Search

A new open biomass burning inventory is presented that relies on the fire radiative power data from the Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi NPP satellite. This VIIRS-based Fire Emission Inventory (VFEI) provides emission data from early 2012 to 2019 for more than 40 species of gases and aerosols at spatial resolutions of around 500 m. We found that VFEI produces similar results when compared to other major inventories in many regions of the world. Additionally, we conducted regional simulations using VFEI with the Weather Research and Forecasting (WRF) model with chemistry (WRF-Chem) for Southern Africa (September 2016) and North America (July–August 2019). We compared aerosol optical depth (AOD) from the model against two observational datasets: the MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) product and AErosol RObotic NETwork (AERONET) stations. Results showed good agreement between both simulations and the datasets, with mean AOD biases of around +0.03 for Southern Africa and −0.01 for North America. Both simulations were not only able to reproduce the AOD magnitudes accurately, but also the inter-diurnal variations of smoke concentration. In addition, we made use of the airborne data from the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES; Southern Africa) and the Fire Influence on Regional to Global Environments Experiment and Air Quality (FIREX-AQ; North America) campaigns to evaluate the simulations. In Southern Africa, results showed correlations higher than 0.77 when comparing carbon monoxide and black carbon. In North America, correlations were lower and biases higher. However, this is because the model was not able to reproduce the timing, shape, and location of individual plumes over complex terrain (Rocky Mountains) during the FIREX-AQ campaign period.

The demand for water has led to an increase in scarcity events in several urban regions. In an urban context, water consumption in buildings plays an important role and rainwater harvesting is one of the ways that consumption can be reduced. One of the input variables for the dimensioning of rainwater tanks is the pluviometric regime's characteristics in the region where the rainwater harvesting system (RWHS) is to be installed. In this study, a bibliometric and systematic literature review was carried out on the types of rainfall data used in the dimensioning of the elements of RWHS. Worldwide, the most-used data comes from meteorological stations, with a historical series size of 30 years, however, other types of data and different sizes of historical series are also used. From this study, it was possible to synthesise the regions where differentiation data can be collected, as well as their characteristics, enabling the researchers to quickly access the definition of separation data collection parameters.

Plume height plays a vital role in wildfire smoke dispersion and the subsequent effects on air quality and human health. In this study, we assess the impact of different plume rise schemes on predicting the dispersion of wildfire air pollution and the exceedances of the National Ambient Air Quality Standards (NAAQS) for fine particulate matter (PM2.5) during the 2020 western United States wildfire season. Three widely used plume rise schemes (Briggs, 1969; Freitas et al., 2007; Sofiev et al., 2012) are compared within the Community Multiscale Air Quality (CMAQ) modeling framework. The plume heights simulated by these schemes are comparable to the aerosol height observed by the Multi-angle Imaging SpectroRadiometer (MISR) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The performance of the simulations with these schemes varies by fire case and weather conditions. On average, simulations with higher plume injection heights predict lower aerosol optical depth (AOD) and surface PM2.5 concentrations near the source region but higher AOD and PM2.5 in downwind regions due to the faster spread of the smoke plume once ejected. The 2-month mean AOD difference caused by different plume rise schemes is approximately 20 %–30 % near the source regions and 5 %–10 % in the downwind regions. Thick smoke blocks sunlight and suppresses photochemical reactions in areas with high AOD. The surface PM2.5 difference reaches 70 % on the West Coast of the USA, and the difference is lower than 15 % in the downwind regions. Moreover, the plume injection height affects pollution exceedance (>35 µg m−3) predictions. Higher plume heights generally produce larger downwind PM2.5 exceedance areas. The PM2.5 exceedance areas predicted by the three schemes largely overlap, suggesting that all schemes perform similarly during large wildfire events when the predicted concentrations are well above the exceedance threshold. At the edges of the smoke plumes, however, there are noticeable differences in the PM2.5 concentration and predicted PM2.5 exceedance region. For the whole period of study, the difference in the total number of exceedance days could be as large as 20 d in northern California and 4 d in the downwind regions. This disagreement among the PM2.5 exceedance forecasts may affect key decision-making regarding early warning of extreme air pollution episodes at local levels during large wildfire events.

