RESEARCH AND DEVELOPMENT

The SOLTER project (https://labren.ccst.inpe.br/solter/) aims to develop diffusion bonding techniques for the construction of efficient, low-cost solar energy accumulators for use in small electric generators, in which phase-change materials attenuate the variations in solar energy typical of Brazil. The LABTUCAL/UFSC team has extensive previous knowledge in the development of solar receivers, compact heat exchangers and the diffusion bonding of special steels and alloys for a wide variety of applications. On the other hand, LABREN/INPE has accumulated decades of data on solar irradiation in Brazil, which is influenced by region and cloud variation. This project allows efforts in these areas to be directed towards the development of a full-scale prototype.

Coordinators: Profa. Dra. Marcia B. H. Mantelli (LABTUCAL/UFSC) / Dr. Rodrigo Santos Costa (LABREN/INPE)

Funderes: FINEP

A consortium of more than 200 scientists from 38 research groups from 15 Brazilian states, with the support of 12 institutions from 11 countries, is involved in the 2nd INCT-Climatic Changes Project (INCT-MC). This new project is a continuation of the previous INCT-MC (2009 to 2014) and is based on the scientific and technological results obtained by it, where the following studies were approached and developed: scientific basis of global environmental changes; impacts, adaptation, vulnerability; mitigation and technological innovation efforts in climate system models, geo-sensors and the natural disaster prevention system. More information on the previous INCT-MC can be obtained at: http://inct.ccst.inpe.br/. In this continuation of INCT-MC will be applied the main scientific results of the previous INCT. Among them we can mention the great scientific contribution to the reports of the IPCC AR5 and the PBMC and also the scientific reinforcement of the CLIMA Network. The previous INCT-MC showed, among other things, that rain extremes (similar to those that caused floods and landslides in the Rio de Janeiro mountainous region in January 2011) have been more frequent and intense since 1950, generating vulnerability in areas of high population density in Southeast Brazil. This vulnerability may increase in the future if disaster risk reduction measures are not created and implemented.

Coordinator: Tercio Ambrizzi

Funderes: National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Foundation for Research Support of the State of São Paulo (FAPESP)

As energy from the Sun participates in several atmospheric processes, the mesoscale models for weather forecast estimate the solar radiation incident on the surface. These estimates find applications in agriculture, architecture and energy sector. In the energy sector, short-term solar radiation forecasts can be employed in the generation activities (operation of hybrid systems that use solar energy) and the distribution of electrical energy (prediction of load dispatch in transmission lines). The description of most atmospheric phenomena by means of differential equations involves uncertainties caused by modeling methods. A strategy to deal with uncertainty in numeric prediction models is to apply an Model Output Statistical (MOS), powered by the data produced by the numerical models. MOS methodology is a refinement technique that consists of determining a statistical relationship between a predictor and variables predicted by a numerical model in different forecast horizons. The use of this technique has been presented as fundamental in the operational practice of the numerical prediction. The proposed project has the goal of developing high resolution modeling methodology using the WRF (Weather Research and Forecasting) model for estimating and predicting solar irradiation on the surface considering the climate and environmental characteristics found in Brazilian territory, adopting methods of artificial intelligence as a technique of statistical refinement and reduction of uncertainty of estimates and forecasts.

Coordenador: Fernando Ramos Martins (UNIFESP)

Financiador: National Council for Scientific and Technological Development (CNPq)

Coordenador: Fernando Ramos Martins (UNIFESP)

Financiador: Coordination of Improvement of Higher Level Personnel (CAPES)

The knowledge of the variability of energy resources as a function of climatic variability is relevant not only for the energy planning of the country, but also for the evaluation of the economic viability and technical detailing of projects and investments in production and insertion of these renewable sources into the electricity distribution system. The studies of economic viability and energy planning should take into account the climatic and environmental impacts of short, medium and long-term, such as increased or reduced precipitation, increased frequency of storms or changes in the coverage of the Soil, etc. As an example, the increase in the speed of winds above the tolerance values specified in the project of a wind farm can prevent the production of energy due to the risks of damage to the mechanical system of the installed generators. As a result, there may be economic and technical losses if this increase is not foreseen in the development of the project.

