13%, and the maximum hourly rainfall simulated by each member is reduced by 15–70 mm in CTRL relative to NURB. The reduction in the simulated rainfall by urbanization is closely associated with numerous cities/towns to the south, southeast, and east of Zhengzhou. Their heating effects jointly lead to formation of anomalous upward motions in and above the planetary boundary layer (PBL), which exaggerates the PBL drying effect due to reduced evapotranspiration and also enhances the wind stilling effect due to increased surface friction in urban areas. As a result, the lateral inflows of moisture and high-θe (equivalent potential temperature) air from south and east to Zhengzhou are reduced.

Estimating Heat-Related Exposures and Urban Heat Island Impacts: A Case Study for the 2012 Chicago Heatwave.

Accelerated urbanization increases both the frequency and intensity of heatwaves (HW) and urban heat islands (UHIs). An extreme HW event occurred in 2012 summer that caused temperatures of more than 40°C in Chicago, Illinois, USA, which is a highly urbanized city impacted by UHIs. In this study, multiple numerical models, including the High Resolution Land Data Assimilation System (HRLDAS) and Weather Research and Forecasting (WRF) model, were used to simulate the HW and UHI, and their performance was evaluated. In addition, sensitivity testing of three different WRF configurations was done to determine the impact of increasing model complexity in simulating urban meteorology. Model performances were evaluated based on the statistical performance metrics, the application of a multi‐layer urban canopy model (MLUCM) helps WRF to provide the best performance in this study. HW caused rural temperatures to increase by ∼4°C, whereas urban Chicago had lower magnitude increases from the HW (∼2–3°C increases). Nighttime UHI intensity (UHII) ranged from 1.44 to 2.83°C during the study period. Spatiotemporal temperature fields were used to estimate the potential heat‐related exposure and to quantify the Excessive Heat Factor (EHF). The EHF during the HW episode provides a risk map indicating that while urban Chicago had higher heat‐related stress during this event, the rural area also had high risk, especially during nighttime in central Illinois. This study provides a reliable method to estimate spatiotemporal exposures for future studies of heat‐related health impacts.

Impact of different urban canopy models on air quality simulation in Chengdu, southwestern China

Urban air pollution has emerged as a prominent public health concern in megacities and highly developed city clusters. Accurate modelling of urban air quality over complex terrain is challenging due to heterogeneous urban landscapes and multiscale land-atmosphere interactions. In this study, we investigated the applicability of urban canopy models in the Weather Research and Forecast (WRF) model and assessed the impacts of implementing these models on the urban air quality simulation in the Community Multiscale Air Quality (CMAQ) model over the megacity Chengdu, southwestern China. The land use and land cover of Chengdu were updated in WRF by using the land-use products in 2017 from the Moderate-resolution Imaging Spectroradiometer (MODIS). Sensitivity experiments with various urban canopy models were conducted to investigate the feasibility of different urban canopy models on WRF-CMAQ simulations. We found that the SLAB model significantly underestimates NO2 and PM2.5 concentrations, with mean fractional bias in winter (summer) reaching 52.93% (−50.34%) and −102.82% (−23.12%), respectively. Such large biases are mainly attributed to overpredicted wind speeds resulting from the flat structure in the SLAB model. In contrast, the BEM (a multilayer urban canopy model coupled with air-conditioning systems) model yields the best model performance in both winter and summer, with mean fractional errors of 33.15% (38.96%) and 34.10% (33.15%) for NO2 and PM2.5 in winter (summer), respectively. The UCM (a single-layer urban canopy model) model illustrates good performance in summer, with MFBs of 25.61% for NO2 and 19.03% for PM2.5, while NO2 and PM2.5 concentrations are overestimated in winter, with MFBs of 62.58% and 38.19%, respectively. In contrast, BEP (a multilevel urban canopy model)-modelled NO2 (MFB: 37.18%) and PM2.5 (MFB: 18.72%) correlate well with observations in winter, while significantly overestimated air pollutant concentrations in summer with MFBs of NO2 and PM2.5 of 49.70% and 44.50%, respectively. In general, the BEP model and the BEM model are well suited for air quality simulations over Chengdu in winter, and the BEM model could be considered for air quality simulations in summer. Furthermore, we assessed the effects of extensive usage of air conditioning systems in Chengdu during summertime, and the results suggest that using air conditioning systems facilitates the dispersion of air pollutants over Chengdu. This study pinpoints the limitations of default WRF configurations and tests the applicability of urban canopy models in the WRF-CMAQ model over Chengdu, in addition highlighting the crucial role of urban canopy models in urban meteorological-air quality simulations.