Resumo O BRAMS-SFIRE é um novo sistema de modelação atmosférica com componente de propagação de fogo desenvolvido no Centro de Previsão de Tempo e Estudos Climáticos (CPTEC / INPE) no Brasil em colaboração com o Instituto Mediterrâneo de Agricultura, Ambiente e Desenvolvimento (MED) em Portugal. O presente artigo descreve a incorporação do modelo de propagação de fogo no Brazilian developments on the Regional Atmospheric Modeling System (BRAMS). Os principais objetivos foram desenvolver o acoplamento entre um modelo atmosférico e um modelo de propagação de fogo que simulasse os efeitos da circulação atmosférica sobre um incêndio florestal e vice-versa. Esta ferramenta tem como objetivo ajudar a entender as relações entre o fogo e a paisagem nas florestas de carvalho mediterrâneas, e avaliar os resultados das simulações deste acoplamento na escala fina no ecossistema do Montado na região do Alentejo. Para isso, três grades de alta resolução espacial ao longo de três incêndios foram configuradas com dados de caracterização de superfície realistas e propriedades dos modelos de combustível. Uma grade foi colocada sobre fogo em uma planície e as outras nas montanhas, para avaliar os diferentes tipos de propagação do fogo. Este trabalho demonstra que este sistema simula de forma consistente a interação entre o fogo, os modelos de combustível e a atmosfera, mostrando que o fogo altera a circulação local ao nível da superfície, intensifica as correntes de vento ascendentes e descendentes, alterando a estrutura da atmosfera. Abstract BRAMS-SFIRE is a new atmospheric modeling system with a fire spreading component developed at the Centro de Previsão de Tempo e Estudos Climáticos (CPTEC/INPE) in Brasil, in collaboration with the Instituto Mediterrâneo para a Agricultura, Ambiente e Desenvolvimento (MED) in Portugal. The present paper describes the incorporation of the fire model into the Brazilian development of the Regional Atmospheric Modelling System (BRAMS). The main objectives were to develop the coupling between an atmospheric and a spreading fire models which simulate the effects of atmospheric circulation over a wildfire and vice-versa. This tool is intended to help understand fire-landscape relationships in Mediterranean oak woodlands and evaluate the simulation results on a fine-scale in the Alentejo region's Montado ecosystem. For this purpose, three grids of very high spatial resolution over three fires were configured with realistic surface characterization data and fuel model properties. One grid was placed at a fire in the plains and the others in the mountains to evaluate fire propagation types. This work demonstrates that this system consistently simulated the interaction between the fire, the fuel models, and the atmosphere, showing the fire changes the local circulation at the surface level, intensify wind currents, and changes the atmosphere structure.

A new open biomass burning inventory is presented that relies on the fire radiative power data from the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP satellite. This VIIRS-based Fire Emission Inventory (VFEI) provides emission data from early 2012 to 2019 for more than 40 species of gases and aerosols at spatial resolutions of around 500 m. We found that VFEI produces similar results when compared to other major inventories in many regions of the world. Additionally, we conducted regional simulations using VFEI with the Weather Research and Forecasting (WRF) model with chemistry (WRF-Chem) for Southern Africa (September 2016) and North America (July–August 2019). We compared aerosol optical depth (AOD) from the model against two observational datasets: the MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) product and AErosol RObotic NETwork (AERONET) stations. Results showed good agreement between both simulations and the datasets, with mean AOD biases of around +0.03 for Southern Africa and –0.01 for North America. Both simulations were not only able to reproduce accurately the AOD magnitudes, but also the inter-diurnal variations of smoke concentration. In addition, we made use of the airborne data from the ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES; Southern Africa) and the Fire Influence on Regional to Global Environments Experiment and Air Quality (FIREX-AQ; North America) campaigns to evaluate the simulations. In Southern Africa, results showed correlations higher than 0.77 when comparing carbon monoxide and black carbon. In North America, correlations were lower and biases higher. However, this is because the model was not able to reproduce the timing, shape, and location of individual plumes over complex terrain (Rocky Mountains) during the FIREX-AQ campaign period.

Recent developments and options in the GF (Grell and Freitas, 2014; Freitas et al., 2018) convection parameterization are presented. The parameterization has been expanded to a trimodal spectral size to simulate three convection modes: shallow, congestus, and deep. In contrast to usual entrainment and detrainment assumptions, we assume that beta functions (BFs), commonly applied to represent probability density functions (PDFs), can be used to characterize the vertical mass flux profiles for the three modes and use the BFs to derive entrainment and detrainment rates. We also added a new closure for nonequilibrium convection that improved the simulation of the diurnal cycle of convection, with a better representation of the transition from shallow to deep convection regimes over land. The transport of chemical constituents (including wet deposition) can be treated inside the GF scheme. The tracer transport is handled in flux form and is mass-conserving. Finally, the cloud microphysics have been extended to include the ice phase to simulate the conversion from liquid water to ice in updrafts with resulting additional heat release and the melting from snow to rain.

The Grell-Freitas (GF) cumulus parameterization is an aerosol-aware, scale-aware convective parameterization. This presentation will focus one of the several developmental activities ongoing in GF: the continued development of its aerosol-aware capabilities and the impact in global forecast models.Previous versions of GF initialized aerosols based on an assumed value of aerosol-optical depth (AOD) that was applied uniformly across the entire globe. Observations of AOD indicate that AOD varies substantially across the globe. Recently, the constant AOD value assumed in GF has been replaced by global AOD data from NASA’s MERRA2 reanalysis. Thus, the distribution of aerosols at initialization more physically reasonable and geographically appropriate. This is important since the treatment of aerosols in GF should be most sensitive in regions with either very high or very low AOD. This method is extremely efficient, but can be adapted so that other aerosol and AOD products can be used in GF. Other products that could be used for initialization include the aerosol climatology used by the Thompson Aerosol-Aware Microphysical Parameterization or predicted aerosols using NOAA’s aerosol prediction model, which is currently one ensemble in the Global Ensemble Forecast System – Aerosols (GEFS-Aerosols). GF includes three aerosol related cloud processes: aerosol-influenced evaporation, aerosol-influenced auto-conversion of cloud water to rain water, and aerosol wet scavenging based on memory. As in Wang (2013) the treatment of wet scavenging has been modified so that the aerosol wet scavenging efficiency is proportional to precipitation efficiency. Additionally, aerosols in GF are now allowed to slowly return to their original concentrations during precipitation-free periods. These changes are important since they allow the aerosols in GF to evolve over time in a physically realistic manner.The impact of these changes to GF will be shown in a version of NOAA’s operational global prediction model.

