Publicações

A ferrugem-do-café (Hemileia vastatrix) é uma doença que ataca praticamente todas as regiões do Brasil, causando grandes prejuízos. O objetivo deste trabalho foi analisar as possíveis ocorrências desta doença, na cultura do café arábica, durante o clima o presente (1961-1990), e nas projeções climáticas (2011-2100) geradas pelo modelo regional Eta/CPTEC (cenário A1B). Selecionaram-se para estudo as cidades de Campinas, Mococa, Pindorama e Ribeirão Preto, localizadas no estado de São Paulo. Séries históricas de precipitação e temperatura média do ar, cedidas pelo Instituto Agronômico de Campinas (IAC), foram utilizadas para ajuste do modelo. Consideram-se como condições para ocorrência da doença temperatura médias entre 20°C e 25°C e precipitação acima de 30 mm, ambas em valores diários. Em relação à temperatura, verificou-se nos cenários futuros (2011-2040; 2041-2070; 2071-2100), em média, uma diminuição do número de dias favoráveis a ocorrência da doença, devido o aumento de temperatura média do ar. Entretanto, observou-se aumento do número de dias com precipitação acima de 30 mm, contribuindo possivelmente para o aumento da incidência da ferrugem-do-café.

The goal of this study was to investigate if the variability of the annual number of thunderstorm days (TD) of Rio de Janeiro from 1951 to 2009 is related to any large scale weather phenomena. Wavelet, cross-wavelet and wavelet coherence analyses, as well as associated statistical significance tests, were used to investigate the frequency structure of TD as well as the Tropical Southern Atlantic Index (TSA), Southern Oscillation Index (SOI), the Pacific decadal oscillation (PDO) and the International Sunspot Number (ISN). Wavelet analyses indicated that the variability of Rio de Janeiros TD can be primarily explained by two distinct significant (p<0.05) peaks of periodicity of 1 year and 12 years. The 1 year periodicity in TD is well established, being associated to the difference in temperature from summer to winter. Our results suggest that the 12 years periodicity in TD is mainly caused by fluctuations in the TSA. The cross-wavelet spectrum of the TD and TSA indicated a significant peak at 12 years. Furthermore, wavelet coherence demonstrated that the intensity of the 12 years periodicity of the TD and TSA were significantly positively correlated through time. The study concludes that TSA contributes significantly to the variability of the TD in Rio de Janeiro indicating it may be potentially used in TD forecasting.

Thunderstorms are known to have a significant impact on society in terms of fatalities and financial losses, making the possibility to predict the response of thunderstorm activity to global warming one of the main goals of current research. However, predicting changes in thunderstorm activity is a very difficult task because its activity is modulated by many physical processes acting simultaneously at many different spatial scales. Among the possible processes for South America, we can identify at local scale the urban activity and at large scale the El Niño Southern Oscillation (ENSO), the South Atlantic Ocean surface temperature anomaly (TSA) and the South Pacific Ocean surface temperature. There is also some speculation about a possible influence of the solar activity on the thunderstorm activity. In this report thunderstorm day monthly records obtained in the last 120 years in the cities of São Paulo and Campinas and in the last 150 years in the city of Rio de Janeiro, all in the Southeast region of Brazil, are analyzed and discussed in the context of the phenomena above. The results of the analysis indicate that the variation in the thunderstorm activity in São Paulo and Campinas are dominated by urban activity and show a significant increase during the period of study, while in Rio de Janeiro it cannot be explained by either urban activity or a single large scale phenomenon, being most probably a result of a complex combination of local and large scale features. Statistically analysis involving a combination of large scale phenomena found that the unique combination that results in a significant variation of the thunderstorm days is the occurrence of both positive anomalies of TSA and La Niña, in comparison with the occurrence of both negative anomalies of TSA and El Niño. This combination produces also significant variations of thunderstorm days in São Paulo and Campinas. If it is assumed that the ENSO phenomenon is relatively independent of the global warming in course, the positive trend of TSA suggest that the thunderstorm activity in the Southeast Brazil tends to increase with the global warming.

