Philosophiae Doctor - PhD / This research study examines those aspects of Indigenous Knowledge (IK) that could be socially and culturally relevant in the Western Cape Province, South Africa, for teaching meteorological science concepts in a grade 9 Social Science (Geography) classroom using dialogical argumentation as an instructional model (DAIM). The literature reviewed in this study explains the use of argumentation as an instructional method of classroom teaching in particular dialogical argumentation, combined with IKS (Indigenous Knowledge Systems), which in this study is seen as a powerful tool both in enhancing learners’ views and positively identifying indigenous knowledge systems within their own cultures and communities, and as tool that facilitates the learning of (meteorological) literacy and science concepts. With the development of the New Curriculum Statements (NCS) and the Curriculum and Assessment Policy Statements (CAPS) for schools, the Department of Basic Education (DBE) of South Africa acknowledges a strong drive towards recognising and affirming the critical role of IK, especially with respect to science and technology education. The policy suggests that the Department of Education take steps to begin the phased integration of IK into curricula and relevant accreditation frameworks. Using a quasi-experimental research design model, the study employed both quantitative and qualitative methods (mixed-methods) to collect data in two public secondary schools in Cape Town, in the Western Cape Province, South Africa. A survey questionnaire on attitudes towards, and perceptions of high school, of a group of grade 9 learners, as well as their conceptions of weather, was administered before the main study to give the researcher baseline information and to develop pilot instruments to use in the main study. An experimental group (E-group) of learners were exposed to an intervention - the results were recorded against a control group (C-group) that were exposed to no intervention. Both the E-group and C-group were exposed to a Meteorological Literacy Test (MLT) evaluation before and after the DAIM intervention. The results from the two groups were then compared and analysed according to the two theoretical frameworks underpinning the study, namely, Toulmin’s Argumentation Pattern - TAP (Toulmin, 1958) and Contiguity Argumentation Theory - CAT (Ogunniyi, 1997). The findings of this study revealed that: Firstly, the socio-cultural background of learners has an influence on their conceptions of weather prediction and there was a significant difference between boy’s and girls’ pre-test conceptions about the existence of indigenous knowledge systems within the community they live in. For instance, from the learners’ excerpts, it emerged that the girls presented predominantly rural experiences as opposed to those of the boys which were predominantly from urban settings. Secondly, those E-group learners exposed to the DAIM intervention shifted from being predominantly equipollent to the school science to emergent stances and they found a way of connecting their IK to the school science. The DAIM model which allowed argumentation to occur amongst learners seemed to have enhanced their understanding of the relevance of IK and how its underlying scientific claims relate to that of school science. Thirdly, the argumentation-based instructional model was found to be effective to a certain extent in equipping the in-service teachers with the necessary argumentation skills that could enable them to take part in a meaningful discourse. The study drew on the personal experiences and encounters from a variety of sources. These included storytelling-and sharing, academic talks with local community members recorded during the research journey, formal round table discussion and talks at international and local conferences, conference presentations, informal interviews, indigenous chats at social event-meetings, and shared experiences at IKS training workshops as a facilitator. These encounters lead to the formulation of the research study and occurred throughout the country in various parts of the Southern African continent including: Namibia, Zimbabwe, Malawi, Botswana, Tanzania and Mozambique.

Visualization is the process of constructing methods, which are able to synthesize interesting and informative images from data sets, to simplify the process of interpreting the data. In this thesis a new approach to construct meteorological visualization methods using neural network technology is described. The methods are trained with examples instead of explicitely designing the appearance of the visualization. This approach is exemplified using two applications. In the fist the problem to compute an image of the sky for dynamic weather, that is taking account of the current weather state, is addressed. It is a complicated problem to tie the appearance of the sky to a weather state. The method is trained with weather data sets and images of the sky to be able to synthesize a sky image for arbitrary weather conditions. The method has been trained with various kinds of weather and images data. The results show that this is a possible method to construct weather visaualizations, but more work remains in characterizing the weather state and further refinement is required before the full potential of the method can be explored. This approach would make it possible to synthesize sky images of dynamic weather using a fast and efficient empirical method. In the second application the problem of computing synthetic satellite images form numerical forecast data sets is addressed. In this case a mode is trained with preclassified satellite images and forecast data sets to be able to synthesize a satellite image representing arbitrary conditions. The resulting method makes it possible to visualize data sets from numerical weather simulations using synthetic satellite images, but could also be the basis for algorithms based on a preliminary cloud classification. / Report code: LiU-Tek-Lic-2004:66.

