Nesse trabalho estudamos um laser de estado sólido sujeito a realimentação optica de frequência modificada de um ponto de vista da teoria de bifurcações. Fizemos uma an alise bastante ampla da dinâmica desse laser no espaço de dois parâmetros de injeção (a dessintonização de frequência e a intensidade da injeção) utilizando métodos de integração direta e continuação numérica. Enquanto o método de integração numérica nos possibilitou analisar as dinâmicas mais complexas, incluindo transições para o caos e hipercaos, o método de continuação numérica nos permitiu estudar curvas de bifurcações estáveis e instáveis. A análise foi realizada estudando os efeitos causados pela mudança dos parâmetros que representam o tempo de vida da inversão populacional e a saturação cruzada, responsável pelo acoplamento dos campos dentro do meio ativo. Mostramos que o parâmetro que descreve o tempo de vida da inversão populacional e responsável pelo surgimento de diversas instabilidades no sistema, como o fenômeno de multiestabilidade, surgimento de orbitas periódicas e quase-peri odicas, assim como rotas para o caos via dobramento de período e torus. Para o parâmetro de acoplamento dos campos, mostramos que ele possibilita a presença de hipercaos em nosso sistema, este podendo se apresentar no que denominamos de hipercaos \fraco" e \forte". Dentro da região de hipercaos \forte", mostramos transições determinísticas de dois regimes, em que num deles o laser opera no modo de Q-switching, enquanto que no outro o laser apresenta pequenas oscilações irregulares. Por m, mostramos a existência de uma estatística de eventos extremos dentro do regime hipercaótico. / In this work we studied a solid state laser subjected to frequency-shifted optical feedback from a bifurcation theory point of view. We performed a very broad analysis of the dynamics of this laser in the space of two injection parameters (frequency detuning and injection intensity) using direct integration and numerical continuation methods. While the numerical integration method allowed us to analyze the more complex dynamics, including chaos and hyperchaos transitions, the numerical continuation method allowed us to study stable and unstable bifurcation curves. The analysis was carried out by studying the e ects caused by the change of the parameters that represent the life time of the population inversion and the cross saturation, responsible for the coupling of the elds within the active medium. We show that the parameter that describes the life time of the population inversion is responsible for the appearance of several instabilities in the system, such as the multistability phenomenon, the appearance of periodic and quasi-periodic orbits, as well as routes to chaos via period doubling and torus . For the eld coupling parameter, we show that it allows the presence of hyperchaos in our system, which may present in what we call "weak"and "strong"hyperchaos. Within the "strong"hyperchaos region, we show deterministic transitions of two regimes, in which one laser operates in the Q-switching mode, while in the other the laser presents small irregular oscillations. Finally, we have shown the existence of a extreme events statistic within the hyperchaotic regime.

Neste estudo foram analisadas possíveis tendências de aumento da precipitação em nove estações pluviométricas na sub-bacia 87, incluindo Porto Alegre, no Estado do Rio Grande do Sul, para 50 anos de dados. Eventos extremos são responsáveis por muitos problemas, principalmente em áreas urbanas, e a frequência e a magnitude destes eventos podem aumentar com as alterações climáticas. No intuito de avaliar o impacto de alterações climáticas, em Porto Alegre, utilizou-se o modelo Long Ashton Research Station - Weather Generator (LARS-WG). O LARS-WG é um gerador estocástico capaz de simular cenários climáticos em escala local. Para cada série histórica das estações analisadas, na sub-bacia 87, foi aplicado o teste estatístico de Mann Kendall para identificar possíveis tendências nos dados anuais e trimestrais. Na estação de Porto Alegre também foi realizada pesquisa para identificar o aumento na frequência de ocorrência de alturas de precipitação em diferentes faixas e análise de tendência noshttp://www.bibliotecadigital.ufrgs.br/da.php?nrb=001053508&loc=2017&l=5219eb420c00bf62 dados sub-diários. A geração de séries sintéticas de precipitação para diferentes cenários teve como base os dados pluviométricos da