Le géothermomètre Δ47 est basé sur la relation entre l’abondance des liaisons 13C–18O des carbonates et la température de calcification. Ce proxy contourne potentiellement les limites des autres thermomètres (δ18O, Mg/Ca) pour reconstruire les paléo-températures des océans, expliquant son développement exponentiel depuis dix ans. Cette thèse teste pour la première fois le potentiel et les limites de la thermométrie Δ47 sur les coccolithes, des nannofossiles calcaires produits par des organismes calcifiants dans la zone photique. Ces biominéraux calcitiques et ubiquistes constituent une part importante de l’archive sédimentaire. Des cultures in vitro nous ont permis d’établir que trois espèces de coccolithes actuelles enregistrent la même relation Δ47 – T que la calcite inorganique, alors qu'elles présentent de très larges effets vitaux en δ18O (±5‰). Nous concluons que ces espèces de coccolithes d'importance géologique ne présentent pas d’effets vitaux en Δ47. Nous avons ensuite appliqué le Δ47 à l’étude des sédiments enregistrant l’événement d’anoxie océanique du Toarcien (–183 Ma) au cours duquel les reconstructions de températures restent encore ambigües, notamment du fait de la méconnaissance de la composition isotopique en oxygène de l’eau de mer. Sur la base des données Δ47 acquises, nous proposons des températures élevées (de l’ordre de 36°C), mais restant relativement stables sur l'intervalle d'étude. En couplant ces températures aux données de δ18O des carbonates, nous suggérons une variation importante du δ18O de l'eau de mer dans le Bassin de Paris lors de la mise en place des faciès black shales. Enfin, sur des sédiments pélagiques subactuels, l’une des espèces étudiées présente des déséquilibres isotopiques en Δ47 non observés en culture et explicables par d’autres paramètres environnementaux comme l’intensité lumineuse. Cette thèse illustre le potentiel du thermomètre Δ47 des coccolithes en différents contextes, ouvrant un vaste champ d’application de reconstruction des paléo-environnements sur le Méso-Cénozoïque / The Δ47 geothermometer relies on the relationship between the 13C–18O abundance in carbonateand temperature of calcification. This proxy has the potential to overcome limitations of other thermometers(δ18O, Mg/Ca) to reconstruct oceanic paleotemperatures. This thesis evaluates for the first time the potentialand the limitations of the Δ47 thermometry of the coccoliths, the calcareous nannofossils produced byorganisms calcifying in the photic zone. These calcitic and ubiquitous biominerals represent an importantpart of the sedimentary archive. In vitro cultures allow us to establish that three modern coccoliths speciesrecord the same Δ47–T relation than inorganic calcite, although exhibiting substantial δ18O vital effects(±5‰). We conclude that these coccoliths species do not present any Δ47 vital effect. We subsequentlyapplied the Δ47 proxy to sediments from the Toarcian oceanic anoxic events (–183 Ma) during which thetemperatures reconstructions are still elusive, mainly due to the unknown oxygen isotopic composition ofseawater. On the basis of our Δ47 data, we infer relatively high, yet steady temperatures (around 36°C) duringthe examined interval. By combining these Δ47-derived temperatures to carbonate δ18O data, we can suggestdrastic change in the seawater δ18O composition in the Paris Basin at the onset of black shale deposition. Acore top calibration of Δ47 of coccoliths revealed that one of the studied cultured species exhibits Δ47disequilibrium that is accountable by other environmental parameters, such as light irradiance in the naturalenvironment. Thus, this thesis illustrates the potential of the coccolith Δ47 thermometer in different settings,opening a wide range of application to reconstruct the palaeoenvironments over the Meso-Cenozoic Eras

In first part of the study we discuss impact of dynamical core in simulation of tropical rainfall. Over years many new dynamical cores have been developed for atmospheric models to increase efficiency and reduce numerical errors. CAM3.1 gives an opportunity to study the impact of the dynamical core on simulations with its three dynamical cores namely Eulerian spectral(EUL) , Semilagrangian dynamics(SLD) and Finite volume(FV) coupled to a single parametrization package. A past study has compared dynamical cores of CAM3 in terms on tracer transport and has showed advantages using FV in terms of tracer transport. In this study we compare the dynamical cores in climate simulations and at their optimal configuration, which is the intended use of the model. The model is forced with AMIP type SST and rainfall over seasonal, interannual scales is compared. The significant differences in simulation of seasonal mean exist over tropics and over monsoon regions with observations and among dynamical cores. The differences among EUL