Coordenador: Fernando Ramos Martins (UNIFESP)

Financiador: National Council for Scientific and Technological Development (CNPq)

The main objective of this study was to enable the evaluation and characterization of the temporal variability of the cloud cover and its influence on the solar resource incident on the surface, important information for projects of energy generation systems that use solar technology. In order to do so, a methodology was developed to estimate the frequency of occurrence of each cloud thickness value for any point in the Brazilian territory from satellite images, generating clouds frequency statistics, translated in the form of specific indexes. These regional maps are useful to evaluate the impact that the cloudiness can cause on different heliothermic plants, due to the specific thermal inertia of each plant, or even to the energy transmission network, since it will allow to infer the expected transient spectrum for each region.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

The prediction of the availability of solar irradiation is of paramount importance for photovoltaic and heliothermic generating plants, since they are dependent on meteorological factors. The scale considered in the forecasts can range from minutes to days. The aim of this study was the development and integration of a hybrid solar irradiation prediction system through the combination of different methodologies. Forecasting methods were developed by sky imaging cameras installed on the ground for a 30-minute horizon through the projection of cloud motion. On the horizon of 1 to 6 hours, satellite images were used to obtain future cloud fields and, consequently, solar irradiance forecasts through radiative transfer models. Finally, it was used mesoscale meteorological modeling adjusted by artificial neural networks to provide forecasts in the horizon from 12 to 72 hours. The results were validated in a pilot heliothermic plant developed by INPE partner institutions. It is expected that the results bring a gain of predictability of solar generation in the country, reducing risks and bringing security to the insertion of solar generation in the national interconnected system.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

Coordenador: Fernando Ramos Martins (UNIFESP)

Financiador: Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Development of models for solar radiation transference in the atmosphere adapted to the climate characteristics and specific seasonal environmental conditions of the various Brazilian mesoclimatic regions, combining satellite data with surface data for the generation of synthetic series of global, direct, direct normal and diffuse solar radiation at the level of the earth's surface with less uncertainty.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

This project aimed to consolidate the investigation of the potential of wind power in hydroelectric reservoirs in view of the current scenario and future scenarios projected by the IPCC, facing the influence of climate change. This pilot study was carried out for four important hydroelectric reservoirs in the state of Minas Gerais: Furnas, Três Marias, Itumbiara (border of Minas Gerais and Goiás) and Estreito (border of Minas Gerais and São Paulo).

Coordinator: Arcilan Treviseu (UNIFEI)

Funder: Foundation for Research Support of the State of Minas Gerais (FAPEMIG)

The main objective of the project was to establish a long-term partnership between the LABREN / DIIAV / INPE and the Energy Meteorology group of the University of Oldenburg (EnMetol), Germany, for the development of methods and meteorological tools specifically applied to the demands of the energy sector regarding the spatial and temporal variability of the energy potential of solar and wind sources. The results and products generated by this partnership will contribute to boost the insertion of solar and wind renewable sources in the energy matrix. Within the scope of this project, part of the CAPES NoPa program, emphasis was placed on the qualification and training of human resources through the exchange of researchers and doctoral students, establishment of a joint agenda of research activities and development of methods and tools for services to the energy sector.

Coordinator: Enio Bueno Pereira

Funder: Coordination of Improvement of Higher Level Personnel (CAPES)

The project has estimated the impacts of future climate changes due to global warming on Brazil's solar and wind energy potentials for the periods 2010-2040, 2040-2070 and 2070-2100. The project also aimed to provide predictions of these impacts for three scenarios of greenhouse gas emissions: A2, B2 and A1B, according to the classification presented in IPCC reports.

Coordinator: Fernando Ramos Martins (UNIFESP)

Funder: National Council for Scientific and Technological Development (CNPq)

Creation of a model of radiative transfer in the atmosphere that allows to estimate the solar irradiation incident in the national territory of Chile with the processing of satellite images, taking into account its particular geographic and climatic conditions. For this, INPE Brazil-SR model was modified and adapted to the Chilean conditions.

Coordinator: Rodrigo Escobar Moragas (Universidade do Chile)

Funder: National Commission for Scientific and Technological Research (Cooperation) - Chile

Development of methodology for the forecasting of short-term wind energy suitable for the Northeast region of Brazil, based on numerical forecasts made operational in the country and compatible with the tropical climate, thus allowing wind power plants to become more competitive and the electricity system to be managed by optimized way. One of the greatest difficulties for the development of wind surveys for wind farms is the existing database. In addition to the scarcity of anemometric data, there is also a gap in terms of knowledge of the atmospheric boundary layer (ABL), especially in the region of greatest potential, the Northeast. The project was carried out through a partnership between three institutions: UFAL, INPE and CTA.