Turbulence Characteristics Across a Range of Idealized Urban Canopy Geometries

Good representation of turbulence in urban canopy models is necessary for accurate prediction of momentum and scalar distribution in and above urban canopies. To develop and improve turbulence closure schemes for one-dimensional multi-layer urban canopy models, turbulence characteristics are investigated here by analyzing existing large-eddy simulation and direct numerical simulation data. A range of geometries and flow regimes are analyzed that span packing densities of 0.0625 to 0.44, different building array configurations (cubes and cuboids, aligned and staggered arrays, and variable building height), and different incident wind directions (0^circ and 45^circ with regards to the building face). Momentum mixing-length profiles share similar characteristics across the range of geometries, making a first-order momentum mixing-length turbulence closure a promising approach. In vegetation canopies turbulence is dominated by mixing-layer eddies of a scale determined by the canopy-top shear length scale. No relationship was found between the depth-averaged momentum mixing length within the canopy and the canopy-top shear length scale in the present study. By careful specification of the intrinsic averaging operator in the canopy, an often-overlooked term that accounts for changes in plan area density with height is included in a first-order momentum mixing-length turbulence closure model. For an array of variable-height buildings, its omission leads to velocity overestimation of up to 17%. Additionally, we observe that the von Kármán coefficient varies between 0.20 and 0.51 across simulations, which is the first time such a range of values has been documented. When driving flow is oblique to the building faces, the ratio of dispersive to turbulent momentum flux is larger than unity in the lower half of the canopy, and wake production becomes significant compared to shear production of turbulent momentum flux. It is probable that dispersive momentum fluxes are more significant than previously thought in real urban settings, where the wind direction is almost always oblique.

On the Localized Extreme Rainfall over the Great Bay Area in South China with Complex Topography and Strong UHI Effects

AbstractIn this study, high-resolution surface and radar observations are used to analyze 24 localized extreme hourly rainfall (EXHR; >60 mm h−1) events with strong urban heat island (UHI) effects over the Great Bay Area (GBA) in South China during the 2011–16 warm seasons. Quasi-idealized, convection-permitting ensemble simulations driven by diurnally varying lateral boundary conditions, which are extracted from the composite global analysis of 3–5 June 2013, are then conducted with a multilayer urban canopy model to unravel the influences of the UHI and various surface properties nearby on the EXHR generation in a complex geographical environment with sea–land contrast, topography, and vegetation variation. Results show that EXHR is mostly distributed over the urban agglomeration and within about 40 km on its downwind side, and produced during the afternoon-to-evening hours by short-lived meso-γ- to meso-β-scale storms. On the EXHR days, the GBA is featured by a weak gradient environment with abundant moisture, and a weak southwesterly flow prevailing in the boundary layer (BL). The UHI effects lead to the development of a deep mixed layer with “warm bubbles” over the urban agglomeration, in which the lower-BL convergence and BL-top divergence is developed, assisting in convective initiation. Such urban BL processes and associated convective development with moisture supply by the synoptic low-level southwesterly flow are enhanced by orographically increased horizontal winds and sea breezes under the influence of the herringbone coastline, thereby increasing the inhomogeneity and intensity of rainfall production over the “Π-shaped” urban clusters. Vegetation variations are not found to be an important factor in determining the EXHR production over the region.

A new perspective on evaluating high-resolution urban climate simulation with urban canopy parameters

The ‘state-of-the-art’ urban climate models have not been evaluated against dense meteorological networks under various weather conditions. In this study, we conducted high-resolution urban climate simulations in Beijing and investigated the relationship between their performances and urban canopy parameters (UCPs). The latest version of single-layer (UCM) and multi-layer (BEP) urban canopy models were tested separately. Results show that model performances are insensitive to rainfall events in summer, but change significantly with wind conditions in winter. Inclusion of UCPs has a limited impact on air temperature simulations. In terms of wind speed simulations, consistent overestimations by UCM and BEP are found in both summer and winter. The overestimation by BEP reduces significantly when UCPs are available, especially on windy days in winter. On the other hand, performance of UCM can degrade over urban areas with canopy parameters. Wind speed biases are found to correlate significantly with UCPs. The accuracy of wind speed simulations by UCM and BEP increases with urban fraction and building surface ratio. This indicates poor model performances over low-density urban areas, which requires enhanced aerodynamic parameterizations to better account for UCPs. This study reveals the limitation of current urban climate simulations and provides guidance for future model developments.