and SLD, which use spectral transform methods are lesser compared that of with FV clearly indicating role of numerics in differences. There exist major errors in simulation of seasonal cycle in all dynamical cores and errors in simulation of seasonal means over many regions are associated with errors in simulation of seasonal cycle such as over south china sea. Seasonal cycle in FV is weaker compared to SLD and EUL. The dynamical cores exhibit different interannual variability of rainfall over Indian monsoon region, the period of maximum power corresponding to a dynamical core differs substantially with another. From this study there seems no superiority associated with FV dynamical core over all climate scales as seen in tracer transport. The next part of the study deals with impact of diurnal ocean atmosphere coupling in an AGCM,CAM3.1. Due to relatively low magnitude of diurnal cycle of SST and lack of SST observations over diurnal scales current atmospheric models are forced with SSTs of periods grater than a day. CAM 3.1 standalone model is forced with monthly SSTs but the interpolation is linear to every time step between any two months and this linear interpolation implies a linear diurnal and intraseasonal variation of SST which is not true in nature. To test the sensitivity of CAM3.1 to coupling of SST on diurnal scales, we prescribed over tropics(20S20N) a diurnal cycle of SST over daily mean interpolated SST of different magnitudes and phase comparable to observations. This idea of using a diurnal cycle of SST retaining seasonal mean SST in an atmospheric model is novel and provides an interesting frame work to test sensitivity of model to interpolations used in coupling of boundary conditions. Our analysis shows a high impact of using diurnal cycle of SST on simulation of mean rainfall over tropics. The impact in a case where diurnal cycle of SST is fixed and retained to daily mean SST implies that changes associated with a coupled model are to some extent due to change in representation of diurnal cycle of SST. A decrease of excess rainfall over western coast of Bay of Bengal and an increase of rainfall over northern bay of Bengal in such case is similar to the improvement due to coupling atmospheric model to a slab ocean model. This also implies that problems with current AMIP models in simulation of seasonal mean Indian monsoon rainfall could be due to erroneous representation of diurnal cycle of SST in models over this region where the diurnal cycle of SST is high in observations. The high spatial variability of the impact in various cases over tropics implies that a similar spatial variation of diurnal cycle could be important for accurate simulation of rainfall over tropics. Preliminary analysis shows that impact on rainfall was due to changes in moisture convergence. We also hypothesized that diurnal cycle of SST could trigger convection over regions such as northern Bay of Bengal and rainfall convergence feedback sustains it. The impact was also found on simulation of internal interannual variability of rainfall

Interannual variation of Indian summer (June-September: JJAS) monsoon rainfall (ISMR) depends on its relative intensity during early (June-July: JJ; contribution 52%) and late (August-September: AS; contribution 49%) phases. Apart from variations in sea surface temperature (SST), the primary reasons behind the variability during JJ and AS can be very different due to change in climatic conditions on account of post-onset processes. Here, using a high resolution general circulation model with seasonally varying climatological SST, mechanisms those govern the intensity of rainfall during JJ and AS are investigated. There is no significant relation-ship between intensity of precipitation over Indian region in JJ and AS. Moreover, the factors determining early monsoon (JJ) precipitation are different than that for late monsoon (AS). In absence of interannual SST variation, pre-monsoon soil moisture do not play a significant role for the interannual variation of monsoon precipitation over India. A large scale oscillation of the ITCZ is noticed on interannual time scale spanning from around 60◦E to 150◦E that brings spatially coherent flood and drought over this region. Early monsoon precipitation has a larger dependency on spring snow depth over Eurasia and phase of the upper tropospheric Rossby wave in May. However, late monsoon precipitation over India is mainly governed by the intensity and time scale of the intraseasonally varying convective cloud bands. This study suggests that early monsoon (JJ) precipitation over Indian region is more correlated with pre-monsoon signatures of land-atmosphere parameters. However, in later parts after the onset (AS), the monsoon intensity is primarily driven by its internal dynamics and characteristics of intraseasonal oscillation.

