Auswahl der wissenschaftlichen Literatur zum Thema „Météorologie micro-échelle“
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Dissertationen zum Thema "Météorologie micro-échelle"
Nzeukou, Takougang Armand Cyrille. „Variabilité spatiale à moyenne échelle des conditions de propagation des micro-ondes dans les précipitations“. Toulouse 3, 2002. http://www.theses.fr/2002TOU30011.
Der volle Inhalt der QuelleBiaou, Angelbert. „De la méso-échelle à la micro-échelle : désagrégation spatio-temporelle multifractale des précipitations“. Phd thesis, École Nationale Supérieure des Mines de Paris, 2004. http://pastel.archives-ouvertes.fr/pastel-00001573.
Der volle Inhalt der QuellePeinke, Isabel. „Étude à micro-échelle du test de pénétration du cône dans la neige“. Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30159.
Der volle Inhalt der QuellePrecise knowledge of the snowpack stratigraphy is crucial for different applications such as avalanche forecasting, predicting the water runoff, or estimating the Earth energy budget. The cone penetration test, which consists of recording the force required to make a cone penetrate the material of interest, is widely used to measure in situ snow profiles. The ramsonde developed in the 1930's was continuously improved into highly-resolved digital snow penetrometers. In particular, the SnowMicroPenetrometer measures the snow penetration resistance at constant speed with a vertical resolution of four microns. The force fluctuations measured at such a resolution contain information about the snow microstructure, which is essential to complete the knowledge of the mean hardness of each snow layer. Nevertheless, the link between the measured hardness profile and the snow microstructure is not yet fully understood. Indeed, existing inversion models neglect obvious interactions between the cone tip and the snow, such as the formation of a compaction zone, and have only been evaluated through empirical relations to macroscopic properties. The goal of this thesis is to investigate the interaction between the cone and the snow at a microscopic scale using X-ray tomography in order to better invert the hardness profiles into microstructural properties. In this work, we analyze cone penetration tests of a few centimeters and thus the measured profiles contain a non negligible transient part due to the progressive formation of a compaction zone. In order to explicitly account for this process in the inversion model, we successfully developed a non-homogeneous Poisson shot noise model which considers a depth dependency of the rupture occurrence rate. We used this model to characterize snow sintering with cone penetration tests under controlled cold-lab conditions. According to the model, the vertical heterogeneity of hardness profiles was due to variations of the rupture occurrence rate, while the time evolution of the macroscopic force was controlled by bond strengthening. This partition is consistent with the expected sintering processes and provides an indirect validation of the proposed model. The second part of the thesis consists of cold-lab experiments combining cone penetration tests and X-ray tomography. High resolution three dimensional images of the snow sample before and after the cone test were measured. On these images, a novel tracking algorithm was applied to determine granular displacements induced by the test. We precisely quantified the size of the compaction zone and its relation to the snow characteristics. Furthermore, we showed that the observed vertical displacements challenge the use of standard cavity expansion models as inversion models. Finally, we linked the microstructural properties obtained from tomography, such as the bond size or the number of failed bonds, to properties derived from hardness profiles. We showed that the properties estimated from cone penetration tests are proxies of the snow microstructure, but remain too conceptual to expect a straightforward relation. In the future, these studies should make it possible to derive in an objective way the stratigraphy of the snowpack from a simple and fast field measurement
de, Montera Louis. „Etude de la variabilité micro-échelle des précipitations : application à la propagation des ondes millimétriques en SATCOM“. Versailles-St Quentin en Yvelines, 2008. http://www.theses.fr/2008VERS0021.
Der volle Inhalt der QuelleAttenuation time series at EHF band exhibit characteristics similar to some stock exchange rates, which suggests that prediction models originally developed in the finance field might be appropriate. The analysis leads to a non linear ARIMA/GARCH model. In order to predict the uplink attenuation from the downlink attenuation that operates at a different frequency, a frequency scaling model has been added to the prediction model. In order to better understand the link between attenuation and its physical causes, an approach based on rain fractal properties is then presented. An assessment of the effect of rain-no rain intermittency on the multifractal analysis shows that it provokes a break in the scaling and may lead to biased parameters. The multifractal analysis is then performed event by event, i. E. With uninterrupted rain periods. The results show that rain can be modeled by a FIF (Fractionally Integrated Flux) which is threholded in order to simulate rain-no rain intermittency
Lumet, Eliott. „Évaluation et réduction des incertitudes pour la simulation numérique de la dispersion atmosphérique à micro-échelle“. Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSES003.
Der volle Inhalt der QuelleAir quality is severely degraded during events such as industrial accidents. Harmful gases and particles are released into the atmosphere and carried by the wind. In built environments, these pollutants can lead to local pollution peaks due to buildings blocking the flow, resulting in short-term health and environmental risks. Locating these peaks requires the use of models solving the fundamental equations of fluid dynamics and their interactions with the built environment. Despite their complexity, these models are subject to uncertainties that are partly linked to atmospheric conditions. The aim of this thesis is to build and validate a modeling system able of estimating these uncertainties and identifying possible dispersion scenarios. This is achieved by using tools derived from statistical learning and by informing the model with in-situ observations