Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / In the present work we studied the vertical profile of the Global Ocean temperature in years of occurrence El Nino-Southern Oscillation events, to better understand the functioning of this phenomenon. For its realization were used three sets of ocean reanalysis: ORAS4 produced by European Centre for Medium-range Weather Forecasts, the GODAS produced by National Centers for Environmental Prediction and SODA produced by Carton and Giese, 2008. The three sets of reanalysis showed the same potential temperature pattern in all layers of depth. The Ocean Temperature Index Equatorial Pacific is very well El Nino-Southern Oscillation events, as detected all El Niños and La Niñas occurred in the period of 52 years. Finally, it is concluded that the proposed new index can be used to determine (characterization) of El Nino-Southern Oscillation events with the same precision as the Oceanic Niño Index, and with superior accuracy for predicting El Nino-Southern Oscillation events as it detects these events several months in advance of the Oceanic Niño Index. Therefore, we can add one more tool to help us predict and better understand the El Nino-Southern Oscillation events. / No presente trabalho foi estudado o perfil vertical da temperatura do Oceano Global, em anos de ocorrência de eventos de El Niño Oscilação Sul, para compreender melhor o funcionamento deste fenômeno. Para a sua realização foram utilizados três conjuntos de reanálises oceânicas: ORAS4 produzida pelo European Centre for Medium-range Weather Forecasts, o GODAS foi desenvolvido pelo National Centers for Environmental Prediction e SODA desenvolvido por Carton e Giese, 2008. Os três conjuntos de reanálises apresentaram o mesmo padrão de temperatura potencial em todas as camadas de profundidade. O Índice de Temperatura Oceânica do Pacífico Equatorial representa muito bem os eventos de El Niño-Oscilação Sul, uma vez que detectou todos os EL Niños e La Niñas ocorridos no período de 52 anos. Por fim, conclui-se que o novo índice proposto pode ser utilizado para determinação (caracterização) de eventos de El Niño-Oscilação Sul com a mesma precisão que o Índice de Niño Oceânico, e com superior precisão para a previsão de eventos de El Niño-Oscilação Sul, uma vez que detecta estes eventos com alguns meses de antecedência em relação ao Índice de Niño Oceânico. Assim podemos acrescentar mais uma ferramenta que nos ajudará a prever e entender melhor os eventos de El Niño-Oscilação Sul.

Afin d'améliorer la qualité des produits et tendre vers des conceptions fiables et robustes, la simulation numérique joue de nos jours un rôle clé dans de nombreux secteurs de l'ingénierie. Malgré l'utilisation de modèles de plus en plus complexes et réalistes, les corrélations entre les mesures expérimentales et les simulations déterministes ne s'avèrent pas toujours évidentes, en particulier, si le phénomène observé est de nature fugace. Afin de prendre en compte les variations possibles de comportement, des techniques de tirages multiples comme les plans d'expériences, les analyses de sensibilité ou les approches non déterministes peuvent être exploitées. Cependant, ces simulations avancées conduisent inévitablement à des temps de calcul prohibitifs qui ne sont pas en adéquation avec des phases de conception de plus en plus courtes.L'objectif de cette thèse est d'explorer de nouvelles stratégies de résolution pour les problèmes mécaniques, où la non-linéarité de contact frottant et des variations sur les paramètres du modèle numérique sont considérés en même temps. Pour y parvenir, nous avons, dans un premier temps, étudié l'intégration de contrôleurs, basés sur la logique floue, pour résoudre un problème de contact frottant. L'idée proposée est de transformer le problème non linéaire en un ensemble de problèmeslinéaires de tailles réduites que l'on peut réanalyser grâce des développements homotopiques et des techniques de projection. Dans un second temps, nous avons étendu la démarche proposée au cas des problèmes de vibrations induites par le frottement comme le crissement. / To improve the quality of products and tend to reliable and robust designs, numerical simulations have nowadays taken a key role in many engineering domains. In spite of more complex and realistic numerical models, the correlation between a deterministic simulation and experimentations are not obvious, especially if the observed phenomenon have a fugitive nature. To take into account possible evolutions of behaviour, multiple samplings techniques such as designs of experiments, sensitivity analyses or non-deterministic approaches are currently performed. Nevertheless, these advanced simulations necessarily generate prohibitive computational times, which are not compatible with more and more shorter design steps.The aim of this work is to explore new numerical ways to solve mechanical problems including both the contact nonlinearity, the friction and several variability on model parameters. To achieve this objective, the integration of Fuzzy Logic Controllers has been first studied in the case of static frictional contact problems. The proposed idea is to decompose the non linear problem in a set of reduced linear problems. These last ones can be reanalyzed thanks to homotopy developments and projection techniques as a function of introduced perturbations. Second, the proposed strategy has been extended to the case of friction induced vibrations problems such as squeal.

