4 resultados para Physics and Astronomy(all)
em ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha
Resumo:
A polar stratospheric cloud submodel has been developed and incorporated in a general circulation model including atmospheric chemistry (ECHAM5/MESSy). The formation and sedimentation of polar stratospheric cloud (PSC) particles can thus be simulated as well as heterogeneous chemical reactions that take place on the PSC particles. For solid PSC particle sedimentation, the need for a tailor-made algorithm has been elucidated. A sedimentation scheme based on first order approximations of vertical mixing ratio profiles has been developed. It produces relatively little numerical diffusion and can deal well with divergent or convergent sedimentation velocity fields. For the determination of solid PSC particle sizes, an efficient algorithm has been adapted. It assumes a monodisperse radii distribution and thermodynamic equilibrium between the gas phase and the solid particle phase. This scheme, though relatively simple, is shown to produce particle number densities and radii within the observed range. The combined effects of the representations of sedimentation and solid PSC particles on vertical H2O and HNO3 redistribution are investigated in a series of tests. The formation of solid PSC particles, especially of those consisting of nitric acid trihydrate, has been discussed extensively in recent years. Three particle formation schemes in accordance with the most widely used approaches have been identified and implemented. For the evaluation of PSC occurrence a new data set with unprecedented spatial and temporal coverage was available. A quantitative method for the comparison of simulation results and observations is developed and applied. It reveals that the relative PSC sighting frequency can be reproduced well with the PSC submodel whereas the detailed modelling of PSC events is beyond the scope of coarse global scale models. In addition to the development and evaluation of new PSC submodel components, parts of existing simulation programs have been improved, e.g. a method for the assimilation of meteorological analysis data in the general circulation model, the liquid PSC particle composition scheme, and the calculation of heterogeneous reaction rate coefficients. The interplay of these model components is demonstrated in a simulation of stratospheric chemistry with the coupled general circulation model. Tests against recent satellite data show that the model successfully reproduces the Antarctic ozone hole.
Resumo:
Im Jahr 2011 wurde am Large Hadron Collider mit dem ATLAS Experiment ein Datensatz von 4.7 inversen Femtobarn bei einer Schwerpunktsenergie von 7 TeV aufgezeichnet. Teil des umfangreichen Physikprogrammes des ATLAS Experiments ist die Suche nach Physik jenseits des Standardmodells. Supersymmetrie - eine neue Symmetrie zwischen Bosonen und Fermionen - wird als aussichtsreichester Kandidat für neue Physik angesehen, und zahlreiche direkte und indirekte Suchen nach Supersymmetrie wurden in den letzten Jahrzehnten bereits durchgeführt. In der folgenden Arbeit wird eine direkte Suche nach Supersymmetrie in Endzuständen mit Jets, fehlender Transversalenergie und genau einem Elektron oder Myon durchgeführt. Der analysierte Datensatz von 4.7 inversen Femtobarn umfasst die gesamte Datenmenge, welche am ATLAS Experiment bei einer Schwerpunktsenergie von 7 TeV aufgezeichnet wurde. Die Ergebnisse der Analyse werden mit verschiedenen anderen leptonischen Suchkanälen kombiniert, um die Sensitivität auf diversen supersymmetrischen Produktions- und Zerfallsmodi zu maximieren. Die gemessenen Daten sind kompatibel mit der Standardmodellerwartung, und neue Ausschlussgrenzen in verschiedenen supersymmetrischen Modellen werden berechnet.