Made available in DSpace on 2014-08-20T14:25:45Z (GMT). No. of bitstreams: 1 dissertacao_catia_cristina_braga_rodrigues.pdf: 1202246 bytes, checksum: 0067166e90de2215d4ec858dba3e1ba5 (MD5) Previous issue date: 2012-04-18 / The periods of large variations in rainfall in the Mato Grosso do Sul State (centralwest region, Brazil), in particular the great floods or droughts, generate large economic losses to the state. The summer drought may further compromise the winter period, which often short rains occur. The main objective of this research is to verify bimonthly rainfall variation in the state of Mato Grosso do Sul during the summer (maximum variation) and the winter (minor variations) and their relationships with the bimonthly SST anomalies combined of the South Pacific and South Atlantic oceans. The combined anomalies were represented by Principal Oscillation Patterns (POPs), which represent the predominant patterns of ocean circulation. Monthly precipitation data from January to December (from 1981 to 2009) and monthly data of Sea Surface Temperature (SST) were used. From the rainfall climatology of the marking periods were selected two periods: December/January (rainier) and July/August (dry season). Homogeneous regions were generated by the K-means Method, three for December/January period and two for the July/August period. The regional accumulated rainfall presented no significant trend at 5% probability. The regional accumulated precipitation anomalies of two-month periods showed no significant correlations with SST anomalies in the Central Pacific (Niño 3.4) along the studied period. During the two months December/January, the largest excess precipitation in the region occurred with a predominance of strong El Nino events and droughts in major events La Niña and neutral. In regions 2 and 3 there is not a predominant sign of some events. During the July/ August period, the greatest excesses of precipitation occurred in the region with a predominance of La Niña events, with less relation respect region 2, both regions in a coherent signal (Neutral and La Niña). In cases of severe dry period, both regions have low relation with the events signals. The settings of multiple regressions of bi-monthly precipitation accumulated in homogeneous regions with the scores of the first six patterns of SST showed significant increase in both studied marking periods. The correlation coefficient between the bimonthly observed accumulated precipitation and regional estimates were significant at 1% probability in all regions. This occur especially in the region that represents the northwest quarter of the state in December/January and in the region that represents the major portion of Mato Grosso do Sul State in the July/August period. / Os períodos de grandes variações da precipitação no Mato Grosso do Sul, em especial as grandes cheias ou grandes estiagens, trazem grandes prejuízos financeiros ao Estado. As estiagens de verão podem comprometer ainda mais o período de inverno, no qual já é normal ocorrer poucas chuvas. Esta pesquisa tem por proposta principal verificar as variações bimensais da precipitação no estado de Mato Grosso do Sul nos períodos de verão (variações máximas) e inverno (variações mínimas) e suas relações com as anomalias bimensais de TSM combinadas dos oceanos Pacífico Sul e Atlântico Sul. As anomalias combinadas foram representadas pelos Padrões de Oscilação Principal (POP), os quais representam os padrões predominantes de circulação oceânica. Foram usados dados de precipitação mensal de janeiro a dezembro, período de 1981 a 2009 e dados médios mensais de Temperatura na Superfície do Mar (TSM). A partir da climatologia da precipitação foi selecionado os bimestres dezembro/janeiro (mais chuvoso) e julho/agosto (menos chuvoso) e geradas pelo método K-means regiões homogêneas, sendo três para o bimestre dezembro/janeiro e duas para o bimestre julho/agosto. As precipitações acumuladas regionais não apresentaram tendência temporal significativas a 5% de probabilidade. As anomalias de precipitação acumulada regionais dos bimestres não apresentaram correlações significativas com as anomalias de TSM na região do Pacífico Central (Niño 3.4) ao longo do período estudado, mas durante o bimestre dezembro/janeiro, os maiores excessos de precipitação da região 1 ocorreram com forte predomínio de eventos El Niño fortes e a maiores estiagens em Eventos La Niña e Neutros. Nas regiões 2 e 3 não existem um sinal predominante de alguns dos eventos. Durante o bimestre julho/agosto, os maiores excessos de precipitação ocorreram na região 1 com predomínio de eventos La Niña, com menor relação na região 2, mas ambas regiões com coerência do sinal (Neutro e La Niña). Nos casos de fortes estiagens, ambas as regiões apresentam baixa relação com os sinais dos eventos. Os ajustes das regressões múltiplas das precipitações acumuladas bimestrais nas regiões homogêneas com os escores dos seis primeiros padrões de TSM apresentaram aumento de significância em ambos bimestres estudados. O coeficiente de correlação entre as precipitações acumuladas regionais bimestrais observadas e estimadas foram significativas a 1% de probabilidade em todas as regiões, especialmente na região que representa o noroeste do Estado no bimestre dezembro/janeiro e a região que representa a maior parte do estado do Mato Grosso do Sul no bimestre julho/agosto.