série de Porto Alegre, que consistiu na utilização do período de 1974 a 2014 na geração da linha de base para calibração do LARS-WG. Após a geração de séries sintéticas de precipitação para um clima atual, foi selecionado o máximo diário anual e este foi desagregado em dados subdiários. Na sequência avaliou-se o impacto das alterações em três cenários do IPCC, A1B, A2 e B1. Em cada um dos arquivos de precipitação diária, geradas por projeção no LARS-WG, foi realizada a desagregação em precipitações sub-diárias Os resultados da aplicação do teste de Mann Kendall indicam tendência no aumento do total anual e no número de dias chuvosos (NDC). O trimestre que mais contribuiu para este aumento corresponde à primavera. Entretanto nas estações de Porto Alegre e Sapucaia do Sul, na região metropolitana de Porto Alegre, São Lourenço no Litoral Sul e Renânia e Serra do Pinto numa região de relevo acidentado próximo ao Litoral Norte também se identificou tendência de aumento no verão e no outono. Em Porto Alegre não foi verificada tendência na precipitação diária máxima anual, permitindo a utilização do LARS-WG que assume que as séries de dados diários observados são estacionárias e gera séries sintéticas com características estatísticas semelhantes à série de dados observados. Uma análise comparativa dos resultados entre as IDFs projetadas com o LARS-WG e a IDF definida por Weschenfelder et al. (2015) indica aumento das precipitações intensas. No primeiro período de projeção no cenário A1B, os desvios ficaram na faixa de 8 a 16% para quatro dos modelos, no cenário A2 os desvios ficaram na faixa de 9 a 19% e no cenário B1 de 7 a 19% em cinco modelos. Para o segundo período de projeção apresentou uma grande variabilidade com desvios entre -3 e 40%. O caminho para reduzir as incertezas é o monitoramento continuado das variáveis meteorológicas, pois a modelagem do clima só pode ser aprimorada com a incorporação de dados reais aos modelos. / This study analyzes possible trends of precipitation increase in nine rainfall stations in subbasin 87, including Porto Alegre, in the State of Rio Grande do Sul, for 50 years of data. Extreme events are responsible for many problems, especially in urban areas, and the frequency and magnitude of these events may increase with climate change. In order to evaluate the impact of climate change in Porto Alegre, the Long Ashton Research Station - Weather Generator (LARS-WG) model was used. The LARS-WG is a stochastic generator capable of simulating local scale climate scenarios. The Mann Kendall's statistical test was applied for each historical series of the analyzed stations in sub-basin 87 in order to identify possible trends in annual and trimestral data. At the Porto Alegre station, research was also conducted to identify the increase in the frequency of occurrence of precipitation heights in different bands and trend analysis in the sub-diary data. The generation of synthetic precipitation series for different scenarios was based on the pluviometric data of the Porto Alegre series, which consisted of the use of the period from 1974 to 2014 in the generation of the baseline for LARS-WG calibration After the generation of synthetic series of precipitation for a current climate, the maximum annual daily was selected and this was disaggregated in sub-diary data. The impact of the changes was then evaluated in three scenarios of the IPCC, A1B, A2 and B1. In each of the daily precipitation files generated by LARS-WG projection, disaggregation in sub-daily precipitation was conducted. The results of the Mann Kendall test indicate a trend in the annual total increase and in the number of rainy days (NDC). The trimester that contributed most to this increase is spring. However, in the Porto Alegre and Sapucaia do Sul stations, in the metropolitan area of Porto Alegre, São Lourenço in the South Coast and Renânia and Serra do Pinto, in an area of rugged relief near the North Coast, there was also a tendency to increase in summer and fall. In Porto Alegre, no trend was observed in the annual maximum daily precipitation, allowing the use of LARSWG, which assumes that the observed daily data series are stationary and generates synthetic series with similar statistical characteristics to the data series observed. A comparative analysis of the results between the IDFs projected with the LARS-WG and the IDF defined by Weschenfelder et al. (2015) indicates an increase in intense precipitation.