Resumo:
Oceans are key sources and sinks in the global budgets of significant atmospheric trace gases, termed Volatile Organic Compounds (VOCs). Despite their low concentrations, these species have an important role in the atmosphere, influencing ozone photochemistry and aerosol physics. Surprisingly, little work has been done on assessing their emissions or transport mechanisms and rates between ocean and atmosphere, all of which are important when modelling the atmosphere accurately.rnA new Needle Trap Device (NTD) - GC-MS method was developed for the effective sampling and analysis of VOCs in seawater. Good repeatability (RSDs <16 %), linearity (R2 = 0.96 - 0.99) and limits of detection in the range of pM were obtained for DMS, isoprene, benzene, toluene, p-xylene, (+)-α-pinene and (-)-α-pinene. Laboratory evaluation and subsequent field application indicated that the proposed method can be used successfully in place of the more usually applied extraction techniques (P&T, SPME) to extend the suite of species typically measured in the ocean and improve detection limits. rnDuring a mesocosm CO2 enrichment study, DMS, isoprene and α-pinene were identified and quantified in seawater samples, using the above mentioned method. Based on correlations with available biological datasets, the effects of ocean acidification as well as possible ocean biological sources were investigated for all examined compounds. Future ocean's acidity was shown to decrease oceanic DMS production, possibly impact isoprene emissions but not affect the production of α-pinene. rnIn a separate activity, ocean - atmosphere interactions were simulated in a large scale wind-wave canal facility, in order to investigate the gas exchange process and its controlling mechanisms. Air-water exchange rates of 14 chemical species (of which 11 VOCs) spanning a wide range of solubility (dimensionless solubility, α = 0:4 to 5470) and diffusivity (Schmidt number in water, Scw = 594 to 1194) were obtained under various turbulent (wind speed at ten meters height, u10 = 0:8 to 15ms-1) and surfactant modulated (two different sized Triton X-100 layers) surface conditions. Reliable and reproducible total gas transfer velocities were obtained and the derived values and trends were comparable to previous investigations. Through this study, a much better and more comprehensive understanding of the gas exchange process was accomplished. The role of friction velocity, uw* and mean square slope, σs2 in defining phenomena such as waves and wave breaking, near surface turbulence, bubbles and surface films was recognized as very significant. uw* was determined as the ideal turbulent parameter while σs2 described best the related surface conditions. A combination of both uw* and σs2 variables, was found to reproduce faithfully the air-water gas exchange process. rnA Total Transfer Velocity (TTV) model provided by a compilation of 14 tracers and a combination of both uw* and σs2 parameters, is proposed for the first time. Through the proposed TTV parameterization, a new physical perspective is presented which provides an accurate TTV for any tracer within the examined solubility range. rnThe development of such a comprehensive air-sea gas exchange parameterization represents a highly useful tool for regional and global models, providing accurate total transfer velocity estimations for any tracer and any sea-surface status, simplifying the calculation process and eliminating inevitable calculation uncertainty connected with the selection or combination of different parameterizations.rnrn
Resumo:
The Standard Model of particle physics is a very successful theory which describes nearly all known processes of particle physics very precisely. Nevertheless, there are several observations which cannot be explained within the existing theory. In this thesis, two analyses with high energy electrons and positrons using data of the ATLAS detector are presented. One, probing the Standard Model of particle physics and another searching for phenomena beyond the Standard Model.rnThe production of an electron-positron pair via the Drell-Yan process leads to a very clean signature in the detector with low background contributions. This allows for a very precise measurement of the cross-section and can be used as a precision test of perturbative quantum chromodynamics (pQCD) where this process has been calculated at next-to-next-to-leading order (NNLO). The invariant mass spectrum mee is sensitive to parton distribution functions (PFDs), in particular to the poorly known distribution of antiquarks at large momentum fraction (Bjoerken x). The measurementrnof the high-mass Drell-Yan cross-section in proton-proton collisions at a center-of-mass energy of sqrt(s) = 7 TeV is performed on a dataset collected with the ATLAS detector, corresponding to an integrated luminosity of 4.7 fb-1. The differential cross-section of pp -> Z/gamma + X -> e+e- + X is measured as a function of the invariant mass in the range 116 GeV < mee < 1500 GeV. The background is estimated using a data driven method and Monte Carlo simulations. The final cross-section is corrected for detector effects and different levels of final state radiation corrections. A comparison isrnmade to various event generators and to predictions of pQCD calculations at NNLO. A good agreement within the uncertainties between measured cross-sections and Standard Model predictions is observed.rnExamples of observed phenomena which can not be explained by the Standard Model are the amount of dark matter in the universe and neutrino oscillations. To explain these phenomena several extensions of the Standard Model are proposed, some of them leading to new processes with a high multiplicity of electrons and/or positrons in the final state. A model independent search in multi-object final states, with objects defined as electrons and positrons, is performed to search for these phenomenas. Therndataset collected at a center-of-mass energy of sqrt(s) = 8 TeV, corresponding to an integrated luminosity of 20.3 fb-1 is used. The events are separated in different categories using the object multiplicity. The data-driven background method, already used for the cross-section measurement was developed further for up to five objects to get an estimation of the number of events including fake contributions. Within the uncertainties the comparison between data and Standard Model predictions shows no significant deviations.