Aktinidijų uogų cheminės sudėties priklausomybė nuo meteorologinių sąlygų 2008-2009 m. tirta margalapės aktinidijos (Actinidia kolomikta) veislių ‘Laiba’, ‘Lankė’, ‘Landė’, ‘Paukstės Šakarva’, augančių Lietuvos žemės ūkio universiteto pomologiniame sode, uogų cheminė sudėtis. Standartiniais metodais uogose nustatyti sausųjų, tirpių sausųjų medžiagų, askorbo rūgšties, žalių pelenų, žalios ląstelienos, žalių baltymų ir aminorūgščių kiekiai, taip pat vidutinė uogos masė. Išanalizuota meteorologinių sąlygų įtaka aktinidijų uogų cheminei sudėčiai. Tyrimais nustatyta, didžiausia vienos uogos masė – 3,22 g – ‘Paukštės Šakarva’ aktinidijų. Mažiausios uogos buvo ‛Lankė’ aktinidijų - 2,09 g. Vidutinė vienos uogos masė – 2,64 g. Daugiausiai sausųjų medžiagų sukaupė ‛Laiba’ uogos – 21,08 %, mažiausiai - ‛Landė’ – 18,02 %. Tirpių sausųjų medžiagų daugiausiai sukaupė ‛Laiba’ – 12,72 %, mažiausiai - ‘Paukštės Šakarva’ – 10,83 %. Didžiausi askorbo rūgšties kiekiai aptinkami sunokusiose ‛Landė’- 5479,86 mg kg-1, mažiausi nesunokusiose ‘Lankė’ – 2698,25 mg kg-1. Daugiausiai žalių pelenų aktinidijų uogų sausojoje medžiagoje sukaupė ‛Laiba’ - vidutiniškai 6,20 %. / The investigation of Actinidia kolomikta cultivars ‘Laiba’, ‘Lanke’, ‘Lande’, ‘Paukstes Sakarva’, grown in Lithuanian University of Agriculture polomogycal garden, chemical composition of berries were caried out during the period of 2008 – 2009. The amount of dry agent, dry deliquescent agent, ascorbic acid, crude ash, crude fibre, crude protein, amino acids and the average berry weight were investigated by standart methods. During investigation there were analyzed the influence of meteorological conditions to A. kolomikta berries chemical composition. The investigation showed the highest weight of A. kolomikta ‘Paukstes Sakarva’breed fruits - 3,22 g. The smallest berries of A. kolomikta breed ‛Lankė’ - 2,09 g. The average weight of berry - 2,64 g. The biggest amounts of dry matters were established in fruits of ‘Laiba’ cultivar – 21,08 %, the smallest amount in fruits of ‘Lande’ cultivar – 18,02 %. The biggest amounts of dry deliquescent matters were established in fruits of ‘Laiba’ cultivar plants –12,72 %, the smallest amount in fruits of ‘Paukstes Sakarva’ cultivar plants – 10,83 %. The biggest amounts of ascorbic acid were determined in ripe fruits of cultivar ‛Lande’- 5479,86 mg kg-1, the lowest level of ascorbic acid were established in immature fruits of cultivar ‘Lanke’ – 2698,25 mg kg-1. Cultivar ‘Laiba’ accumulated the highest contents of crude ash in dry agent of berries (about 6,20 % on average).

