Although gas turbine engines are designed to use dry air as the working fluid, the great demand over the last decades for air travel at several altitudes and speeds has increased aircraft’s exposure to inclement weather conditions. Although, they are required to perform safely under the effect of various meteorological phenomena, in which air entering the engine contains water, several incidents have been reported to the aviation authorities about power loss during flight at inclement weather. It was understood that the rain ingestion into a gas turbine engine influences the performance of the engine and particular the compressor and the combustor. The effects of water ingestion on gas turbine engines are aerodynamic, thermodynamic and mechanical. These effects occur simultaneously and affect each other. Considering the above effects and the fact that they are timedependent, there are few gas turbine performance simulation tools, which take into account the water ingestion phenomenon. This study is a new research of investigating theoretically the water ingestion effects on a gas turbine performance. It focuses on the aerodynamic and mechanical effects of the phenomenon on the compressor and the combustor. The application of Computational Fluid Dynamics (CFD) is the basic methodology to examine the details of the flow in an axial compressor and how it is affected by the presence of water. The calculations of water film thickness, which is formed on the rotor blade, its motion (direction and speed) and the extra torque demand, are provided by a code created by the author using FORTRAN programming language. Considering the change in blade’s profile and the wavy characteristics of the liquid film, the compressor’s performance deterioration is calculated. The compressor and combustor’s deterioration data are imported to a gas turbine simulation code, which is upgraded to calculate overall engine’s performance deterioration. The results show a considerable alteration in engine’s performance parameters and arrive at the same conclusions with the relevant experimental observations.

A lot of research has been conducted in the past decades on urban heat island (UHI) all over the world. Nevertheless, the UHI effect has not been included in weather data used by building services engineers to design buildings and size their heating and cooling plants. This research was carried out to investigate the UHI effect in Greater Manchester by setting up fixed point monitoring stations over the city. Woodford Met Office ground observation station was selected to be the rural reference point. A multiple regression model was developed to incorporate the heat island effect into the Manchester weather data for engineering usage.It was found that the urban heat island intensity (the difference between the rural and urban area temperatures) can be as high as 8°C in summer and 10°C in winter in Manchester. Clear and calm nocturnal temperature data was used (when maximum heat island occurs ) to find the relationship between the UHI intensity and sky view factor (SVF), distance away from the city centre, evapotranspiration fraction (EF), wind speed, cloud cover and rural reference temperature. Results indicate that all factors have a negative linear relationship with UHI intensity. All measured data were fed into a statistical software package to create general linear regression models. Validation showed that these models were capable of predicting average UHI effect to a good accuracy. The maximum heat island effect peaks are not so accurate. However, an analytical model was developed based on energy balance equations to predict the maximum heat island effect. Validation shows a good prediction for summer but not so good for winter. This is probably due to the lower average UHI intensity in winter than in summer.

This dissertation describes research designed to enhance hydrometeorological forecasts. The objective of the research is to deliver an optimal methodology to produce reliable, skillful and economically valuable probabilistic temperature and precipitation forecasts. Weather plays a dominant role for energy companies relying on forecasts of watershed precipitation and temperature to drive reservoir models, and forecasts of temperatures to meet energy demand requirements. Extraordinary precipitation events and temperature extremes involve consequential water- and power-management decisions. This research compared weighted-average, recursive, and model output statistics bias-correction methods and determined optimal window-length to calibrate temperature and precipitation forecasts. The research evaluated seven different methods for daily maximum and minimum temperature forecasts, and three different methods for daily quantitative precipitation forecasts, within a region of complex terrain in southwestern British Columbia, Canada. This research then examined ensemble prediction system design by assessing a three-model suite of multi-resolution limited area mesoscale models. The research employed two different economic models to investigate the ensemble design that produced the highest-quality, most valuable forecasts. The best post-processing methods for temperature forecasts included moving-weighted average methods and a Kalman filter method. The optimal window-length proved to be 14 days. The best post-processing methods for achieving mass balance in quantitative precipitation forecasts were a moving-average method and the best easy systematic estimator method. The optimal window-length for moving-average quantitative precipitation forecasts was 40 days. The best ensemble configuration incorporated all resolution members from all three models. A cost/loss model adapted specifically for the hydro-electric energy sector indicated that operators managing rainfall-dominated, high-head reservoirs should lower their reservoir with relatively low probabilities of forecast precipitation. A reservoir-operation model based on decision theory and variable energy pricing showed that applying an ensemble-average or full-ensemble precipitation forecast provided a much greater profit than using only a single deterministic high-resolution forecast. Finally, a bias-corrected super-ensemble prediction system was designed to produce probabilistic temperature forecasts for ten cities in western North America. The system exhibited skill and value nine days into the future when using the ensemble average, and 12 days into the future when employing the full ensemble forecast. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