La caractérisation des dynamiques de sous-mésoéchelle (<10km) à la surface de l'océan et leurs impacts sur les processus océaniques globaux sont des enjeux scientifiques majeurs. L'imagerie satellitaire est un outil essentiel dans ce contexte, qui présente toutefois des limitations liées aux instruments de télédétection. Dans le cas des images de température de surface des océans (SST), les mesures satellitaires des structures océaniques sont limitées par la résolution grossière des capteurs micro-ondes (~50km) d'une part, et par la sensibilité aux conditions climatiques (e.g., couverture nuageuse) des instruments de mesure infrarouge haute-résolution. Dans cette thèse, nous nous intéressons à l'analyse, la modélisation et la reconstruction des structures turbulentes haute-résolution capturées par imagerie satellitaire de SST, et proposons quatre contributions principales. Dans un premier temps, nous développons une méthode de filtrage conjointe Fourier-ondelettes pour le prétraitement d'artefacts géométriques dans les observations satellitaires infrarouges. Dans un deuxième temps, nous nous focalisons sur la caractérisation de la variabilité géométrique de champs de température de surface (SST) en utilisant des modèles de marches aléatoires appliqués aux lignes de niveaux. En particulier, nous considérons des processus aléatoires de type schramm Loewner (SLE). Nous nous intéressons ensuite à la modélisation stochastique des variabilités inter-échelles de champs de SST. Des modèles stochastiques de textures multivariées sont introduits. Ces modèles permettent de reproduire des propriétés statistiques et spectrales similaires à celles des données ayant servi à les calibrer. Nous développons ensuite des méthodes de super-résolution de champs de SST conditionnellement à une observation basse-résolution. Nous utilisons des modèles multivariés de textures formulés dans le domaine des ondelettes, en exploitant l'apprentissage d'à priori statistiques (i.e., covariances et covariances croisées) des différentes sous-bandes à partir d'images haute-résolution. Des contraintes supplémentaires imposées sur la phase de Fourier des différentes sous-bandes simulées permettent la reconstruction de structures géométriques marquées tels que les fronts. Nous démontrons la pertinence de la méthode proposée sur des images satellitaires de SST obtenues à partir du capteur Modis/Aqua. / The characterization of sub-mesoscale dynamics (<10 km) in the ocean surface and their impact on global ocean processes are major scientific issues. Satellite imagery is an essential tool within this framework. However, the use of remote sensing techniques still raise challenging. For instance, regarding Sea Surface Temperature (SST) images, satellite measurements of oceanic structures are limited by the coarse resolution of microwave sensors (~50km) on one hand, and by sensitivity to climatic conditions (eg., Cloud cover) of high-resolution infrared instruments on the other hand. In this thesis, we are interested in analysis, modeling and reconstruction of high-resolution turbulent structures captured by satellite SST imagery. In this context, we propose four main contributions. First, we develop a joint Fourier-Wavelet filtering method for the pre-processing of geometrical noises in satellite-based infrared observations, namely the striping noises. Secondly, we focus on the characterization of the geometric variability of sea surface temperature (SST) fields using random walk models applied to SST isolines. In particular, we consider the class of Schramm Loewner evolution curves (SLE). We then focus on the stochastic modeling of the cross-scale variabilities of SST fields. Stochastic multivariate texture-based models are introduced. These models are designed to reproduce several statistics and spectral properties that are observed on the data that are used to calibrate the model. We then develop our framework for stochastic super-resolution of SST fields conditionally to low-resolution observations. We use multivariate texture-based models formulated in the wavelet domain. These models exploit the formulation of statistical and spectral priors (i.e., covariances and cross-covariances) on wavelet subbands. These priors are directly learned from exemplar high-resolution images. Additional constraints imposed on the Fourier-phase of the different simulated subbands allow the reconstruction of coherent geometric structures such as the edge information. Our method is tested and validated using infrared high-resolution satellite SST images provided by Aqua Modis sensor.

