Les données de télédétection dans l'infrarouge thermique (IRT) sont une source indispensable d'information pour estimer les flux de surface et suivre le fonctionnement des agro-écosystèmes. Cependant, les mesures de température de surface sont sujettes à des effets directionnels très importants (présence de 'hot spot') pouvant entraîner une erreur allant jusqu'à une dizaine de degrés Celsius. Ils doivent être pris en compte en vue des applications opérationnelles. Le travail proposé ici vise à modéliser l'anisotropie directionnelle des couverts végétaux pour mettre au point des méthodes opérationnelles de correction des mesures satellitaires de température de surface. Il est largement motivé par les projets du CNES visant à élaborer une mission spatiale nouvelle combinant une haute résolution spatiale et des capacités fortes de revisite dans l'IRT. Deux étapes de travail ont été menées. La première repose sur l'utilisation du modèle déterministe de transfert Sol-Végétation-Atmosphère SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), capable de simuler les radiances directionnelles dans l'optique et l'IRT. Dans ce manuscrit, il est validé par rapport à des mesures de terrain et sa capacité à simuler correctement les effets d'anisotropie démontrée. Il est ensuite utilisé pour étudier de façon systématique la sensibilité de l'anisotropie directionnelle à la structure de la canopée, à son état hydrique, au forçage météorologique et aux configurations angulaires solaire et de visée. Les conséquences en terme d'impact combiné des caractéristiques orbitales des satellites, de la position géographique des sites observés et de la date d'acquisition sur l'anisotropie sont discutées. La seconde étape vise à proposer un modèle paramétrique simplifié (dit RL). SCOPE est ici utilisé en tant que générateur de données. Le modèle RL se révèle robuste et capable de restituer avec succès les signatures directionnelles sur le plan géométrique (position du hot spot) comme pour l'amplitude des effets directionnels. Une comparaison avec le seul autre modèle paramétrique utilisé jusqu'alors en télédétection IRT (le modèle de Vinnikov) confirme les qualités du modèle RL, ce qui en fait un candidat potentiel pour les chaines de traitement des futures données satellitaires. / Remotely-sensed data in thermal infrared (TIR) are an essential source of information to estimate surface fluxes and to monitor the functioning of agro-ecosystems. However, surface temperature measurements are prone to directional effects ('hot spot' phenomenon)which may result in an error up to 10°C. They have to be taken into account in the framework of operational applications. The work proposed here aims at modelling the directional anisotropy of continuous vegetated canopies in order to develop operational methods for correcting land surface temperature measurements carried out by TIR satellites. This work is mainly motivated by the CNES projects aiming at developing a new TIR spatial mission combining both high spatial resolution and high revisit time capacities. Two steps were carried out. The first is based on the use of the deterministic SVAT model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), able to simulate directional radiances at top of canopy in both optical and TIR domains. In this thesis, it is validated against experimental measurements and its ability to successfully simulate TIR directional anisotropy demonstrated. Then it is used to study the sensitivity of anisotropy to canopy structure, water status of soil and vegetation, meteorological forcing and solar and observer angular configurations. The consequences of the combined features of satellites orbits, geographical position of the scanned sites and acquisition date on anisotropy are discussed. In the second part, we propose a simplified parametric model (called 'RL'). SCOPE is used as a data generator. The RL model is deemed suitable and able to correctly reproduce directional signatures both in terms of geometry (hot spot position) and amplitude of these effects. A comparison with the only one parametric model previously used in TIR remote sensing (Vinnikov's approach) confirms the good capacities of the RL model. The RL model is thus a potential candidate to the future satellite processing chains.