Study of Urban Heat Islands Using Different Urban Canopy Models and Identification Methods

This work aims to compare the performance of the single‑(SLUCM) and multilayer (BEP-Building effect parameterization) urban canopy models (UCMs) coupled with the Weather Research and Forecasting model (WRF), along with the application of two urban heat island (UHI) identification methods. The identification methods are: (1) the “classic method”, based on the temperature difference between urban and rural areas; (2) the “local method” based on the temperature difference at each urban location when the model land use is considered urban, and when it is replaced by the dominant rural land use category of the urban surroundings. The study is performed as a case study for the city of Lisbon, Portugal, during the record-breaking August 2003 heatwave event. Two main differences were found in the UHI intensity (UHII) and spatial distribution between the identification methods: a reduction by half in the UHII during nighttime when using the local method; and a dipole signal in the daytime and nighttime UHI spatial pattern when using the classic method, associated with the sheltering effect provided by the high topography in the northern part of the city, that reduces the advective cooling in the lower areas under prevalent northern wind conditions. These results highlight the importance of using the local method in UHI modeling studies to fully isolate urban canopy and regional geographic contributions to the UHII and distribution. Considerable improvements were obtained in the near‑surface temperature representation by coupling WRF with the UCMs but better with SLUCM. The nighttime UHII over the most densely urbanized areas is lower in BEP, which can be linked to its larger nocturnal turbulent kinetic energy (TKE) near the surface and negative sensible heat (SH) fluxes. The latter may be associated with the lower surface skin temperature found in BEP, possibly owing to larger turbulent SH fluxes near the surface. Due to its higher urban TKE, BEP significantly overestimates the planetary boundary layer height compared with SLUCM and observations from soundings. The comparison with a previous study for the city of Lisbon shows that BEP model simulation results heavily rely on the number and distribution of vertical levels within the urban canopy.

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.

Multi-layer coupling between SURFEX-TEB-v9.0 and Meso-NH-v5.3 for modelling the urban climate of high-rise cities

Abstract. Urban canopy models (UCMs) represent the exchange of momentum, heat, and moisture between cities and the atmosphere. Single-layer UCMs interact with the lowest atmospheric model level and are suited for low- to mid-rise cities, whereas multi-layer UCMs interact with multiple levels and can also be employed for high-rise cities. The present study describes the multi-layer coupling between the Town Energy Balance (TEB) UCM included in the Surface Externalisée (SURFEX) land surface model and the Meso-NH mesoscale atmospheric model. This is a step towards better high-resolution weather prediction for urban areas in the future and studies quantifying the impact of climate change adaptation measures in high-rise cities. The effect of the buildings on the wind is considered using a drag force and a production term in the prognostic equation for turbulent kinetic energy. The heat and moisture fluxes from the walls and the roofs to the atmosphere are released at the model levels intersecting these urban facets. No variety of building height at grid-point scale is considered to remain the consistency between the modification of the Meso-NH equations and the geometric assumptions of TEB. The multi-layer coupling is evaluated for the heterogeneous high-rise, high-density city of Hong Kong. It leads to a strong improvement of model results for near-surface air temperature and relative humidity, which is due to better consideration of the process of horizontal advection in the urban canopy layer. For wind speed, model results are improved on average by the multi-layer coupling but not for all stations. Future developments of the multi-layer SURFEX-TEB will focus on improving the calculation of radiative exchanges, which will allow a variety of building heights at grid-point scale to be taken into account.

Effects of using different urban parametrization schemes and land-cover datasets on the accuracy of WRF model over the City of Ottawa

In the face of rapid urbanization and global warming, it is important to acquire a better understanding of urban climate and land-atmosphere interactions operating therein. The Weather Research and Forecasting (WRF) model is a limited area model that has been used to study urban microclimate in many cities across the globe. However, such a study is lacking for the Canada's capital city: Ottawa. In this article, the WRF model is set-up at 1 km spatial resolution over the Ottawa region and its sensitivity towards the use of different urban parametrization schemes and land-cover datasets is investigated from 01 June to 31 August 2018 which includes an extreme heat weather event spanning from June 30 to July 6. WRF-simulations are performed using the Noah land surface model with two urban parametrization schemes of different complexity, i.e., a simple bulk urban parametrization and a more advanced multilayer urban canopy model (UCM). Both WRF-simulations used the default land use-land cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS) available in WRF. Between these two WRF-simulations, the simulation with the multilayer UCM is found to be more accurate than the bulk scheme simulation in terms of modeled near-surface wind-speed, relative humidity, and total precipitation compared to observations recorded at one urban weather gauging station located within the city limits. Finally, a third WRF-simulation is performed with the multilayer UCM but using a higher resolution 30 m land use-land cover data product for the urban domain. This third WRF-experiment improved further the near-surface wind speed, relative humidity, and total precipitation correspondence to observations within the city. It is worthy to mention that modeled total precipitation is found to be sensitive to both urban parametrization schemes and urban land use-land cover data sets.