Convective clouds are important for both the vertical redistribution of tropospheric trace gases and the removal, via microphysical scavenging, of soluble trace gas precursors of ozone. We investigate wet scavenging of formaldehyde (CH2O), hydrogen peroxide (H2O2), and methyl hydrogen peroxide (CH3OOH) in quasi-marine and land convective storms over Texas, USA observed on 18 September 2013 during the 2013 SEAC(4)RS campaign. Cloud-resolving simulations using the Weather Research and Forecasting model with Chemistry (WRF-Chem) were performed to understand the effect of entrainment, scavenging efficiency (SE), and ice physics processes on these trace gases with varying solubility. While marine and land convection can have distinctly different microphysical properties, we did not find significant differences in the SEs of CH2O, H2O2, or CH3OOH. The SEs of 44%-53% for CH2O and 85%-90% for H2O2 are consistent with our previous studies from SEAC(4)RS and the 2012 DC3 field experiment storms. Using WRF-Chem simulations, the ice retention factor (r(f)) for CH2O was determined to be 0.5-0.9, which is higher than found in previous studies. We show that the CH2O r(f) is higher in airmass and multicell storms than in severe storms and hypothesize that ice shattering may affect CH2O r(f) values. The CH3OOH SEs (39%-73%) were higher than expected from Henry's Law equilibrium. While recent studies suggest that CH3OOH measurements have interference due to methane diol, we find that this interference cannot fully explain the higher-than-expected CH3OOH SEs determined here and during DC3, suggesting further research is needed to understand CH3OOH vertical redistribution.

The convectively driven transport of soluble trace gases from the lower to the upper troposphere can occur on timescales of less than an hour, and recent studies suggest that microphysical scavenging is the dominant removal process of tropospheric ozone precursors. We examine the processes responsible for vertical transport, entrainment, and scavenging of soluble ozone precursors (formaldehyde and peroxides) for midlatitude convective storms sampled on 2 September 2013 during the Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) study. Cloud‐resolving simulations using the Weather Research and Forecasting with Chemistry model combined with aircraft measurements were performed to understand the effect of entrainment, scavenging efficiency (SE), and ice physics processes on these trace gases. Analysis of the observations revealed that the SEs of formaldehyde (43–53%) and hydrogen peroxide (~80–90%) were consistent between SEAC4RS storms and the severe convection observed during the Deep Convective Clouds and Chemistry Experiment (DC3) campaign. However, methyl hydrogen peroxide SE was generally smaller in the SEAC4RS storms (4%–27%) compared to DC3 convection. Predicted ice retention factors exhibit different values for some species compared to DC3, and we attribute these differences to variations in net precipitation production. The analyses show that much larger production of precipitation between condensation and freezing levels for DC3 severe convection compared to smaller SEAC4RS storms is largely responsible for the lower amount of soluble gases transported to colder temperatures, reducing the amount of soluble gases which eventually interact with cloud ice particles.

The role of the sea/bay breeze in the planetary boundary layer evolution and air quality during a high ozone event day in the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Texas 2013 campaign was examined. Data from surface air quality monitoring network stations, airborne lidar data, and additional ground-based lidar instrumentation deployed during the campaign allowed for a unique three-dimensional spatial and temporal study of the progression of both meteorological and air quality conditions in the Houston-Galveston regions on 25 September 2013. The Weather Research and Forecasting model coupled with Chemistry model was used to examine the relationship of the land and bay/sea breeze circulations and its influence on air quality during the case study. Comparisons between observations and simulations revealed the largest discrepancies near the Galveston Bay shore areas where the highly localized ozone concentrations were observed and were linked to the strength and timing of the bay/sea breeze progression. Additionally, results indicate vertical downmixing from the remnants of the nighttime residual layer during morning hours into the convective boundary layer and from the lofted offshore return flow into the subjacent bay breeze flow.

In this study, we performed meteorological and chemical sensitivity studies employing two different Weather Research and Forecasting model with Chemistry (WRF-Chem) simulations: one with the standard Planetary Boundary Layer (PBL) Yonsei scheme (YSU), and one with a modified YSU PBL scheme proposed in a previous work. The WRF-Chem results were compared to observational temporally highly resolved boundary layer data obtained during the Vertical Mixing Experiment (VME) which was part of the 2006 TexAQS-II radical and aerosol measurement project (TRAMP) campaign. The analysis of meteorological variables indicates that in particular during the morning transition of the PBL (at 10 CDT), which is a critical time period for pollutant dispersion, the statistical scores presented improvements for all variables, when the modified YSU PBL scheme was used. Overall, the sensitivity of pollutant concentrations in the WRF-Chem model towards the representation of diffusion processes of the evening transition in the vertical mixing calculation showed reasonably good agreement with observations during the VME period. The comparison of vertical profiles of O-3 showed appreciable differences (up to similar to 8 ppbv) between the standard and modified YSU scheme during the morning hours; in the afternoon, the modified YSU presented only a slight improvement in the simulation of O-3 precursors concentrations such as CO and NOx. These improvements were possible without a significant increase in complexity or computer time. However, the model still oversimplifies the vertical mixing within the PBL, and uncertainties in the turbulence structure of the PBL in the WRF-Chem still remain.