Coordinator: Roberto Fernando da Fonseca Lyra

Funder: National Council for Scientific and Technological Development (CNPq)

Generation and organization, in a geo-referenced database, of technical-scientific information containing environmental data, data of renewable resources and information on technology and infrastructure available in Brazil.

Coordinator: Enio Bueno Pereira

Funder: United Nations Environment Program (UNEP)

The subproject aims to conduct a study on the impacts of the various global climate change scenarios on the incident solar radiation flux and on the wind regime and, in this way, estimate how these changes will change their energy potentials in Brazil in the long-term, medium-term and short-term deadlines.

Coordinator: Enio Bueno Pereira

Funder: National Council for Scientific and Technological Development (CNPq)

Survey of solar energy resources in Brazil through the collection, qualification and distribution of solar data from the national environmental data collection network SONDA and by the modification of the BRASIL-SR radiation model for the use of semi-hourly satellite data.

Coordinator: Enio Bueno Pereira

Funder: Research and Development Center Leopoldo Américo Miguêz de Mello (CENPES)

Coordinator: Enio Bueno Pereira

Funder: Financier of Studies and Projects (FINEP)

Coordinator: Enio Bueno Pereira

Funder: United Nations Environment Program (UNEP)

In a scenario of global climate change and depletion of ecosystems, the growing demand for natural resources implies adopting new practices in human activities. The Nexus concept reads the interrelationship between Water, Energy and Food and how actions can systematically affect the three elements. It proposes appropriate management, based on information and governance, to ensure availability and access to resources in the long term.

In Brazil, the São Francisco river basin is emblematic territory for the Nexus concept, where water is demanded in energy generation, food production and direct use by the population. The periods of drought intensify the dispute over water, with social, economic and political effects. At the same time, solar irradiation is an abundant resource in the region, with an average level above 5 kWh / m² / day. Underutilized until now, its use to generate electricity has the potential to reduce water reserves, with the possibility of changing the region's sustainability index.

In this context, the research aims to analyze scenarios of application of solar source technologies to generate electricity in different functional, economic, spatial and land use arrangements. Nexus and Life Cycle Assessment will be methodological tools used to compose scenarios and quantify resource indicators. The scenarios will aim to provide information to decision making and subsidize governance and public policies focused on water, energy and food security in a region with an asymmetry in resource use.

Student: Érica Ferraz de Campos

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

The study of cloudiness through imaging cameras installed on the surface has as positive points the spatial resolution of clouds, on the order of tens of meters, and temporal resolution, which can be seconds to a few minutes. The identification and classification of clouds are important for several areas of meteorology, and can contribute to the understanding of the evolution of convective processes, especially in periods and situations of convection transition. This knowledge can be applied in radiative transfer models and short-term weather forecasting.

In this project, a literature review of existing methods for automatic cloud classification with imaging cameras will be performed by implementing machine learning techniques, allowing future cloud fields to be estimated by evaluating shallow and deep convection processes. The erosion of the nighttime boundary layer and the evolution of the convective boundary layer in the early morning also benefit from these results. Validation will be performed using data and images collected in two experiments, coming from the GoAmazon 2014/5 conducted in the Amazon and from the SONDA network at several locations in Brazil, in particular in the Paraíba Valley. The methodology will allow the automatic classification of the images, as well as the characterization of their evolution.

Student: Vinicius Roggério da Rocha

Degree: Doutorado

Advisor: Gilberto Fisch

Funder: CAPES

The global climate system presents variations that affect the availability of energy resources. The analysis of the variability of the energy resources is of great importance for the national energy planning, and can still bring benefits to other sectors of society. Studies on the influence of atmospheric variability on the availability of solar and wind resources are still scarce, especially for interannual and interdecadal scales. Based on climatic data that include reanalysis of atmospheric models, satellite images and surface observations, and using multivariate statistical analysis techniques, we intend to investigate, together, how solar, wind and hydraulic resources vary over the territory national, with emphasis on seasonal and interannual scales. This temporal variability between different sources allows to explore possible complementarities, while its spatial variability allows the quantification of the smoothing effect of load curves, a phenomenon of great importance in a country with continental dimensions such as Brazil. Therefore, it is intended to identify favorable regions for the installation of each type of generating plant from spatial optimization models, obtaining patterns of distribution of generating units that minimize the risk of energy shortage. Studies of this type become gradually more relevant as the trend towards a diversified electrical matrix is ​​observed and are evidenced as fundamental for the sustainability of the main economies of the world. It is expected that the results of this work will be another source of information to support the decisions of the government in planning the expansion of the national electricity system.

