This study aims to improve the efficiency of Brazilian air traffic by analyzing the Brazilian Airspace Control System (SISCEAB) performance indicators. The methodology used combined alternative data sources, namely BIMTRA, TATIC FLOW, and VRA, which were employed to examine the impact of different variations in taxiing times. Specifically, Additional Taxi-Out Time (KPI 02) and Additional Taxi-In Time (KPI 13) were analyzed to identify discrepancies among these data sources and determine the most precise combination. The results indicate that airport layout, gate distribution, and runway threshold selection significantly impacted taxiing times. Statistical analysis revealed substantial variations in unimpeded taxi times across different gates and runway thresholds, emphasizing optimizing operational flows. Based on these findings, integrating BIMTRA and VRA is recommended for more accurate KPI measurement. Therefore, this study contributes to implementing operational enhancements, optimizing airport operation flow, and leading to a more efficient management of Brazilian air traffic.
O uso de plataformas aéreas não tripuladas tem sido cada vez mais demandado em diversas aplicações. Dentre elas, destaca-se a inspeção em voo, atividade realizada tradicionalmente por aeronaves equipadas com diversos sensores que objetivam aferir requisitos de desempenho de auxílios à navegação instalados no solo, assim como procedimentos de navegação aérea para fins de homologação. A atividade de inspeção em voo é custosa em termos de tempo, pessoal qualificado, equipamentos necessários, horas de voo e impacto operacional sobre o aeródromo inspecionado. Neste contexto, o emprego de plataformas aéreas não tripuladas, ou UAS (Unmanned Air Systems), se apresenta inicialmente como uma alternativa economicamente viável com o potencial de reduzir significativamente os custos com a operação de inspeção em voo de auxílios à navegação. Neste trabalho, é apresentada a metodologia e os resultados oriundos de uma campanha de testes para a inspeção em voo do auxílio visual PAPI (Precision Path Approach Indicator) com o uso de UAS. Os resultados de mais de uma dezena de campanhas em campo, com procedimentos de inspeção adaptados para substituir a aeronave pelo UAS foram comparados com resultados de inspeções reais feitos de maneira convencional por aeronaves do Grupo Especial de Inspeção em Voo (GEIV). Os reultados indicam um forte nível de similaridade entre a metodologia com o emprego de UAS e a inspeção convencional sugerindo elevado potencial de que o uso de UAS possa substituir em parte ou totalmente a inspeção realizada de maneira convencional, reduzindo significativamente o tempo, os custos e o impacto de uma inspeção realizada por aeronave.
As electric vertical take-off and landing (eVTOL) technology advances, planning for data-driven and safe urban airspaces becomes increasingly essential. This study employs artificial intelligence clustering techniques to analyze aircraft trajectories in São Paulo’s urban airspace – one of the world’s busiest – to characterize the current airspace usage against official regulations and provide a foundational framework for future eVTOL trajectory studies. Using radar data from helicopter flights, this research applies unsupervised learning algorithms, specifically DBSCAN and hierarchical agglomerative clustering, to group and analyze trajectories. Data preprocessing steps, including filtering and dimensionality reduction through Principal Component Analysis, prepared the dataset for meaningful clustering. Results indicate that the models effectively identified daily and hourly flight patterns, offering insights into air traffic behavior relative to regulated air corridors. A comparison of cluster centroids with established visual corridors for helicopters in TMA-SP 2 highlights the potential of these methods to support safe and efficient airspace management and monitor compliance with designated routes. Future work will focus on refining models, expanding data sources, and performing analyses of airspace use with a focus on emerging urban air mobility vehicles.
The complexity and criticality of airspace control, combined with the increasing demand for flights, underscore the need for advanced tools to enhance the optimization and safety of operations. Given the numerous variables that influence air traffic and the difficulty of analytically assessing the impact of each, Artificial Intelligence (AI) techniques provide a viable strategy for more accurately weighting each factor. Considering that runway configuration change is one of the most influential variables in air traffic management, this work presents the development of a system to predict runway configuration at Congonhas Airport (SBSP) using Gradient Boosting techniques, specifically LightGBM. The developed LightGBM-based classification model utilizes data from the Meteorological Aerodrome Report (METAR), Terminal Aerodrome Forecast (TAF), and Weather Research and Forecasting (WRF) to predict potential runway reconfigurations, determining which side of the runway will be in use. Predictions are made for 12 future time points, spaced 15 minutes apart, providing forecasts from the next 15 minutes up to 3 hours ahead. The model achieved a 98.6% accuracy on the test set and, when tested on an unseen data period outside the training and test set, maintained a high accuracy of 92.0% with an F1-Score of 91.8%. These results highlight the effectiveness of the developed model, outperforming traditional rule-based methods currently in use at ICEA (Institute of Airspace Control), which achieve approximately 79% accuracy. The objective is to provide a more precise quantification of meteorological variables’ influence on airport operations, contributing to more efficient and safer airport activity planning.