Made available in DSpace on 2018-12-11T17:23:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-01-13 Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) 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 5km 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. Centro de Previsão de Tempo e Estudos Climáticos Instituto Nacional de Pesquisas Espaciais Divisão de Ciência da Computação Instituto Tecnológico de AeronáUtica Universidade Estadual Paulista (Unesp) Faculdade de Ciências Centro de Meteorologia de Bauru (IPMet) Departamento de Ciências Ambientais Universidade Federal de São Paulo Instituto de Astronomia Geofísica e Ciências Atmosféricas Universidade de São Paulo Departamento de Ciências Atmosféricas Universidade Federal de Campina Grande Embrapa Informática Agropecuária Instituto de Ciência e Tecnologia Universidade Federal de São Paulo Departamento de Ciências Atmosféricas e Climáticas Programa de Pós Graduação em Ciências Climáticas Universidade Federal Do Rio Grande Do Norte Centro de Ciências Do Sistema Terrestre Instituto Nacional de Pesquisas Espaciais Departamento de Geociências Universidade Federal de São João Del-Rei Laboratório Associado de Computação e Matemática Aplicada Instituto Nacional de Pesquisas Espaciais Instituto de Ciências Agrárias e Ambientais Mediterrânicas Universidade de Évora Centro Interdisciplinar de Desenvolvimento em Ambiente Gestão Aplicada e Espaço Universidade Lusófona de Humanidades e Tecnologia Campo Grande Faculdade de Meteorologia Universidade Federal de Pelotas Universidade Tecnológica Federal Do Paraná Universities Space Research Association Goddard Earth Sciences Technology and Research at the Global Modeling and Assimilation Office NASA Goddard Space Flight Center Universidade Estadual Paulista (Unesp) Faculdade de Ciências FAPESP: 2014/01563-1 FAPESP: 2014/01564-8 FAPESP: 2015/10206-0 CNPq: 306340/2011-9

We detail recent developments in the GF (Grell and Freitas, 2014, Freitas et al., 2018) convection parameterization and applications. The parameterization has been extended to a trimodal spectral size to simulate the interaction and transition from shallow, congestus and deep convection regimes. Another main new feature is the inclusion of a closure for non-equilibrium convection that resulted in a substantial gain of realism in the simulation of the diurnal cycle of convection, mainly associated with boundary layer forcing over the land. Additional changes include the transport of momentum, the use of three Probability Density Functions (PDF's) to describe the normalized vertical mass flux profiles from deep, congestus, and shallow plumes (respectively) in the grid box, and the option of using temporal and spatial correlations to stochastically perturb PDF's, momentum transport and the closures. Cloud water detrainment is proportional to mass detrainment and in-cloud hydrometeor mixing ratio, and transport of chemical constituents (including wet deposition) can be treated inside the GF scheme. Transport is handled in flux form and is mass conserving. Finally, the cloud microphysics has been extended to include the ice phase to simulate the conversion from liquid water to ice in updrafts with resulting additional heating release, and the melting from snow to rain within a user-specified melting vertical layer.

We will present some recent improvements to the GF parameterization. These include two features that were added to the Grell-Freitas (GF) Cumulus Parameterization to improve the representation of the particle size distribution and to allow parameterized deep convection to propagate. These also include the treatment of tracer transport, wet scavenging, and aqueous phase chemistry, and improvements on interactions with aerosols. A more complete implementation for transport and treatment of atmospheric composition variables was necessary to complement recent new developments at NOAA/ESRL coupling chemical modules within the NWP model.Estimates of cloud water and ice crystal number concentrations are added to GF base on the water-friendly aerosol content, temperature, and the cloud water and ice crystal mixing ratios. This modification is designed to diminish the artificial modification of the particle size distribution that occurs when the single moment cumulus schemes are used with the double-moment microphysics schemes. Simulations demonstrate that the addition of GF ice number concentrations substantially increases ice content aloft in the tropics, which shifts the outgoing longwave radiation distribution towards colder brightness temperatures.The key modification used to enable the propagation of parameterized deep convective is the addition of an advected scalar that represents the cloud base mass flux associated with GF downdrafts. Our implementation of this advected scalar allows the impact of downdrafts from previous time steps to foster propagation. Evaluation and tuning of the new downdraft mass advection term is ongoing.