Satellite data have shown that east-west oriented cloud bands, known as Intertropical convergence zone (ITCZ), propagate eastwards along the equator throughout the year and northwards during boreal summer on intraseasonal time scales. The northward propagations over Bay of Bengal have important connection with onset of south Asian monsoon and active-break cycles of the Indian monsoon. Some studies on mean structure of ITCZ have concluded that preferred location of ITCZ is governed by meridional variation of sea surface temperature (SST) while other studies have stressed the importance of heating in the free atmosphere. Studies on the migration of ITCZ have shown that northward migration of maximum convergence zone is due to generation of positive barotropic vorticity north of the convection in the boundary layer due to internal dynamics of the atmosphere. In the present study mean and transient structure of northward migration of ITCZ over Bay of Bengal is simulated with the help of a general circulation model (GCM). The mean ITCZ is found not to occur at SST maximum or SST gradient maxima. A new simple model for the mean state of ITCZ based on moisture budget, linear friction and hydrostatic assumption is proposed. It highlights the relative importance of SST and atmospheric effects in generation of maximum convergence. The large cancellation between the effect of SST on boundary layer and thermodynamic effects in free troposphere is shown to control convergence. The model also shows that latitude and time independent linear friction parameterization in a simple model is able to predict monthly mean location of ITCZ in a GCM. The results give a quantitative understanding about the relative role of surface effects and atmospheric effects in determining location of the mean ITCZ. A simple linear model for understanding the mechanism of instability that governs the northward migration of ITCZ is proposed. Vertical shear in mean winds couples the barotrpic and baroclinic modes in free troposphere in this model. The model is able to predict the correct scale with standard values of friction and diffusion parameters. The mechanism of instability is found to be due to internal dynamics of troposphere. It is shown that direction of propagation is decided by vertical shear in zonal as well as meridional mean winds. This is contrary to the previous studies which conclude that either vertical shear in zonal winds or vertical shear in meridional winds control the direction of propagation.

The aim of master´s thesis is to get acquainted with the design and materials used in selected automotive light source – tungsten halogen lamp. Further, the thesis focused on the theory and appropriate selection of the thermal measurement method on a real sample. Subsequently, a model of the light source and its simulation in the ANSYS – Maxwell 3D and Mechanical programs are created. Finally, the results of the thermal simulation and the non-contact measurement of the tungsten halogen lamp are evaluated

This diploma thesis deals with the issue of regrigerant cooling. The theoretical part describes laws of termodynamics, basic thermodynamic processes of ideal gas and cooling cycles. The dependence of the cooler bypass factor of air handling unit on its capacity is the main issue of the experimental part. The aim of practical part is to design the air-conditioning device using knowledge of experimental part and compare it with the proposal of air-conditiong device in my bachelor thesis.

Glass has sophisticated front properties and are used as facades in high buildings. During cold periods, these glass facades could cause thermal discomfort, due to cold downdraught. Cold downdraught can be countered by placing heaters under glass surfaces. Nowadays technology offers highly insulating windows, which is why there is an interest to investigate the indoor climate with only underfloor heating. The research in this area is limited, and few empirical methods are available. Theoretical analysis has begun but it still brand new. The aim of this investigation was to present the thermal indoor climate influenced by various parameters, such as outdoor temperature, U-value and the glass height. The results were also meant to be used as reference tools in future projects. A reference building was modeled in simulation software called CFD Star-CCM+. The assignment was initiated by Incoord, a leading consulting company in energy, indoor climate and installation planning. The results showed that the air velocity increases with decreasing outdoor temperature and decreases with increasing thermal insulation (lower U-value). At the edges of the glass the air velocity becomes twice as large compared to the velocity of the air in the middle of the atrium. The air velocity (maximum and average) at 0.1 m above the floor is always higher than at 2.0 m. The lowest air velocities start from about 0.25 m/s at 0 ℃ and reaches to 0.60 m/s at -20 ℃. That means these air velocities are too high for what is accepted as a good indoor climate, where the maximum allowable air velocity is 0.15 m/s. The outdoor temperatures and the glass facade’s U-value also have an effect on the surface temperature of the glass facade. This decreases the surface temperature with decreased outdoor temperature, and the surface temperature increases at lower U-value. The height of the glass facades proved to affect both the air velocity in the occupied zone and in the glass surface temperature. The air velocity increases with the glass’ height. The increase is higher at 0.1 m than at 2.0 m above the floor. The result shows also that the average air velocity is lower than 0,15 m/s at window height lower than 5 m. But, at the same height the maximum air velocity is higher than 0.3 m/s. The surface temperature of the glass facades increases with the glass’ height. This is because the indoor heat transfer coefficient increases with height. The outdoor heat transfer coefficient is a function of the wind speed and was assumed to be constant. The underfloor heating, which is represented in the simulations with a floor surface temperature of 27 ℃, is not enough to maintain a good indoor climate in any of simulations. The results of this thesis showed a strong relation between indoor climate, outdoor temperature, U-value and the glass height. This study also showed that the floor heating is not enough to counteract the cold draft during extreme cold periods, in high glass buildings. The presented results can be used as a reference tool for the assessment of air velocities and surface temperatures, in similar high buildings.