The rapid growth in global air travel demand has significantly increased air traffic, leading to heightened delays and environmental concerns. This surge underscores the critical need for optimized sequencing techniques in air traffic management to maintain operational efficiency. Operational Research provides powerful methods to tackle these complex issues by offering structured approaches for optimization. In this study, we develop a Mixed-Integer Programming model to address the Aircraft Landing Problem, incorporating operational constraints specific to Guarulhos International Airport. Our model aims to enhance the efficiency of aircraft landing sequences by minimizing cumulative deviations from unimpeded times, thereby reducing fuel consumption and improving overall airport performance. To assess the model’s viability and efficacy, we employed a data-driven approach, collecting real operational data from Guarulhos International Airport during select days in 2023. This approach enabled us to evaluate the model under various traffic scenarios, including those involving threshold changes. The results indicate that our model’s implementation consistently achieved viable solutions with practical execution times and outperformed both actual operational data and the First-Come, First-Served (FCFS) baseline regarding deviations from unimpeded times. Under clear visibility and moderate traffic conditions, the model showed an average improvement of 93.33% over real data and 29.91% over the FCFS baseline. In peak traffic scenarios, it demonstrated a maximum improvement of 60.15% compared to FCFS when optimization began at 100 nautical miles (NM) from the airport, with an average improvement of 45.37% across the analyzed days. When optimization began at 40 NM from the airport, the model achieved an average improvement of 31.64% over FCFS. Similar gains were observed in scenarios involving threshold changes. These findings demonstrate the model’s potential as a robust tool for optimizing landing sequences, contributing to reduced deviations from unimpeded times and enhanced airport efficiency.
A operação dos aeroportos está diretamente relacionada às condições meteorológicas, especialmente à direção e intensidade dos ventos. Fatores como mudança na direção e intensidade do vento, podem gerar riscos para as operações de pousos, que desencadeiam eventos de reconfiguração de pista (ou troca de cabeceira). Essa reconfiguração pode resultar em atrasos, acúmulo de voos em fase de aproximação e, por consequência, o aumento no consumo de combustível, ampliando as emissões de CO2, uma vez que manobras nessa fase são menos eficientes. Esse acúmulo de voos esperando autorização para pouso é denominado Efeito de Fila. Neste cenário, até que o voo receba autorização para pouso, diversas medidas ATFM podem ser aplicadas, como a Espera em voo. O trabalho propõe avaliar a influência da reconfiguração de pista na ocorrência de esperas em voo. Inicialmente, foi verificada a relação entre a ocorrência de espera e a reconfiguração de pista, por meio do teste Qui-quadrado com p<0,001. Além disso, o teste de Wilcoxon indicou que o evento de reconfiguração de pista ocasiona uma diferença na mediana de esperas quando comparados os períodos de 3 horas antes e 3 horas depois da reconfiguração de pista, com p < 0,001. Os resultados indicaram que a reconfiguração de pista exerce influência na ocorrência de espera em voo no aeroporto internacional de Guarulhos.
Aprimorar a eficiência do espaço aéreo é uma prioridade contínua na gestão do tráfego aéreo. Um indicador fundamental de desempenho nesse contexto é o tempo adicional gasto nas áreas terminais. Ao monitorarmos esse indicador de forma adequada, podemos tomar decisões que trarão benefícios tanto econômicos quanto ambientais. Um requisito para calcular esse indicador é identificar os setores de entrada na área terminal. Com base no cenário apresentado, o objetivo do estudo foi implementar um modelo para identificação automática de setores de entrada nas regiões a 40 NM (Milhas Náuticas) e 100 NM de distância de cada um dos quatro aeroporto mais movimentados do Brasil. Para isso, foram testados os métodos de aprendizado não supervisionado K-Means e DBSCAN, para a tarefa de clusterizar movimentos e, portanto, identificar regiões com maior densidade de entrada de voos em área terminal. A avaliação foi conduzida de forma qualitativa, levando em consideração a densidade de voos nas áreas terminais em comparação com os procedimentos de aproximação disponíveis nas cartas aeronáuticas dos aeroportos. Além disso, uma análise de ruído foi realizada, indicando a presença de ruídos entre 0,06% e 6,59% em cada setor, considerados como outliers ou movimentos atípicos. Esses resultados apontaram que os clusters foram bem identificados, mantendo um conjunto significativo de dados. As principais vantagens apresentadas neste artigo foram: a utilização de um modelo para identificação automática dos setores de entrada em área terminal, que, com um único conjunto de parâmetros, demonstrou robustez nos experimentos para os diferentes aeroportos, indicando a escalabilidade computacional da solução proposta; e a possibilidade de calcular o indicador de tempo adicional em área terminal de forma mais assertiva.
The increasing global air traffic requires efficient management systems. One way to achieve that is optimizing arrival sequences, reducing flight duration, and enhancing operational safety. A method to address these requirements is a sequencing technique called Point Merge system (PM). This study analyzes the adherence to the PM at Guarulhos International Airport (GRU), aiming to understand the peak and off-peak usage times, and provide a detailed sector-by-sector analysis. Two methods were applied for trajectories classification according to their adherence to the PM: A method based on the 8th ICAO’s Key Performance Indicator (KPI08-based method), which consists of thresholding based on additional time in terminal area, and clustering by the agglomerative method using trajectories data. The experimental data were collected from: KPI08 dataset, airport movements and radar synthesis, focusing on medium-sized commercial aircraft. The total number of flights analyzed was 2427. The results obtained indicate a better performance of the KPI08-based method, which achieved a more defined representation between the classified trajectory groups. The results highlighted a behavior pattern in relation to peak and off-peak times in the use of PM in all periods analyzed. Evaluating the North and West sectors, it was possible to show that some time slots exhibited similar behaviors when using the KPI08-based method. The time slots 8h-9h and 18h-19h stand out as they show that more than 70% of flights execute the PM. The time slot 20h-22h showed similar behavior in both sectors, with approximately 50% of flights executing the PM. This work contributes by proposing the KPI08-based method, an innovative method to classify flights according to the adherence to the PM, which proved to be more accurate than the agglomerative trajectory clustering method. Additionally, this study may indicate an improvement in the arrival flow management at GRU, due to demand predictability. This predictability enables better route planning, which may result in additional fuel reduction.