The Canadian Precipitation Analysis (CaPA) system has been developed by Environment and Climate Change Canada (ECCC) to optimally combine different sources of information to estimate precipitation accumulation across Canada. The system combines observations from different networks of weather stations and radar measurements with the background information generated by ECCC's Regional Deterministic Prediction System (RDPS), derived from the Global Environmental Multiscale (GEM) model. The main scope of this study is to assess the importance of weather stations when combined with the background information for hydrological modeling. A new approach to meteorological network design, considered to be a stochastic hydro-geostatistical scheme, is proposed and investigated which is particularly useful for augmenting data-sparse networks. The approach stands out from similar approaches of its kind in that it is comprised of a data assimilation component included based on the paradigm of an Observing System Simulation Experiment (OSSE), a technique used to simulate data assimilation systems in order to evaluate the sensitivity of the analysis to new observation network. The proposed OSSE-based algorithm develops gridded stochastic precipitation and temperature models to generate synthetic time-series assumed to represent the 'reference' atmosphere over the basin. The precipitation realizations are used to simulate synthetic observations, associated with hypothetical station networks of various densities, and synthetic background data, which in turn are assimilated in CaPA to realize various pseudo-analyses. The reference atmosphere and the pseudo-analyses are then compared through hydrological modeling in WATFLOOD. By comparing the flow rates, the relative performance of each pseudo-analysis associated with a specific network density is assessed. The simulations show that as the network density increases, the accuracy of the hydrological signature of the CaPA precipitation products improves hyperbolically to a certain limit beyond which adding more stations to the network does not result in further accuracy. This study identifies an observation network density that can satisfy the hydrological criteria as well as the threshold at which assimilated products outperforms numerical weather prediction outputs. It also underlines the importance of augmenting observation networks in small river basins to better resolve mesoscale weather patterns and thus improve the predictive accuracy of streamflow simulation. / May 2017

La mesure de la visibilité météorologique est un élément important pour la sécurité des transports routiers et aériens. Nous proposons dans ce travail de recherche un indicateur de la visibilité météorologique adapté aux caméras fixes de vidéo surveillance du réseau routier. Il est fondé sur le module du gradient sélectionné dans des zones dont le comportement suit une loi de réflexion de Lambert vis à vis des conditions d'éclairage. La réponse de cet indicateur est issue d'une modélisation fondée sur une hypothèse de la distribution des profondeurs dans la scène. Celle-ci est calibrée avec des données provenant d'un visibilimètre ou bien avec une carte de profondeurs issue d'un modèle numérique de terrain. Les estimations sont ensuite comparées avec des données de référence obtenues par un visibilimètre et montrent une erreur moyenne similaire pour des images prises dans différentes conditions d'éclairage et de visibilité météorologique / The measurement of the meteorological visibility is an important element for the safety of road and air transport. We propose in this thesis a meteorological visibility indicator adapted to video surveillance cameras of the road network. This descriptor is based on the module of the gradient selected in areas that follow Lambert's reflection law. The response of this descriptor is derived from a model based on the statistical distribution of depth in the scene. Calibration is performed with data from a visibilimeter, or with a depth map from a digital terrainmodel. The results are then compared with reference data obtained from a visibilimeter and show a similar mean error for images taken in different illumination and meteorological visibility conditions

Master of Science / Department of Biology / Samantha M. Wisely / Nearly 30% of emerging infectious diseases are caused by vector-borne pathogens with wildlife origins, posing a risk for public health, livestock, and wildlife species of conservation concern. Understanding the spatial patterns of exposure to dipteran vectors and their associated pathogens is critical for epidemiological research to target prevention and control of vector-borne infectious diseases. In recent years, Western Equine encephalitis, St. Louis encephalitis, West Nile Virus encephalitis and avian malaria have not only been a public health concern but also a conservation concern, specifically the conservation of grassland nesting birds. Although the central Great Plains is the most specious region for grassland nesting birds, their role in the enzootic (primary) amplification cycle of infectious diseases may lead to further population depressions, and could potentially result in spill-over events to humans and livestock. The goals of my thesis were 1) to identify the underlying causes of spatio-temporal abundance patterns of mosquito vectors within the grasslands of the eastern Smoky Hills, and 2) to create probabilistic distributions of functional disease vectors, to evaluate disease risk in Greater Prairie-chicken (Tympanuchus cupido, surrogate species for other grassland nesting birds). First, I found that temporal dynamics in mosquito abundances were explained by maximum and minimum temperature indices. Spatial dynamics in mosquito abundances were best explained by environmental variables, such as curvature, TWI (Topographic Wetness Index), distance to woodland and distance to road. Second, the overall predictive power of the ecological niche models of important vector species in the grasslands of the Smoky Hills was better than random predictions, indicating that the most important predictor variables in their distribution were: distance to water, TWI, AASHTO (soil particle size distribution), and mean temperature during the coldest quarter. Furthermore, the spatial analysis indicated that Greater Prairie-chicken nest in areas with a higher probability of vector occurrence than other potentially available habitats within the grasslands. However, I failed to detect a significant difference in the probability of vector occurrence at nest of infected versus uninfected females. Understanding the distribution and abundance patterns of vectors of infectious diseases can provide important insights for wildlife conservation as well as public health management.

