Literatura científica selecionada sobre o tema "Données océanographiques"
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Artigos de revistas sobre o assunto "Données océanographiques"
Reverdin, Gilles, Nicolas Metzl, Thierry Reynaud, Paul Poli e Yvan Griboval. "Le voilier OceanoScientific Explorer Boogaloo : Une campagne péri-antarctique en 2017". La Météorologie, n.º 109 (2020): 040. http://dx.doi.org/10.37053/lameteorologie-2020-0045.
Texto completo da fonteAuroux, Didier. "Assimilation variationnelle de données océanographiques Approches primale et duale". Annales mathématiques Blaise Pascal 9, n.º 2 (2002): 147–59. http://dx.doi.org/10.5802/ambp.154.
Texto completo da fonteThomas, Pierre. "Constitution d’une base de données océanographiques d’un site Portuaire". Bulletin of the International Association of Engineering Geology 42, n.º 1 (outubro de 1990): 101–5. http://dx.doi.org/10.1007/bf02592625.
Texto completo da fonteBroquet, Paul. "Sicily in his paleogeographic neotethysian frame". Annales de la Société géologique du Nord - (2e Série), Tome XXX, n.º 30 (15 de dezembro de 2023): 91–100. http://dx.doi.org/10.54563/asgn.2292.
Texto completo da fonteLedoux, Hugo, e Christopher Gold. "La modélisation de données océanographiques à l'aide du diagramme de Voronoï tridimensionnel". Revue internationale de géomatique 16, n.º 1 (30 de março de 2006): 51–70. http://dx.doi.org/10.3166/rig.16.51-70.
Texto completo da fonteGalbraith, Peter S., Daniel Bourgault e Mélany Belzile. "Circulation et renouvellement des masses d’eau du fjord du Saguenay". Océanographie 142, n.º 2 (5 de junho de 2018): 36–46. http://dx.doi.org/10.7202/1047147ar.
Texto completo da fonted'Hondt, Jean-Loup, e Jacqueline Carpine-Lancre. "Une page majeure de la zoologie lyonnaise : René Koehler (1860-1931) et la campagne océanographique du Caudan (1895)". Bulletin mensuel de la Société linnéenne de Lyon 85, n.º 3 (2016): 83–92. http://dx.doi.org/10.3406/linly.2016.17881.
Texto completo da fonteAllouis, Tristan, Jean-Stéphane Bailly, Yves Pastol e Catherine Le Roux. "Utilisation conjointe de trains d'ondes lidar vert et infrarouge pour la bathymétrie des eaux de très faibles profondeurs". Revue Française de Photogrammétrie et de Télédétection, n.º 213 (27 de abril de 2017): 33–42. http://dx.doi.org/10.52638/rfpt.2017.362.
Texto completo da fonteSoanes, Louise M., Judy Pierce, Daniel Nellis, Susan Zaluski e Lewis G. Halsey. "Abundance and distribution of Roseate Terns (<em>Sterna dougallii</em>) in the Virgin Islands". Journal of Caribbean Ornithology 33 (17 de abril de 2020): 43–48. http://dx.doi.org/10.55431/jco.2020.33.43-48.
Texto completo da fonteHouekpoheha, Mathias Adjimon, Basile Bruno Kounouhewa, Joël Toyigbé Hounsou, Bernard Noukpo Tokpohozin e Cossi Norbert Awanou. "Analyse statistique des hauteurs de la houle sur la côte du Bénin dans le Golfe de Guinée: Puissance énergétique de la houle non-linéaire dans la zone de shoaling". Journal of Renewable Energies 18, n.º 1 (18 de outubro de 2023). http://dx.doi.org/10.54966/jreen.v18i1.489.
Texto completo da fonteTeses / dissertações sobre o assunto "Données océanographiques"
Bayle, Severine. "Modélisation statistique de données fonctionnelles environnementales : application à l'analyse de profils océanographiques". Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM4016.