Weather has a significant impact on business activities of many kinds. The list of economic activities subjected to the risk of the weather include: the energy producers and consumers, the industry of leisure, the insurance industry, the food industry and the agricultural industries but the primary industry, namely the energy industry, has given rise to the demand for weather derivatives and has caused the weather risk management industry to evolve actively. A derivative is a contract or security, whose payoffs depend upon the price of an underlying asset price, and is used to control the risks of naturally-arising exposures to such an asset price. Therefore weather derivatives are financial contracts with payouts that depend on weather in some form. It is a contract that provides a payoff in response to an index level based on weather phenomena (West, 2002).The underlying variable can be for example humidity, rain, snowfall, temperature, or even sunshine. The main players who take part in the weather derivatives markets industry can be grouped in to five main categories, namely: 1) End users who are also referred to as hedgers 2) Speculators 3) Market makers 4) Brokers 5) Insurance and re-insurance companies. Since the late 90’s when the first weather derivatives transactions were recorded, the underlying market has witnessed the development of a new derivative market in the United States, which is gradually expanding across Europe. However, the newly developed market for weather derivatives is not liquid in Africa and specifically South Africa mainly due to the following factors: 1) Many companies and business organisations have not yet established a hedging policy or even figured out how their businesses or industries are exposed to weather risks. 2 2) “Since many companies and industries depend on insurance companies to cover their risks, it is possible that the solutions suggested by these companies or industries looking for protection from weather risks differ according to the cover provided by these insurance organisations “(Micali, 2008). The main aim of this study is to review available statistical models for pricing derivatives, with temperature as the underlying which could enable industries, businesses and other organisations in South Africa to protect themselves against losses due to fluctuations in the weather and therefore hedge their risks.

Recent in-flight instances of aircraft engine power loss involving hail ingestion have forced the manufacturers to demonstrate successful engine operation whilst ingesting hail. The main objective of this research project has been to obtain an understanding of the basic characteristics of hailstone impacts. A hail gun was designed to fire simulated hailstones at speeds up to 175 m/s. Three measurement techniques were used to determine the impact characteristics of the hailstones, i.e: patternator, high speed cine-photography, and still photography with short duration flashes. Using these techniques, the basic impact characteristics in terms of post-impact particle size, velocity and mass distribution were obtained for a variety of target configurations. The influence of seemingly important parameters on the impact characteristics were investigated, including approach angle and velocity, target curvature, and target rotation. Studies were further made into multiple impacts, and the effect of target curvature and rotation on the impact characteristics. Based on the experimental results, a set of empirical rules and a mathematical model describing hailstone break-up were defined.

No description available.

The first line of defense for the threat of an oncoming hurricane are meteorologists. From their guidance, warnings are drafted and evacuation plans are made ready. This study explores uncertainty that operational meteorologists encounter with hurricane prediction, and more importantly, how meteorologists translate the uncertainty for the public. The study is based on a web survey of individual meteorologists, in cooperation with the National Weather Association (NWA). The survey received 254 responses with an estimated 18% response rate. Specifically, the study focuses on three key areas: displaying uncertainty in hurricane track forecasts, perceived relationships between the public and the media and message characteristics on various platforms (e.g., television, web, and social media), and reliance on numerical weather prediction in the forecasting process. Results show that tracking graphics are varied between their use and usefulness and meteorologists think that they have a bigger role in information dissemination than previously thought. / National Science Foundation (NSF) Grant CMMI1520338

<p>In order to ensure the successful demonstration that the Weather Message switching center Replacement (WMSCR) of the Federal Aviation Administration (FAA) can complete its primary mission of accepting and distributing various data formats in use today and those of future systems, including the expected message traffic, this study was initiated.</p> <p> This Test Data set Formulation will specify the various data formats, worst-case traffic load/size, and a distribution scenario for the WMSCR. From this Formulation, an actual Test Data Set can be constructed and used to test the WMSCR.</p> <p> A description of the WMSCR, its operational environment, current users, future users, various message formats and associated sizing requirements per interface are detailed within.</p> / Master of Engineering

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Thesis. 1975. M.S.--Massachusetts Institute of Technology. Dept. of Meteorology. / Bibliography: leaves 66-67. / by William K.-F. Grant, Jr. / M.S.