Este projeto de mestrado apresenta uma caracterização das chuvas estimadas pelo radar meteorológico Doppler de dupla polarização banda S (SPOL) do Departamento de Águas e Energia Elétrica (DAEE) e Fundação Centro Tecnológico de Hidráulica (FCTH) durante eventos com ou sem alagamento para cada bairro da cidade de São Paulo durante o ano de 2015. A caracterização foi determinada a partir da função densidade de probabilidade (PDF) da chuva acumulada e da taxa de precipitação, duração da chuva e fração da área de cada bairro onde ocorreu a chuva. Na média, os eventos de alagamento estavam associados com um volume de chuva maior que 30mm e taxa precipitação máxima maior que 30mm/h. Com relação à duração não foi possível encontrar um padrão médio, pois a chuva teve duração mínima de 20 minutos e máxima de 23 horas. Por outro lado, eventos de alagamento tinham alcançado mais de 27% da área do bairro com taxa de precipitação maior que 30 mm/h e 50 mm/h. Destaca-se ao longo desta análise que os bairros localizados próximos aos rios Tietê e Pinheiros e a região central da cidade de São Paulo apresentaram maior probabilidade de ocorrência de alagamento com volumes de chuva mais baixos do que a média de 30 mm por dia e também registraram maior recorrência de pontos alagados. Por último foi desenvolvido um método de regressão logística binária para calcular a probabilidade de ocorrência de alagamentos nos diversos bairros da cidade São Paulo. Este modelo utiliza como parâmetros de entrada a duração da chuva, a taxa de precipitação máxima e a chuva acumulada nas últimas 24 horas. O modelo apresentou uma probabilidade de detecção (POD) média de 1% e uma taxa de falso alarme média (FAR) de 0,6 para os eventos de alagamento, já para eventos sem alagamento o POD médio foi de 96% e a FAR foi de 2,5%. Portanto o modelo consegue prever os casos sem alagamento. / This dissertation project presents a characterization of the rainfall estimated from a dual-polarization S-band Doppler meteorological radar (SPOL) of the Department of Water and Electric Energy (DAEE) and Foundation Technological Center of Hydraulics (FCTH) during with or without flooding events for each neighborhood of the city of São Paulo over the year 2015. The characterization was determined by the probability density function (PDF) of the accumulated rainfall and the precipitation rate, rainfall duration and rainfall-area fraction in the neighborhoods. In average, flood events were associated with a rainfall volume greater than 30mm and a maximum rainfall rate greater than 30mm/h. Regarding the duration, it was not possible to find an average pattern, because the rain had a minimum duration of 20 minutes and a maximum of 23 hours. On the other hand, flood events had reached more than 27% of the neighborhood\'s area with a precipitation rate greater than 30 mm/h and 50 mm/h. It is highlighted throughout this analysis that the neighborhoods located near the Tietê and Pinheiros rivers and central region of the city of São Paulo presented a higher probability of flood occurrence with rainfall volumes lower than the average of 30 mm per day and also recorded higher recurrence of flooded spots. Finally, a binary logistic regression method was developed to estimate the probability of occurrence of flooding in the various neighborhoods of the city of São Paulo. This model uses as input parameters rainfall duration, maximum rainfall rate and accumulated rainfall in the last 24 hours. The model presented a mean probability of detection (POD) of 1% and a mean false alarm rate (FAR) of 0,6 for flood events. On the other hand, for events without occurrence of flood a mean POD was 96% and FAR 2,5. Therefore, the model can predict the events without flooding.