Texto completo da fonteTo study biogeochemical processes in the Southern Ocean, tags placed on elephant seals allowed to collect during 2009-2010 oceanographic variables profiles (Chlorophyll a (Chl a), temperature, salinity, light) in an area ranging from southern Kerguelen until the Antarctic continent. This thesis focuses on Chl a data as it is contained in photosynthetic organisms and these ones play an essential role in the oceanic carbon cycle. The infrequently collected vertical Chl a profiles don't provide a mapping of this variable in this area of the ocean. However, we have light profiles sampled more often. The aim of this thesis was then to develop a methodology for reconstructing indirectly Chl a profiles from light profiles, and that takes into account characteristics of this kind of data that naturally occur as functional data. For this, we adressed the profiles decomposition to rebuild or explanations on splines basis, as well as issues related adjustment. A functional linear model was used to predict Chl a profiles from light profiles derivatives. It was shown that the use of such a model provides a good quality of reconstruction to access high frequency variations of Chl a profiles at fine scale. Finally, a functional kriging interpolation predicted the Chl a concentration during night, as light measurements acquired at that time can't be exploited. In the future, the methodology aims to be applied to any type of functional data
Schreiber, Floriane. "Estimation des conditions océanographiques par inversion de données issues d'un radar imageur non calibré". Electronic Thesis or Diss., Toulon, 2020. http://www.theses.fr/2020TOUL0016.
Texto completo da fonteMany empirical models describing sea clutter statistical distribution exist but they do not directly depend on the sea sate. They are not suitable to perform inversion. To model the statistical distribution of the backscattered intensity, we use a two-scale model (TSM) which is linked to the sea state via the mss (mean square slope). This model allows to retrieve the NRCS but does not perfectly describes the sea clutter distribution simultaneously in the two direct polarization channels. This is due to an overestimation of the Bragg polarization ratio (PR)
Moussa, Hadjer. "Traitement automatique de données océanographiques pour l'interpolation de la ∫CO₂ de surface dans l'océan Atlantique tropical, en utilisant les données satellitaires". Thesis, Perpignan, 2016. http://www.theses.fr/2016PERP0025/document.
Texto completo da fonteThis thesis work consists of using satellite data of SST (sea surface temperature), SSS (sea surface salinity), and Chl-a (chlorophyll-a), in order to interpolate the CO2 fugacity (fCO2) in the surface of the tropical Atlantic ocean, for seasons of the period 2002-2013. Three data types were used: in situ (SOCAT V.3 DB (database)); satellite (MODIS-A, Sea-WIFS, and SMOS sensors); and assimilated (SODA V.2.2.4 DB). The first step was the data classification based on SST. The second step was the fCO2 interpolation (for each class of each season), using feedforward NNs (artificial neural networks) with a backpropagation learning method. Obtained results (RMSEs (root mean square error) between 8,8 and 15,7 µatm) confirm the importance of: process each season separately, pass through data classification step, and choose the best NN on the basis of generalization step results. This allowed the development of 138 monthly fCO2 CSV (Comma-separated values) file, with 4 km x 4 km spatial resolution, for the period from July 2002 to December 2013
Neveu, Emilie. "Applications des méthodes multigrilles à l'assimilation de données en géophysique". Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00693486.
Texto completo da fonteNeveu, Émilie. "Application des méthodes multigrilles à l'assimilation variationnelle de données en géophysique". Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00574221.
Texto completo da fonteDéchelle-Marquet, Marie. "Deep learning based physical-statistics modeling of ocean dynamics". Electronic Thesis or Diss., Sorbonne université, 2023. https://theses.hal.science/tel-04166816.
Texto completo da fonteThe modeling of dynamical phenomena in geophysics and climate is based on a deep understanding of the underlying physics, described in the form of PDEs, and on their resolution by numerical models. The ever-increasing number of observations of physical systems, the recent rise of deep learning and the huge computational power required by numerical solvers, which hinders the resolution of existing models, suggest that the future of physical models could be data-driven. But for this prognosis to come true, deep learning must tackle several challenges, such as the interpretability and physical consistency of deep models, still largely under-addressed by the deep learning community.In this thesis, we address both challenges: we study the prediction of sea surface temperature (SST) using hybrid models combining a data-driven and a physical model. Ensuring the physical plausibility of hybrid models necessitates well-posing their learning: otherwise, the high versatility of neural networks may lead the data-driven part to bypass the physical part.Our study is divided into two parts: a theoretical study on hybrid models, and a practical confrontation of our model on simulations of real data. First, we propose a new generic well- posed learning framework based on the optimization of an upper-bound of a prediction error. Second, we study real-like ocean observations of SST and velocity fields from the Gulf Stream current in the North Atlantic (from the NATL60 model). This application highlights the challenges raised by confronting physics aware learning to the complexity of real-world physics. It also raises issues such as model generalization, which we discuss as a possible perspective
Livros sobre o assunto "Données océanographiques"
Ouellet, M. Données océanographiques recueillies dans le fjord du Saguenay pendant l'été 2000 dans le cadre du projet Saguenay post-déluge. Québec: INRS-Eau, terre et environnement, 2006.
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