Building Effect Parameterization Research Articles

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.

Satellite-Based Optimization and Planning of Urban Ventilation Corridors for a Healthy Microclimate Environment

Urban ventilation corridors (UVCs) have the potential to effectively mitigate urban heat islands and air pollution. Shanghai, a densely populated city located in eastern China, is among the hottest cities in the country and requires urgent measures in order to enhance its ventilation system. This study introduces a novel approach that integrates land surface temperature retrieval, PM2.5 concentration retrieval, and wind field simulation to design UVCs at the city level. Through remote sensing data inversion of land surface temperature (LST) and PM2.5 concentration, the study identifies the action spaces and compensation spaces for UVCs. The Weather Research and Forecasting (WRF) model, coupled with the multilayer urban scheme Building Effect Parameterization (BEP) model, is employed to numerically simulate and analyze the wind field. Based on the identification of thirty high-temperature zones and high PM2.5 concentration zones as action spaces, and twenty-two low-temperature zones and low PM2.5 concentration zones as compensation spaces in Shanghai, the study constructs seven first-class ventilation corridors and nine secondary ventilation corridors according to local circulation patterns. Unlike previous UVC research, this study assesses the cleanliness of cold air, which is a common oversight in UVC planning. Ignoring the assessment of cold air cleanliness can result in less effective UVCs in improving urban air quality and even exacerbate air pollution in the central city. Therefore, this study serves as a crucial contribution by rectifying this significant deficiency. It not only provides a fresh perspective and methodology for urban-scale ventilation corridor planning but also contributes to enhancing the urban microclimate by mitigating the effects of urban heat islands and reducing air pollution, ultimately creating a livable and comfortable environment for urban residents.

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.

Spatially Explicit Correction of Simulated Urban Air Temperatures Using Crowdsourced Data.

Urban climate model evaluation often remains limited by a lack of trusted urban weather observations. The increasing density of personal weather sensors (PWSs) make them a potential rich source of data for urban climate studies that address the lack of representative urban weather observations. In our study, we demonstrate that carefully quality-checked PWS data not only improve urban climate models' evaluation but can also serve for bias correcting their output prior to any urban climate impact studies. After simulating near-surface air temperatures over London and south-east England during the hot summer of 2018 with the Weather Research and Forecasting (WRF) Model and its building Effect parameterization with the building energy model (BEP-BEM) activated, we evaluated the modeled temperatures against 402 urban PWSs and showcased a heterogeneous spatial distribution of the model's cool bias that was not captured using official weather stations only. This finding indicated a need for spatially explicit urban bias corrections of air temperatures, which we performed using an innovative method using machine learning to predict the models' biases in each urban grid cell. This bias-correction technique is the first to consider that modeled urban temperatures follow a nonlinear spatially heterogeneous bias that is decorrelated from urban fraction. Our results showed that the bias correction was beneficial to bias correct daily minimum, daily mean, and daily maximum temperatures in the cities. We recommend that urban climate modelers further investigate the use of quality-checked PWSs for model evaluation and derive a framework for bias correction of urban climate simulations that can serve urban climate impact studies.

Net impact of air conditioning on heat-related mortality in Japanese cities

BackgroundAir conditioning (AC) presents a viable means of tackling the ill-effects of heat on human health. However, AC releases additional anthropogenic heat outdoors, and this could be detrimental to human health, especially in urban communities. This study determined the excess heat-related mortality attributable to anthropogenic heat from AC use under various projected global warming scenarios in seven Japanese cities. The overall protection from AC use was also measured. MethodsDaily average 2-meter temperatures in the hottest month of August from 2000 to 2010 were modeled using the Weather Research and Forecasting (WRF) model with BEP+BEM (building effect parameterization and building energy model). Risk functions for heat–mortality associations were generated with and without AC use from a two-stage time series analysis. We coupled simulated August temperatures and heat–mortality risk functions to estimate averted deaths and unavoidable deaths from AC use. ResultsAnthropogenic heat from AC use slightly augmented the daily urban temperatures by 0.046 °C in Augusts of 2000–2010 and up to 0.181 °C in a future with 3 °C urban warming. This temperature rise was attributable to 3.1–3.5 % of heat-related deaths in Augusts of 2000–2010 under various urban warming scenarios. About 36–47 % of heat-related deaths could be averted by air conditioning use under various urban warming scenarios. DiscussionAC has a valuable protective effect from heat despite some unavoidable mortality from anthropogenic heat release. Overall, the use of AC as a major adaptive strategy requires careful consideration.