A doença meningocócica (DM), uma forma específica de meningite bacteriana, provocada pela Neisseria Meningitidis, bactéria essa que contamina o SNC (Sistema nervoso central), pela corrente sanguínea ou pelas membranas leptomeníngeas, atingindo o cérebro humano. Pode apresentar-se sob três formas diferentes: a meningite meningocócica, a meningococemia ou as duas formas associadas (meningite meningocócica mais meningococemia). O principal reservatório da bactéria é o homem e a transmissão ocorre de indivíduo para indivíduo. No Brasil e, principalmente em Manaus, lugar onde se realizou esta pesquisa, a forma mais comum é a meningococemia, de sorotipo B, umas das mais agressivas que quando não diagnosticada e tratada a tempo, leva o paciente a óbito em menos de vinte e quatro horas ou deixando seqüelas para o resto da vida. As faixas etárias mais acometidas são as crianças de zero a quatro anos, pelo fato de estarem com o sistema imunológico mais enfraquecido, já que tiveram diminuídas as resistências naturais adquiridas da mãe que vão geralmente até os seis meses de idade. A pesquisa comprovou que há também ocorrências em outras faixas etárias, como os adolescentes, os adultos jovens e os idosos. É obrigatória a notificação dos casos confirmados em fichas próprias e específicas do SINAN (Sistema de Informação de Agravos de Notificação) do SVS/MS. A doença meningocócica é de ocorrência mundial, embora seja em países subdesenvolvidos onde ocorram as maiores incidências. A pesquisa procurou investigar o período de maior incidência da DM em Manaus, detectando o período de dezembro a maio. A utilização do programa SatScan permitiu fazer a varredura espacial, temporal e espaço-temporal, mostrando resultados quanto aos bairros de Manaus com ocorrências acima do esperado e as ocorrências em um período curto de tempo. Nas análises meteorológicas, calcularam-se as anomalias de temperatura (média, mínima e máxima) para o município, considerando-se uma série histórica de trinta e sete anos e outra de 2000 a 2009. O mesmo procedimento foi feito para as precipitações e para a umidade relativa do ar. Em seguida, a partir dados de incidência de DM no período de 2000 a 2009, foram verificadas possíveis relações com as médias de anomalias das variáveis climáticas para o período de estudo 2007 a 2009. A pesquisa permitiu verificar que a incidência de DM é mais elevada no primeiro semestre, quando também ocorrem a maior precipitação e umidade relativa do ar e temperaturas do ar mais baixas. No entanto, a análise das anomalias das variáveis mostra que quando se remove o efeito da sazonalidade, as associações entre a incidência de DM e cada uma das variáveis meteorológicas são muito fracas ou até mesmo nulas. Assim, pode-se concluir que a influência climática nesta doença ocorre mais devido às diferenças de hábitos da população nos períodos chuvosos e menos chuvosos. As análises espaciais mostraram que a incidência é maior em bairros onde o padrão sócio-econômico é mais baixo do que a média do município, mas não o mais baixo. / Meningococcal disease (MD), a specific form of bacterial meningitis caused by Neisseria meningitidis, a bacterium that infects the CNS (central nervous system), the bloodstream or the leptomeningeal membranes, reaching the brain. It can present in three different forms: a meningococcal meningitis, meningococcemia or two related forms (meningococcal meningitis and meningococcemia). The main reservoir of the bacteria is the man and its transmission occurs from individual to individual. In Brazil and especially in Manaus, where this work was conducted, the most common is meningococcemia, serotype B, one of the most aggressive, which if not diagnosed and treated in time, can lead the patient to death in less than twenty four hours or leaving serious damage to the rest of his life. The age groups most affected are children aged zero to four years, because they have the most weakened immune system, which had already reduced the natural resistance acquired from the mother who usually go up to six months old. Some researches show that there are instances in other age groups, as adolescents, young adults and the elderly. It is mandatory reporting of confirmed cases, specific forms of SINAN (Information System for Notifiable Diseases) of the SVS/MS. Meningococcal disease is occurring worldwide, although in developing countries where the highest incidences occur. The research sought to investigate the period of highest incidence of MD in Manaus, detecting the period from December to May. The use of the program SatScan allowed scanning the spatial, temporal and spatial-temporal, showing results for the neighborhoods of Manaus with higher than expected occurrences and the occurrences in a short period of time. In meteorological analysis, we calculated the temperature anomalies (average, minimum and maximum) for the municipality, considering a series of thirty-seven years and another from 2000 to 2009. The same procedure was done for the rainfall and the relative humidity. Then, from data on the incidence of MD in the period 2000 to 2009, there were possible links to the mean anomalies of climate variables for the study period - 2007 to 2009. The research showed that the incidence of MD is higher in the first semester; it also occurs at the same period of the heaviest rainfall and relative humidity and air temperatures are lower. However, the analysis of anomalies of the variables shows that when the effect of seasonality is removed, the associations between the incidence of MD and each of the meteorological variables are very weak or even nil. Thus, one can conclude that the climatic influence on this disease occurs more due to differences in habits of the population in rainy and less rainy. The spatial analysis showed that the incidence is higher in neighborhoods where the socio-economic status is lower than the municipal average, but not the lowest.