Este trabalho apresenta o cálculo da cota de inundação para a Enseada do Itapocorói e para a praia de Morro dos Conventos, litoral do Estado de Santa Catarina. Para atingir os objetivos desse trabalho, a cota de inundação foi calculada através da soma das marés meteorológica e astronômica e do wave run-up. Foi utilizada uma base de 60 anos (horária) de dados de marés e ondas, além de dados de batimetria e topografia das praias. Com o intuito de se obter dados mais realistas do wave run-up, os parâmetros ondulatórios da base de dados foram transferidos de águas profundas para próximo da costa com a utilização do modelo SWAN (Simulating Waves Nearshore). A Enseada do Itapocorói foi dividida em quatro setores (exposto, semiexposto, semiprotegido e protegido) em função dos diferentes graus de exposição à ação de ondas, sendo as equações calibradas para cada setor. A partir dos resultados para Enseada do Itapocorói, notou-se que quanto mais exposta a praia, melhor as equações existentes representavam o wave run-up, assim, para a praia de Morro dos Conventos foi utilizada a equação mais aceita na literatura sem calibração. A cota de inundação instantânea foi calculada para cada hora da série de 60 anos somando-se o wave run-up às marés astronômicas e meteorológicas. Sobre a série de cota de inundação instantânea, para ambas as áreas, foi calculada a cota atingida durante 50% do tempo e por eventos extremos com recorrência de 50, 100 e 200 anos. A estas foi adicionada a previsão de elevação do nível do mar de longo prazo para o mesmo período. A cota atingida durante 50% do tempo na Enseada do Itapocorói foi de 1,35 m no setor exposto, enquanto nos setores semiexposto, semiprotegido e protegido foi de 1 m, 0,9 m e 0,7 m respectivamente. Também, o setor exposto foi o que apresentou as maiores cotas atingidas, sendo 3,45 m, 3,85 m e 4,45 m com tempo de recorrência de 50,100 e 200 anos respectivamente. No setor semiexposto, os valores calculados foram de 2,85 m (50 anos), 3,25 m (100 anos) e 3,9 m (200 anos). No setor semiprotegido, as cotas com tempo de recorrência de 50, 100 e 200 anos foram de 2,65 m, 3,05 m, 3,75 m respectivamente. Já o setor protegido apresentou as menores cotas entre os setores, 2,4 m, 2,85 m e 3,5 m para 50, 100 e 200 anos de tempo de recorrência. Considerando a extensão da área costeira que possui um levantamento de topografia do terreno, 2,4 % da área é inundada durante 50% do tempo, subindo para 26%, 29% e 33% nos casos de recorrência com 50, 100 e 200 anos. A cota atingida na praia de Morro dos Conventos durante 50% do tempo é de 1,1 m, já as cotas calculadas para os tempos de recorrência de 50, 100 e 200 anos foram de 4,2 m, 4,6 m e 5,35 m respectivamente. E, da mesma forma, a área costeira com levantamento topográfico teve 15% de superfície é inundada em 50% do tempo, passando para 85%, 91% e 96% da área total analisada com 50, 100 e 200 anos de tempo de recorrência. A metodologia proposta neste trabalho contribui para o planejamento de zonas costeiras, à medida que indica áreas afetadas por inundação aos eventos extremos. A apresentação de cartas contendo esse tipo de informação em ambiente de SIG facilita a tomada de decisão e o entendimento da área por determinado evento extremo. / The goal of this study is to determine the inundation levels at Ensenada do Itapocorói and Morro dos Conventos beaches, located in Santa Catarina State. This was accomplished through the calculation of the inundation level as the sum of astronomical and meteorological tides and wave run-up. The database for this study included -60 years of hourly waves and tides, bathymetric and topographic data. The instantaneous sea level has been defined for each hour of the data series through the summation of astronomical and meteorological tides. To determine more realistic wave run-up data, the wave parameters have been propagated to shallower water using the SWAN (Simulating WAves Nearshore) model. Published equations were used and results were compared with measured data at a headland bay beach (Enseada do Itapocorói); furthermore, the equations have been calibrated for four sectors of the bay (exposed, semi-exposed, semi-protected and protected). Morro dos Conventos is an exposed beach, comparable to those for which the equations have been developed, so the raw, un-calibrated equations were applied for this site. The inundation level was calculated for each hour of the 60 year-long series by summing the run-up values to obtain the instantaneous level. Over the series of inundation levels, the area inundated during 50% of the time, and the return period for this inundation, have been calculated for 50, 100 and 200 years. The sea-level rise prediction for each calculated period has also been incorporated in order estimate the area likely to be inundated by future events. For Enseada do Itapocorói, the inundation level reached 50% of the time was 1,35 m in the exposed sector, 1 m in the semi-exposed sector, 0,9 m in the semi-protected sector and 0,7 in the protected sector. The exposed sector demonstrated the highest values of inundation, 3,45, 3,85 and 4,5 m for 50, 100 and 200 years of return period respectively. At the semi-exposed sector, the values calculated were 2,85 (50 years), 3,25 (100 years) and 3,9 (200 years) m. At semi-protected sector, inundation levels for the 50-, 100- and 200-year return period intervals were 2,65, 3,05 and 3,75 m, respectively. At the protected sector the lowest levels were reached: 2,4, 2,85 and 3,5 m for 50-, 100- and 200-year return period intervals. 2,4% of the total area for which topographic data is available would be inundated during 50% of the time, increasing to 26%, 29% and 33% for 50-, 100- and 200-year return periods. At Morro dos Conventos, the level of inundation reaches 1,1 m 50% of the time;, for 50,100 and 200 years the level rises to 4,2, 4,6 and 5,36 m respectively. Approximately 15% of the area for which topographic data is available would be area is inundated during 50% of the time, 85% with a 50 year return period, 91% with a 100-year period and 96% with a 200 year period.