Modelling the impacts of emission changes on O3 sensitivity, atmospheric oxidation capacity, and pollution transport over the Catalonia region

Abstract. Tropospheric ozone (O3) is an important surface pollutant in urban areas, and it has complex formation mechanisms that depend on the atmospheric chemistry and on meteorological factors. The severe reductions observed in anthropogenic emissions during the COVID-19 pandemic can further our understanding of the photochemical mechanisms leading to O3 formation and provide guidance for policies aimed at reducing air pollution. In this study, we use the Weather Research and Forecasting model with Chemistry (WRF-Chem) coupled with the urban canopy building effect parameterization and building energy model (BEP + BEM) to investigate changes in the ozone chemistry over the metropolitan area of Barcelona (AMB) and its atmospheric plume moving northwards, which is responsible for the highest number of hourly O3 exceedances in Spain. The trajectories of the air masses from the AMB to the Pyrenees are studied with the Lagrangian FLEXible PARTicle dispersion model with WRF (FLEXPART-WRF). The aim is to investigate the response of ozone chemistry to reduction in precursor emissions (NOx – nitrogen oxides; VOCs – volatile organic compounds). The results show that, with the reduction in emissions, (1) the ozone chemistry tends to enter the NOx-limited or transition regimes, but highly polluted urban areas are still in the VOC-limited regime; (2) the reduced O3 production is overwhelmed by reduced nitric oxide (NO) titration, resulting in a net increase in the O3 concentration (up to 20 %) in the evening; (3) the increase in the maximum O3 level (up to 6 %) during the highest emission-reduction period could be attributed to an enhancement in the atmospheric oxidants hydroxyl and nitrate radical (OH and NO3) given their strong link with O3 loss or production chemistry; (4) the daily maximum levels of ozone and odd oxygen species (Ox) generally decreased (4 %) in May – a period with intense radiation which favours ozone production – with the reduced atmospheric OH and NO3 oxidants, indicating an improvement in the air quality; and (5) ozone precursor concentration changes in the urban plume of Barcelona contribute significantly to the level of pollution along the 150 km south-to-north valley in the Pyrenees. Our results indicate that O3 abatement strategies cannot rely only on NOx emission control but must include a significant reduction in anthropogenic sources of VOCs. In addition, our results show that mitigation strategies intended to reduce O3 should be designed according to the local meteorology, air transport, particular ozone regimes, and oxidation capacity of the atmosphere of the urban area.

Thermal effects of cool roofs and urban vegetation during extreme heat events in three Canadian regions

The need to mitigate and adapt to a changing climate is becoming more urgent, especially in highly urbanized areas where a growing portion of the population lives. This study quantifies the effectiveness of two Nature-Based Solutions - cool roofs and urban vegetation - in the moderation of urban temperature during past Extreme Heat Events in the Ottawa-Montreal, Calgary, and Vancouver regions of Canada. The Weather Research and Forecasting model coupled with the multi-layer building effect parameterization and building energy model at a horizontal resolution of 1km is evaluated under diverse climates, and is used to simulate different levels of both NBS applied across each of the aforementioned regions. Increasing implementation of cool roofs and urban vegetation lead to reductions of near-surface air temperature and wind speed, and enhancements in relative humidity. The largest cooling occurred when both cool roofs and increased vegetation are implemented in each of the cities. The largest cooling effect was found in Vancouver, where a maximum reduction of 3.5°C in 2m air temperature could be felt, while the weakest effect was found in Ottawa at 1.2°C across the city.