The increasing volume of data in the area of environmental sciences needs analysis and interpretation. Among the challenges generated by this “data deluge”, the development of efficient strategies for the knowledge discovery is an important issue. Here, statistical and tools from computational intelligence are applied to analyze large data sets from meteorology and climate sciences. Our approach allows a geographical mapping of the statistical property to be easily interpreted by meteorologists. Our data analysis comprises two main steps of knowledge extraction, applied successively in order to reduce the complexity from the original data set. The goal is to identify a much smaller subset of climatic variables that might still be able to describe or even predict the probability of occurrence of an extreme event. The first step applies a class comparison technique: p-value estimation. The second step consists of a decision tree (DT) configured from the data available and the p-value analysis. The DT is used as a predictive model, identifying the most statistically significant climate variables of the precipitation intensity. The methodology is employed to the study the climatic causes of an extreme precipitation events occurred in Alagoas and Pernambuco States (Brazil) at June/2010.

Online coupled meteorology–atmospheric chemistry models have greatly evolved in recent years. Although mainly developed by the air quality modeling community, these integrated models are also of interest for numerical weather prediction and climate modeling, as they can consider both the effects of meteorology on air quality and the potentially important effects of atmospheric composition on weather. This paper summarizes the main conclusions from the “Symposium on Coupled Chemistry–Meteorology/Climate Modelling: Status and Relevance for Numerical Weather Prediction, Air Quality and Climate Research,” which was initiated by the European COST Action ES1004 “European Framework for Online Integrated Air Quality and Meteorology Modelling (EuMetChem).” It offers a brief review of the current status of online coupled meteorology and atmospheric chemistry modeling and a survey of processes relevant to the interactions between atmospheric physics, dynamics, and composition. In addition, it highlights scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for three main application areas: air quality, meteorology (including weather prediction), and climate modeling. It presents a synthesis of scientific progress in the form of answers to nine key questions, and provides recommendations for future research directions and priorities in the development, application, and evaluation of online coupled models.

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 κp = 0.04, an overestimation of the cloud droplet number concentration Nd for the three selected case studies between 22.4 ± 1.4 and 54.3 ± 3.7 % was obtained when assuming a hygroscopicity parameter κp = 0.20. Assuming internal mixing of the aerosol population led to overestimations of up to 20 % of Nd 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 κpeff 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 κpeff = 0.35 and κpeff = 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.

Made available in DSpace on 2021-07-14T10:23:46Z (GMT). No. of bitstreams: 0 Previous issue date: 2016. Added 1 bitstream(s) on 2021-07-14T11:29:11Z : No. of bitstreams: 1 S0102-77862016000800377.pdf: 7188353 bytes, checksum: aae690f108682ecae0c360d6e8aefb60 (MD5) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Este trabalho possui dois objetivos principais, o primeiro é apresentar uma descrição de como o modelo atmosférico BRAMS foi estruturado com o intuito de capacitá-lo a simular a emissão, dispersão e sedimentação de cinzas vulcânicas; o segundo é fazer uma análise de sensibilidade com relação a diversas configurações do modelo, com o intuito de obter uma configuração adequada para prever a concentração de cinzas vulcânicas após eventos eruptivos. Avaliando os resultados do modelo com dados observados, principalmente com relação ao satélite CALIPSO, concluiu-se que o modelo BRAMS foi capaz de simular e prever com relativa precisão a posição e concentração das cinzas vulcânicas na atmosfera. This work has two main goals, the first is provide a description of how the atmospheric BRAMS model was structured in order to enable it to simulate the emission, dispersion and sedimentation of volcanic ash; the second is do a sensitivity analysis, with respect to several configurations of the model, in order to obtain an optimized configuration for predict the volcanic ash concentration after eruptive events. Comparing model results with observed data, mostly related with CALIPSO satellite, we concluded that the BRAMS model was able to simulate and forecast with relative accuracy the location, sedimentation and concentration of volcanic ash in the atmosphere. Instituto Nacional de Pesquisas Espaciais, Centro de Previsão do Tempo e Estudos Climáticos National Aeronautics and Space Administration, Goddard Space Flight Center Universidade Federal de São Paulo, São José dos Campos Universidade Estadual Paulista “Júlio de Mesquita Filho” Universidade Estadual Paulista “Júlio de Mesquita Filho” CNPq: 3006340/2011-9

