Academic literature on the topic 'Cloud analysi'

The study of radiative transfer in multifractal clouds is of great interest, an important application being to Global Climate Models. In this work we develop a formalism analogous to the multifractal singularity formalism for understanding photon scattering statistics in radiative transfer in multifractals, and test the results numerically on lognormal multifractals. Although the results are only exactly valid in the thick cloud limit, the approximation is found to be quite accurate down to optical thickness of $ tau approx1$-10, so the results may be widely applicable. Furthermore we show the possibility of "renormalizing" the multifractal by replacing it with a near equivalent homogeneous medium but with a "renormalized" optical thickness $ tau sp{1/(1+C sb1)}$ where C$ sb1$ is the codimension of the mean singularity of the cloud. We argue that this approximation is likely to continue to be valid for multiple scattering, and is also compatible with recent results for diffusion on multifractals. Finally we analyze cloud liquid water content data and estimate the universal multifractal indices. We find that the scaling is respected over the whole range 5m-330km and that the cloud can in fact be reasonably described by a lognormal multifractal.

Cirrus clouds cover between 20% - 50% of the globe and are an essential component in the climate. The improved understanding of ice cloud microphysical properties is contingent on acquiring and analyzing in-situ and remote sensing data from cirrus clouds. In ??u observations of microphysical properties of ice and mixed-phase clouds using the mini-Video Ice Particle Sizer (mini-VIPS) aboard robotic unmanned aerial vehicles (UAVs) provide a promising and powerful platform for obtaining valuable data in a cost-effective, safe, and long-term manner. The purpose of this study is to better understand cirrus microphysical properties by analyzing the effectiveness of the mini-VIPS/UAV in-situ platform. The specific goals include: (1) To validate the mini-VIPS performance by comparing the mini-VIPS data retrieved during an Artic UAV mission with data retrieved from the millimeterwavelength cloud radar (MMCR) at the Barrow ARM/CART site. (2) To analyze mini-VIPS data to survey the properties of high latitude mixedphase clouds The intercomparison between in-situ and remote sensing measurements was carried out by comparing reflectivity values calculated from in-situ measurements with observations from the MMCR facility. Good agreement between observations and measurements is obtained during the time frame where the sampled volume was saturated with respect to ice. We also have 1 2 shown that the degree of closure between calculated and observed reflectivity strongly correlates with the assumption of ice crystal geometry observed in the mini-VIPS images. The good correlation increases the confidence in mini-VIPS and MMCR measurements. Finally, the size distribution and ice crystal geometry obtained from the data analysis is consistent with published literature for similar conditions of temperature and ice supersaturation.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California<br>The development and analysis cloud is a rapid development system being designed to support the Air Force Research Lab (AFRL) Simulation & Technology Assessment Branch. The purpose is to isolate research, development, test, and evaluation of unique software within a Zone D enclave [1] to allow researchers and analysts to develop and test software free of the many IT requirements that hamper development and without risk of contaminating the overall Air Force network. The cloud system is being designed so researchers and analysts will utilize Software as a Service (SaaS) models. Such a model makes it transparent to users such things as where the software originates and any licensing concerns. Utilities, tools, and other enhancing software that users need are published and using them frees the developer to focus on their specific development efforts versus tertiary development modules.

