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Understanding and evaluating the implications of photovoltaic solar panels (PVSPs) deployment on urban settings, as well as the pessimistic effects of densely populated areas on PVSPs efficiency, is becoming incredibly valuable. Thus, the deployment of low-efficiency, low-cost, and widely available PVSPs may diminish total solar reflectance, raising the risks of PVSPs-based urban heating, particularly during the summertime heatwaves. This study employs and assesses physical parameterizations that account for the impact of PVSPs on Sydney's urban environment in the context of the mesoscale model weather research and forecasting (WRF). To account for the impacts of PVSPs, the parameterization presented in this paper assumes that PVSP arrays are parallel, detachable from roofs, and consist of a single layer. Results showed that increasing PVSPs can raise peak summer ambient temperatures by up to 1.4 °C and surface temperatures by up to 2.3°C at city-scale. Temperature variability was found between the city's eastern and western parts due to the presence of PVSPs. In addition, local warming effects of PVSP were observed at urban district-scale as well. The large-scale deployment of PVSPs at local district-scale of the Sydney during a typical hot day caused air temperature to rise by 1.5 °C during the daytime and decrease by 2.7 °C at nighttime. The patterns of the city's ambient temperature distribution were found to be strongly dependent on synoptic meteorological conditions and advection flow strength. The maximum increases in sensible heat flux and latent heat flux were 245.5 Wm−2 and 11.5 Wm−2, respectively. Wind speed may be raised by up to 1.2 ms−2 due to regional low effect over city domain. As a result, large-scale deployment of PVSPs promotes advective flow between the city and its environs. Modification of the PVSPs in Sydney results in an increase in planetary boundary layer (PBL) heights of up to 537.9 m above the city and may lower pollutant concentrations at ground level. The advent of sea breeze in the city's eastern parts, which reduces the temperature of the coastal zone, along with inland westerly winds, which heat the city's western zones, lessened the intensity of the urban heat island (UHI) phenomenon induced by PVSPs warming. The findings of this study can be used to help policymakers make informed decisions about the use of PVSPs systems. PVSPs with a high solar reflectance in wavelengths that do not convert solar energy to electricity can be considered as an alternative solution to reduce local warming in urban environments. [ABSTRACT FROM AUTHOR]

Understanding and evaluating the implications of photovoltaic solar panels (PVSPs) deployment on urban settings, as well as the pessimistic effects of densely populated areas on PVSPs efficiency, is becoming incredibly valuable. Thus, the deployment of low-efficiency, low-cost, and widely available PVSPs may diminish total solar reflectance, raising the risks of PVSPs-based urban heating, particularly during the summertime heatwaves. This study employs and assesses physical parameterizations that account for the impact of PVSPs on Sydney's urban environment in the context of the mesoscale model weather research and forecasting (WRF). To account for the impacts of PVSPs, the parameterization presented in this paper assumes that PVSP arrays are parallel, detachable from roofs, and consist of a single layer. Results showed that increasing PVSPs can raise peak summer ambient temperatures by up to 1.4 °C and surface temperatures by up to 2.3°C at city-scale. Temperature variability was found between the city's eastern and western parts due to the presence of PVSPs. In addition, local warming effects of PVSP were observed at urban district-scale as well. The large-scale deployment of PVSPs at local district-scale of the Sydney during a typical hot day caused air temperature to rise by 1.5 °C during the daytime and decrease by 2.7 °C at nighttime. The patterns of the city's ambient temperature distribution were found to be strongly dependent on synoptic meteorological conditions and advection flow strength. The maximum increases in sensible heat flux and latent heat flux were 245.5 Wm−2 and 11.5 Wm−2, respectively. Wind speed may be raised by up to 1.2 ms−2 due to regional low effect over city domain. As a result, large-scale deployment of PVSPs promotes advective flow between the city and its environs. Modification of the PVSPs in Sydney results in an increase in planetary boundary layer (PBL) heights of up to 537.9 m above the city and may lower pollutant concentrations at ground level. The advent of sea breeze in the city's eastern parts, which reduces the temperature of the coastal zone, along with inland westerly winds, which heat the city's western zones, lessened the intensity of the urban heat island (UHI) phenomenon induced by PVSPs warming. The findings of this study can be used to help policymakers make informed decisions about the use of PVSPs systems. PVSPs with a high solar reflectance in wavelengths that do not convert solar energy to electricity can be considered as an alternative solution to reduce local warming in urban environments. [ABSTRACT FROM AUTHOR]