Fires associated with land use and land cover changes release large amounts of aerosols and trace gases into the atmosphere. Although several inventories of biomass burning emissions cover Brazil, there are still considerable uncertainties and differences among them. While most fire emission inventories utilize the parameters of burned area, vegetation fuel load, emission factors, and other parameters to estimate the biomass burned and its associated emissions, several more recent inventories apply an alternative method based on fire radiative power (FRP) observations to estimate the amount of biomass burned and the corresponding emissions of trace gases and aerosols. The Brazilian Biomass Burning Emission Model (3BEM) and the Fire Inventory from NCAR (FINN) are examples of the first, while the Brazilian Biomass Burning Emission Model with FRP assimilation (3BEM_FRP) and the Global Fire Assimilation System (GFAS) are examples of the latter. These four biomass burning emission inventories were used during the South American Biomass Burning Analysis (SAMBBA) field campaign. This paper analyzes and inter-compared them, focusing on eight regions in Brazil and the time period of 1 September–31 October 2012. Aerosol optical thickness (AOT550 nm) derived from measurements made by the Moderate Resolution Imaging Spectroradiometer (MODIS) operating on board the Terra and Aqua satellites is also applied to assess the inventories' consistency. The daily area-averaged pyrogenic carbon monoxide (CO) emission estimates exhibit significant linear correlations (r, p > 0.05 level, Student t test) between 3BEM and FINN and between 3BEM_ FRP and GFAS, with values of 0.86 and 0.85, respectively. These results indicate that emission estimates in this region derived via similar methods tend to agree with one other. However, they differ more from the estimates derived via the alternative approach. The evaluation of MODIS AOT550 nm indicates that model simulation driven by 3BEM and FINN typically underestimate the smoke particle loading in the eastern region of Amazon forest, while 3BEM_FRP estimations to the area tend to overestimate fire emissions. The daily regional CO emission fluxes from 3BEM and FINN have linear correlation coefficients of 0.75–0.92, with typically 20–30 % higher emission fluxes in FINN. The daily regional CO emission fluxes from 3BEM_FRP and GFAS show linear correlation coefficients between 0.82 and 0.90, with a particularly strong correlation near the arc of deforestation in the Amazon rainforest. In this region, GFAS has a tendency to present higher CO emissions than 3BEM_FRP, while 3BEM_FRP yields more emissions in the area of soybean expansion east of the Amazon forest. Atmospheric aerosol optical thickness is simulated by using the emission inventories with two operational atmospheric chemistry transport models: the IFS from Monitoring Atmospheric Composition and Climate (MACC) and the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modelling System (CCATT-BRAMS). Evaluation against MODIS observations shows a good representation of the general patterns of the AOT550 nm time series. However, the aerosol emissions from fires with particularly high biomass consumption still lead to an underestimation of the atmospheric aerosol load in both models.

The authors implemented the Grell–Freitas (GF) parameterization of convection in which the cloud-base mass flux varies quadratically as a function of the convective updraft fraction in the global nonhydrostatic Model for Prediction Across Scales (MPAS). They evaluated the performance of GF using quasi-uniform meshes and a variable-resolution mesh centered over South America, the resolution of which varied between hydrostatic (50 km) and nonhydrostatic (3 km) scales. Four-day forecasts using a 50-km and a 15-km quasi-uniform mesh, initialized with GFS data for 0000 UTC 10 January 2014, reveal that MPAS overestimates precipitation in the tropics relative to the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis data. Results of 4-day forecasts using the variable-resolution mesh reveal that over the refined region of the mesh, GF performs as a precipitating shallow convective scheme, whereas over the coarse region of the mesh, GF acts as a conventional deep convective scheme. As horizontal resolution increases and subgrid-scale motions become increasingly resolved, the contribution of convective and grid-scale precipitation to the total precipitation decreases and increases, respectively. Probability density distributions of precipitation highlight a smooth transition in the partitioning between convective and grid-scale precipitation, including at gray-zone scales across the transition region between the coarsest and finest regions of the global mesh. Variable-resolution meshes spanning between hydrostatic and nonhydrostatic scales are shown to be ideal tools to evaluate the horizontal scale dependence of parameterized convective and grid-scale moist processes.

A new module has been developed by the limited area model BRAMS to parameterize a wind farm power plant. BRAMS is developed to be a system for numerical weather prediction, and it is currently employed for operational environmental prediction by the CPTEC/INPE. The new module was able to simulate the impact from a set of wind turbines. The additional drag from turbines changes the turbulent kinetic energy (TKE). Some simulations were carried out considering wind power plant installed on the Brazilian territory.

Convective systems dominate the vertical transport of aerosols and trace gases. The most recent in situ aerosol measurements presented here show that the concentrations of primary aerosols including sea salt and black carbon drop by factors of 10 to 10,000 from the surface to the upper troposphere. In this study we show that the default convective transport scheme in the National Science Foundation/Department of Energy Community Earth System Model results in a high bias of 10–1,000 times the measured aerosol mass for black carbon and sea salt in the middle and upper troposphere. A modified transport scheme, which considers aerosol activation from entrained air above the cloud base and aerosol‐cloud interaction associated with convection, dramatically improves model agreement with in situ measurements suggesting that deep convection can efficiently remove primary aerosols. We suggest that models that fail to consider secondary activation may overestimate black carbon's radiative forcing by a factor of 2., Key Points Deep convection efficiently removes particles at and above the cloud baseThe default convective scheme in climate model overestimates middle and upper tropospheric aerosol (sea salt and black carbon) by a factor of 10–1,000The default convective transport scheme overestimates black carbon's radiative forcing by a factor of 2