abstract: This study performs numerical modeling for the climate of semi-arid regions by running a high-resolution atmospheric model constrained by large-scale climatic boundary conditions, a practice commonly called climate downscaling. These investigations focus especially on precipitation and temperature, quantities that are critical to life in semi-arid regions. Using the Weather Research and Forecast (WRF) model, a non-hydrostatic geophysical fluid dynamical model with a full suite of physical parameterization, a series of numerical sensitivity experiments are conducted to test how the intensity and spatial/temporal distribution of precipitation change with grid resolution, time step size, the resolution of lower boundary topography and surface characteristics. Two regions, Arizona in U.S. and Aral Sea region in Central Asia, are chosen as the test-beds for the numerical experiments: The former for its complex terrain and the latter for the dramatic man-made changes in its lower boundary conditions (the shrinkage of Aral Sea). Sensitivity tests show that the parameterization schemes for rainfall are not resolution-independent, thus a refinement of resolution is no guarantee of a better result. But, simulations (at all resolutions) do capture the inter-annual variability of rainfall over Arizona. Nevertheless, temperature is simulated more accurately with refinement in resolution. Results show that both seasonal mean rainfall and frequency of extreme rainfall events increase with resolution. For Aral Sea, sensitivity tests indicate that while the shrinkage of Aral Sea has a dramatic impact on the precipitation over the confine of (former) Aral Sea itself, its effect on the precipitation over greater Central Asia is not necessarily greater than the inter-annual variability induced by the lateral boundary conditions in the model and large scale warming in the region. The numerical simulations in the study are cross validated with observations to address the realism of the regional climate model. The findings of this sensitivity study are useful for water resource management in semi-arid regions. Such high spatio-temporal resolution gridded-data can be used as an input for hydrological models for regions such as Arizona with complex terrain and sparse observations. Results from simulations of Aral Sea region are expected to contribute to ecosystems management for Central Asia. / Dissertation/Thesis / Ph.D. Aerospace Engineering 2012

A dissertação apresenta um estudo das chuvas extremas relacionadas a quatro desastres naturais ocorridos no Brasil: as inundações do Vale do Itajaí SC, em novembro de 2008, a inundação histórica de São Luís do Paraitinga - SP, em janeiro de 2010, as inundações ocorridas no Vale do Mundaú AL, em junho de 2010 e as inundações e escorregamentos da Região Serrana - RJ, em janeiro de 2011. As chuvas catastróficas foram analisadas através de estatísticas básicas dos dados dos pluviômetros localizados nas regiões. No Vale do Itajaí, as chuvas registradas nos dias 23 e 24 de novembro foram elevadas, atingindo valores acima de 250 mm. Na estação Blumenau, choveu 243,5 mm e 250,9 mm nesses. Na estação localizada em São Luís do Paraitinga, choveu apenas 64,7 mm no dia 1 de janeiro de 2010, quando ocorreu a inundação. Porém, foram observados 205,7 mm em uma das estações localizadas em Cunha. Nesse caso, o elevado volume precipitado na cabeceira da bacia deflagrou as inundações observadas nos dois municípios. No Vale do Mundaú e Paraíba, choveu cerca de 200 mm no dia 5 de junho, em duas das seis estações analisadas. O elevado volume precipitado no dia 5, combinado com as chuvas ocorridas no período de 17 a 19, pode ter causado as inundações observadas no dia 19 nessas bacias. Os dados indicaram que, na Região Serrana do RJ, as inundações e escorregamentos foram causados pela chuva extrema ocorrida nos dias 11 e 12 de janeiro de 2011, que ultrapassou 270 mm no intervalo de 24 h em uma das estações. As chuvas acumuladas nos meses que antecedem os eventos e a alta declividade contribuíram para a saturação do solo e posteriores escorregamentos. Os eventos pluviométricos, classificados através do SPI resultaram, na maioria das estações, chuvas severas ou chuvas extremas A vulnerabilidade das regiões, onde inúmeras habitações estão localizadas em áreas de risco, também foi determinante para que os desastres acontecessem. Outros eventos de magnitude elevada foram observados anteriormente, o que indica que estes eventos são característicos das regiões estudadas. Constatou-se que as regiões analisadas estão sujeitas a chuvas extremas com frequência relativamente alta, muito embora tenha sido observado, em alguns casos, certo grau de raridade nesses eventos. Portanto, nessas áreas devem ser adotadas medidas regionais no sentido de disciplinar o uso e ocupação do solo e reduzir os riscos dos desastres. É fundamental buscar medidas de adaptação da ocupação dessas áreas, considerando o regime hidrológico dessas regiões. / The paper presents a study of extreme rainfall related to four natural disasters occurring in Brazil: the floods in Itajaí Valley, state of Santa Catarina, in November, 2008; the historic flood in São Luís do Paraitinga, state of São Paulo, in January, 2010; the floods in Mundaú Valley, state of Alagoas, in June, 2010; and the floods and landslides in the mountainous region of Rio de Janeiro in January, 2011. The catastrophic rains were analyzed through basic statistical data collected from rain gauges located in those regions. In Itajaí Valley, extremely high rainfalls exceeding 250 mm were recorded on November 23 and 24. In Blumenau, it rained 243.5 mm and 