Simulation of interaction between high-temperature process and heat emission from electricity system in summer

During the hot summer season, using electricity systems increases the local anthropogenic heat emission, further increasing the temperature. Regarding anthropogenic heat sources, electric energy consumption, heat generation, indoor and outdoor heat transfer, and exchange in buildings play a critical role in the change in the urban thermal environment. Therefore, the Weather Research and Forecasting (WRF) Model was applied in this study to investigate the heat generation from an indoor electricity system and its influence on the outdoor thermal environment. Through the building effect parameterization (BEP) of a multistorey urban canopy scheme, a building energy model (BEM) to increase the influence of indoor air conditioning on the electricity consumption system was proposed. In other words, the BEP+BEM urban canopy parameterization scheme was set. High temperatures and a summer heat wave were simulated as the background weather. The results show that using the BEP+BEM parameterization scheme of indoor and outdoor energy exchange in the WRF model can better simulate the air temperature near the surface layer on a sunny summer. During the day, the turning on the air conditioning and other electrical systems have no obvious effect on the air temperature near the surface layer in the city, whereas at night, the air temperature generally increases by 0.6 ℃, especially in densely populated areas, with a maximum temperature rise of approximately 1.2 ℃ from 22:00 to 23:00. When the indoor air conditioning target temperature is adjusted to 25–27 ℃, the total energy release of the air conditioning system is reduced by 12.66%, and the temperature drops the most from 13:00 to 16:00, with an average of approximately 1 ℃. Further, the denser the building is, the greater the temperature drop.

Impact of urban parameterization and integration of WUDAPT on the severe convection

Amplified rates of urban convective systems pose a severe peril to the life and property of the inhabitants over urban regions, requiring a reliable urban weather forecasting system. However, the city scale's accurate rainfall forecast has constantly been a challenge, as they are significantly affected by land use/ land cover changes (LULCC). Therefore, an attempt has been made to improve the forecast of the severe convective event by employing the comprehensive urban LULC map using Local Climate Zone (LCZ) classification from the World Urban Database and Access Portal Tools (WUDAPT) over the tropical city of Bhubaneswar in the eastern coast of India. These LCZs denote specific land cover classes based on urban morphology characteristics. It can be used in the Advanced Research version of the Weather Research and Forecasting (ARW) model, which also encapsulates the Building Effect Parameterization (BEP) scheme. The BEP scheme considers the buildings' 3D structure and allows complex land–atmosphere interaction for an urban area. The temple city Bhubaneswar, the capital of eastern state Odisha, possesses significant rapid urbanization during the recent decade. The LCZs are generated at 500 m grids using supervised classification and are ingested into the ARW model. Two different LULC dataset, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS) and WUDAPT derived LCZs and initial, and boundary conditions from NCEP GFS 6-h interval are used for two pre-monsoon severe convective events of the year 2016. The results from WUDAPT based LCZ have shown an improvement in spatial variability and reduction in overall BIAS over MODIS LULC experiments. The WUDAPT based LCZ map enhances high-resolution forecast from ARW by incorporating the details of building height, terrain roughness, and urban fraction.

Multi-Scale Numerical Assessments of Urban Wind Resource Using Coupled WRF-BEP and RANS Simulation: A Case Study

