The preprocessor PREP-CHEM-SRC presented in the paper is a comprehensive tool aiming at preparing emission fields of trace gases and aerosols for use in atmospheric-chemistry transport models. The considered emissions are from the most recent databases of urban/industrial, biogenic, biomass burning, volcanic, biofuel use and burning from agricultural waste sources. For biomass burning, emissions can be also estimated directly from satellite fire detections using a fire emission model included in the tool. The preprocessor provides emission fields interpolated onto the transport model grid. Several map projections can be chosen. The inclusion of these emissions in transport models is also presented. The preprocessor is coded using Fortran90 and C and is driven by a namelist allowing the user to choose the type of emissions and the databases.

We present a new version of the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS), in which different previous versions for weather, chemistry, and carbon cycle were unified in a single integrated modeling system software. This new version also has a new set of state-of-the-art physical parameterizations and greater computational parallel and memory usage efficiency. The description of the main model features includes several examples illustrating the quality of the transport scheme for scalars, radiative fluxes on surface, and model simulation of rainfall systems over South America at different spatial resolutions using a scale aware convective parameterization. Additionally, the simulation of the diurnal cycle of the convection and carbon dioxide concentration over the Amazon Basin, as well as carbon dioxide fluxes from biogenic processes over a large portion of South America, are shown. Atmospheric chemistry examples show the model performance in simulating near-surface carbon monoxide and ozone in the Amazon Basin and the megacity of Rio de Janeiro. For tracer transport and dispersion, the model capabilities to simulate the volcanic ash 3-D redistribution associated with the eruption of a Chilean volcano are demonstrated. The gain of computational efficiency is described in some detail. BRAMS has been applied for research and operational forecasting mainly in South America. Model results from the operational weather forecast of BRAMS on 5 km grid spacing in the Center for Weather Forecasting and Climate Studies, INPE/Brazil, since 2013 are used to quantify the model skill of near-surface variables and rainfall. The scores show the reliability of BRAMS for the tropical and subtropical areas of South America. Requirements for keeping this modeling system competitive regarding both its functionalities and skills are discussed. Finally, we highlight the relevant contribution of this work to building a South American community of model developers.

Coupled Chemistry Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT-BRAMS, version 4.5) is an on-line regional chemical transport model designed for local and regional studies of atmospheric chemistry from the surface to the lower stratosphere suitable both for operational and research purposes. It includes gaseous/aqueous chemistry, photochemistry, scavenging and dry deposition. The CCATT-BRAMS model takes advantage of BRAMS-specific development for the tropics/subtropics as well as the recent availability of preprocessing tools for chemical mechanisms and fast codes for photolysis rates. BRAMS includes state-of-the-art physical parameterizations and dynamic formulations to simulate atmospheric circulations down to the meter. This on-line coupling of meteorology and chemistry allows the system to be used for simultaneous weather and chemical composition forecasts as well as potential feedback between the two. The entire system is made of three preprocessing software tools for user-defined chemical mechanisms, aerosol and trace gas emissions fields and the interpolation of initial and boundary conditions for meteorology and chemistry. In this paper, the model description is provided along with the evaluations performed by using observational data obtained from ground-based stations, instruments aboard aircrafts and retrieval from space remote sensing. The evaluation accounts for model applications at different scales from megacities and the Amazon Basin up to the intercontinental region of the Southern Hemisphere.

This paper evaluates the implementation of the Weather Research and Forecasting model, WRF, for its use as the meteorological pre–processor for diagnostic air quality modeling in Cuba. The implementation of the WRF involved two studies: the first one was aimed at defining which global meteorological data is more suited for Cuba; the second one consisted of an analysis of the results for long–term runs on two domains, with the specific objective of assessing the general performance of the model. The results of the model were compared with the observations of the National Weather Service surface stations. The comparisons showed good performance for temperature and acceptable performance for prediction of wind tendencies. On average, the wind speed is overestimated in the model and the wind direction deviations exceed 30 degrees for several of the meteorological stations. These deviations are related to nearby topography and the low–wind speed. Some additional studies must be conducted in order to clarify and reduce the wind deviations. The research concludes that the WRF output is able to provide realistic meteorological patterns for air quality models, which require high–resolution three–dimensional (3D) meteorological data. The WRF–fsl tool was developed to use WRF to feed the local models as AERMOD when upper air data is not available. This tool takes the WRF output and gets the upper air data, in the fsl radiosonde format. The WRF–fsl results were compared to other solution, which incorporates a surface data parameterization. The conclusion is that the efforts, to run WRF for long periods, are not justified with the improvement in the results for regulatory purposes. However, as the differences in convective mixing height could be significant, this solution would be very useful for other kind of studies

Smoke aerosols prevail throughout Amazonia because of widespread biomass burning during the dry season, and external mixing, low variability in the particle size distribution and low particle hygroscopicity are typical. There can be profound effects on cloud properties. This study uses an adiabatic cloud model to simulate the activation of smoke particles as cloud condensation nuclei (CCN) for three hypothetical case studies, chosen as to resemble biomass burning aerosol observations in Amazonia. The relative importance of variability in hygroscopicity, mixing state, and activation kinetics for the activated fraction and maximum supersaturation is assessed. For a population with κ_p = 0.04, an overestimation of the cloud droplet number concentration N_d for the three selected case studies between 22.4 ± 1.4 and 54.3 ± 3.7 % was obtained when assuming a hygroscopicity parameter κ_p = 0.20. Assuming internal mixing of the aerosol population led to overestimations of up to 20 % of N_d when a group of particles with medium hygroscopicity was present in the externally mixed population cases. However, the overestimations were below 10 % for external mixtures between very low and low-hygroscopicity particles, as seems to be the case for Amazon smoke particles. Kinetic limitations were significant for medium- and high-hygroscopicity particles, and much lower for very low and low-hygroscopicity particles. When particles were assumed to be at equilibrium and to respond instantly to changes in the air parcel supersaturation, the overestimation of the droplet concentration was up to ∼ 100 % in internally mixed populations, and up to ∼ 250 % in externally mixed ones, being larger for the higher values of hygroscopicity. In addition, a perceptible delay between the times when maximum supersaturation and maximum aerosol activated fraction are reached was noticed and, for aerosol populations with effective hygroscopicity κp_eff higher than a certain threshold value, the delay in particle activation was such that no particles were activated at the time of maximum supersaturation. Considering internally mixed populations, for an updraft velocity W = 0.5 m s⁻¹ this threshold of no activation varied between κp_eff = 0.35 and κp_eff = 0.5 for the different case studies. However, for low hygroscopicity, kinetic limitations played a weaker role for CCN activation of particles, even when taking into account the large aerosol mass and number concentrations. For the very low range of hygroscopicities, the overestimation of the droplet concentration due to the equilibrium assumption was lowest and the delay between the times when maximum supersaturation and maximum activated fraction were reached was greatly reduced or no longer observed (depending on the case study). These findings on uncertainties and sensitivities provide guidance on appropriate simplifications that can be used for modeling of smoke aerosols within general circulation models. The use of medium values of hygroscopicity representative of smoke aerosols for other biomass burning regions on Earth can lead to significant errors compared to the use of low hygroscopicity for Amazonia (between 0.05 and 0.13, according to available observations). Also in this region, consideration of the biomass burning population as internally mixed will lead to small errors in the droplet concentration, while significantly increasing the computational burden. Regardless of the large smoke aerosol loads in the region during the dry season, kinetic limitations are expected to be low.