Emissions of gases and particulates in urban areas are associated with a mixture of various sources, both natural and anthropogenic. Understanding and quantifying these emissions is necessary in studies of climate change, local air pollution issues and weather modification. Studies have highlighted that the transport sector is key to closing the world’s emissions gap. Vehicles contribute substantially with the emission of carbon dioxide (CO2), carbon monoxide (CO), nitrogen oxides (NOx), non-methane hydrocarbon (NMHC), particulate matter (PM), methane (CH4), hydrofluorocarbon (HFC) and nitrous oxide (N2O). Several studies show that vehicle emission inventories are an important approach to providing a baseline estimate of on-road emissions in several scales, mainly in urban areas. This approach is essential to areas with incomplete or non-existent monitoring networks as well as for air quality models. Conversely, the direct downscale of global emission inventories in chemical transport and air quality models may not be able to reproduce the observed evolution of atmospheric pollution processes at finer spatial scales. To address this caveat, we developed a bottom-up vehicular emission inventory along the 258 main traffic routes from Manaus, based on local vehicle fleet data and emission factors (EFs). The results show that the light vehicles are responsible for the largest fraction of the pollutants, contributing 2.6, 0.87, 0.32, 0.03, 456 and 0.8 ton/h of CO, NOx, CH4, PM, CO2 and NMHC, respectively. Including the emissions of motorcycles, buses and trucks, our total estimation of the emissions is 4.1, 1.0, 0.37, 0.07, 63.5 and 2.56 ton/h, respectively. We also noted that light vehicles accounted for about 62.8 %, 84.7 %, 87.9 %, 45.1 %, 71.8 %, and 33.9 % and motorcycles in the order of 32.3 %, 6.5 %, 12.1 %, 6.2 %, 14.8 %, 8.7 %, respectively. Nevertheless, we can highlight the bus emissions which are around 35.7 % and 45.3 % for NMHC and PM. Our results indicate a better distribution over the domain reflecting the influences of standard behavior of traffic distribution per vehicle category. Finally, this inventory provides more detailed information to improving the current understanding of how vehicle emissions contribute to the ambient pollutant concentrations in Manaus and their impacts on regional climate changes. This work will also contribute to improved air quality numerical simulations, provide more accurate scenarios for policymakers and regulatory agencies to develop strategies for controlling the vehicular emissions, and, consequently, mitigate associated impacts on local and regional scales of the Amazon ecosystems.

The South American Biomass Burning Analysis (SAMBBA) field campaign took detailed in situ flight measurements of aerosol during the 2012 dry season to characterise biomass burning aerosol and improve understanding of its impacts on weather and climate. Developments have been made to the Weather Research and Forecast model with chemistry (WRF-Chem) model to improve the representation of biomass burning aerosol in the region, by coupling a sectional aerosol scheme to the plume-rise parameterisation. Brazilian Biomass Burning Emissions Model (3BEM) fire emissions are used, prepared using PREP-CHEM-SRC, and mapped to CBM-Z and MOSAIC species. Model results have been evaluated against remote sensing products, AERONET sites, and four case studies of flight measurements from the SAMBBA campaign. WRF-Chem predicted layers of elevated aerosol loadings (5–20 μg sm−3) of particulate organic matter at high altitude (6–8 km) over tropical forest regions, while flight measurements showed a sharp decrease above 2–4 km altitude. This difference was attributed to the plume-rise parameterisation overestimating injection height. The 3BEM emissions product was modified using estimates of active fire size and burned area for the 2012 fire season, which reduced the fire size. The enhancement factor for fire emissions was increased from 1.3 to 5 to retain reasonable aerosol optical depths (AODs). The smaller fire size lowered the injection height of the emissions, but WRF-Chem still showed elevated aerosol loadings between 4–5 km altitude. Over eastern cerrado (savannah-like) regions, both modelled and measured aerosol loadings decreased above approximately 4 km altitude. Compared with MODIS satellite data and AERONET sites, WRF-Chem represented AOD magnitude well (between 0.3–1.5) over western tropical forest fire regions in the first half of the campaign, but tended to over-predict them in the second half, when precipitation was more significant. Over eastern cerrado regions, WRF-Chem tended to under-predict AODs. Modelled aerosol loadings in the east were higher in the modified emission scenario. The primary organic matter to black carbon ratio was typically between 8–10 in WRF-Chem. This was lower than the western flight measurements (interquartile range of 11.6–15.7 in B734, 14.7–24.0 in B739), but similar to the eastern flight B742 (8.1–10.4). However, single scattering albedo was close to measured over the western flights (0.87–0.89 in model; 0.86–0.91 in flight B734, and 0.81–0.95 in flight B739 measurements) but too high over the eastern flight B742 (0.86–0.87 in model, 0.79–0.82 in measurements). This suggests that improvements are needed to both modelled aerosol composition and optical properties calculations in WRF-Chem.

In this paper we consider an optimization problem applying the metaheuristic Firefly algorithm (FY) to weight an ensemble of rainfall forecasts from daily precipitation simulations with the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) over South America during January 2006. The method is addressed as a parameter estimation problem to weight the ensemble of precipitation forecasts carried out using different options of the convective parameterization scheme. Ensemble simulations were performed using different choices of closures, representing different formulations of dynamic control (the modulation of convection by the environment) in a deep convection scheme. The optimization problem is solved as an inverse problem of parameter estimation. The application and validation of the methodology is carried out using daily precipitation fields, defined over South America and obtained by merging remote sensing estimations with rain gauge observations. The quadratic difference between the model and observed data was used as the objective function to determine the best combination of the ensemble members to reproduce the observations. To reduce the model rainfall biases, the set of weights determined by the algorithm is used to weight members of an ensemble of model simulations in order to compute a new precipitation field that represents the observed precipitation as closely as possible. The validation of the methodology is carried out using classical statistical scores. The algorithm has produced the best combination of the weights, resulting in a new precipitation field closest to the observations.