With the aim of understanding the impact of air pollution on human health and ecosystems in the tropical Andes region (TAR), we aim to couple the Weather Research and Forecasting Model (WRF) with the chemical transport models (CTM) Long-Term Ozone Simulation and European Operational Smog (LOTOS–EUROS), at high and regional resolutions, with and without assimilation. The factors set for WRF, are based on the optimized estimates of climate and weather in cities and urban heat islands in the TAR region. It is well known in the weather research and forecasting field, that the uncertainty of non-linear models is a major issue, thus making a sensitivity analysis essential. Consequently, this paper seeks to quantify the performance of the WRF model in the presence of disturbances to the initial conditions (IC), for an arbitrary set of state-space variables (pressure and temperature), simulating a disruption in the inputs of the model. To this aim, we considered three distributions over the error term: a normal standard distribution, a normal distribution, and an exponential distribution. We analyze the sensitivity of the outputs of the WRF model by employing non-parametric and robust statistical techniques, such as kernel distribution estimates, rank tests, and bootstrap. The results show that the WRF model is sensitive in time, space, and vertical levels to changes in the IC. Finally, we demonstrate that the error distribution of the output differs from the error distribution induced over the input data, especially for Gaussian distributions. [ABSTRACT FROM AUTHOR]

Due to global warming and urbanization, high-temperature events—which frequently occur in cities—are presenting an increasing threat to the daily lives of human beings. In coastal cities, sea breezes can cool the near surface and improve the urban environment to some extent. Understanding the cooling characteristics of sea breeze on the urban environment is informative for improving and mitigating the urban heat island (UHI) effect. In this paper, we analyze the basic characteristics of the timing of the cooling effect of sea breeze in urban summer based on the long-term multi-point measurements of air temperatures. Additionally, the Weather Research and Forecasting (WRF) model is used to show the influence of sea breeze on cities in terms of the cooling action time. The whole process is reproduced based on a time distribution map created using the results of the WRF simulation. The measured temperature and WRF simulation results are also evaluated with observations. The results show little difference between the two. The analysis of the distribution map shows that the sea breeze gradually penetrates inland from coastal areas. It can therefore be concluded that the sea breeze blows at different speeds in different areas. Our results show that the sea breeze is weak in places near the coast, while it is significantly stronger around inland rivers. Moreover, in urban areas that are far from inland rivers, the speed of the sea breeze is evenly distributed in space. The spatial pattern of sea breeze retreat time and arrival time is reversed: retreats happen earlier in inland areas. The duration of the sea breeze shows a significantly decreasing trend from the coast to inland, with the longest duration at the southern end of the urban area near the coast. [ABSTRACT FROM AUTHOR]

Accurate simulation of planetary boundary layer height (PBLH) is key to greenhouse gas emission estimation, air quality prediction, and weather forecasting. This paper describes an extensive performance assessment of several Weather Research and Forecasting (WRF) Model configurations in which novel observations from ceilometers, surface stations, and a flux tower were used to study their ability to reproduce the PBLH and the impact that the urban heat island (UHI) has on the modeled PBLHs in the greaterWashington, D.C., area. In addition, CO2 measurements at two urban towers were compared with tracer transport simulations. The ensemble of models used four PBL parameterizations, two sources of initial and boundary conditions, and one configuration including the building energy parameterization urban canopy model. Results have shown low biases over the whole domain and period for wind speed, wind direction, and temperature, with no drastic differences between meteorological drivers. We find that PBLH errors are mostly positively correlated with sensible heat flux errors and that modeled positive UHI intensities are associated with deeper modeled PBLs over the urban areas. In addition, we find that modeled PBLHs are typically biased low during nighttime for most of the configurations with the exception of those using theMYNN parameterization, and these biases directly translate to tracer biases. Overall, the configurations using the MYNN scheme performed the best, reproducing the PBLH and CO2 molar fractions reasonably well during all hours and thus opening the door to future nighttime inverse modeling. [ABSTRACT FROM AUTHOR]