Este projeto de mestrado apresenta uma caracterização das chuvas estimadas pelo radar meteorológico Doppler de dupla polarização banda S (SPOL) do Departamento de Águas e Energia Elétrica (DAEE) e Fundação Centro Tecnológico de Hidráulica (FCTH) durante eventos com ou sem alagamento para cada bairro da cidade de São Paulo durante o ano de 2015. A caracterização foi determinada a partir da função densidade de probabilidade (PDF) da chuva acumulada e da taxa de precipitação, duração da chuva e fração da área de cada bairro onde ocorreu a chuva. Na média, os eventos de alagamento estavam associados com um volume de chuva maior que 30mm e taxa precipitação máxima maior que 30mm/h. Com relação à duração não foi possível encontrar um padrão médio, pois a chuva teve duração mínima de 20 minutos e máxima de 23 horas. Por outro lado, eventos de alagamento tinham alcançado mais de 27% da área do bairro com taxa de precipitação maior que 30 mm/h e 50 mm/h. Destaca-se ao longo desta análise que os bairros localizados próximos aos rios Tietê e Pinheiros e a região central da cidade de São Paulo apresentaram maior probabilidade de ocorrência de alagamento com volumes de chuva mais baixos do que a média de 30 mm por dia e também registraram maior recorrência de pontos alagados. Por último foi desenvolvido um método de regressão logística binária para calcular a probabilidade de ocorrência de alagamentos nos diversos bairros da cidade São Paulo. Este modelo utiliza como parâmetros de entrada a duração da chuva, a taxa de precipitação máxima e a chuva acumulada nas últimas 24 horas. O modelo apresentou uma probabilidade de detecção (POD) média de 1% e uma taxa de falso alarme média (FAR) de 0,6 para os eventos de alagamento, já para eventos sem alagamento o POD médio foi de 96% e a FAR foi de 2,5%. Portanto o modelo consegue prever os casos sem alagamento. / This dissertation project presents a characterization of the rainfall estimated from a dual-polarization S-band Doppler meteorological radar (SPOL) of the Department of Water and Electric Energy (DAEE) and Foundation Technological Center of Hydraulics (FCTH) during with or without flooding events for each neighborhood of the city of São Paulo over the year 2015. The characterization was determined by the probability density function (PDF) of the accumulated rainfall and the precipitation rate, rainfall duration and rainfall-area fraction in the neighborhoods. In average, flood events were associated with a rainfall volume greater than 30mm and a maximum rainfall rate greater than 30mm/h. Regarding the duration, it was not possible to find an average pattern, because the rain had a minimum duration of 20 minutes and a maximum of 23 hours. On the other hand, flood events had reached more than 27% of the neighborhood\'s area with a precipitation rate greater than 30 mm/h and 50 mm/h. It is highlighted throughout this analysis that the neighborhoods located near the Tietê and Pinheiros rivers and central region of the city of São Paulo presented a higher probability of flood occurrence with rainfall volumes lower than the average of 30 mm per day and also recorded higher recurrence of flooded spots. Finally, a binary logistic regression method was developed to estimate the probability of occurrence of flooding in the various neighborhoods of the city of São Paulo. This model uses as input parameters rainfall duration, maximum rainfall rate and accumulated rainfall in the last 24 hours. The model presented a mean probability of detection (POD) of 1% and a mean false alarm rate (FAR) of 0,6 for flood events. On the other hand, for events without occurrence of flood a mean POD was 96% and FAR 2,5. Therefore, the model can predict the events without flooding.