Student: André Rodrigues Gonçalves

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: Non-existent

The photovoltaic modules in general have been evaluated in very well controlled conditions taking into account the solar spectrum according to ASTM G 173-03 standard prepared with data from North America. Considering that North American climate is particular of that region and the spectrum in field tends to vary during the year, we can say that such evaluation may not be representative for the conditions found throughout the Brazilian territory. So, this work aims to carry out a preliminary assessment of the effect of spectral variations in the performance of photovoltaic modules of six different technologies in a particular region of Brazil.

Student: Guilherme Marques Neves

Degree: PhD

Advisors: Enio Bueno Pereira / Waldeir Amaral Vilela

Funder: CAPES

The energy sector is one of the largest contributors to greenhouse gas emissions. Data from the Food and Agriculture Organization of the United Nations indicate that more than 30% of these emissions are associated with the production of energy and heat. The generation of electricity from renewable sources depends on prior assessments of the availability and variability of the associated resources. Computer models are one way to obtain this information for planning and management purposes in this area. To this end, the models must be able to accurately represent physical phenomena, taking into account local atmospheric factors. However, radiative transfer models employed in solar irradiance studies are limited and inefficient in separating the calculated global irradiance into its direct normal and diffuse components.

This work aims to implement mechanisms to separate these components and improve the spectral modeling adopted in the BRASIL-SR model, whose importance in the country is demonstrated by its use in the preparation of the Brazilian Solar Energy Atlas. The functionalities proposed here will enable the model to generate more accurate maps of the radiative components, contributing to the planning and development of the Brazilian energy matrix based on renewable sources and also to other sectors of society for which the spectral evaluation of solar irradiance is necessary information, such as health (ultraviolet radiation) and agricultural productivity (photosynthetically active radiation), among others.

Student: Antonio Maurício Zarzur

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

The research is to analyze the spectral characteristics of the materials that make up the urban areas in Brazil, their relationship to the land use and energy demand. Aims to provide technical information that results in alleviating the phenomenon of warming of urban areas, called heat Island. The methodology consists of analyzing the phenomenon on the scale of the building and on the scale of cities and through models and simulations promote interaction with actual data: materials, construction methods, climate and use. The result of this project it is intended to complement information about the factors that determine the energy efficiency of cities, human well-being and environmental preservation and provide subsidies for the implementation of urban-related parameters.

Student: Fabiana Lourenço e Silva Ferreira

Degree: PhD

Advisors: Enio Bueno Pereira

Funder: CAPES

The radiative transfer model BRASIL-SR was developed by LABREN/CCST/INPE and uses satellite images in conjunction with monthly average climatological data to calculate estimates of incident solar irradiation, allowing the mapping of sites suitable for the use of solar resources. The estimates provided by the model focus on monthly results and also on atmospheric transmittance calculated only for hourly averages in the center of the monthly interval, due to the high computational cost. Despite being exhaustively validated and presenting errors in the same order as other computational tools in the literature, the extrapolations performed imply higher bias values in the estimates of hourly and daily irradiance. This work aimed at optimizing the computational performance of the BRASIL-SR model on multicore systems, through the use of parallelization directives of OpenMP with loop scheduling and changes in the input and output data to the NetCDF format. The processing time for the BRASIL-SR model was reduced from 27 hours to 1 hour and 30 minutes using 24 threads. Other traditional optimization techniques, such as blocking and vectorization, were also investigated, but did not show an improvement in performance due to the structure of the model code. With the initial results of this research, it was possible to change the mode of transmittance calculation, which was previously calculated for the center of the monthly interval, to a daily transmittance calculation. A script was developed to perform the preprocessing and processing of the model, obtaining a total preprocessing and processing time of 1 hour and 40 minutes, an improvement of 3700%. The use of the model parallelized with OpenMP, together with the Python scripts developed for the operationalization of the model, will be determinant for the development of short and very short term solar irradiation forecast models, being of extreme relevance for the decision making of several actors, such as the National Electric System Operator.