This paper examines summer- and wintertime variations of the surface and near-surface urban heat island (UHI) for the Phoenix metropolitan area using the Moderate Resolution Imaging Spectroradiometer (MODIS), near-surface meteorological observations, and the Weather Research and Forecasting (WRF) Model during a 31-day summer- and a 31-day wintertime period. The surface UHI (defined based on the urban-rural land surface temperature difference) is found to be higher at night and during the warm season. On the other hand, the morning surface UHI is low and frequently exhibits an urban cool island that increases during the summertime period. Similarly, the near-surface UHI (defined based on the urban-rural 2-m air temperature difference) is higher at night and during summertime. On the other hand, the daytime near-surface UHI is low but rarely exhibits an urban cool island. To evaluate the WRF Model's ability to reproduce the diurnal cycle of near-surface meteorology and surface skin temperature, two WRF Model experiments (one using the Bougeault and Lacarrere turbulent scheme and one with the Mellor-Yamada-Janjić turbulent parameterization) at high spatial resolution (1-km horizontal grid spacing) are conducted for each 31-day period. Modeled results show that the WRF Model (coupled to the Noah-MP land surface model) tends to underestimate to some extent surface skin temperature during daytime and overestimate nighttime values during the wintertime period. In the same way, the WRF Model tends to accurately reproduce the diurnal cycle of near-surface air temperature, including maximum and minimum temperatures, and wind speed during summertime, but notably overestimates nighttime near-surface air temperature during wintertime. This nighttime overestimation is especially remarkable with the Bougeault and Lacarrere turbulent scheme for both urban and rural areas. [ABSTRACT FROM AUTHOR]

This paper examines the collective impacts of urban building complexes on the planetary boundary layer (PBL) winds using both observations and a mesoscale model. Horizontal winds measured on the rooftops of federal buildings over the regions of Washington, D.C., and a small city nearby (i.e., Reston, Virginia) show the blocking effects of urban building complexes on the downstream winds during the daytime of 9 July 2007. A modeling study of the case using a coupled version of the Weather Research and Forecasting (WRF)–multilayer urban canopy model in which the observed building height and density information is implemented to advance the calculations of momentum and heat, reproduces the rooftop-observed wind patterns and the related urban heat island effects, especially the wake flows on the downstream sides of the above-mentioned two cities. Results show that under daytime conditions the building complexes can collectively form a mesoscale wake on the downwind side of each city, about 2–10 km away, horizontally from the edge of the building complexes. The wake flow may extend to much higher levels than the building tops, depending on the incoming flow strength, the static stability in the PBL, the height of the building complexes, and the time of the day because of the strength of surface insolation. [ABSTRACT FROM AUTHOR]

The present paper discusses development of a hybrid model for predicting near surface air temperature (2 m) over the city scale (∼100 m). The model is based on the premise that temperature at each place within the city is correlated with its mean temperature. The proposed model estimates the mean temperature of a city, using the forecast generated (5 km × 5 km resolution) by regional weather prediction model viz., Weather and Research Forecast (WRF) and downscale it to city scale, using the correlations estimated from the satellite based high-resolution (1 km × 1 km) surface characteristics i.e. Land Surface Temperature (LST). The downscaling coefficients at each grid (1 km x1 km) are generated by formulating the statistical relationship between the LST over the grid to the mean temperature of a city. LST from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor on-board Aqua satellite during the Indian summer season (April–June) of the year 2017–2018 has been employed for this purpose. The relationship between LST and air temperature is established using the collocated satellite estimated LST and monitored air temperature observations. As a case study, the model is demonstrated for the Indian city Ahmedabad, but the same procedure can be extended for any other cities. The existence of strong urban heat island during night hours over Ahmedabad city with a temperature gradient of 4-5 °C has been found in the study. During day hours the different parts of the city depicts different temperature based on their surface characteristics. The results have been validated using the in-situ data based on the ground based observational network temporally installed at different locations of the city for the year 2022. The developed model shows that it has a potential to be used in operational mode for generating location specific extreme temperature or heat wave warning within a city. • Development of a hybrid model for predicting near surface air temperature over the city scale. • Model involves downscaling numerical model forecast using LST and air temperature. • The developed model shows the potential for predicting location specific extreme temperature. [ABSTRACT FROM AUTHOR]