We implemented the Weather Research and Forecast (WRF) model and WRF Large-Eddy Simulation (WRF–LES), focusing on calculations for the planetary boundary layer (PBL), and compared the results against a data set of a well-documented campaign, in the Houston–Galveston area, Texas, in summer 2006. A methodology using WRF in a mesoscale and LES was implemented to assess the performance of the model in simulating the evolution and structure of the PBL over Houston during the Vertical Mixing Experiment. Also, the WRF model in a real case mode was examined to explore potential differences between the results of each simulation approach. We analyzed both WRF results for key meteorological parameters like wind speed, wind direction and potential temperature, and compared the model results against the observations. The reasonably good agreement of LES results forced with observed surface fluxes provides confidence that LES describes turbulence quantities such as turbulent kinetic energy correctly and warrants further turbulence structure analysis. The LES results indicate a weak but noticeable nighttime turbulent kinetic energy which was produced by wind shear in Houston’s planetary boundary layer and which may likely be related to intermittent turbulence. This is supported by observations made at the University of Houston Moody Tower air quality station when intermittent peaks of carbon monoxide occurred in the evening, although the variability in wind conditions was very little.

On January 4, 2014, during the summer period in South America, an intense forest and dry pasture wildfire occurred nearby the city of Santiago de Chile. On that day the biomass-burning plume was transported by low-intensity winds towards the metropolitan area of Santiago and impacted the concentration of pollutants in this region. In this study, the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) is implemented to investigate the biomass-burning plume associated with these wildfires nearby Santiago, which impacted the ground-level ozone concentration and exacerbated Santiago's air quality. Meteorological variables simulated by WRF/Chem are compared against surface and radiosonde observations, and the results show that the model reproduces fairly well the observed wind speed, wind direction air temperature and relative humidity for the case studied. Based on an analysis of the transport of an inert tracer released over the locations, and at the time the wildfires were captured by the satellite-borne Moderate Resolution Imaging Spectroradiometer (MODIS), the model reproduced reasonably well the transport of biomass burning plume towards the city of Santiago de Chile within a time delay of two hours as observed in ceilometer data. A six day air quality simulation was performed: the first three days were used to validate the anthropogenic and biogenic emissions, and the last three days (during and after the wildfire event) to analyze the performance of WRF/Chem plume-rise model within FINNv1 fire emission estimations. The model presented a satisfactory performance on the first days of the simulation when contrasted against data from the well-established air quality network over the city of Santiago de Chile. These days represent the urban air quality base case for Santiago de Chile unimpacted by fire emissions. However, for the last three simulation days, which were impacted by the fire emissions, the statistical indices showed a decrease in the model performance. While the model showed a satisfactory evidence that wildfires plumes that originated in the vicinity of Santiago de Chile were transported towards the urban area and impacted the air quality, the model still underpredicted some pollutants substantially, likely due to misrepresentation of fire emission sources during those days. Potential uncertainties may include to the land use/land cover classifications and its characteristics, such as type and density of vegetation assigned to the region, where the fire spots are detected. The variability of the ecosystem type during the fire event might also play a role.

In the present study, the well-known case of day 33 of the Wangara experiment is resimulated using the Weather Research and Forecasting (WRF) model in an idealized single-column mode to assess the performance of a frequently used planetary boundary layer (PBL) scheme, the Yonsei University PBL scheme. These results are compared with two large eddy simulations for the same case study imposing different surface fluxes: one using previous surface fluxes calculated for the Wangara experiment and a second one using output from the WRF model. Finally, an alternative set of eddy diffusivity equations was tested to represent the transition characteristics of a sunset period, which led to a gradual decrease of the eddy diffusivity, and replaces the instantaneous collapse of traditional diagnostics for eddy diffusivities. More appreciable changes were observed in air temperature and wind speed (up to 0.5 K, and 0.6 m s −1 , respectively), whereas the changes in specific humidity were modest (up to 0.003 g kg −1 ). Although the representation of the convective decay in the standard parameterization did not show noticeable improvements in the simulation of state variables for the selected Wangara case study day, small changes in the eddy diffusivity over consecutive hours throughout the night can impact the simulation of distribution of trace gases in air quality models. So, this work points out the relevance of simulating the turbulent decay during sunset, which could help air quality forecast models to better represent the distribution of pollutants storage in the residual layer during the entire night.