Available at Production / Theses and Dissertations

Aluno: Jefferson Gonçalves de Souza

Grau: Master

Orientador: Celso Luiz Mendes / Rodrigo Santos Costa

Financiador: CAPES

The variability of solar energy is one of the most important issues in the integration of solar energy into the power grid. The development of methods for assessing the movement of clouds and the resulting buoyancy in power generation make this study of great importance to the Brazilian energy sector. In this way, the work aimmed to classify and study the clouds in different regions of the Brazilian territory, using sky imagers, for a regional climatological knowledge and possible short-term forecasts of the cloud movement.

Student: Eduardo Weide Luiz

Degree: PhD

Advisor: Enio Bueno Pereira

Funders: CAPES / CNPq

The objective of this work was to carry out a careful evaluation for estimation and prediction of short term and high resolution of the wind power potential at high spatial resolution through simulations with two versions of the WRF model (WRF-Real and WRF-LES) for some regions of Northeastern Brazil.

Student: Lucía Iracema Chipponelli Pinto

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

Being of knowledge that Brazil has enormous resource potential of solar energy, this project proposed to develop a methodology for the seasonal forecast of solar irradiance, aimed at commercial exploitation of photovoltaic plants, with the aim of contributing to the country's energy planning, reducing the need for operation of thermoelectric plants that use fossil fuels and alleviate national energy security risks. This will be done through an approach involving the treatment of historical data, numerical modeling and utilization of artificial neural networks in order to get a joint analysis of the information obtained.

Student: Maria Francisca Azeredo Velloso

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: CAPES

A study was conducted for climate variability and change of the minimum and maximum extreme winds to 10 m starting from the Brazilian airfields database of 10 m wind along with the downscaling of the HadCM3 global model made by ETA regional climate model to South America targeting the future scenario of the 2010 to 2100 of the IPCC AR4 scenario A1B 2100. It was also made the bias correction of the EtaHadCM3 model using the method of Artificial Neural Networks.

Student: Marcelo Pizzuti Pes

Degree: PhD

Advisors: Enio Bueno Pereira / José A. Marengo

Funders: INCT / CAPES

The WRF model was used to generate forecasts of surface solar radiation to the Northeast of Brazil, which were adjusted by statistical models based on multiple linear regression and artificial neural networks.

Student: Francisco José Lopes Lima

Degree: PhD

Advisor: Enio Bueno Pereira

Funders: CAPES / CNPq

The research aimed to develop methodologies for estimating parameters of cloud cover using data from long-wave radiation incident on the surface, along with weather data measured in surface stations in two localities, Brasília (DF) and Petrolina (PE). The first methodology employed atmospheric physics concepts to estimate the fraction of cloud coverage and presented behavior similar to the climatology of the localities studied. The second method proposed the use of Artificial Neural Networks for estimating the Effective Cloud Coverage and featured good correlation with satellite measurements. In addition, the method was able to evaluate the non-linearities of the estimate, when compared with linear methods such as Multiple Linear Regression.

Student: Eduardo Weide Luiz

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

Estimates of surface solar irradiance fields were made for the territory of Northeast Brazil in the years 2008 to 2011. For this, it was employed a estimating method based on interpolation by kriging. For evaluation of his performance, it was made an inter-comparison of the values estimated by interpolation with values measured in sampling points represented by Data Collection Platforms (DCPs) and estimates performed by the physical model of radiative transfer BRASIL-SR. The evaluation was performed through statistical indexes allied to cross-validation method and the visual analysis of maps of spatial variability of solar irradiance.

Student: Roque Magalhães Brito dos Santos

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

Several studies have shown, over the past few decades, that in fact the solar radiation that reaches the Earth's surface does not remain unchanged over the decades, but suffers increases and decreases known as solar dimming and solar brightening, respectively. However, the shortage of solar radiation data measured in the surface on long-term in Brazil is still a problem for the evaluation of the occurrence of these phenomena. Given this, this study proposed to assess trends in cloudiness, main factor modulator of solar radiation, through the study of spatio-temporal variability of the coefficient of cloud cover, determined through satellite images. For this, it were developed methods of estimation of irradiances of clear sky and overcast, necessary for the estimation of the coefficient of effective cloud coverage. The clear sky radiance is determined by the histogram of visible radiance frequencies measured by satellites, by assigning to it the value more often observed in a given area of the images within one quarter. The radiance of overcast skies, in turn, is determined by a setting that relates texture in the cloudtops, through the standard deviation of the visible radiance whose infrared measurement exceeds 280 K, with the sun-pixel-satellite geometry. The cloud cover was estimated for all the images of GOES-8 satellite, GOES-10 and GOES-12, in 1145, 1445, 1745 and 2045 GMT, in the period from 1999 to 2012. The trends of these coefficients were then evaluated through the use of non-parametric test of Mann-Kendall, with a significance level of 5%.