The complexity and criticality of airspace control, coupled with the increasing demand for flights, highlight the need for advanced tools to optimize and secure operations. Additionally, many variables influence the air traffic scenario and, given the difficulty of analytically assessing the impact of each variable, a possible strategy is to use Machine Learning techniques to more accurately assign the weight of each factor, by processing historical data. In this context, considering that one of the variables that most influences air traffic is runway reconfiguration, this paper presents the development of a system to predict which runway will be in use at Congonhas Airport (SBSP) using a Gradient Boosting technique, called LightGBM. A classification model based on LightGBM was developed using data from the Meteorological Aerodrome Report (METAR), Terminal Aerodrome Forecast (TAF), and Weather Research and Forecasting (WRF). The model makes predictions about possible runway reconfigurations, deciding which side of the runway will be used in the coming hours. With this data, an accuracy of 98% in predictions was achieved and when testing the model on a period outside the training and test dataset, an accuracy of 88% was obtained. These results highlight the efficiency of the developed model compared to the currently used rule-based methods, which achieved approximately 81%, according to related works. This work contributes by providing a better quantification of the influence of meteorological variables on airspace operations, according to a feature importance analysis, which can support a more efficient and safer airspace activity planning.
Improving the efficiency of commercial aviation is an important economic and environmental factor. Jet fuel costs account for at least 30% of airlines’ operating costs, which are consequently passed on to passengers after all. By analyzing flight trajectories for events, nonconformities, and anomalies, it is possible to gain a better understanding of how these factors contribute to increases in the cost of air operations and associate carbon dioxide emissions. Studies should also be undertaken in order to understand the correlation between these nonconformities and other situational factors, such as adverse weather conditions, restrictive traffic management measures, or events of capacity degradation, should also be undertaken. This paper presents a rule-based algorithm and the validation process to detect the in-flight holding pattern in 4D trajectory data. In addition to the method, a near-real-time holding pattern monitor has been evaluated and applied by the Brazilian Air Navigation Management Center (CGNA), which enhances situational awareness in air traffic flow management and creates a historical database of the Brazilian Airspace Control System (SISCEAB). With this database, future work is being proposed to increase the predictability of aircraft arrival times, the correlation with the weather forecast, and the prediction of occurrences of holdings for flight plans.
Este relatório pretende apresentar o resultado da prova de conceito de aplicação de Aeronaves Não Tripuladas (UAS) na inspeção do Indicador de Precisão de Rampa de Aproximação (Precision Approach Path Indicator - PAPI) com a finalidade de apoiar as atividades de inspeção em voo do Grupo Especial de Inspeção Voo (GEIV).
Recent studies show that data assimilation improves the efficiency of weather forecast models, however, it is not properly quantified the impacts of radar data assimilation related to the physical model parameterizations, especially the microphysics. The goal of this study was to study the impact of the use of radar data with different microphysics parameterizations of the Weather Research and Forecasting (WRF) model with its data assimilation system (WRFDA3DVAR) for cases of intense precipitation. The study area covers the South-western Brazil and Southeastern Paraguay. The simulations were done for three cases in 2014. The comparison is performed through the statistical metrics Fractional Skill Score (FSS) and Local Root Mean Square Error (LRMSE). Different microphysics parameterizations were tested when assimilating conventional and radar data for three events. Thus, we evaluated nine microphysical parameterizations in order to determine which one provides the most realistic short-term forecasts of meteorological fields over the radar coverage, as well as the relative impact of different microphysical parameterization and the assimilation of conventional and radar data. The positive impact of the radar data assimilation was in the average up to 20% in the FSS, while the positive impact among the microphysics options reached 70% in the FSS.
Severe weather events can affect airport activities and air traffic management, as well as other socioeconomic activities. In this work, for 3 severe weather cases that occurred in the International Airport of São Paulo – Guarulhos between 2016 and 2017, the performance of high resolution simulations with the Weather Research and Forecasting Model (WRF) using multiphysics ensemble was evaluated. In the 3 cases, there was a common synoptic condition: the presence of a frontal system over the region. The number of members in the ensemble was 9. The simulations were performed in two nested domains with 9 km and 3 km horizontal spacing approximately centered at the airport. Initial and boundary conditions were provided by Global Forecast System (GFS) forecasts. The forecast range was 24 h. The analysis of results focused on two variables: precipitation and wind at 10 m. To compare simulations with observations, for precipitation, statistics computed from information contained in a 100 km x 100 km box centered at the airport were used; for wind, values at the grid point closest to the airport were used. The time series for observations were compared with that for simulations by using ensemble metrics (median, dispersion and outlier) represented in boxplot. The results showed that the time of occurrence and the duration of heavy precipitation can be predicted in both domains by outliers. For the maximum precipitation intensity, the value and the time of occurrence can be predicted by outliers in the 9 km domain and the median in the 3 km domain. The time of occurrence and duration of wind gusts can be predicted by the dispersion in both domains. All these results, being valid for all 3 cases, can be regarded as robust. The methodology used in the work, due to its simplicity, can be adapted and implemented in operational centers, such as the Centro Integrado de Meteorologia Aeronáutica (CIMAER), to assist the weather forecasting activities for the International Airport of São Paulo.