250.9 mm on the same days. At the station located in São Luís do Paraitinga, it rained just 64.7 mm on January 1, 2010, when the flood occurred. However, 205.7 mm were observed in one of the stations located in Cunha. In this case, the high volume of rainfall at the headwater of the basin triggered flooding observed in these two cities. In the valleys of Mundaú and Paraíba, it rained nearly 200 mm on June 5, in two of the six stations analyzed. The high volume of rainfall on June 5, combined with the rains from the 17th to the 19th, may have led to the floods in these basins on June 19. The data indicated that, in the mountainous region of Rio de Janeiro, the flooding and landslides were caused by massive rainfall on January 11 and 12, 2011, which exceeded 270 mm within a period of 24 hours in one of the stations. The rainfall accumulated in the months prior to the events and the high sloping land contributed to soil saturation and subsequent landslides. The rainfall events, sorted through the SPI, resulted in severe or extreme rains in most of the stations. The vulnerability of the regions, which include many homes located in hazardous areas, was also crucial for the disasters to happen. Other major events were previously observed, which indicates that these events are characteristic of the studied regions. It was noted that the analyzed regions are subject to extreme rains with a relatively high frequency, although in some cases these events have demonstrated to be somewhat rare. Therefore, in these areas, region-based measures should be adopted with a view to regulating the use and occupation of the soil and reducing risk of disasters. It is essential to seek adaptation measures of occupation of these areas, considering their hydrological regime.

O objetivo deste trabalho à estabelecer critÃrios para definir valores normais e extremos para a chuva no Estado do Cearà e verificar sua relaÃÃo com a ocorrÃncia de desastres naturais. Metodologias estatÃsticas (tÃcnica dos quantis e metodologia dos mÃximos de precipitaÃÃo) foram utilizadas no intuito de analisar eventos extremos no Estado na sÃrie histÃrica em anÃlise (1980-2013). A metodologia presente no banco de dados Emergency Events Database (EM-DAT) tambÃm serviu de subsÃdio para identificar sinais de ocorrÃncia de desastres e sua relaÃÃo com a ocorrÃncia de eventos extremos (estiagens e inundaÃÃes) em diferentes regiÃes do Estado do CearÃ. Os resultados obtidos apÃs a aplicaÃÃo das tÃcnicas estatÃsticas permitiu pontuar e identificar vÃrios eventos de chuva extrema em diversas Ãreas do Estado, tanto na porÃÃo litorÃnea, como nos municÃpios mais interioranos. A maioria destes eventos foram registrados nos meses iniciais do ano e geralmente estavam associados a atuaÃÃo da Zona de ConvergÃncia Intertropical â ZCIT. Os fenÃmenos de estiagem tambÃm foram identificados a partir das tÃcnicas estatÃsticas que possibilitaram uma anÃlise do comportamento da chuva em diferentes regiÃes do Estado. A partir da identificaÃÃo dos eventos extremos, estes apresentaram alguma evidÃncia de impacto (nÃmero de atingidos, decretos de situaÃÃo de emergÃncia, etc.) que proporcionaram a deflagraÃÃo de um desastre natural. Os municÃpios interioranos, situados em Ãreas de ocorrÃncia da depressÃo sertaneja foram os mais afetados por estiagens. No entanto, as inundaÃÃes, quando ocorrem, nÃo se limitam somente Ãs porÃÃes litorÃneas ou serranas do Estado e acabam repercutindo inclusive em municÃpios localizados no sertÃo cearense. Evitar a ocorrÃncia de eventos extremos no Estado à humanamente impossÃvel. Contudo, a sociedade e o poder pÃblico devem adotar medidas que minimizem consideravelmente os impactos, possibilitando assim uma cultura de convivÃncia com os desastres naturais. / The aim of this study is to establish criteria for the definition of both normal and extreme values for the rain in the state of Cearà and check their relationship with the occurrence of natural disasters. Statistical methodologies (the quantile technique and the maximum precipitation methodology) were used in order to analyze extreme events in the State of Cearà in the time series in question (1980-2013). This methodology that is present in the Emergency Events Database (EM-DAT) also served as a subsidy to identify signs of disaster occurrence and their relationship with the occurrence of extreme events (droughts and floods) in different regions of the State of CearÃ. The results obtained after applications of statistical techniques allowed counting and identifying various heavy rainfall events in many areas of the state, both in the coastal part and in most provincial municipalities. Most of these events were recorded in the early months of the year and were usually associated with activities of Intertropical Convergence Zone - ITCZ. The dry season phenomena were also identified from statistical techniques that made possible an analysis of the rain behavior in different regions of the state. The extreme events, based on their identification, showed some evidence of impact (number of people affected, emergency decrees, etc.) that provided the outbreak of a natural disaster. The provincials municipalities, located in occurrence areas of depressÃo sertaneja were the most affected by drought. However, floods are not only restricted to coastal or mountainous parts of the state and end up impacting also in municipalities located in the SertÃo. It is humanly impossible to prevent the occurrence of extreme events in the state. However, the society and the government must adopt measures that significantly minimize the impacts, thus enabling a coexistence culture with the natural disasters.