A fine-resolution, meso-urban meteorological model was updated and applied, using new data and techniques in this study, in driving fine-resolution photochemical simulations to evaluate the air-quality impacts of urban heat island mitigation. The drag-force-based formulation of the model improves the simulation of fine-resolution meteorological and air-pollutant concentration fields in the urban canopy layer. Compared to the meso scale, the meso-urban modeling of heat island mitigation produces larger localized impacts on meteorology and ozone air quality and captures phenomena of interest that are typically not detectable at the coarser scale. These include, for example, cool islands, heat islands, flow convergence associated with heat island circulation, flow divergence at the leading edge of urban areas, and vertical variation in turbulent kinetic energy budget components within the canopy layer in response to vertical changes in densities of buildings and vegetation. They also include fine-resolution features in the simulated ozone concentration field and its response to surface modifications. Model results show that heat island mitigation is effective in reducing local ozone concentrations. This paper presents results from Sacramento, California, as an example using increased urban albedo as the control mechanism. For the region, episodic conditions, and surface modification scenarios examined in this paper, air temperature is decreased by up to 3°C. Changes in ozone consist overwhelmingly of decreases but can also involve increases with the latter being confined to small areas and short time intervals. While larger reductions in ozone are detected, decreases of up to 5–10ppb are more representative and the daily maximum 8-h average can be decreased by up to 13%. [Copyright &y& Elsevier]

An increasing trend in ground-level ozone (O3) concentrations has recently been recognized in Japan, although concentrations of ozone precursors, nitrogen oxides (NOx), volatile organic compounds (VOCs) and nonmethane hydrocarbons (NMHCs) have decreased. In this paper, the relationship between meteorological factors (temperature and wind speed) and ground-level ozone concentrations in the summer over the central Kanto area of Japan was examined using both statistical analyses and numerical models. The Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) and the Community Multiscale Air Quality (CMAQ) model were employed in this study. It was found that there is a close relationship between meteorological conditions and ground-level ozone concentrations over the central Kanto area. In summer, up to 84% of the long-term variation in peak ozone concentrations may be accounted for by changes in the seasonally averaged daily maximum temperature and seasonally averaged wind speed, while about 70% of the recent short-term variation in peak ozone depends on the daily maximum temperature and the daily averaged wind speed. The results of numerical simulations also indicate that urban heat island (UHI) phenomena can play an important role in the formation of high ozone concentrations in this area. [ABSTRACT FROM AUTHOR]

Urban modification of precipitation regimes is well documented in the urban climate literature. Studies investigating urbanization and non-convective precipitation, specifically winter precipitation, are limited. The theoretical framework here argues that the collective influence of urbanization extends beyond traditional city limits and the surrounding rural areas and can impact regional climate in non-adjacent cities. This paper utilizes the weather research and forecasting model (WRF-ARW) to simulate a cold-season synoptic system over the Northeastern United States over a variety of urban land surface scenarios. This case study centers on the potential boundary layer urban heat island effect on the lower troposphere and its ability to impact winter precipitation type at the local to regional scales. Results show a significant reduction in temperatures near the modified surface and subtle reductions over adjacent urban areas. When surface wind speeds are less than 5 ms−1, the boundary layer heat island increases air temperatures on the order of 3–4 °C at altitudes up to 925 mb. When combined with encroaching warm air near 850 mb during transitional precipitation events, the boundary layer heat island increases the thickness of the melting layer and consequently exposes falling hydrometeors to longer melting duration and phase change. Model simulations also show regional connections through remote temperature and relative humidity changes in urban areas removed from reforested areas. [ABSTRACT FROM AUTHOR]