A commonly used tool in data analysis is to compute a sample mean. Assuming a uni-modal distribution, its mean provides valuable information about which value is typically found in an observation. Also, it is one of the simplest and therefore very robust statistics to compute and suffers much less from sampling effects of tails of the distribution than estimates of higher moments. In the context of a time series, the sample mean is a time average. Due to correla- tions among successive data points, the information stored in a time series might be much less than the information stored in a sample of independently drawn data points of equal size, since correlation always implies redundancy. Hence, the issue of how close the sample estimate of a time average is to the true mean value of the process depends on correlations in data. In this thesis, we will study the proba- bility that a single time average deviates by more than some threshold value from the true process mean. This will be called the Large Deviation Probability (LDP), and it will be a function of the time interval over which the average is taken: The longer the time interval, the smaller will this probability be. However, it is the precise functional form of this decay which will be in the focus of this thesis. The LDP is proven to decay exponentially for identically independently distributed data. On the other hand we will see in this thesis that this result does not apply to long-range correlated data. The LDP is found to decay slower than exponential for such data. It will be shown that for intermittent series this exponential decay breaks down severely and the LDP is a power law. These findings are outlined in the methodological explanations in chapter 3, after an overview of the theoretical background in chapter 2. In chapter 4, the theoretical and numerical results for the studied models in chapter 3 are compared to two types of empirical data sets which are both known to be long- range correlated in the literature. The earth surface temperature of two stations of two climatic zones are modelled and the error bars for the finite time averages are estimated. Knowing that the data is long-range correlated by estimating the scaling exponent of the so called fluctuation function, the LDP estimation leads to noticeably enlarged error bars of time averages, based on the results in chapter 3. The same analysis is applied on heart inter-beat data in chapter 5. The contra- diction to the classical large deviation principle is even more severe in this case, induced by the long-range correlations and additional inherent non-stationarity. It will be shown that the inter-beat intervals can be well modeled by bounded fractional Brownian motion. The theoretical and numerical LDP, both for the model and the data, surprisingly indicates no clear decay of LDP for the time scales under study.