Le culle dei neonati pretermine presso l’Unità di Terapia Intensiva Neonatale (UTIN) dell’Ospedale Pediatrico “G. Salesi” di Ancona sono circondati da numerosi dispositivi per il monitoraggio, la diagnosi e il trattamento delle malattie e forniscono un’enorme quantità di dati che, fino ad ora, venivano visualizzati solo su monitor e trascritti in una cartella clinica cartacea. Le note manuali, quindi, venivano periodicamente, ma non immediatamente, trascritte in un foglio elettronico sul PC della UTIN con il rischio di errori e dimenticanze. I medici hanno espresso la necessità di raccogliere automaticamente i dati dai dispositivi per garantire che non venissero trascurati dettagli importanti per la cura del paziente, essendo consapevoli che l’automazione di tale processo possa facilitare e migliorare l’implementazione delle procedure della pratica clinica quotidiana. L’obiettivo di questa tesi è quello di permettere l’interfacciamento delle strumentazioni biomediche della UTIN in un’unica infrastruttura cloud, che ne consenta la comunicazione con un DB unico. L’architettura proposta consente l’automatizzazione del processo di raccolta, trasmissione, memorizzazione, elaborazione e disponibilità dei dati dei dispositivi per il personale medico. Questa è garantita dalla realizzazione di un’interfaccia web che supera le funzionalità di una semplice Cartella Clinica Elettronica, grazie allo sviluppo di moduli clinici innovativi. Essi contengono tecniche di estrazione e analisi dei dati e algoritmi decisionali, che forniscono in output reminder, allarmi e indicatori, in grado di supportare i medici nella previsione e nella diagnosi di malattie come l’ittero neonatale o le disabilità motorie, nel monitoraggio dei parametri fisiologici, come la frequenza respiratoria e i parametri di crescita, e nelle decisioni da prendere riguardo problemi clinici, come gli apporti nutrizionali giornalieri e i follow-up. Tutte le soluzioni sopra descritte sono state validate attraverso esperimenti condotti nella UTIN sotto la supervisione del primario e dei medici del reparto.<br>Preterm infants’ cribs in Neonatal Intensive Care Unit (NICU) of “Women’s and Children’s Hospital G. Salesi” of Ancona are surrounded by many devices for the monitoring, diagnosis and treatment of diseases, which provide a huge amount of data that, until now, was only displayed on monitors and periodically transcribed in a paper medical record. Then manual notes were regularly, but not immediately, transcribed in an electronic sheet on a NICU PC with the risk of errors and forgetfulnesses. In this context, physicians have expressed the need to automatically gather data from all these devices to ensure that no key details for patient care were overlooked, as they are aware that the automation of this process could improve the implementation of the procedures of their daily clinical practice. The objective of this thesis is to allow the interfacing of NICU biomedical instruments into a single cloud-based infrastructure that enables the communication between different medical devices and a unique DB. The proposed architecture permits the automation of the process of device data collection, transmission, storage, processing and availability for medical staff, that is guaranteed through the implementation of a web interface that exceeds the functionalities of a simple Electronic Medical Record, thanks to the development of innovative clinical tools. They contain data extraction and analysis techniques and decision-making algorithms, which provide in output advices, reminders, alarms, and indicators that can support physicians in predicting and diagnosing diseases, such as neonatal jaundice or motor disabilities, in monitoring physiological parameters, such as respiratory rate and growth parameters, and in making decisions about clinical problems, such as daily nutritional intakes and follow-ups. All the solutions described above have been validated through experiments conducted in the NICU under the supervision of the physicians and the Head Physician.

Thesis (Ph. D.)--University of Missouri-Columbia, 2008.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on June 15, 2009) Vita. Includes bibliographical references.

As virtualization platforms or cloud computing have become more of a commodity, many more organizations have been utilizing them. Many organizations and technologies have emerged to fulfill those cloud needs. Cloud vendors provide similar services, but the differences can have significant impact on specific applications. Selecting the right provider is difficult and confusing because of the number of options. It can be difficult to determine which application characteristics will impact the choice of implementation. There has not been a concise process to select which cloud vendor and characteristics are best suited for the application requirements and organization requirements. This thesis provides a model that identifies crucial application characteristics, organization requirements and also characteristics of a cloud. The model is used to analyze the interaction of the application with multiple cloud platforms and select the best option based on a suitability score. Case studies utilize this model to test three applications against three cloud implementations to identify the best fit cloud implementation. The model is further validated by a small group of peers through a survey. The studies show that the model is useful in identifying and comparing cloud implementations with regard to application requirements.

This work is motivated by the question: how much complexity is appropriate for a cloud parameterization used in general circulation models (GCM). To approach this question, cloud parameterizations across the complexity range are explored using general circulation models and theoretical Monte-Carlo simulations. Their results are compared with high-resolution satellite observations and simulations that resolve the GCM subgrid-scale variability explicitly. A process-orientated evaluation is facilitated by GCM forecast simulations which reproduce the synoptic state. For this purpose novel methods were develop to a) conceptually relate the underlying saturation deficit probability density function (PDF) with its saturated cloudy part, b) analytically compute the vertical integrated liquid water path (LWP) variability, c) diagnose the relevant PDF-moments from cloud parameterizations, d) derive high-resolution LWP from satellite observations and e) deduce the LWP statistics by aggregating the LWP onto boxes equivalent to the GCM grid size. On this basis, this work shows that it is possible to evaluate the sub-grid scale variability of cloud parameterizations in terms of cloud variables. Differences among the PDF types increase with complexity, in particular the more advanced cloud parameterizations can make use of their double Gaussian PDF in conditions, where cumulus convection forms a separate mode with respect to the remainder of the grid-box. Therefore, it is concluded that the difference between unimodal and bimodal PDFs is more important, than the shape within each mode. However, the simulations and their evaluation reveals that the advanced parameterizations do not take full advantage of their abilities and their statistical relationships are broadly similar to less complex PDF shapes, while the results from observations and cloud resolving simulations indicate even more complex distributions. Therefore, this work suggests that the use of less complex PDF shapes might yield a better trade-off. With increasing model resolution initial weaknesses of simpler, e.g. unimodal PDFs, will be diminished. While cloud schemes for coarse-resolved models need to parameterize multiple cloud regimes per grid-box, higher spatial resolution of future GCMs will separate them better, so that the unimodal approximation improves.

Thesis (Ph. D.)--University of California, San Diego, 2008.<br>Title from first page of PDF file (viewed Mar. 24, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 108-112).