BRASIL. Ministério da Defesa. Departamento de Controle do Espaço Aéreo. DECEA promove 3º workshop CYBER e SWIM. Publicado em 31 maio 2019. Fonte: Assessoria de Comunicação Social do DECEA. Reportagem: Denise Fontes. Fotos: Fábio Maciel.
BRASIL. Ministério da Defesa. Força Aérea Brasileira. FAB testa uso de aeronaves remotamente pilotadas para inspeção em voo: Organizações Militares da FAB realizaram ensaios em São José dos Campos (SP). Publicado em 08 maio 2019. Fonte: ICEA. Edição: Agência Força Aérea, por Tenente Gabrielli. Revisão Capitão Monteiro.
IRIART, Paulo et al. Avaliação do modelo Weather Research and Forecasting para as variáveis temperatura do ar e velocidade do vento durante o ano de 2014 no Aeroporto de Recife. In: WORKSHOP BRASILEIRO DE MICROMETEOROLOGIA, 2019, São José dos Campos. Pôster apresentado... São José dos Campos: MICROMETEOROLOGIA, 2019. 1 pôster.
DIAS, Marcos Vinicius da Silva. Análise sinótica de um evento extremo ocorrido na cidade do Rio de Janeiro. Artigo técnico MET001. São José dos Campos: Instituto de Controle do Espaço Aéreo (ICEA), 2018.
The study was developed with the objective of making a synoptic analysis for an event extreme event occurred in the area of the Terminal of Rio de Janeiro between February 14 and 15, 2018. In some surface stations 148 mm of rain were registered in 24 hours and surface winds of approximately 100 km / h. The storm's highest severity moment showed a cloud top temperature of -70° C and indicated a reflectivity of the weather radar near 50 dBZ. Top air analysis was carried out to the top (top down) and it was verified that the severe storm was caused by the presence of a surface dug that expanded to the level of 850hpa, near the coast of Rio de Janeiro, associated to a cold front on the surface. A confluence of winds at the 500hpa level contributed to the instability in the middle atmosphere. Finally, the level of 250hpa showed a dug and a subtropical jet giving support to the cold front, in addition to the diffluence of high level winds in southeastern Brazil. This all favored instability in the atmosphere. Rising currents, high relative humidity, confluence of winds and other factors gave rise to cumulonimbus clouds that remained active for a period of more than 6 hours. The radiosonding, on the day of the storm, confirmed through the instability indexes the synoptic characteristics presented above. The results of these forcants and ingredients were the closures of the main airports of the city, besides.
SOUZA, Filipe Menegardo de. Avaliação dos resultados do Ábaco de Harrison no diagnóstico de turbulência no cruzamento da Cordilheira dos Andes. Artigo técnico MET001. São José dos Campos: Instituto de Controle do Espaço Aéreo (ICEA), 2018.
This study was developed with the objective of evaluating the results of Harrison´s Abacus in the identification of the Andes Mountains turbulence between 2016 and 2017. The data on the occurrences of the phenomena were obtained by means of the SIGMET code issued to the SAMF FIR, calculating the total duration and descriptive statistics, with hourly and monthly frequencies. Using the observational data from the METAR code of the airports of Santiago e Mendonza and the wind of the FL180 of the Santo Domingo radiosondes, an hourly analysis of the cases identified in the Harrison´s Abacus was performed. The results pointed out that the method is important tool and can assit the Meteorologist in his evaluation of the weather conditions and weather forecast.
System Wide Information Management (SWIM) including SWIM Registry for Air Traffic Management (ATM) has been successfully developed and applied in Europe and United States. The most of developing countries have just started to study the employment of SWIM conceipt, which its establishment is required prior to the development of SWIM Registry. In this paper, we introduce the experience of the development of SWIM Registry Brazil, which comprises the study of the architecture, components, services and data accessing. In order to encourage consumers and providers to participate in the SWIM community, we developed a prototype of SWIM Registry Demonstration for the Brazilian ATM society. We propose a model based on Blockchain for managing services currently provided by Brazilian ATM in order to certificate operations which are performed by consumers, authorities and involved stakeholders. The proposed model is ecpected to provide services for SWIM Registry with integrity, efficiency, security and authenticity, which are fundamental for the proper operation of Brazilian aviation system.
In aviation, short-term weather forecast is very important for the planning of air navigation. Recent studies show that data assimilation improves the efficiency of weather forecast models, however it is not properly quantified the impacts of radar data assimilation related to the physical model parameterizations, especially the microphysics. The goal of this study is to perform experiments using 9 different parameterization of microphysics using the Weather Research and Forcasting (WRF) model and its data assimilation system (WRFDA-3DVAR) in a grid with 2 km horizontal resolution. The study area covers the South-western Brazil and Southeastern Paraguay. The simulations were done for October 30th, November 7th and December 13th of 2014, due to the intensity of precipitation, as well as the quality and availability of observational data, i.e., surface, radiosonde and radar data. The comparison is performed through the statistical metrics Fractional Skill Score (FSS) and Local Root Mean Square Error (LRMSE). Different microphysics parametrizations were tested when assimilating conventional and radar data for three events, totalling 81 run of the model. Thus, it is expected to determine the best microphysical parameterization that provides the more realistic short-term forecasts of meteorological fields over the radars area, as well as the relative impact of different microphysical parameterization and the assimilation of conventional and radar data. The positive impact of the radar data assimilation was in the average up to 20% in the FSS, while the positive impact among the microphysics options reached 70% in FSS.