Este trabalho apresenta o cálculo da cota de inundação para a Enseada do Itapocorói e para a praia de Morro dos Conventos, litoral do Estado de Santa Catarina. Para atingir os objetivos desse trabalho, a cota de inundação foi calculada através da soma das marés meteorológica e astronômica e do wave run-up. Foi utilizada uma base de 60 anos (horária) de dados de marés e ondas, além de dados de batimetria e topografia das praias. Com o intuito de se obter dados mais realistas do wave run-up, os parâmetros ondulatórios da base de dados foram transferidos de águas profundas para próximo da costa com a utilização do modelo SWAN (Simulating Waves Nearshore). A Enseada do Itapocorói foi dividida em quatro setores (exposto, semiexposto, semiprotegido e protegido) em função dos diferentes graus de exposição à ação de ondas, sendo as equações calibradas para cada setor. A partir dos resultados para Enseada do Itapocorói, notou-se que quanto mais exposta a praia, melhor as equações existentes representavam o wave run-up, assim, para a praia de Morro dos Conventos foi utilizada a equação mais aceita na literatura sem calibração. A cota de inundação instantânea foi calculada para cada hora da série de 60 anos somando-se o wave run-up às marés astronômicas e meteorológicas. Sobre a série de cota de inundação instantânea, para ambas as áreas, foi calculada a cota atingida durante 50% do tempo e por eventos extremos com recorrência de 50, 100 e 200 anos. A estas foi adicionada a previsão de elevação do nível do mar de longo prazo para o mesmo período. A cota atingida durante 50% do tempo na Enseada do Itapocorói foi de 1,35 m no setor exposto, enquanto nos setores semiexposto, semiprotegido e protegido foi de 1 m, 0,9 m e 0,7 m respectivamente. Também, o setor exposto foi o que apresentou as maiores cotas atingidas, sendo 3,45 m, 3,85 m e 4,45 m com tempo de recorrência de 50,100 e 200 anos respectivamente. No setor semiexposto, os valores calculados foram de 2,85 m (50 anos), 3,25 m (100 anos) e 3,9 m (200 anos). No setor semiprotegido, as cotas com tempo de recorrência de 50, 100 e 200 anos foram de 2,65 m, 3,05 m, 3,75 m respectivamente. Já o setor protegido apresentou as menores cotas entre os setores, 2,4 m, 2,85 m e 3,5 m para 50, 100 e 200 anos de tempo de recorrência. Considerando a extensão da área costeira que possui um levantamento de topografia do terreno, 2,4 % da área é inundada durante 50% do tempo, subindo para 26%, 29% e 33% nos casos de recorrência com 50, 100 e 200 anos. A cota atingida na praia de Morro dos Conventos durante 50% do tempo é de 1,1 m, já as cotas calculadas para os tempos de recorrência de 50, 100 e 200 anos foram de 4,2 m, 4,6 m e 5,35 m respectivamente. E, da mesma forma, a área costeira com levantamento topográfico teve 15% de superfície é inundada em 50% do tempo, passando para 85%, 91% e 96% da área total analisada com 50, 100 e 200 anos de tempo de recorrência. A metodologia proposta neste trabalho contribui para o planejamento de zonas costeiras, à medida que indica áreas afetadas por inundação aos eventos extremos. A apresentação de cartas contendo esse tipo de informação em ambiente de SIG facilita a tomada de decisão e o entendimento da área por determinado evento extremo. / The goal of this study is to determine the inundation levels at Ensenada do Itapocorói and Morro dos Conventos beaches, located in Santa Catarina State. This was accomplished through the calculation of the inundation level as the sum of astronomical and meteorological tides and wave run-up. The database for this study included -60 years of hourly waves and tides, bathymetric and topographic data. The instantaneous sea level has been defined for each hour of the data series through the summation of astronomical and meteorological tides. To determine more realistic wave run-up data, the wave parameters have been propagated to shallower water using the SWAN (Simulating WAves Nearshore) model. Published equations were used and results were compared with measured data at a headland bay beach (Enseada do Itapocorói); furthermore, the equations have been calibrated for four sectors of the bay (exposed, semi-exposed, semi-protected and protected). Morro dos Conventos is an exposed beach, comparable to those for which the