Heatwaves have considerable socioeconomic impact. Because of the urban heat island effect, risks associated with heatwaves are exacerbated in urban areas compared with surrounding regions. This study investigated the behaviors of local-scale urban heat island during a heatwave in Beijing using in situ observations and kilometer-scale simulations based on the Weather Research and Forecasting model. Results showed the observed urban heat island was enhanced by 0.78 °C during the heatwave episode, with greater increase at night than during daytime. The model with gridded urban canopy parameters was able to capture the spatiotemporal variation of surface air temperature, although it overestimated the magnitude. Spatial variation of urban canopy parameters could improve simulation of the spatiotemporal variations of near-surface air temperature in urban areas. Using a biophysical factorization method, urbanization-induced temperature changes were attributed to different driving factors. Results suggested that heatwave-related enhancement of urban heat island during daytime is primarily because of increased urban–rural contrast in surface evapotranspiration, whereas such enhancement at night is associated mainly with greater anthropogenic heat and enhanced warm advection. Since climate change make heatwaves more frequent, intense and persistent, targeted implementation of adaptation measures are needed to reduce the negative effects of urban heat island and to minimize their related risks to public health, power grids, and infrastructure. • This paper demonstrates the enhancement of urban heat island (UHI) due to heat wave using observations and numerical model. • Observed UHI in Beijing was enhanced by 0.78 °C during a heatwave episode, more profoundly during night than during daytime. • Enhanced UHI is due to increased urban–rural contrasts in surface evapotranspiration, anthropogenic heat and warm advection. • Synergistic interactions between UHI and heatwave present further heat-related risks for urban society and residents. [ABSTRACT FROM AUTHOR]

• Weather Research and Forecasting (WRF) model is coupled with building energy models. • The albedo of roofs, walls and grounds is increased from 0.2 to 0.65, 0.60 and 0.45 respectively. • Maximum decrease in air temperature as predicted by the WRF model is 2°C at noon. • Daily averaged decrease of surface temperature and absolute humidity are 3.3 °C and 0.6 g/kg. • Cooling energy demand savings in Toronto with higher surface albedo ranged from 7% to 10%. In this paper, the numerical Weather Research and Forecasting (WRF) model is coupled with a Building Effect Parameterization (BEP) and Building Energy Model (BEM) to investigate the effects on the urban microclimate and building energy demand of increasing the albedo of urban surfaces. For the scope of this study, while the WRP performs real-data applications numerical weather prediction, the BEP serves to predict the heat and moisture fluxes from the urban canopies to the atmosphere and the BEM simulates the effects of anthropogenic heat emissions. As such the overall simulations are capable of taking into account the several factors that influence the urban microclimate and couple their mutual interactions. Outdoor microclimate results for the air temperature and wind speed are compared against measurements in Toronto, ON, during the 2018 heatwave period. The validation confirms the reliability of the WRF model and the selected approach. Then, in order to assess possible urban heat island mitigation strategies, the albedos of roofs, walls, and ground surfaces are increased from 0.2 to 0.65, 0.60, and 0.45, respectively. Results show that the maximum decrease in air temperature through these higher albedo values is nearly 2 °C at noon with a slight increase in wind speed. Moreover, the daily averaged decrease in the urban surface temperature and in the absolute humidity is 3.3 °C and 0.6 g/kg, respectively. Increasing the surface albedo would reduce the solar radiation balance at noon by almost 30 W/m2. Finally, the combined effect of decreased solar heat gains by urban surfaces and decreased air temperature would reduce the cooling energy demand by almost 10%. [ABSTRACT FROM AUTHOR]