Student: Márcio Cecconi

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

The influence of atmospheric aerosols in quantifying of the solar resource was assessed from three data sources of horizontal visibility: climatological base model, the interpolation of the values of visibility of 105 airports in South America and visibility estimates obtained through the optical thickness of the aerosols from the CATT-BRAMS model. The simulations that used the data of horizontal visibility observed at airports showed significant improvements in estimates of global irradiation values, while the results of the simulations with the base of horizontal visibility estimated showed best performance in months and in regions where there was a high load of aerosols, with specific bias and RMSE decreases of up to 11%. Even when the new bases did not indicate improvements, error values were close to those obtained in the model integrations using horizontal climatological visibility.

Student: Rodrigo Santos Costa

Degree: PhD

Advisors: Enio Bueno Pereira / Fernando Ramos Martins

Funders: CAPES / CNPq

The ETA model outputs have been adjusted by statistical models based on multiple linear regression and artificial neural networks for the forecast of wind in surface (50 m). The results showed a significant gain in the correlations and reduction of errors in the forecast of wind in a horizon of 36 hours.

Student: André Rodrigues Gonçalves

Degree: Master

Advisors: Enio Bueno Pereira / Fernando Ramos Martins

Funder: CAPES

The work has developed a new methodology of analysis, knowledge representation and classification of atmospheric patterns from the values of the pixels of images obtained on the surface. The methodology aims to replace the synoptic observers (SO) that classify the sky from tacit knowledge and subjective criteria. The methods of analysis raised in specialized literature and in commercially available equipment use a binary approach of the results and mathematical simplification. The proposed methodology establishes an appropriate task domain to map the data represented by the values of the pixels in knowledge, necessary for the classification of standards based on the theory of atmospheric physics. Preliminary results indicated that the methodology proposed is superior to the main technique existing in specialized literature in the following aspects: more rigorous mathematical modeling, precise breakdown of the atmospheric patterns observed in the images, invariance with respect to solar incidence angle (brightness), comparison of the images with solar radiation sensors and the identification of other weather phenomena from the same images.

Student: Sylvio Luiz Mantelli Neto

Degree: PhD (Engineering and Knowledge Management)

Advisors: Aldo von Wangenheim / Enio Bueno Pereira

The work consisted of developing a methodology for assessing the impacts of climate change on the wind potential in the southern region of Brazil. For this study were used observational climatic series, ERA40 reanalysis from 1960 to 2007 and projections of the climatic ETA HadCM model from CPTEC, for the climatic scenario A1B until 2100.

Student: Marcelo Pizzuti Pes

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CAPES

Marajó island, in the State of Pará, North Brazil, shows a low level of economic development compared to other regions of the country. Among other factors that limit this development is the low availability of energy which, today, is produced exclusively by thermoelectric plants in isolated systems. This work aimed to make a preliminary survey on the feasibility of wind power generation in the region. The results indicated that the best winds occur in the months of September to November along the coastal region, on the north-northwest of the island. For this region there was an average wind power density of 151 W / m², and a form factor of 1.7. Based on wind data obtained by the ETA model and using the commercial package WasP wind systems analysis, was developed a scenario of use of wind energy in cogeneration scheme with the thermoelectric plants today installed in the region.

Student: Eliude Introvini da Cruz Segundo

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CNPq

The ETA model outputs have been adjusted by statistical models based on multiple linear regression and artificial neural networks for the forecast of solar radiation at the surface, showing gains in the application of statistical models in post processing of atmospheric models.