The System Wide Information Management (SWIM) consists of standards,
infrastructure and governance enabling the management of air traffic
information and services. The main component in the SWIM is the
registry, a central repository for services and service related
information, which improves interoperability. SESAR (Europe) and
NextGen (USA) embraced SWIM for modernizing their Air Traffic
Management programs. In Brazil, the SWIM ecosystem and the SWIM
registry are at an early stage of development. This work presents a
review of the main concepts of SWIM and introduces an architecture for
a SWIM registry in a Brazilian scenario.
The G3DVAR assimilation system, based in the Gridpoint Statistical Interpolation (GSI), coupled to Atmospheric General Circulation Model (AGCM), is an initiative of CPTEC/INPE (Center for Weather Forecast and Climate Studies) in generate an initial condition that takes into account the model balances and, consequently, be one that also fosters the obtainment of the best forecasts with emphasis on the South America. To obtain the analysis, G3DVAR looks for a great condition that takes into account the observations and short-term forecasts of the model, beyond their errors. The analysis of the humidity fields presents in some cases negative values and humidity values above the saturation value. These solutions are purely numerical and mostly generated in the process of data assimilation and model integration, that is, they don´t correspond at the physical reality and need to be treated during the process of minimizing of the cost function so that they doesn’t be amplified. G3DVAR uses an additional term in the cost function, called moisture constraint. This term has the function of regulate the process of minimizing, taking the solution to humidity values closer to the physical reality. However, this regulation process depends of parameters that control the acting of this additional term. Aiming to identify the values of the moisture constraint parameters used in the process of minimizing of the G3DVAR cost function, that improve the analysis quality and, consequently, the generated forecasts, were realized experiments that varied the value of these parameters, in the month June 2014. The data analysis showed that the grid points with negative humidity values are distributed throughout the atmosphere simulated in the model over the high latitudes of the Southern Hemisphere and tend to spread toward the low latitudes where the value of moisture constraint parameters increases.
Data assimilation combines the information from numerical models and meteorological observations through a physical-statistical process generating the best representation of atmospheric state in a moment of time. The goal of this work is to tune the background error covariance matrix while assimilating Doppler radar data in order to improve the analysis and then the short-term precipitation forecast. The atmospheric model and the assimilation system used are the Weather Research and Forecasting (WRF) and the WRF Data Assimilation (WRFDA) 3D-Var. The domain covers the west of Southern Brazil, including the state of Parana, Santa Catarina and Rio Grande do Sul and part of Paraguay with horizontal resolution of 2-km and 45 levels. The period of study is from October 15 to November 15, 2014, and the evaluation of the precipitation was made by comparing the results from modeling against the Tropical Rainfall Measuring Mission (TRMM) 3B42 data, using statistical index such the Root Mean Square Error (RMSE). The other meteorological fields were also evaluated using the same statistical indice comparing them to the surface observations. Observations of the surface weather stations were used for comparison with the model results with and without radar data assimilation. The selected stations were Curitiba, Bacacheri, Londrina and Foz do Iguaçu. During the assimilation process, the conventional data from Global Telecommunication System was also assimilated. The background error covariance matrix was generated using utility WRFDA applying the NMC method with 03 months of simulations of 24-h starting at 00UTC and 12UTC. The process of generating the matrix B horizontally spreads the information from a specific observation using a recursive filter, and then setting the error covariance matrix background was applied by adjusting the parameters variance scaling related to the intensity at each observation will influence the state variables in the model grid points , and the length scaling, related to the influence of the error in distance scale the values of the grid points of the model state variables, in order to adjust them to the region study, the assimilated data and the weather system studied. Different values of the two parameters were tested and the results based on statistical indicator showed improvements in predicting the location and intensity of precipitation when applied adjustments to the covariance matrix of background error.
BUENO, Humberto de Campos. Estudo das características do vento associado a nevoeiro na Academia da Força Aérea. Artigo técnico MET001. São José dos Campos: Instituto de Controle do Espaço Aéreo (ICEA), 2016.
This study investigated the relationship between the direction of the wind observed with the occurrence of fog in the Air Force Academy Airport - AFA. Was made a statistical analysis of 81 fog events in 2008, 116 in 2009, 35 in 2010, 61 in 2011 and 76 in 2012. It was also analyzed the 2008-2012 period as a single to find what kind of fog is prevalent, and the wind characteristics associated with the occurrence of this phenomenon. We came to the conclusion that predominates in the region, the radiation fog, especially in calm wind. However, it also observed that, according to the data of the last two years, collected the newly installed weather station, there is a significant contribution of weak wind with component of this (E) associated with advection fog formation in the area of AFA , which can serve as future research object.
ROBERTO, Carlos Eduardo Pacheco. Análise da frequência de ocorrência de teto baixo no Aeroporto de Campina Grande, Paraíba, no período de 2006 a 2015. Artigo técnico MET001. São José dos Campos: Instituto de Controle do Espaço Aéreo (ICEA), 2016.