Urban wind resource assessments (WRAs) contribute to the effective exploitation of wind energy and thus are of significant importance to the sustainable development of cities. To improve the simulation accuracy of urban wind flow with high spatial resolution, this study implemented a multi-scale numerical assessment of the wind power potential in a highly-urbanized region with realistic terrain conditions by integrating the Reynolds-averaged Navier-Stokes (RANS) equations into the Weather Research and Forecasting (WRF) model with Building Effect Parameterization (WRF-BEP). The sensitivity analyses are first conducted to obtain an appropriate combination of physical parameterization schemes in the WRF-BEP model. Then, the wind tunnel tests are performed to validate the computational accuracy of urban wind flow using the RANS equations. Based on a close examination of the urban wind flow resulting from the coupled WRF-BEP and RANS simulations, the integration of micro-wind turbines into the building skin is not recommended in the highly-urbanized region. Furthermore, five optimum roof installation locations with low turbulence intensities (smaller than 18%) and high wind power densities (approximately 220 W/m2, 260 W/m2, 270 W/m2, 300 W/m2 and 400 W/m2, respectively) are identified. Finally, the important effects of the terrain conditions, planetary boundary layer (PBL) parameterization schemes and turbulence models on WRAs are discussed. The results of WRAs in this multi-scale numerical case study presented a systemic approach to effectively determine the installation locations of micro-wind turbines that possess the greatest potential to harness wind energy in a realistic highly-urbanized area.

A city-scale inverse modelling method for air pollutant source determination

Urban air pollution is a major environmental hazard. Accurate and rapid identification of pollutant sources is a crucial component of efficient strategies to protect public health. The mostly used back-trajectory analysis and source-receptor likelihood function have limitations in real scenarios. Inverse prediction models such as the adjoint probability method have shown viability in indoor environment. A novel application of this method is conducted to determine the air pollutant source at city-scale. The adjoint probability method is physically deduced, parameterized, and first implemented in the Weather Research and Forecasting (WRF) model coupled with building effect parameterization (BEP) and building energy model (BEM). The predictive performance of the method is investigated using an ideal case and a real urban case study in the city of Hong Kong. The results show that the proposed method can precisely identify both the source location and strength. The main distinction of the method is the fast and accurate determination of the potential source with limited known information collected from three mobile sensors or three fixed sensors. The results of this study can provide insights on sensor distribution and sensor selection in the urban environment. The method of this study can be extended to other source-term problems.

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.

Impact of land-use land-cover datasets and urban parameterization on weather simulation over the Jakarta Metropolitan Area

Human-caused changes in land-use and land-cover (LULC) are most visible in metropolitan areas, when the majority of the land has been converted to urban land or built up. This study presents a modeling approach for simulating the spatiotemporal distribution of urban microclimate with the Weather Research and Forecasting (WRF) model using four urban parameterization schemes, namely a bulk, urban canopy model (UCM), building effect parameterization (BEP), and building energy model (BEM). The WRF model is set-up at 1 km spatial resolutions over the Jakarta Metropolitan Area to study the model’s sensitivity to the usage of alternative LULC datasets, the default MODIS and its modification 2017. The results show that the UCM and BEM schemes appear to be reliable in mapping urban weather conditions for all meteorological parameters examined. Given that the LULC categories in urban areas remained unchanged, changing the LULC in the model did not result in a large difference in error. The LULC dataset, on the other hand, can be used as information related to suburban areas that continue to grow in concurrently with urbanization. LULC updates can provide insight into how much temperature rise is occurring in urban areas and how it affects climate change.

Development and Evaluation of a New Urban Parameterization in the Weather Research and Forecasting (WRF) Model

AbstractIn mesoscale Weather Research and Forecasting (WRF) model, several urban‐modeling options exist, such as Single‐layer Urban Canopy Model, Building Effect Parameterization, and Building Energy Model. However, these models have limitations in terms of the choice of land surface models (LSMs) and planetary boundary layer (PBL) schemes, the associated computational expenses, and other constraints. Recently, Dy et al. (2019, https://doi.org/10.1029/2018JD029333) included the urban‐momentum drag effect for wind‐speed modeling by developing a new multilayer model based on a modified nonlocal Asymmetric Convective Model version‐2 (ACM2) PBL scheme. This urban‐based ACM2 (UACM) has demonstrated a significantly improved ability over the base‐ACM2 (BACM) to predict wind speed near the urban ground surface and shown an inflection point at roof level in the vertical profile of horizontal wind. In this study, urban thermal and moisture components are introduced into the Pleim‐Xiu (PX) LSM and coupled with UACM. The diurnal variation in street, walls, and roof‐surface temperatures is modeled using the two‐layer force‐restore algorithm. Simple radiation treatment is considered to account for shadowing on streets based on the solar zenith angle and building morphology. Heat and moisture flux evolution are considered explicitly on all urban surfaces. The advantages of this novel UACM are simple formulation, more efficient execution, and its requirement for only a few fundamental urban morphological parameters. The idealized and real urban data case WRF simulations are performed over the Pearl River Delta region in southern China to test the new UACM. The computationally efficient UACM is expected to perform faster for operational forecasting runs.