equations have been developed, so the raw, un-calibrated equations were applied for this site. The inundation level was calculated for each hour of the 60 year-long series by summing the run-up values to obtain the instantaneous level. Over the series of inundation levels, the area inundated during 50% of the time, and the return period for this inundation, have been calculated for 50, 100 and 200 years. The sea-level rise prediction for each calculated period has also been incorporated in order estimate the area likely to be inundated by future events. For Enseada do Itapocorói, the inundation level reached 50% of the time was 1,35 m in the exposed sector, 1 m in the semi-exposed sector, 0,9 m in the semi-protected sector and 0,7 in the protected sector. The exposed sector demonstrated the highest values of inundation, 3,45, 3,85 and 4,5 m for 50, 100 and 200 years of return period respectively. At the semi-exposed sector, the values calculated were 2,85 (50 years), 3,25 (100 years) and 3,9 (200 years) m. At semi-protected sector, inundation levels for the 50-, 100- and 200-year return period intervals were 2,65, 3,05 and 3,75 m, respectively. At the protected sector the lowest levels were reached: 2,4, 2,85 and 3,5 m for 50-, 100- and 200-year return period intervals. 2,4% of the total area for which topographic data is available would be inundated during 50% of the time, increasing to 26%, 29% and 33% for 50-, 100- and 200-year return periods. At Morro dos Conventos, the level of inundation reaches 1,1 m 50% of the time;, for 50,100 and 200 years the level rises to 4,2, 4,6 and 5,36 m respectively. Approximately 15% of the area for which topographic data is available would be area is inundated during 50% of the time, 85% with a 50 year return period, 91% with a 100-year period and 96% with a 200 year period.

Future impacts from climate change can be better understood by placing modern climate trends into perspective through extension of the short instrumental records of climate variability. This is especially true for extreme climatic events, such as extreme precipitation and wildfires, as the period of instrumental records provides only a few examples and these have likely have been influenced by anthropogenic warming. Multi-parameter records showing the past range of climate variability can be obtained from lakes. Lakes are particularly good recorders of climate variability because sediment from the surrounding environment accumulates in lakes, making them sensitive recorders of climate variability and providing high-resolution histories of local environmental conditions in the past. In some cases, such as at Basin Pond, sediment is persevered efficiently enough to produce distinguishable annual laminations (varves) in the sedimentary record. The varved record at Basin Pond was used to construct an accurate, highly-resolved age-to-depth model over the past 300 years. Using a multi-proxy analysis, including organic biomarker analysis of molecular compounds and sedimentological features preserved in the sediment record, a history of environmental and climatic change at Basin Pond was constructed. These analyses were compared with the record of known extreme events (from instrumental measurements and historical documents), including 129 years of high-resolution precipitation and temperature meteorological data, 19 tropical systems over the past 145 years, and two known wildfire events over the past 200 years. Long-term trends in precipitation, including the increase in precipitation seen throughout the last half of the 20th century and the drought of the 1940’s, were captured in the analysis of long-chain n-alkane distributions and through varve thickness measurements obtained through X-Ray Fluorescence analysis. Furthermore, Polycyclic Aromatic Hydrocarbons (PAHs), a class of organic compounds that can be used to trace combustion activity, were found in abundance in the Basin Pond sedimentary record. Peaks in the abundances of two PAHs (retene and chrysene) and the ratio retene/(retene + chrysene) were found to be highly correlated with the known wildfire events occurring in the historical period, giving promise as using these compounds and ratio as a robust proxy for regional wildfire events in the northeastern U.S.