Issued by the weather stations surface, the height of the estimated information of the cloud base and quantity are very important for air operations. Knowledge of cloudiness at aerodromes is indispensable for the realization of a safe flight as well as for operational planning of airlines. Thus, this study aimed to determine the frequency of occurrence of cloudiness less than 45 dekameters (dam) at the airport in Campina Grande, Paraíba. For this, we used data of Surface Weather Station clouds (EMS) of Campina Grande Airport in the period 2006-2015, registered in proper forms, filed in the Bank of Climatological Data (BDC) of the Institute of Airspace Control (ICEA). The analysis of these data, it was observed that the month of July is the most low ceilings occur in the town, and the slot of 00h00min to 03h00min (local time) the period of highest frequency. During the period, also could see that 30-38 dam is the height range of the cloud base that is more in the airport area and the stratocumulus cloud is the predominant cloud in the ceiling instances less than 45 dam. Thus, the purpose of the study is to serve as an additional tool to assist in decision making for the airport Campina Grande when dealing with operational ceiling.
ROSSETE, Alessandra Carrijo. Avaliação do modelo WRF ICEA para um caso de tempestade severa no Aeroporto Internacional do Galeão. Artigo técnico MET001. São José dos Campos: Instituto de Controle do Espaço Aéreo (ICEA), 2015.
A case of severe storm that occurred entire december 11 and december 12 of 2013 in Galeão International Airport (GLIA) was simulated by the model Weather Research and Forecasting (WRF) installed at the Institute of Airspace Control (ICEA) with the objective of to assess the model's ability to represent precipitation associated with the event. The results indicated that the model underestimated the amount of precipitation in a point, but could well simulate the dynamic and thermodynamic aspects of system and represent, with little differences, the spatial distribution of precipitation.
IRIART, Paulo et al. Avaliação da velocidade do vento obtida no modelo Weather Research and Forecasting para Recife para Abril de 2014. In: SIMPÓSIO INTERNACIONAL DE CLIMATOLOGIA, 2015, Natal.
O aumento da capacidade pistas do aeródromos congestionados é uma necessidade que pode ser suprida usando pistas paralelas de forma mais eficiente; Existem diversas limitações quando se trata do incremento de capacidade de pista paralelas, essas dificuldades agravam-se quando a configuração das pistas são próximas devido a interferência da esteira de turbulência nas operações da pista adjacente. Diante disso, o desafio de superar a restrição dos procedimentos de aproximação devido aos vórtices gerados pelas aeronaves motiva o estudo de alternativas para operações de pouso na configuração de pista paralela e próxima de forma mais eficiente. Com base nesse objetivo são analisadas capacidades de pista sob diversos cenários em simulação computational, em que o software TAAM (Total Airspace and Airport Modeller) foi utilizado. Os cenários propostos abrangem operações regulamentadas e outras inovadoras, tais como SGAP (Staggered Approach Procedure) e SEAP (Steeper Approach Procedure), de forma a permitir aproximações simultâneas ou ainda reduções das separações longitudinais entre aeronaves nas aproximações para pouso. Verificou-se que melhorias tecnológicas que permitem reduções de separação no cenário atual poderiam aumentar em 17% a quantidade de movimentos, o procedimento SEAP levaria a um aumento de 22% de operações, além de procedimentos visuais que chegam a incrementar em 39% os movimentos de pouso.
The increasing complexity and demand of airspace use has motivated the International Civil Aviation Organization (ICAO) to upgrade the current Air Traffic Management (ATM). One of these new technologies that will be implemented in the airspace control system is the System Wide Information Management (SWIM). SWIM is aligned with the principles of Service-Oriented Architecture (SOA). The SWIM standard does not implement or suggest a semantic service description. This article is concerned with modeling of consumer applications requirement services capabilities based on semantics to improve service discovery and selection. From the perspective of the consumer, it is possible to make services pre-selection that fit system requirements. Anticipating the services' pre-selection for the consumer system modeling phase, the discovery and selection can be improved. The main goal of this approach is to provide the architecture model with functional and non-functional information about services available that meets the consumer system needs. As viability test, the proposed approach was applied in a case study, a scenario in which a consumer application presents a query report integrating weather services, flight information and airport services. Model experiments show that it is possible to improve the service discovery process with pre-selection services modeled at client application.
Cyber security is often only seen as protecting networks. However, during critical operations there is a desire to detect, assess and respond to cyber threats. Given the unknown vulnerabilities of large, complex Command and Control (C2) systems, organizations will protect the most critical assets essential for mission success. Cyber-ARGUS is a methodology that provides a mapping between the cyber and the operational domains, substantially improving the monitoring of information infrastructure (networks) supporting missions by correlating their status to mission goals. This enables a proactive, context-based response to ensure that cyber attacks will not affect ongoing operations. Cyber-ARGUS relies upon a unique approach of modeling the network and the mission separately. After modeling the mission, the mission?s tasks are mapped into services required for the mission, and these services are allocated to network nodes to form a Mission Network Graph. A vulnerability assessment and an enemy behavior analysis are conducted to determine which vulnerabilities the network is exposed to. This information is then used to adjust the node values in the Mission Network Graph, represented as a Bayesian Network, to calculate the impact assessment for each node. Finally, a simulation is run using both an Entity Level simulation and a Network emulator to determine the C2 impact of a cyber attack on the Mission. We illustrate this methodology with a detailed use case. In Brazil, the Campos Basin is a petroleum rich area that accounts for 80% of Brazil’s oil production. Because the Campos Basin is offshore, there is a high volume of helicopter traffic in the area. A new technology ? ADS-B (Automatic Dependent Surveillance ? Broadcast) will supplement radar coverage in the restricted oceanic airspace supporting the oil platforms. Results from this use case are assessed and extrapolated to determine if this methodology can be used to improve the agility of operations.