Reconstruire des champs géophysiques à partir d'observations bruitées et partielles est un problème classique bien étudié dans la littérature. L'assimilation de données est une méthode populaire pour aborder ce problème, et se fait par l'utilisation de techniques classiques, comme le filtrage de Kalman d’ensemble ou des filtres particulaires qui procèdent à une évaluation online du modèle physique afin de fournir une prévision de l'état. La performance de l'assimilation de données dépend alors fortement de du modèle physique. En revanche, la quantité de données d'observation et de simulation a augmenté rapidement au cours des dernières années. Cette thèse traite l'assimilation de données d'une manière data-driven et ce, sans avoir accès aux équations explicites du modèle. Nous avons développé et évalué l'assimilation des données par analogues (AnDA), qui combine la méthode des analogues et des méthodes de filtrage stochastiques (filtres Kalman, filtres à particules, chaînes de Markov cachées). Des applications aux modèles chaotiques simplifiés et à des études de cas de télédétection réelle (température de surface de lamer, anomalies du niveau de la mer), nous démontrons la pertinence d'AnDA pour l'interpolation de données manquantes des systèmes dynamiques non linéaires et à haute dimension à partir d'observations irrégulières et bruyantes.Motivé par l'essor du machine learning récemment, la dernière partie de cette thèse est consacrée à l'élaboration de modèles deep learning pour la détection et de tourbillons océaniques à partir de données de sources multiples et/ou multi temporelles (ex: SST-SSH), l'objectif général étant de surpasser les approches dites expertes. / Reconstructing geophysical fields from noisy and partial remote sensing observations is a classical problem well studied in the literature. Data assimilation is one class of popular methods to address this issue, and is done through the use of classical stochastic filtering techniques, such as ensemble Kalman or particle filters and smoothers. They proceed by an online evaluation of the physical modelin order to provide a forecast for the state. Therefore, the performanceof data assimilation heavily relies on the definition of the physical model. In contrast, the amount of observation and simulation data has grown very quickly in the last decades. This thesis focuses on performing data assimilation in a data-driven way and this without having access to explicit model equations. The main contribution of this thesis lies in developing and evaluating the Analog Data Assimilation(AnDA), which combines analog methods (nearest neighbors search) and stochastic filtering methods (Kalman filters, particle filters, Hidden Markov Models). Through applications to both simplified chaotic models and real ocean remote sensing case-studies (sea surface temperature, along-track sea level anomalies), we demonstrate the relevance of AnDA for missing data interpolation of nonlinear and high dimensional dynamical systems from irregularly-sampled and noisy observations. Driven by the rise of machine learning in the recent years, the last part of this thesis is dedicated to the development of deep learning models for the detection and tracking of ocean eddies from multi-source and/or multi-temporal data (e.g., SST-SSH), the general objective being to outperform expert-based approaches.

Porites lobata is an important reef building coral in the tropical eastern Pacific and the dominant Porites species in the Galápagos archipelago. Following the 1982-83 El Niño-Southern Oscillation the Galápagos Islands experienced 97-99% coral mortality, leaving many areas throughout the archipelago denuded of corals. Because very few long term assessments have been conducted on the growth and resilience of P. lobata to natural disturbances in the Galápagos Islands (Glynn et al., 2001; Glynn et al., 2009), benthic surveys were performed on a uniquely dense aggregation of P. lobata colonies at Devil’s Crown, Floreana Island between 1993 and 2011. Annual changes in live tissue area were calculated for the majority of the population (n=17) using Coral Point Count with Excel extensions (CPCe 3.6) software to determine growth and recovery trends for this aggregation. Total live tissue area (n=10) increased from 1993 to 2011, however due to high interannual variability this increase was not significant. Within this overall pattern, a general trend of decline was observed in live tissue cover from 1993 to 2000, with increases in tissue area observed from 2000 to 2011. Severe bleaching (85-100%) was observed during the 1998 survey, followed by 42% tissue loss (n=10), coinciding with sea water warming associated with the very strong 1997-1998 El Niño-Southern Oscillation event. Subsequent regrowth of coral tissue was observed during the 2001 survey with continued recovery through 2009. Multiple comparison testing revealed a significant difference between the impacted state (1999) and the recovered state (2009), (p = 0.002, Dunn’s method, n=17), suggesting this aggregation required a period of ten years to recover from this disturbance. During this recovery period the moderately strong 2007-2008 La Niña, with accompanying stressful low temperatures, occurred but did not interrupt tissue regrowth. Warmer than average sea surface temperatures occurred during the warm months from 2008 to 2011, during which time a cool period occurred from 2010 to 2011. While the magnitude and duration of temperature anomalies during warming were not as great as those observed during the 1997-98 ENSO, low temperatures observed during the cool period were similar to those experienced throughout the 2007-08 La Niña. During this time total live tissue cover was reduced by 19% (n=10); however it is unknown whether this was due to warming or the following cool period. Based on results from the 1997-98 El Niño and 2007-08 La Niña, this reduction in live tissue was most likely caused by elevated sea surface temperatures. Data on the growth and resilience of P. lobata populations at Devil’s Crown will be used for conservation and management of this important resource.