Thunderstorms cause a significant number of faults in energy distribution systems. The possibility to forecast the thunderstorm frequency in the summer period with a reasonable anticipation (a few months) would be of great importance to support preventive actions for protection and recomposition of the electrical system, improving its performance and reliability. Thunderstorm day monthly records obtained in the last 50 years in the city of Campinas are used to develop a forecast method to predict the lightning activity with at least a month in advance in the area of operation of the Elektro power electric company in the state of São Paulo, in the Southeast region of Brazil. It was found that the thunderstorm day monthly records during the summer period are not correlated with large scale meteorological parameters that are considered to be associated to the convective activity in the South America such as the El Niño Southern Oscillation (ENSO), the South Atlantic Ocean surface temperature anomaly, the Pacific Decadal Oscillation (PDO) and the international sunspot number related to the solar activity, while they are good correlated with previous thunderstorm days if conveniently filtered to avoid high frequency changes. Based on this fact, a prediction method with a one month in advance was developed with a reasonable level of success. For larger periods the confidence of the results decreases significantly. The preliminary results of the method are supported by comparisons with lightning data obtained by the Brazilian Lightning Detection Network (BrasilDat) and interruptions data in the distribution network for the last years, indicating its high potential to support operation management.

A new lightning detection network using WeatherBug Total Lightning Sensors (WTLS) is being deployed in Brazil. The network can acquire detailed signals emitted from both IC and CG flashes and continuously sends information to a central server. A WTLS is composed of an antenna, a global positioning system (GPS) receiver, a high-accuracy GPS-based timing circuit, a digital signal processor (DSP), and onboard storage and internet communication equipment. The sensor is a wideband system with detection frequency ranging from 1Hz to 12MHz. The wide frequency range enables the sensor to not only detect strong CG strokes, but to also detect weak IC pulses. The sensor records whole waveforms of each flash and sends them back, in compressed data packets, to the central server. Instead of using some waveform parameters, the whole waveforms are used in locating the flashes and differentiating between IC and CG strokes. A 75-sensor network is being installed in the South, Southeast, Center and Northeast regions of the country and should operated simultaneously with the integrated lightning detection network (RINDAT), which is composed by 34 lowfrequency (LF) sensors using Vaisala technology, covering the Southeast and parts of the South and Center regions of the country. Details of the new network configuration and its main applications will be described.

Lightning monitoring technologies to support electric power applications have been developed and used for at least 30 years in many countries. The main technology available consists of Lightning Location Systems (LLS). They have been used in conjunction with specific computational tools by power utilities for many different applications dedicated to reduce the lightning impact on electric power systems. In most cases, the LLS operate in the LF frequency range and are designed to detect and locate mainly cloud-to-ground flashes. In general, most of the applications are concentrated in the operation and analysis of performance of distribution and transmission networks, involving the use of real time and historic data. The goal of this article is describe the most common uses of LLS data by power utilities. Examples of applications involving cloud lightning data obtained by these networks are also discussed. The potential use of LLS data is strongly dependent on the adequate knowledge by power utility personal of such aspects.

Recentemente, há um aumento de CO2 na atmosfera, decorrente do uso de combustíveis fósseis (carvão, petróleo, gás natural) em termelétricas, indústrias, automóveis e também da devastação e queima de florestas contribuindo para o aquecimento global. O objetivo do presente trabalho é estimar o fluxo de CO2 entre a superfície e a atmosfera, empregando uma rede neural artificial (RNA) Perceptron de Múltiplas Camadas (PMC). Os dados observacionais são assumidos como dados de satélites ambientais. O processo de inversão ocorre em 2 etapas: (a) estimativa de perfis de concentração de CO2 a partir de radiâncias, (b) identificação de fluxo de CO2 a partir da concentração obtida no item (a). Os resultados dos processos de inversão foram satisfatórios em que a RNA-PMC apresentou robustez ao estimar o fluxo de superfície entre o solo e a atmosfera com dados ruidosos.