The capacity value (CV) of a power generation unit indicates the extent to which it contributes to the generation system adequacy of a region’s bulk power system. Given the capricious nature of the wind resource, determining wind generation’s CV is nontrivial, but can be understood simply as how well its power output temporally correlates with a region’s electricity load during times of system need. Both wind generation and load are governed by weather phenomena that exhibit variability across all timescales, including low frequency weather cycles that span decades. Thus, a data-driven determination of wind’s CV should involve the use of long-term (i.e., multiple decades) coincident load and wind data. In addition to the challenge of finding high-quality, long-term wind data, existing load data more than several years old is of limited utility due to shifting end usage patterns that alter a region’s electricity load profile. Due to a lack of long-term data, current industry practice does not adequately account for the effects of weather variability in CV calculations. To that end, the objective of this thesis is to develop a model to “hindcast” what the historic regional load in New England would have been if governed by the conjoined influence of historic weather and a more current load profile. Modeling focuses exclusively on summer weekdays since this period is typically the most influential on CV. The summer weekday model is developed using multiple linear regression (MLR), and features a separate hour-based model for eight sub-regions within New England. A total of eighty-four candidate weather predictors are made available to the model, including lagged temperature, humidity, and solar insolation variables. A reanalysis weather dataset produced by the National Aeronautics and Space Administration (NASA) – the Modern Era Retrospective-Analysis for Research and Applications (MERRA) dataset – is used since it offers data homogeneity throughout New England over multiple decades, and includes atmospheric fields that may be used for long-term wind resource characterization. Weather regressors are selected using both stepwise regression and a genetic algorithm(GA) based method, and the resulting models and their performance are compared. To avoid a tendency for overfitting, the GA-based method employs triple cross-validation as a fitness function. Results indicate a regional mean absolute percent error (MAPE) of less than 3% over all hours of the summer weekday period, suggesting that the modeling approach developed as part of this research has merit and that further development of the hindcasting model is warranted.

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Although sea-breezes frequently initiate convection, it is oftentimes challenging to forecast the precise location of storm development. This research examines temporal and spatial characteristics of sea-breeze driven convection and environmental conditions that support convective or non-convective sea-breeze days along the Northern Gulf Coast. Base reflectivity products were used to identify the initial time of convection (values greater than 30 dBZs) along the sea-breeze front. It was found that convective sea-breezes initiated earlier in the day compared to non-convective sea-breezes. Mapping convective cells in ArcGIS revealed favored locations of thunderstorm development including the southeastern cusp of Mobile County, Alabama and convex coastlines. Meteorological variables from the North American Regional Reanalysis dataset were compared between convective and non-convective sea-breeze days via a bootstrap analysis to reveal environmental characteristics pertinent to forecasting sea-breeze driven convection. Lapse rates, CAPE, CIN, specific humidity, dew point temperature, relative humidity, and precipitable water values were statistically significant.

High dimensional space-time datasets are available nowadays in various aspects of life such as economy, agriculture, health, environment, etc. Meanwhile, it is challenging to reveal possible connections between climate change and weather extreme events such as hurricanes or tornadoes. In particular, the relationship between tornado occurrence and climate change has remained elusive. Moreover, modeling multivariate spatio-temporal data is computationally expensive. There is great need to computationally feasible models that account for temporal, spatial, and inter-variables dependence. Our research focuses on those areas in two ways. First, we investigate connections between changes in tornado risk and the increase in atmospheric instability over Oklahoma. Second, we propose two multiscale spatio-temporal models, one for multivariate Gaussian data, and the other for matrix-variate Gaussian data. Those frameworks are novel additions to the existing literature on Bayesian multiscale models. In addition, we have proposed parallelizable MCMC algorithms to sample from the posterior distributions of the model parameters with enhanced computations. / Doctor of Philosophy / Over 1000 tornadoes are reported every year in the United States causing massive losses in lives and possessions according to the National Oceanic and Atmospheric Administration. Therefore, it is worthy to investigate possible connections between climate change and tornado occurrence. However, there are massive environmental datasets in three or four dimensions (2 or 3 dimensional space, and time), and the relationship between tornado occurrence and climate change has remained elusive. Moreover, it is computationally expensive to analyze those high dimensional space-time datasets. In part of our research, we have found a significant relationship between occurrence of strong tornadoes over Oklahoma and meteorological variables. Some of those meteorological variables have been affected by ozone depletion and emissions of greenhouse gases. Additionally, we propose two Bayesian frameworks to analyze multivariate space-time datasets with fast and feasible computations. Finally, our analyses indicate different patterns of temperatures at atmospheric altitudes with distinctive rates over the United States.

