Numerical Weather Prediction Applied to Aeronautical Meteorology : Study of Local Hazardous Phenomena

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Físicas, leída el 27-11-2020Aviation and meteorology are intrinsically related. Even if the safety level of the industry is indisputable, the sustained growth represents a constant challenge to maintain the standards assumed today. In this task weather hazards are one of the priorities, as some of these still pose alarge risk for aircraft operation. The main objective of this doctoral thesis is to improve the knowledge of numerical weather prediction models when applied to aeronautical meteorology events. This is done by means of the evaluation of four different hazards: mountain wave icing, low visibility, deep convective precipitation and microbursts. These phenomena are linked not only by the disruption they may create to aircraft operation, but also by the fact that they can occur in very local and reduced spatiotemporal domains, which renders them very difficult to predict. The events are analysed using simulations run by a mesoscale atmospheric numerica lmodel, mostly the Weather Research and Forecasting (WRF) model. Different parametrizations and configurations are tested. Several skill scores and validation methods are applied, adapted to each phenomenon. Other nowcasting techniques, not based in numerical weather prediction, are used to support the assessment...La aviación y la meteorología están intrínsecamente relacionadas. A pesar de que los niveles de seguridad operacional de la industria son indiscutibles, el crecimiento sostenido supone un desafío constante para mantener los estándares asumidos a día de hoy. En esta tarea, los peligros relacionados con la meteorología son una de las prioridades, ya que algunos de ellos todavía suponen un gran riesgo para la operación de aeronaves. El objetivo principal de esta tesis doctorales mejorar el conocimiento de la predicción numérica aplicada a eventos de meteorología aeronáutica. El mismo se lleva a cabo a través de la evaluación de cuatro eventos peligrosos diferentes: engelamiento en onda de montaña, baja visibilidad, precipitación por convección profunda y micro bursts. Estos fenómenos están relacionados no solo por la alteración que pueden ocasionar en la operación de aeronaves, sino también por el hecho de que pueden darse endominios espacio-temporales muy reducidos y locales, lo cual los hace muy difíciles de predecir. Los eventos se analizan usando simulaciones realizadas con un modelo atmosférico mesoescalar, mayormente el modelo Weather Research and Forecasting (WRF). Se prueban diferentes parametrizaciones y configuraciones. También se aplican diferentes métodos de validación y criterios de cualificación. La evaluación se complementa con el uso de otras técnicas de nowcasting, no basadas en predicción numérica...Fac. de Ciencias FísicasTRUEunpu

Aeronautical engineering, a continuing bibliography with indexes (supplement 197)

This bibliography lists 488 reports, articles and other documents introduced into the NASA scientific and technical information system in January 1986

Research and Technology, 1995

This report presents some of the challenging research and technology accomplished at NASA Ames Research Center during FY95. The accomplishments address almost all goals of NASA's four Strategic Enterprises: Aeronautics and Space Transportation Technology, Space Sciences, Human Exploration and Development of Space, and Mission to Planet Earth. The report's primary purpose is to inform stakeholders, customers, partners, colleagues, contractors, employees, and the American people in general about the scope and diversity of the research and technology activities. Additionally, the report will enable the reader to know how these goals are being addressed

2007 Research and Technology

The NASA Glenn Research Center is pushing the envelope of research and technology in aeronautics, space exploration, science, and space operations. Our research in aeropropulsion, structures and materials, and instrumentation and controls is enabling next-generation transportation systems that are faster, more environmentally friendly, more fuel efficient, and safer. Our research and development of space flight systems is enabling advanced power, propulsion, communications, and human health systems that will advance the exploration of our solar system. This report selectively summarizes NASA Glenn Research Center s research and technology accomplishments for fiscal year 2007. Comprising 104 short articles submitted by the staff scientists and engineers, the report is organized into six major sections: Aeropropulsion, Power and Space Propulsion, Communications, Space Processes and Experiments, Instrumentation and Controls, and Structures and Materials. It is not intended to be a comprehensive summary of all the research and technology work done over the past fiscal year; most of the work is reported in Glenn-published technical reports, journal articles, and presentations. For each article in this report, a Glenn contact person has been identified, and where possible, a reference document is listed so that additional information can be easily obtained

30th European Congress on Obesity (ECO 2023)

This is the abstract book of 30th European Congress on Obesity (ECO 2023

Indoor air Quality and Its Effects on Health in Urban Houses of Indonesia: A case study of Surabaya

There is a possibility that the sick building syndrome has already spread widely among the newly constructed apartments in major cities of Indonesia. This study investigates the current conditions of indoor air quality, focusing especially on formaldehyde and TVOC, and their effects on health among occupants in the urban houses located in the city of Surabaya. A total of 471 respondents were interviewed and 82 rooms were measured from September 2017 to January 2018. The results indicated that around 50% of the respondents in the apartments showed some degrees of chemical sensitivity risk. More than 60% of the measured formaldehyde levels in the apartments exceeded the WHO standard, 0.08 ppm. The respondents living in rooms with higher mean formaldehyde values tended to have higher multiple chemical sensitivity risk scores. KEYWORDS: Indoor air quality, Sick building syndrome, QEESI, Formaldehyde, Developing countrie

Saving Energy in U.S. Transportation

This report focuses on energy use in U.S. transportation, which accounts for over 60 percent of U.S. oil consumption. The report attempts to put these opinions into context by examining the current status of the system and evaluating critical problems such as congestion, presenting forecasts of future energy use, making some pointed comparisons with European transportation, and describing and evaluating a range of options for saving energy

Developing artificial intelligence and machine learning to support primary care research and practice

This thesis was motivated by the potential to use everyday data , especially that collected in electronic health records (EHRs) as part of healthcare delivery, to improve primary care for clients facing complex clinical and/or social situations. Artificial intelligence (AI) techniques can identify patterns or make predictions with these data, producing information to learn about and inform care delivery. Our first objective was to understand and critique the body of literature on AI and primary care. This was achieved through a scoping review wherein we found the field was at an early stage of maturity, primarily focused on clinical decision support for chronic conditions in high-income countries, with low levels of primary care involvement and model evaluation in real-world settings. Our second objective was to demonstrate how AI methods can be applied to problems in descriptive epidemiology. To achieve this, we collaborated with the Alliance for Healthier Communities, which provides team-based primary health care through Community Health Centres (CHCs) across Ontario to clients who experience barriers to regular care. We described sociodemographic, clinical, and healthcare use characteristics of their adult primary care population using EHR data from 2009-2019. We used both simple statistical and unsupervised learning techniques, applied with an epidemiological lens. In addition to substantive findings, we identified potential avenues for future learning initiatives, including the development of decision support tools, and methodological considerations therein. Our third objective was to advance interpretable AI methodology that is well-suited for heterogeneous data, and is applicable in clinical epidemiology as well as other settings. To achieve this, we developed a new hybrid feature- and similarity-based model for supervised learning. There are two versions, fit by convex optimization with a sparsity-inducing penalty on the kernel (similarity) portion of the model. We compared our hybrid models with solely feature- and similarity-based approaches using synthetic data and using CHC data to predict future loneliness or social isolation. We also proposed a new strategy for kernel construction with indicator-coded data. Altogether, this thesis progressed AI for primary care in general and for a particular health care organization, while making research contributions to epidemiology and to computer science