Exploring the impacts of heat release of vehicles on urban heat mitigation in Sendai, Japan using WRF model integrated with urban LCZ

Studies have been conducted globally on urban heat countermeasures utilizing Weather Research and Forecasting (WRF) numerical modeling system. Yet, the effects of vehicle heat (VH) on near-surface air temperature in Japanese cities were not clarified. In this study, the WRF Building Effect Parameterization and Building Energy Model (BEP-BEM) coupled with local climate zones (LCZs) was adopted for simulating the influences of VH on the urban climate over Sendai, Japan. To do so, we proposed a novel method to estimate the hourly VH for LCZs via open-source data. Integrating VH and specific urban canopy parameters (UCPs) into BEP-BEM, the climate model was established and then validated with the observed data. Based on that, effects of various urban heat countermeasures were analyzed at a high spatial resolution. It was found that eliminating the vehicle heat contributes up to 0.12°C to urban heat mitigation, as the most effective countermeasures for the compact areas of city center. This study provided a feasible and reliable workflow to quantitatively evaluate urban heat mitigation strategies at high spatial resolution, specifically for reducing VH in Japanese cities, that can support related urban planners and decision makers for implementing targeted urban heat mitigation strategies.

Assessment of Air Quality and Meteorological Changes Induced by Future Vegetation in Madrid

Nature-based solutions and green urban infrastructures are becoming common measures in local air quality and climate strategies. However, there is a lack of analytical frameworks to anticipate the effect of such interventions on urban meteorology and air quality at a city scale. We present a modelling methodology that relies on the weather research and forecasting model (WRF) with the building effect parameterization (BEP) and the community multiscale air quality (CMAQ) model and apply it to assess envisaged plans involving vegetation in the Madrid (Spain) region. The study, developed within the VEGGAP Life project, includes the development of two detailed vegetation scenarios making use of Madrid’s municipality tree inventory (current situation) and future vegetation-related interventions. An annual simulation was performed for both scenarios (considering constant anthropogenic emissions) to identify (i) variations in surface temperature and the reasons for such changes, and (ii) implications on air-quality standards according to EU legislation for the main pollutants (PM10, PM2.5, NO2 and O3). Our results suggest that vegetation may have significant effects on urban meteorology due to changes induced in relevant surface properties such as albedo, roughness length or emissivity. We found a net-heating effect of around +0.18 °C when trees are introduced in dry, scarcely vegetated surfaces in the city outskirts. In turn, this enhances the planetary boundary layer height (PBLH), which brings about reductions in ambient concentrations of relevant pollutants such as NO2 (in the range of 0.5–0.8 µg m−3 for the annual mean, and 2–4 µg m−3 for the 19th highest 1 h value). Conversely, planting new trees in consolidated urban areas causes a cooling effect (up to −0.15 °C as an annual mean) that may slightly increase concentration levels due to less-effective vertical mixing and wind-speed reduction caused by increased roughness. This highlights the need to combine nature-based solutions with emission-reduction measures in Madrid.