Air quality forecasting requires atmospheric weather models to generate accurate meteorological conditions, one of which is the development of the planetary boundary layer (PBL). An important contributor to the development of the PBL is the land–air exchange captured in the energy budget as well as turbulence parameters. Standard and surface energy variables were modeled using the fifth-generation Penn State/National Center for Atmospheric Research mesoscale model (MM5), version 3.6.1, and the Weather Research and Forecasting (WRF) model, version 3.5.1, and compared to measurements for a southeastern Texas coastal region. The study period was 28 August–1 September 2006. It also included a frontal passage. The results of the study are ambiguous. Although WRF does not perform as well as MM5 in predicting PBL heights, it better simulates energy budget and most of the general variables. Both models overestimate incoming solar radiation, which implies a surplus of energy that could be redistributed in either the partitioning of the surface energy variables or in some other aspect of the meteorological modeling not examined here. The MM5 model consistently had much drier conditions than the WRF model, which could lead to more energy available to other parts of the meteorological system. On the clearest day of the study period, MM5 had increased latent heat flux, which could lead to higher evaporation rates and lower moisture in the model. However, this latent heat disparity between the two models is not visible during any other part of the study. The observed frontal passage affected the performance of most of the variables, including the radiation, flux, and turbulence variables, at times creating dramatic differences in the r2 values.

Foi realizado o estudo do comportamento das concentrações de ozônio (O3) de superfície, monóxido de carbono (CO), óxidos de nitrogênio (NOX) e hidrocarbonetos (HC) na Região Metropolitana de Porto Alegre (RMPA), através de simulações numéricas realizadas utilizando o PREP-CHEM (Preprocessor of trace gas and aerosol emission fields for regional and global atmospheric chemistry models) no modelo CCATT-BRAMS (Coupled Chemistry Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System). O domínio da modelagem foi implementado sobre uma área cobrindo a RMPA, dando ênfase às fontes antrópicas (móveis) e biogênicas. Para a validação dos resultados, foram realizadas comparações com dados de razão de mistura obtidos pelo monitoramento da qualidade do ar na RMPA.

With over 6 million inhabitants the Houston metropolitan area is the fourth-largest in the United States. Ozone concentration in this southeast Texas region frequently exceeds the National Ambient Air Quality Standard (NAAQS). For this reason our study employed the Weather Research and Forecasting model with Chemistry (WRF/Chem) to quantify meteorological prediction differences produced by four widely used PBL schemes and analyzed its impact on ozone predictions. The model results were compared to observational data in order to identify one superior PBL scheme better suited for the area. The four PBL schemes include two first-order closure schemes, the Yonsei University (YSU) and the Asymmetric Convective Model version 2 (ACM2); as well as two turbulent kinetic energy closure schemes, the Mellor-Yamada-Janjic (MYJ) and Quasi-Normal Scale Elimination (QNSE). Four 24 h forecasts were performed, one for each PBL scheme. Simulated vertical profiles for temperature, potential temperature, relative humidity, water vapor mixing ratio, and the u-v components of the wind were compared to measurements collected during the Second Texas Air Quality Study (TexAQS-II) Radical and Aerosol Measurements Project (TRAMP) experiment in summer 2006. Simulated ozone was compared against TRAMP data, and air quality stations from Continuous Monitoring Station (CAMS). Also, the evolutions of the PBL height and vertical mixing properties within the PBL for the four simulations were explored. Although the results yielded high correlation coefficients and small biases in almost all meteorological variables, the overall results did not indicate any preferred PBL scheme for the Houston case. However, for ozone prediction the YSU scheme showed greatest agreements with observed values. (C) 2014 Elsevier Ltd. All rights reserved.

A diffusion equation limit derived from the Langevin stochastic particle model is used to study the dispersion of scalars caused by an evolving turbulence in the transition process occurring during the sunset period. Therefore, the random displacement equation is employed to simulate the cross-wind concentrations of pollutants released from low and high point sources. Turbulence inputs are parameterized to describe in a continuous manner the dispersion effects produced by a decaying convective elevated and a shear-dominated stable surface turbulence. The simulation results show that for the initial stage of the sunset transition phenomenon, the pollutants are transported rapidly to the surface. On the other hand, for the sunset evolution advanced stages, the dispersion process happens in a deep stable boundary layer (SBL), in which the pollutants can travel long distances practically without reaching the surface. The major progress shown in this analysis is the description of the transport properties associated to decaying convective eddies in the residual layer (RL). The study shows that the diffusion effects associated to these decaying convective eddies strongly influence the dispersion of scalars during the sunset transition period.