This thesis explores key aspects for synthesizing data across spatiotemporal scales relevant for water resources management in an Eastern Africa context. Specifically, the potential of large scale global precipitation datasets (GPDs) in data limited regions to overcome spatial and temporal data gaps is considered. The thesis also explores the potential to utilize limited and non-continuous streamflow and stream water chemistry observations to increase hydrological process understanding. The information gained is then used to build a coherent hydro-climatic framework for streamflow modelling. In this thesis, Kilombero Valley Drainage Basin (KVDB) in Tanzania is used as an example of a data limited region targeted for rapid development, intensification and expansion of agriculture. As such, it is representative for many regions across the Eastern Africa. With regards to the data synthesis, two satellite products, three reanalysis products and three interpolated products were evaluated based on their spatial and temporal precipitation patterns. Streamflow data from KVDB and eight subcatchments were then assessed for quality with regards to missing data. Furthermore, recession analysis was used to estimate catchment-scale characteristic drainage timescale. Results from these streamflow analyses, in conjunction with a hydrological tracer-based analysis, were then used for improved understanding of streamflow generation in the region. Finally, a coherent modelling framework using the HBV rainfall-runoff model was implemented and evaluated based on daily streamflow simulation. Despite the challenges of data limited regions and the often large uncertainty in results, this thesis demonstrates that improved process understanding could be obtained from limited streamflow records and a focused hydrochemical sampling when experimental design natural variability were leveraged to gain a large  signal to noise ratio. Combining results across all investigations rendered information useful for the conceptualization and implementation of the hydro-climatic modelling framework relevant in Kilombero Valley. For example, when synthesized into a coherent framework the GPDs could be downscaled and used for daily streamflow simulations at the catchment scale with moderate success. This is promising when considering the need for estimating impacts of potential future land use and climate change as well as agricultural intensification. / Denna avhandling utforskar aspekter på att syntetisera data med olika rumslig och temporal upplösning, vilket är centralt för vattenförvaltning i östra Afrika. Särskilt fokus ligger på att undersöka möjligheten till att använda globala nederbördsdataset för att fylla rumsliga och temporala luckor där data saknas. Avhandlingen undersökeräven möjligheten till att använda flödesdata med icke-kompletta tidsserier samt kemidata från vattendrag för att utöka kunskap-en om hydrologiska processer. Informationen används för att bygga upp ett integrerande ram-verk för hydro-klimatologisk modellering som exempelvis kan användas för att utforska ef-fekten av ett utökat och intensifierat jordburk på vattenresurser. I denna avhandling användes Kilomberodalens avrinningsområde (Tanzania) som exempel på ett databegränsat område där det pågår en intensiv utökning av jordbruksverksamhet. Detta område kan ses som representa-tivt för ett stort antal områden inom östra Afrika.Datasyntesen innefattade två nederbördsprodukter baserade på satellitdata, tre baserade på återanalysprodukter samt två baserade på interpolering av observervationsdata från regnmä-tare. Dessa åtta produkter utvärderades baserat på deras nederbördsmönster i rum och tid. Ut-över detta utvärderades vattenföringsdata från Kilomberodalens avrinningsområde samt åtta delavrinningsområden utifrån mängden saknad data i respektive tidsserie. Vidare användes resultaten från hydrologisk recessionsanalysför att uppskatta den karaktäristiska avrinningsti-den för avrinningsområden. Resultaten från recessionsanalysensamthydrologiskt spårämnes-försök användessedan för att utöka kunskapen om avrinningsbildning och vattenföring i om-rådet samt som stöd i valet av hydrologiskt modelleringsverktyg. Avslutningsvis användes HBV-avrinningsmodellen för att simulera daglig vattenföring. Trots utmaningen i att arbeta iett databegränsat område och de osäkerheter i resultat som detta tenderar att leda till visar resultaten att det var möjligt att använda begränsad vattenfö-ringsdata och vattenkemidata för att utöka den hydrologiska processförståelsen av området. Detta möjliggjordes genom ett experimentellt upplägg som utnyttjade till ett stort signal-till-brusförhållande under rådande förhållanden av naturlig variabilitet. Kombinerade resultat från alla genomförda studier kunde utnyttjas vid konceptualiseringen och implementeringen av ramverket för hydroklimatologisk modellering av Kilomberodalens avrinningsområde. Till exempel kunde de globala nederbördsdataseten användas för lokal modellering av flödesdata med viss framgång efter syntes och implementering i det integrerande ramverket för hydro-klimatologisk modellering. Detta är lovande med tanke på behovet av att undersöka vilken påverkan möjliga framtida förändringar i markanvändning, klimat samt jordbruk har på den lokala och regionala miljön. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Manuscript. Paper 4: Manuscript.</p>

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Die Gletscher Hochasiens beeinflussen durch ihr Schmelzwasser die Wasserverfügbarkeit eines der gefährdetsten ‚globalen Wassertürme‘. Des Weiteren stellen diese Gletscher und die Gletscherseen eine Gefahr durch Überschwemmungen, Lawinen und Erdrutsche dar. Die Sensitivität und Variabilität von Gletschermassenbilanzen in Hochasien werden in dieser Dissertation untersucht. Das Energie- und Massenbilanzmodell „COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY)“ ist dabei das Hauptwerkzeug. Neun verschiedene gegitterte Niederschlagsdatensätze wurden verglichen, um Aussagen über deren Anwendungsmöglichkeiten zu treffen. Es wurden Verfahren für die Vorverarbeitung von Reanalyse-Datensätzen entwickelt, um diese als klimatische Antriebsdaten für COSIPY zu verwenden. Dazu standen Daten von drei automatischen Wetterstationen an verschiedenen Gletschern zur Verfügung. Die Modellevaluation auf der Basis von Beobachtungsdaten bildete den Ausgangspunkt, um die klimatische Massenbilanz von 14 Gletschern in allen großen Gebirgszügen Hochasiens mit einem konsistenten Ansatz zu modellieren. Die räumlich aufgelösten klimatischen Massenbilanzen von 2000 bis 2018 wurden mithilfe geodätischer Massenbilanzen aus Fernerkundungsdaten kalibriert. Generell haben mehr südöstlich gelegene Gletscher höhere Massenumsätze und diese sind sensitiver gegenüber Schwankungen von Temperatur und Niederschlag. Alle Gletschermassenbilanzen sind am sensitivsten gegenüber Temperaturänderungen im Sommer und gegenüber Niederschlagsänderungen im Sommer oder Frühling. Die Resultate unterstreichen die Notwendigkeit zukünftiger Forschung zu räumlich aufgelösten Reaktionen von Gletschern auf Klimaantrieb und daraus resultierender Variabilität von Schmelzwasser unter Verwendung interdisziplinärer Methoden in Hochasien. Aufgrund der Heterogenität der Gletscher in Hochasien ist diese Forschung essentiell für die künftige Anpassung an Klimavariabilität und Klimawandel in der Region. / The meltwater from the glaciers of High Mountain Asia (HMA) impacts water availability of one of the most vulnerable ‘water towers’ of the globe. Furthermore, glaciers and glacial lakes represent a danger through floods, avalanches and landslides. The climatic sensitivity and variability of the glacier mass balances are investigated within this thesis. The COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) is thereby the main tool. Nine gridded precipitation datasets have been compared to evaluate possible applications in HMA. The variability and timing of precipitation between May and September 2017 are consistent between the datasets, whereas great differences in precipitation amount were found. A preprocessing toolbox has been developed to use reanalysis datasets as climate forcing for COSIPY within the thesis. Measurements of three automatic weather stations at different glaciers were available for bias correction. Based on these model validations with observed data, climatic mass balances of 14 glaciers in all major mountain ranges in HMA were simulated using a consistent approach. The distributed climatic mass balances for the period from October 2000 to September 2018 were calibrated with remote-sensing-based geodetic mass balances. In general, glaciers with higher mass turnover are located in the southeast of HMA. They are more sensitive to perturbations of temperature and precipitation. All glaciers are most sensitive to monthly temperature perturbations in summer and to precipitation perturbations in summer, spring or spring and summer. The results emphasise the need for future research on spatially resolved responses of glaciers to climate forcing and resulting variability of meltwater using coherent interdisciplinary methods in HMA. Due to the heterogeneity of glaciers in HMA, such research is essential for adaptation to future climate variability and climate change in the region.