The Regional Carbon Balance in Amazonia (BARCA) campaign provided the first Amazon Basin-wide aircraft measurements of ozone (O3) during both the dry-to-wet (November and December 2008) and wet-to-dry (May 2009) transition seasons. Extremely low background values (< 20 ppb) were observed to the west and north of Manaus in both seasons and in all regions during the wet-to-dry transition. On the other hand, elevated O3 levels (40–60 ppb) were seen during the dry-to-wet transition to the east and south of Manaus, where biomass burning emissions of O3 precursors were present. Chemistry simulations with the CCATT-BRAMS and WRF-Chem models are within the error bars of the observed O3 profiles in the boundary layer (0–3 km a.s.l.) in polluted conditions. However, the models overestimate O3 in the boundary layer in clean conditions, despite lacking the predominant NO source from soil. In addition, O3 simulated by the models was either within the error bars or lower than BARCA observations in mid-levels (3–5 km a.s.l.), and lower than total tropospheric O3 retrieved from the OMI/MLS instruments, which is primarily comprised of middle troposphere O3 and thus reflects long-range transport processes. Therefore, the models do a relatively poor job of representing the free troposphere-boundary layer gradient in O3 compared with aircraft and satellite observations, which could be due to missing long-range and convective transport of O3 at mid-levels. Additional simulations with WRF-Chem showed that the model O3 production is very sensitive to both the O3 deposition velocities and the NOx emissions, which were both about one-half of observed values. These results indicate the necessity of more realistic model representations of emissions, deposition, and convective processes for accurate monitoring and prediction of increases in O3 production in the Amazon Basin as the regional population grows.

We present a characterization of the chemical composition of the atmosphere of the Brazilian Amazon rainforest based on trace gases measurements carried out during the South American Biomass Burning Analysis (SAMBBA) airborne experiment in September 2012. We analyzed the observations of primary biomass burning emission tracers, i.e., carbon monoxide (CO) and nitrogen oxides (NOx), ozone (O3), isoprene, and its main oxidation products, methyl vinyl ketone (MVK), methacrolein (MACR), and hydroxyhydroperoxides (ISOPOOH). The focus of SAMBBA was primarily on biomass burning emissions, but there were also several flights in areas of the Amazon forest not directly affected by biomass burning, revealing a background with a signature of biomass burning in the chemical composition due to long-range transport of biomass burning tracers from both Africa and the eastern part of Amazonia. We used the [MVK + MACR + ISOPOOH] / [Isoprene] ratio and the hydroxyl radical (OH) indirect calculation to assess the oxidative capacity of the Amazon forest atmosphere. We compared the background regions (CO

We implemented and began to evaluate an alternative convection parameterization for the NASA Goddard Earth Observing System (GEOS) general circulation model (GCM). The proposed parameterization follows the mass flux approach with several closures, for equilibrium and nonequilibrium convection, and includes scale and aerosol aware functionalities. Recently, we extended the scheme to a trimodal spectral size distribution of allowed convective plumes to simulate the transition among shallow, congestus, and deep convection regimes. In addition, the inclusion of a new closure for nonequilibrium convection resulted in a substantial gain of realism in the model representation of the diurnal cycle of convection over the land. We demonstrated the scale‐dependence functionality with a cascade of global‐scale simulations from a nominal horizontal resolution of 50 km down to 6 km. The ability to realistically simulate the diurnal cycle of precipitation over various regions of the earth was verified against several remote sensing‐derived intradiurnal precipitation estimates. We extended the model performance evaluation for weather‐scale applications by bringing together some available operational short‐range weather forecast models and global atmospheric reanalyses. Our results demonstrate that the GEOS GCM with the alternative convective parameterization has good properties and competitive skill in comparison with state‐of‐the‐art observations and numerical simulations., Key Points A scale and aerosol aware convection parameterization in the NASA GEOS GCMThe trimodal approach and the diurnal cycle in the GF convection parameterizationMultimodels and remote sensing data applied for assessment of the NASA GEOS GCM with the GF scheme

The state of Sao Paulo is the largest sugarcane producer in Brazil, with a cultivated area of about 5.4 Mha in 2011. Approximately 2 Mha were harvested annually from 2006 to 2011 with the pre-harvest straw burning practice, which emits trace gases and particulate material to the atmosphere. The development of emission inventories for sugarcane straw burning is crucial in order to assess its environmental impacts. This study aimed to estimate annual emissions associated with the pre-harvest sugarcane burning practice in the state of Sao Paulo based on remote sensing maps and emission and combustion factors for sugarcane straw burning. Average estimated emissions (Gg/year) were 1130 ± 152 for CO, 26 ± 4 for NOx, 16 ± 2 for CH4, 45 ± 6 for PM2.5, 120 ± 16 for PM10 and 154 ± 21 for NMHC (non-methane hydrocarbons). An intercomparison among annual emissions from this study and annual emissions from four other different approaches indicated that the estimates obtained by satellite fire detection or low spatial resolution approaches tend to underestimate sugarcane burned area, due to unique characteristics of this type of biomass fire. Overall, our results also indicated that government actions to reduce sugarcane straw burning emissions are becoming effective.