Com a necessidade mundial de serviços de navegação aérea mais seguros e eficientes, a ICAO (International Civil Aviation Organization) desenvolveu um plano de modernização dos Sistemas de Controle do Espaço Aéreo, estabelecendo conceitos como Airport-CDM (Airport Collaborative Decision Making), cuja a finalidade é dar maior eficiência e segurança na gestão das operações aeroportuárias, através da unificação dos processos operacionais e automatizados, e o SWIM (System Wide Information Management), que é a infraestrutura definida para dar suporte ao Airport-CDM, que permitirá que dados de diversas fontes prestadoras de serviços de tráfego aéreo possam ser intercambiados de forma segura e transparente. Nesse contexto, o presente artigo apresenta uma proposta de arquitetura de serviços, modelada usando conceitos SOAML (Service Oriented Architecture Modeling Language), para implementar um ambiente Airport-CDM específico para as necessidades do Sistema de Controle do Espaço Aéreo Brasileiro, utilizando como referência o SWIM.
Due to their many advantages over their hardwarebased counterparts, Software Defined Radios are becoming the new paradigm for radio and radar applications. In particular, Automatic Dependent Surveillance-Broadcast (ADS-B) is an emerging software defined radar technology, which has been already deployed in Europe and Australia. Deployment in the US is underway as part of the Next Generation Transportation Systems (NextGen). In spite of its several benefits, this technology has been widely criticized for being designed without security in mind, making it vulnerable to numerous attacks. Most approaches addressing this issue fail to adopt a holistic viewpoint, focusing only on part of the problem. In this paper, we propose a methodology that uses semantic technologies to address the security requirements definition from a systemic perspective. More specifically, knowledge engineering focused on misuse scenarios is applied for building customized resilient software defined radar applications, as well as classifying cyber attack severity according to measurable security metrics. We showcase our ideas using an ADS-B-related scenario developed to evaluate our research.
This work presents an observational study of the Intertropical Convergence Zone (ITCZ) features over the central portion of the Atlantic Ocean. The Atlantic ITCZ position, width and intensity (mean precipitation) variability for 10 years (1999-2008) was obtained objectively from pentad precipitation data. The composite method was used to obtain of the spatial distribution of precipitation, sea surface temperature (SST) and surface winds in order to identify the factors associated with ITCZ width variation. The results confirmed previous works on ITCZ position variability and showed additional information concerning the variability of the intensity and width. At monthly timescale, the ITCZ width and intensity tend to decrease when ITCZ reaches its southernmost positions (February, March and April). The annual variation amplitude was about 7° of latitude for the mean position (1°N in April to 8°N in August), 3° for the width (3° in March to 6° in October) and 3 mm.day-1 for the precipitation intensity (10 mm.day-1 in March to 13 mm.day-1 in July). The composite analysis of precipitation, SST and surface winds divergence over the Tropical Atlantic region showed that, under conditions of ITCZ position close to the average, positive width anomalies would be related to negative SST anomalies and positive convergence of surface winds, but the differences had no statistical significance.
Numa clara afirmação da sua aplicabilidade em diferentes áreas, em particular nas atividades aeronáuticas e aeroespaciais, o Weather Research and Forecasting (WRF) vem sendo amplamente empregado como ferramenta que representa o estado da arte na previsão numérica do tempo. Com a sua implementação, o Instituto de Controle do Espaço Aéreo (ICEA) consegue estar inserido no crescimento natural das pesquisas na área de previsão operacional do tempo, ao disponibilizar prognósticos das condições do tempo em alta resolução para todas as Regiões de Informação de Voo (FIR) do território brasileiro, com o objetivo de auxiliar os órgãos tomadores de decisão no gerenciamento do fluxo do tráfego aéreo.
CARVALHO, M. A. V. et al. Simulação de um caso de evento extremo de precipitação no Aeroporto Internacional de Guarulhos com o modelo WRF utilizando diferente passos de tempo. In: CONGRESSO BRASILEIRO DE METEOROLOGIA, 17, 2012, Gramado. Trabalho apresentado... Gramado: CBMET, Incertezas e Desafios para a Sustentabilidade Planetária: O Papel da Ciência Meteorológica, 2012.
OYAMA, M. D. et al. Influência da zona de convergência Intertropical Atlântica na precipitação da região do centro de lançamento de Alcântara: estudo preliminar. In: CONGRESSO BRASILEIRO DE METEOROLOGIA, 17, 2012, Gramado. Trabalho apresentado... Gramado: CBMET, Incertezas e Desafios para a Sustentabilidade Planetária: O Papel da Ciência Meteorológica, 2012.