This study examines the efficacy of Sentinel-1 Radial Velocity (RVL) imagery at determining the position of ocean current front features, using the Gulf Stream (GS) and Agulhas Current (AC) as case studies. Fronts derived from RVL imagery are compared to fronts derived from Sea Surface Temperature (SST) imagery, specifically Multi-scale Ultra-high Resolution Sea Surface Temperature Analysis (MURSST) data. In the case of the GS, front locations from the Naval Oceanographic Office (NAVOCEANO) were also used for comparison. Only the northern walls of ocean current features are considered in this study, which is broken into three main steps: Preprocessing, front extraction, and front comparison. First, RVL imagery is selected from Sentinel-1 ocean products, preprocessed to remove antenna mispointing artifacts, and all products from the same orbit are combined into a single swath. Second, front features are extracted from both the RVL and MURSST imagery using a ridge detection algorithm, the main ocean current is chosen from all ridge features using a ranking algorithm, and the northern wall of this current is extracted. Third, the RVL, SST, and in the case of the GS, NAVOCEANO GS locations, features are compared using a symmetric Hausdorff Distance (HD) measure, and Mean Hausdorff Distance (MHD). In some cases, the automatic front extraction failed by either misclassifying an eddy or similar ocean feature as the ocean current in either the RVL or SST image or failed to extract the entire length of the front visible within the image. All the SST and RVL fronts were classified manually to determine the success rate of the automatic front extraction and to exclude failed front extractions from the analysis, as they are not accurate representations of the SST and RVL data’s ability to detect fronts. In special cases, the RVL image itself does not detect the entire ocean current, such that there are noticeable gaps in the ocean current. Similarly, in special cases the MURSST does not detect the entire ocean current. The automatic front extraction succeeded 65% of the time, including the special cases. The results demonstrated that RVL products were effective at determining the location of ocean fronts where the angle of the front's normal vector is within approximately 40° of the sensor’s azimuthal heading. A mean HD of 31.9 km and a mean MHD of 13.2 km was calculated for all front pairs over all study areas. The RVL fronts appeared consistently to the north of the SST fronts, with an average offset of 25.4 km between the centroids of the SST and RVL fronts. Positive correlations were noted between cloud coverage and MURSST error in both study regions. Several RVL images detected ocean currents in regions of high MURSST error where the MURSST did not detect the ocean currents, suggesting that RVL may provide more accuracy than SST-based products in clouded regions where there is no auxiliary data.

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As urbanization and global warming increase, an increasing importance is set on that urban planning processes take the possible effects of urban heat islands into account. In order to provide local city planners with site specific knowledge of the current situation in Stockholm, this study has explored the intra-urban heat island effect in Stockholm municipality by identifying major problem areas as well as addressing the statistical relationship between temperature and factors relating to land cover and urban planning strategies. Remotely sensed land surface temperature (LST) and the Swedish National Land Cover Database (NMD) have formed the data basis for the analyses that were carried out using GIS. The LST and land cover information have been extracted from randomly placed circle polygons in order to create a sample for the statistical analyses.  The results show that there exist differences in temperature within Stockholm municipality, both within the municipality as a whole and between various urban characters. In both cases, land cover is identified as an important, but not sole, factor to explain the differences. On land areas, artificial non-vegetated surfaces and forest is identified as the land cover classes of most relevance when it comes to the urban heat island effect. For both land cover classes, a strong correlation to LST is seen. Even though certain uncertainties and limitations are embedded in the data as well as in the method choices, the study can conclude in that the urban heat island effect is present in Stockholm municipality and that it can be derived from both land cover and urban characters. / I takt med att urbaniseringen och den globala uppvärmningen ökar kommer högre krav ställas på att stadsplaneringen tar hänsyn till de effekter som väntas uppstå kopplat till urbana värmeöar. I syfte att bistå lokala stadsplanerare med platsspecifik kunskap om den nuvarande situationen i Stockholm har den här studien utforskat intraurbana temperaturvariationer i Stockholms stad genom att identifiera de mest utsatta områdena samt genom att undersöka det statistiska sambandet mellan temperatur och faktorer kopplat till marktäcke och stadsutformning. Markens yttemperatur uppmätt från satellit och Nationella marktäckedata (NMD) har utgjort det främsta dataunderlaget för analyserna som genomförts med hjälp av GIS. Genom att extrahera information om yttemperatur och marktäcke från slumpmässigt placerade cirkelpolygoner kunde ett urval till de statistiska analyserna skapas.  Resultaten från studien visar att det finns skillnader i temperatur inom Stockholms stad, både inom kommunen som helhet och mellan olika stadsbyggnadskaraktärer. I båda fallen kan marktäcke identifieras som en viktig, men inte ensam, faktor till att förklara skillnaderna. På landområdena identifieras exploaterad mark och skog som de marktäcken med störst betydelse när det kommer till urbana värmeöar. För båda marktäckena ses i studien en stark korrelation till yttemperatur. Trots att vissa osäkerheter och begräsningar kan kopplas till både använd data och de metoder som använts kan slutsatsen att effekten från urbana värmeöar finns i Stockholms kommun dras. Dessutom kan konstateras att effekten kan härledas både till marktäcke och stadsbyggnadskaraktär.