<p>Droughts are complex natural disasters caused due to deficit in water availability over a region. Water availability is strongly linked to precipitation in many parts of the world that rely on monsoonal rains. Recent studies indicate that the choice of precipitation datasets and drought indices could influence drought analysis. Therefore, drought characteristics for the Indian monsoon region were reassessed for the period 1901-2004 using two different datasets and standard precipitation index (SPI), standardized precipitation-evapotranspiration index (SPEI), Gaussian mixture model-based drought index (GMM-DI), and hidden Markov model-based drought index (HMM-DI). Drought trends and variability were analyzed for three epochs: 1901-1935, 1936-1970 and 1971-2004. Irrespective of the dataset and methodology used, the results indicate an increasing trend in drought severity and frequency during the recent decades (1971-2004). Droughts are becoming more regional and are showing a general shift to the agriculturally important coastal south-India, central Maharashtra, and Indo‑Gangetic plains indicating food security challenges and socioeconomic vulnerability in the region.</p><p><br></p><p> </p><p><br></p><p>Drought severities are commonly reported using drought classes obtained by assigning pre-defined thresholds on drought indices. Current drought classification methods ignore modeling uncertainties and provide discrete drought classification. However, the users of drought classification are often interested in knowing inherent uncertainties in classification so that they can make informed decisions. A probabilistic Gamma mixture model (Gamma-MM)-based drought index is proposed as an alternative to deterministic classification by SPI. The Bayesian framework of the proposed model avoids over-specification and overfitting by choosing the optimum number of mixture components required to model the data - a problem that is often encountered in other probabilistic drought indices (e.g., HMM-DI). When sufficient number of components are used in Gamma-MM, it can provide a good approximation to any continuous distribution in the range (0,infinity), thus addressing the problem of choosing an appropriate distribution for SPI analysis. The Gamma-MM propagates model uncertainties to drought classification. The method is tested on rainfall data over India. A comparison of the results with standard SPI shows significant differences, particularly when SPI assumptions on data distribution are violated.</p><p><br></p><p> </p><p><br></p><p>Finding regions with similar drought characteristics is useful for policy-makers and water resources planners in the optimal allocation of resources, developing drought management plans, and taking timely actions to mitigate the negative impacts during droughts. Drought characteristics such as intensity, frequency, and duration, along with land-use and geographic information, were used as input features for clustering algorithms. Three methods, namely, (i) a Bayesian graph cuts algorithm that combines the Gaussian mixture model (GMM) and Markov random fields (MRF), (ii) k-means, and (iii) hierarchical agglomerative clustering algorithm were used to find homogeneous drought regions that are spatially contiguous and possess similar drought characteristics. The number of homogeneous clusters and their shape was found to be sensitive to the choice of the drought index, the time window of drought, period of analysis, dimensionality of input datasets, clustering method, and model parameters of clustering algorithms. Regionalization for different epochs provided useful insight into the space-time evolution of homogeneous drought regions over the study area. Strategies to combine the results from multiple clustering methods were presented. These results can help policy-makers and water resources planners in the optimal allocation of resources, developing drought management plans, and taking timely actions to mitigate the negative impacts during droughts.</p>

Nowcasting – short-term forecasting using current observations – is a key challenge that human activities have to face on a daily basis. We heavily rely on short-term meteorological predictions in domains such as aviation, agriculture, mobility, and energy production. One of the most important and challenging task for meteorology is the nowcasting of extreme events, whose anticipation is highly needed to mitigate risk in terms of social or economic costs and human safety. The goal of this thesis is to contribute with new machine learning methods to improve the spatio-temporal precision of nowcasting of extreme precipitation events. This work relies on recent advances in deep learning for nowcasting, adding methods targeted at improving nowcasting using ensembles and trained on novel original data resources. Indeed, the new curated multi-year radar scan dataset (TAASRAD19) is introduced that contains more than 350.000 labelled precipitation records over 10 years, to provide a baseline benchmark, and foster reproducibility of machine learning modeling. A TrajGRU model is applied to TAASRAD19, and implemented in an operational prototype. The thesis also introduces a novel method for fast analog search based on manifold learning: the tool leverages the entire dataset history in less than 5 seconds and demonstrates the feasibility of predictive ensembles. In the final part of the thesis, the new deep learning architecture ConvSG based on stacked generalization is presented, introducing novel concepts for deep learning in precipitation nowcasting: ConvSG is specifically designed to improve predictions of extreme precipitation regimes over published methods, and shows a 117% skill improvement on extreme rain regimes over a single member. Moreover, ConvSG shows superior or equal skills compared to Lagrangian Extrapolation models for all rain rates, achieving a 49% average improvement in predictive skill over extrapolation on the higher precipitation regimes.