CHUVA, meaning “rain” in Portuguese, is the acronym for the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (GPM). The CHUVA project has conducted five field campaigns; the sixth and last campaign will be held in Manaus in 2014. The primary scientific objective of CHUVA is to contribute to the understanding of cloud processes, which represent one of the least understood components of the weather and climate system. The five CHUVA campaigns were designed to investigate specific tropical weather regimes. The first two experiments, in Alcantara and Fortaleza in northeastern Brazil, focused on warm clouds. The third campaign, which was conducted in Belém, was dedicated to tropical squall lines that often form along the sea-breeze front. The fourth campaign was in the Vale do Paraiba of southeastern Brazil, which is a region with intense lightning activity. In addition to contributing to the understanding of cloud process evolution from storms to thunderstorms, this fourth campaign also provided a high-fidelity total lightning proxy dataset for the NOAA Geostationary Operational Environmental Satellite (GOES)-R program. The fifth campaign was carried out in Santa Maria, in southern Brazil, a region of intense hailstorms associated with frequent mesoscale convective complexes. This campaign employed a multimodel high-resolution ensemble experiment. The data collected from contrasting precipitation regimes in tropical continental regions allow the various cloud processes in diverse environments to be compared. Some examples of these previous experiments are presented to illustrate the variability of convection across the tropics.

A convective parameterization is described and evaluated that may be used in high resolution non-hydrostatic mesoscale models as well as in modeling system with unstructured varying grid resolutions and for convection aware simulations. This scheme is based on a stochastic approach originally implemented by Grell and Devenyi (2002). Two approaches are tested on resolutions ranging from 20 km to 5 km. One approach is based on spreading subsidence to neighboring grid points, the other one on a recently introduced method by Arakawa et al. (2011). Results from model intercomparisons, as well as verification with observations indicate that both the spreading of the subsidence and Arakawa's approach work well for the highest resolution runs. Because of its simplicity and its capability for an automatic smooth transition as the resolution is increased, Arakawa's approach may be preferred. Additionally, interactions with aerosols have been implemented through a cloud condensation nuclei (CCN) dependent autoconversion of cloud water to rain as well as an aerosol dependent evaporation of cloud drops. Initial tests with this newly implemented aerosol approach show plausible results with a decrease in predicted precipitation in some areas, caused by the changed autoconversion mechanism. This change also causes a significant increase of cloud water and ice detrainment near the cloud tops. Some areas also experience an increase of precipitation, most likely caused by strengthened downdrafts.

This article presents the coupling of the JULES surface model to the CCATT-BRAMS atmospheric chemistry model. This new numerical system is denominated JULES-CCATT-BRAMS. We demonstrate the performance of this new model system in relation to several meteorological variables and the CO2 mixing ratio over a large part of South America, focusing on the Amazon basin. The evaluation was conducted for two time periods, the wet (March) and dry (September) seasons of 2010. The model errors were calculated in relation to meteorological observations at conventional stations in airports and automatic stations. In addition, CO2 mixing ratios in the first model level were compared with meteorological tower measurements and vertical CO2 profiles were compared with observations obtained with airborne instruments. The results of this study show that the JULES-CCATT-BRAMS modeling system provided a significant gain in performance for the considered atmospheric fields relative to those simulated by the LEAF (version 3) surface model originally employed by CCATT-BRAMS. In addition, the new system significantly increases the ability to simulate processes involving air–surface interactions, due to the ability of JULES to simulate photosynthesis, respiration and dynamic vegetation, among other processes. We also discuss a wide range of numerical studies involving coupled atmospheric, land surface and chemistry processes that could be done with the system introduced here. Thus, this work presents to the scientific community a free modeling tool, with good performance in comparison with observational data and reanalysis model data, at least for the region and time period discussed here. Therefore, in principle, this model is able to produce atmospheric hindcast/forecast simulations at different spatial resolutions for any time period and any region of the globe.

Satellite remote sensing data presents an important tool to map and analyze airborne volcanic ash, both spatially and temporally. However, such data only represents an instant in time. To supplement the satellite data and to forecast plume and cloud movement, volcanic ash transport and dispersion models are used. Mount Redoubt Volcano erupted in March and April 2009 with 19 detected events. By analyzing events 5 and 19, we show how satellite data can be used in combination with PUFF and the Weather Research and Forecast model with online Chemistry (WRF-Chem). WRF-Chem has been combined and initialized with a volcanic eruption model. PUFF as well as WRF-Chem show a good assessment of the plume characteristics compared to the satellite data. Especially for event 19, we observed a very close match between WRF-CHEM and satellite data, where PUFF showed an offset of the predicted plume.