Student: Ricardo André Guarnieri

Degree: Master

Advisor: Enio Bueno Pereira

Funder: CNPq

The work describes the development of a prototype of an automatic mapping system of the fraction of cloud cover and the first results obtained. It was used a system consisting of a digital Pixera brand camera, model PCS20232, operating in the range of visible radiation, along with a wide angle lens FCE8, Nikon's manufacturing, with a nominal opening of 178°. The results were compared with the atmospheric transmittance (Kt) and the ratio of global and diffuse solar radiations (Kd), besides the BRASIL-SR model, which estimates the solar radiation at the surface. It were employed, comparatively, as input to the model, the clouds fractions generated by the new imager system and data obtained by the GOES-8 satellite. The results showed important differences that have been attributed to the fact that the data obtained by the imager does not contain information on the optical depth of the clouds.

Student: Mariza Pereira de Souza Echer

Degree: PhD (Space Geophysics)

Advisor: Enio Bueno Pereira

Funder: CNPq

In this study it were evaluated, developed and implemented in the BRASIL-SR model parameterizations of cloud cover index and aerosols released into the atmosphere in events of burning, seeking the improvement of estimates of solar irradiation. Two techniques were proposed for the composition of images of clear sky and overcast. The visual analysis of the compositions of images showed that the reason IR/VIS offers greater efficiency in identifying pixels with persistent conditions. The technique implemented for parameterization of aerosol from burning adopted optical properties obtained with the use of "Global Aerosol Data Set" and showed good agreement with values obtained in TRACE-A and SCAR-B missions. The studies showed that, with more appropriate parameterization for the determination procedures of cloud cover and the influence of aerosols, model performance is improved.

Student: Fernando Ramos Martins

Degree: PhD

Advisor: Enio Bueno Pereira

Funder: FAPESP

The paper presents a method to increase the precision of estimates of cloud cover made from the surface and compare it with satellite images. Were used: an inexpensive digital camera from the surface, image processing algorithms, an atmospheric physical model for the calculation of solar radiation on the surface, solar irradiation data, synoptic data and images from the GOES-8 satellite. The proposed methodology concluded that the interpretation of the estimates of cloud cover can not be binary, assigning a pixel of an image corresponding representation of a cloud or not, with a range of intermediate values ​​of transparency. This classification can lead to misinterpretation, as there are in the sky a series of physical manifestations as scattering and atmospheric turbidity that, despite representing clear sky, can confuse an automated interpretation system to due to proximity of intensity values with a small cloud optical depth (such as cirrus and the edges of other types of clouds), super sizing the final amount of cloud cover. This finding was possible only after using anisotropic diffusion on the images of clouds.

Student: Sylvio Luiz Mantelli Neto

Degree: Master (Computer Science)

Advisors: Aldo von Wangenheim / Enio Bueno Pereira

The new method described in work employs a database obtained in surface through a digital camera with sensor type Charge Coupled Device (CCD), in the range of visible radiation and acquiring images in red, green and blue (RGB). To analyze the collected images it was developed an algorithm whose function is to classify the pixels based on a decision process established empirically by field observers, determining the fraction of the sky covered by clouds. RGB attributes were transformed to Intensity, Hue and Saturation (IHS) using the saturation (S) in the separation of the pixels that match the sky and the clouds. The methodology was tested on images collected in the Antarctic Brazilian Station "Comandante Ferraz" and the results showed that the technique is suitable for the proposed work. The hit percentage for the pixels classified as clear sky was among 94% and 99% and classified as fully covered between 99.96% and 100%. The hit percentage to partially overcast sky presents a great difficulty in validating due to the very subjective characteristic of the visual identification process, usually employed in weather stations. The evaluation of the results of the automatic classification method was obtained by analysis of case studies based in various sky coverage states. These cases were chosen in order to represent: (1) sky with cloud cover patterns well defined (outlines of clouds well defined) and (2) sky with vague patterns and large amount of cloudiness (clouds with poorly defined edges and / or indefinite coverage states). To these conditions the recognition program also displays response consistent with the subjective process of classification based on visual inspection. Images collected for different Zenithal angle values and states of cloud cover were classified by the method. The sorting algorithm divided the results in three separate cases: (1) effectively clouds (11% to 82.93%); (2) indefinite state (10% to 23.41%) and (3) clear sky (13.82% to 85.32%). All groups were tested with a confidence level of 99.73%.

Student: Mariza Pereira de Souza Echer

Degree: Master (Space Geophysics)

Advisor: Enio Bueno Pereira

Funder: CNPq