nÃo hà / Sistemas climatolÃgicos sÃo caracterizados por apresentarem modelagem complexa e de baixa previsibilidade. Em regiÃes de clima semiÃrido, como o Nordeste Brasileiro, informaÃÃes de previsÃo climatolÃgicas sÃo de interesse para um melhor aproveitamento dos recursos hÃdricos. O Estado do CearÃ, localizado no norte do Nordeste Brasileiro, sofre periodicamente com os problemas de estiagem. Atualmente a FundaÃÃo Cearense de Meteorologia e Recursos HÃdricos (FUNCEME), ÃrgÃo pertencente ao governo do Estado do CearÃ, à responsÃvel por gerar pesquisas voltadas a trazer um melhor entendimento fenomenolÃgico do clima do Estado e com isso efetuar uma melhor previsÃo de como serà o perÃodo de chuvas. Hoje a FundaÃÃo utiliza-se de modelagem numÃrica composta por dois modelos regionais, Modelo Regional Espectral 97 (MRE) e o Regional Modeling Atmospheric System (RAMS), aninhados por uma tÃcnica de downscaling ao modelo dinÃmico de grande escala ECHAM4.5, para efetuar suas previsÃes. Os modelos dinÃmicos sÃo caracterizados por apresentarem elevado custo computacional, grande quantidade de dados para sua entrada e alta complexidade na utilizaÃÃo. O desenvolvimento de modelos de previsÃo baseados em Redes Neurais Artificias (RNA) abrange diversas Ãreas do conhecimento e tem apresentado resultados promissores. Modelos baseados em redes neurais sÃo capazes de reproduzir deferentes tipos de sistemas atravÃs da sua capacidade de aprendizado. Nesta dissertaÃÃo foi desenvolvido um modelo de previsÃo de chuvas para as oito regiÃes homogÃneas do Estado do CearÃ, que apresenta um baixo custo computacional e de fÃcil utilizaÃÃo. Para atingir este desenvolvimento foi utilizada uma RNA baseada na tÃcnica Neo-Fuzzy Neuron (NFN). Apesar de ser proposto um novo modelo de previsÃo, nÃo se deseja a substituiÃÃo dos atuais modelos, o novo modelo proposto nesta dissertaÃÃo tem por finalidade enriquecer as informaÃÃes geradas atravÃs de modelos de previsÃo para que assim possa ser gerada uma melhor prediÃÃo de como serà o perÃodo de chuvas no Estado do CearÃ. O modelo proposto foi comparado ao modelo MRE que à atualmente utilizado pela FUNCEME para suas previsÃes. Nesta comparaÃÃo utilizou-se como indicadores de desempenho: tempo de execuÃÃo, valor da raiz quadrada do erro mÃdio quadrÃtico (REMQ) e a correlaÃÃo com os valores observados. Ao final pode-se concluir que o modelo desenvolvido apresentou um melhor desempenho com menor tempo de processamento em relaÃÃo ao modelo dinÃmico MRE para efetuar a previsÃo de chuvas. / Climatological systems are characterized by complex modeling and having low predictability. In semi-arid regions, as the Brazilian Northeast, weather forecast information are necessary for the maintenance of life and a better use of water resources. The State of CearÃ, located on the north of Brazilian Northeast, is a region that suffers with drought for a long time. The FundaÃÃo Cearense de Meteorologia e Recursos HÃdricos (FUNCEME), which belongs to the state government, is responsible for generating research to bring a better phenomenological understanding on the weather of the State of Cearà and thus make a better prediction on how the rainy season will be. Today the foundation makes use of numerical modeling consisting of two regional models, the Regional Spectral Model (RSM) and the Regional Modeling Atmospheric System (RAMS), nested by a downscaling technique to the large scale dynamic model ECHAM4.5, in order to do its predictions. Dynamic models are characterized by their high computational costs, large amounts of information on its input and high complexity usage. The development of forecasting models based on Artificial Neural Networks (ANN) covers various areas of knowledge showing promising results. Neural network based models are capable of reproducing different types of systems through its learning capability. In this thesis it was developed a model for predicting rain for the eight homogeneous regions of the state of Cearà that presents low computational cost and easy use. In order to achieve this development it was used an ANN base on a Neo-Fuzzy Neuron (NFN) technique. Despite being offered a new prediction model, this thesis aims to enrich the information generated by forecast models and do a better prediction on the rainy season of the State of CearÃ. The proposed model was compared to the RSM model that is currently in use by FUNCEME in its predictions. In this comparison, as performance indicators, it was used: the execution time, value of the root mean square error (RMSE) and the correlation with the observed values. At the end, it is concluded that the proposed model had a better performance and was faster than the RSM dynamic model in its predictions.