Reproductive success in loggerhead (Caretta caretta) sea turtles is strongly dependent on the effective placement and internal conditions of their nests. Embryos rely on optimal incubation conditions for proper development and growth, which determines how many hatchlings will emerge from the nest. The internal microclimate of each nest is delicately balanced and can be easily influenced by external environmental conditions. This study was designed to examine several environmental variables and determine their effects on sea turtle nesting numbers, hatching success, and incubation conditions in Broward County Florida. Over a span of 25 years (1991-2015), the Broward County Sea Turtle Conservation Program has collected data on each sea turtle nest laid in Broward County. This data was analyzed and plotted to visualize nesting and hatching trends, and regressions were fitted to make comparisons to historic air temperature, sea surface temperature, precipitation, and lunar illumination data. These regressions were tested for significance, and each environmental variable was found to have varying levels of impact on sea turtle nesting and hatching behavior. Of the environmental variables considered in this study, analyses suggest that sea turtles are most responsive to temperature, with sea surface temperature serving as the best proxy for predicting nesting behaviors. Air temperature over the incubation period was found to be the best indicator for hatch success percentage. Air temperature, sea surface temperature, and precipitation averages all significantly affected the length of the incubation period. The regression models created in this study could be used to examine the interactions between climatic variables, and to indicate what impacts can be expected by these various environmental factors. This information could be used to estimate the future effects of climate change on sea turtle reproduction, and to predict general reproductive success and future population trends.

No description available.

In this thesis we examine intra-seasonal oscillations (ISO) in the aqua-planet setup of the Community Atmospheric Model (CAM) version 5.1, mainly based on July and January climatological sea surface temperature (SST). We investigate mainly two questions -what should be the SST distribution for the existence of (a) northward moving ISO in summer, and (b) eastward moving MJO-like modes in winter. In the first part of the thesis we discuss the northward propagation. A series of experiments were performed with zonally symmetric and asymmetric SST distributions. The basic lower boundary condition is specified from zonally averaged observed July and January SST. The zonally symmetric July SST experiment produced an inter tropical convergence zone (ITCZ) on both sides of the equator. Poleward movement is not clear, and it is confined to the region between the double ITCZ. In July, the Bay of Bengal (BOB) and West Pacific SST is high compared to the rest of the northern tropics. When we impose a zonally asymmetric SST structure with warm SST spanning about 80 of longitude, the model shows a monsoon-like circulation, and some northward propagating convective events. Analysis of these events shows that two adjacent cells with cyclonic and anticyclonic vorticity are created over the warm SST anomaly and to the west. The propagation occurs due to the convective region drawn north in the convergence zone between these vortices. Zonally propagating Madden-Julian oscillations (MJO) are discussed in the second part of the thesis. All the experiments in this part are based on the zonally symmetric SST. The zonally symmetric January SST configuration gives an MJO-like mode, with zonal wave number 1 and a period of 40-90 days. The SST structure has a nearly meridionally symmetric structure, with local SST maxima on either side of the equator, and a small dip in the equatorial region. If we replace this dip with an SST maximum, the time-scale of MJO becomes significantly smaller (20-40 days). The implication is that an SST maximum in the equatorial region reduces the strength of MJO, and a flat SST profile in the equatorial region is required for more energetic of MJO. This result was tested and found to be valid in a series of further experiments.