Simulation of the Air Quality in Southern California, USA in July and October of the Year 2018

A numerical investigation of the air quality in Southern California, USA in the year 2018 is presented using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). In July, a heat wave occurred, and in October, Santa Ana conditions prevailed; these conditions and their impact on air quality are the scope of the present numerical study.The high spatial resolution in the simulation includes two nested domains of 1 km and 3 km, respectively. Local climate zones land use categories are combined with the complex urban model building effect parameterization coupled with the building energy model (BEP+BEM) and the detailed MOZCART-T1 chemical reaction mechanism, which is the MOZART-T1 mechanism for trace gases with GOCART aerosols. Thus, the model is suitable to compare simulation results to in situ and satellite measurements of O3, NO2, CH4, and CO. The meteorology is captured well by the model. Comparison of simulation results with observations shows a good agreement of NO2 and ozone, whereas CO mixing ratios are generally underestimated. This hints at missing emissions in the 2017 National Emissions Inventory (NEI) dataset. Both the heat wave and the Santa Ana winds increase the air pollution with gas-phase species in Los Angeles. In both cases, nighttime boundary layer heights are small, which causes emissions to reside near the ground. During Santa Ana winds, NOx removal on aerosols is reduced. Methane mixing ratios are modeled very well at most stations in Los Angeles, but predictions of low emissions near the University of California cause inaccuracies at that location. Modeled and observed PM2.5 agree well on low-pollution days, but high-pollution events are generally missed by the model. During the heat wave, both modeled and observed PM2.5 concentrations exceed the recommended NAAQS National Ambient Air Quality Standards value of 12.5 g/m3. The present modeling approach serves as a base for the study and prediction of special weather events and their impact on air pollution.

Improved Urban Finescale Forecasting During a Heat Wave by Using High-Resolution Urban Canopy Parameters

For urban weather finescale forecasting, obtaining accurate and up-to-date urban canopy parameters (UCPs) is necessary and still a challenge. In this study, a high-resolution dataset of UCPs was developed by using vector-format building information and then applied in the WRF/urban system with the single-layer urban canopy model (SLUCM)/building effect parameterization (BEP) model to improve the urban finescale forecasting of a typical heat wave event during summer 2016 in Hangzhou. A series of sensitivity experiments were conducted, and the results showed that the high-resolution UCP data improved the model skill in simulating the spatial distributions and diurnal variations of 2-m temperature, 2-m relative humidity, and 10-m wind speed in the urban areas of Hangzhou, especially for the BEP model. Better results were produced when refining the computation domain due to more realistic urban morphological characteristics were adopted. The sensitive experiments suggest that the high-resolution UCPs played a significant role in representing the UHI effect though changing the surface thermodynamic parameters (e.g., roughness length), hereafter increasing the sensible heat and surface heat flux, and finally resulting a notable urban heat island (UHI) effect.

Sensitivity study of PBL schemes and soil initialization using the WRF-BEP-BEM model over a Mediterranean coastal city

Due to increased urbanization and global warming, cities are experiencing more heat wave (HW) events that cause extreme heat stress. To mitigate such effects, a better understanding of the impact of urban morphology on the boundary layer development is needed. This study investigates the sensitivity of mesoscale simulations using the WRF model coupled with the building effect parameterization and the building energy model (BEP-BEM) at a 1-km resolution to 1) soil moisture initializations; 2) the inclusion of site-specific urban morphology parameters; and 3) the planetary boundary layer (PBL) scheme. A HW episode that occurred in the metropolitan area of Barcelona serves as the case study. We find that the use of a high-resolution land data assimilation system (HRLDAS) to initialize soil properties results in larger temperature diurnal range, but it did not improve the performance of simulated temperatures compared to using low-resolution ERA5 data. The inclusion of site-specific urban parameters improved the representation of urban fractions, reducing the night-time overprediction of 2-m temperatures compared to using default urban parameters. Overall, the Bougeault-Lacarrere (BouLac) scheme represents the PBL-height noontime observations better than the Mellor-Yamada-Janjic (MYJ) scheme. This was related to a better representation of daytime near-surface temperatures by the BouLac scheme compared to the MYJ scheme