This work presents an observational and modeling study of the Intertropical Convergence Zone (ITCZ) features on the central portion of the Tropical Atlantic Ocean. The variabilities of the position, width and mean precipitation (intensity) of ITCZ for 10 years (1999-2008) are obtained objectively from pentad precipitation data. The influence of the ITCZ over three areas with distinct pluviometric behavior in Northeast of Brazil (NEB), for March and April (1999-2008), when ITCZ is located in its southernmost position, is also studied. The sensitivity of the simulated precipitation from the MM5 regional model to different explicit convection schemes, activation of the Grell shallow convection scheme and adjustments in the Kain-Fritsch convective parameterization scheme (KF2) is tested. The adjustments in KF2 comprise changes in the minimum cloud depth necessary to activate deep convection, in the convective trigger function parameters and in the advective and convective time scales. The observational study confirmed previous works on the variability of ITCZ position and showed new aspects on the variability of ITCZ width and intensity. In the monthly scale, the ITCZ width and intensity tend to decrease when ITCZ reaches its southernmost positions (February, March and April). The amplitude of the annual variation is about 7° for the ITCZ position (1°N in April to 8°N in August), 3° for the width (3° in March to 6° in October) and 3 mm.dia-1 for the intensity (10 mm.day-1 in March to 13 mm.day-1 in July). For the interannual variability of March and April, the largest correlation coefficients were found for the relation between the position and width of ITCZ and the precipitation in the northwestern coast of NEB. The modeling study showed that the use of warm rain scheme and Grell shallow convection scheme (together with KF2 shallow convection scheme) led to marked reduction of the simulated precipitation for the central portion of ITCZ. There were also improvements in the simulated precipitation under the following adjustments in the KF2: convective time increase (5400 s) and minimum cloud depth necessary to activate the convection increase (now ranging from 3500 to 7000 m). The inclusion of all the proposed changes not only removed the bias, but also reduced the root mean square error with a gain of 69%, when compared to the control simulation.
CARVALHO, M. A. V. et al. Variabilidade da largura e intensidade da zona de convergência Intertropical Atlântica: aspectos observacionais. In: SIMPÓSIO INTERNACIONAL DE CLIMATOLOGIA, 4, 2011, João Pessoa. Trabalho apresentado... João Pessoa: SIC, Mudanças Climáticas e seus Impactos nas Áreas Urbanas, 2011.
O aumento do tráfego aéreo nos grandes aeroportos brasileiros, aliado a uma configuração de rede de rotas estabelecida por auxílios à navegação aérea convencionais baseados no solo (VOR, DME, NDB), tem gerado constantes congestionamentos nas áreas de controle terminal e respectivas regiões circunvizinhas. A fim de dirimir estas questões, a ICAO institui o conceito de Navegação Baseada em Performance (PBN), objetivando aumentar a capacidade do espaço aéreo e diminuir os custos operacionais. Baseado neste conceito, este trabalho visa analisar as rotas ATS de Salvador de acordo com a futura expansão do seu aeroporto internacional, prevista em plano diretor e na qual é considerada a implantação de pistas paralelas. Os efeitos no tráfego aéreo de Salvador são aqui analisados confrontando três cenários modelados: (a) a configuração atual da rede de rotas considerando as pistas convergentes existentes nesse aeroporto; (b) a configuração atual de pistas com uma estrutura de rotas PBN e (c) uma estrutura de rotas PBN numa possível configuração de pistas paralelas. Neste contexto são adotadas métricas de tempo e distância de vôo, resolução de conflito, tempo de atraso nas decolagens e complexidade do espaço aéreo. O RAM PLUS é utilizado como ferramenta de simulação computational fast-time para esta análisede espaço aéreo.
Propõe-se no presente trabalho analisar, por meio de simulação, a carga de trabalho dos controladores de tráfego aéreo do Controle de Aproximação de Brasília (APP-BR) em seis diferentes cenários de sua área. Para tanto, utiliza-se o software RAMS Plus, ferramenta computational especialmente desenvolvida para operações em espaço em espaço aéreo e lado aéreo e lado aéreo dos aeroportos. O escopo da análise foi montado para as operações no espaço aéreo que apresentam origem ou destino no Aeroporto Internacional de Brasília (Juscelino Kubitscheck). Os quatros primeiros cenários abordados, chamados de iniciais, apresentam configurações de trajetória de vôo distintas realizadas em dois tipos de setorização (Norte/Sul e Leste/Oeste), cada um deles com dois setores. Após a análise dos cenários iniciais, foi criada uma nova situação com o intuito de avaliar a carga de trabalho dos Controladores num momento futuro onde deverá haver maior demanda do Tráfego Aéreo. No cenário proposto, o tráfego foi acrescido em 30% (trinta por cento) em relação aos primeiros. Assim incrementou-se um terceiro setor, não utilizado nas primeiras situações, buscando verificar a eficácia da divisão do controle do espaço aéreo na redução da carga de trabalho ora estudada. Além da análise de carga de trabalho, foram abordados outras questões de relevância no planejamento do espaço aéreo como: potenciais conflitos, número de aeronaves controladas simultaneamente, tempo de vôo, e, custo de combustível em cada cenário.
CORRÊA, C.S. et al. Teste estatístico não-paramétrico de aleatoriedade com análise da tendência linear no estudo das séries da temperatura média, máxima e mínima mensais entre os anos de 1951-2007 dos Aeroportos Internacionais de Porto Alegre, Congonhas e Galeão. In: CONFERÊNCIA REGIONAL SOBRE MUDANÇAS GLOBAIS: AMÉRICA DO SUL, 3, 2007, São Paulo. Anais... São Paulo: USP, 2007. 1 CD-ROM.
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