Thesis (M.Soc.Sc.)--University of Hong Kong, 1989. / Also available in print.

Scanning strategies for research and operational applications were developed for meteorological measurements with an experimental PAR, the MWR-05XP. A tornadic storm sampling strategy was developed with a 502.26 ms volumetric update and a resolution of 1.8 Az x 2 El x 150 m range. A sampling strategy for severe thunderstorm clusters was developed with a 10 second volumetric update and a resolution of 1.8 Az x 2 El x 300 m range. An operational weather scanning strategy was developed with an 81 second volumetric update and a resolution of 1.8 Az x 2 El x 150 m range. In general, for the acquisition of weather data, single frequency phased array radars offer only a slight sampling advantage over conventional scanning radars. This research verified that for meteorological sampling with the MWR-05XP, frequency diversity, coupled with electronic elevation scanning, offers a significant sampling advantage over conventional radars. The combination of electronic beam steering and frequency diversity produces a synergistic reduction in sampling time that increases the overall volumetric update rate. This research has also shown that, based on assumptions about the MWR-05XP operating parameters, it is possible to incorporate operational weather scanning into the radar's multifunction capability.

Bankruptcy is a costly event. Holders of publicly traded securities can rely on security prices to reflect their risk. Other stakeholders have no such mechanism. Hence, methods for accurately forecasting bankruptcy would be valuable to them. A large body of literature has arisen on bankruptcy forecasting with statistical classification since Beaver (1967) and Altman (1968). Reported total error rates typically are 10%-20%, suggesting that these models reveal information which otherwise is unavailable and has value after financial data is released. This conflicts with evidence on market efficiency which indicates that securities markets adjust rapidly and actually anticipate announcements of financial data. Efforts to resolve this conflict with event study methodology have run afoul of market model specification difficulties. A different approach is taken here. Most extant criticism of research design in this literature concerns inferential techniques but not sampling design. This paper attempts to resolve major sampling design issues. The most important conclusion concerns the usual choice of the individual firm as the sampling unit. While this choice is logically inconsistent with how a forecaster observes financial data over time, no evidence of bias could be found. In this paper, prediction performance is evaluated in terms of expected loss. Most authors calculate total error rates, which fail to reflect documented asymmetries in misclassification costs and prior probabilities. Expected loss overcomes this weakness and also offers a formal means to evaluate forecasts from the perspective of stakeholders other than investors. This study shows that cost of misclassifying bankruptcy must be at least an order of magnitude greater than cost of misclassifying nonbankruptcy before discriminant analysis methods have value. This conclusion follows from both sampling experiments on historical financial data and Monte Carlo experiments on simulated data. However, the Monte Carlo experiments reveal that as the cost ratio increases, robustness of linear discriminant rules improves; performance appears to depend more on the cost ratio than form of the distributions.

Thesis (M.Sc. Earth Sciences)--University of Waikato, 2008. / Title from PDF cover (viewed February 23, 2009) Includes bibliographical references (p. 72-75)

Thesis (Ph.D.) - Carleton University, 2002. / Includes bibliographical references (p. 253-260). Also available in electronic format on the Internet.

published_or_final_version / Business Administration / Master / Master of Business Administration

Dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg for the Degree of Master of Science / Various techniques and procedures suited to monthly forecasting are investigated and tested. These include using the products generated by atmospheric general circulation models during a 17-year hindcast experiment, and downscaling the forecast circulation to regional rainfall in South Africa using circulation indices and canonical correlation analysis. The downscaling methods are evaluated using the cross-validation technique. Various model forecast bias-correction methods and skill-enhancing ensemble techniques are employed to improve the 30-day prognosis of the model. Forecasts from the general circulation model and each technique are evaluated. Those demonstrating reasonable skill over the southern Africa region, and which are feasible when considering available resources, are adopted into a strategy which can be used operationally to produce monthly outlooks. Various practical issues regarding the operational aspects of long-term forecasting are also discussed. / Andrew Chakane 2019

"The most widely used spectral models with the transform method are the de-aliased spectral model in which the de-aliased technique is used in the discrete Fourier transform according to the 3/2-rule. From the viewpoint of the Walsh-Hadamard transform, the multiplications of the values of the variables on the gridpoints do not yield the aliasing terms. In the shallow water equations, we compare the aliased spectral model with the de-aliased spectral model using the initial conditions of the Rossby-Haurwitz wave and the FGGE data. The aliased spectral models are more accurate and more efficient than the de-aliased spectral models. For the same wavenumber truncation, the computational amount of the aliased spectral model is only 60 percent of the de-aliased spectral model. We have not yet discovered the phenomenon of the nonlinear computational instability induced by the aliasing terms in the long time integration of the aliased spectral models. Thus, in the spectral models with the transform method the necessity of using the 3/2-rule in the discrete Fourier transform may be viewed with suspicion"--Abstract. / Typescript. / "Spring Semester, 1991." / "Submitted to the Department of Meteorology in partial fulfillment of the requirements for the degree of Master of Science." / Advisor: Richard L. Pfeffer, Professor Directing Thesis. / Includes bibliographical references (leaves 92-95).

Multiple linear regression was used to develop equations for 12-, 24-, and 36-hour surface wind forecasts for the wind energy site at Goodnoe Hills. Equations were derived separately for warm and cool seasons. The potential predictors included LFM II model output, MOS surface wind forecasts extrapolated from surrounding stations, pressure observations corrected to mean sea level, and two types of climatological variables. Forecasts of wind speed and direction were formulated for an independent sample of predictands and predictors. The forecasts were evaluated using standard methods of forecast verification and the results are summarized in terms of several verification scores. Comparisons of scores were made by season, projection time, and cycle (or preparation) time, and some patterns were evident in the scores with respect to these stratifications. The minimum value of the mean absolute error attained by the forecast system presented here was 5.64 mph for a 12-hour, cool season forecast equation. The minimum value of the root mean square error was 7.57 mph for a 12-hour, warm season forecast equation. Comparison of these results with the results of other statistical wind forecasting studies indicates that the forecast equations for Goodnoe Hills are of comparable accuracy to the equations developed for other wind energy sites. Suggestions for future investigations of statistical wind forecasting are offered as well as recommendations concerning ways of improving the forecasting system described in this study. / Graduation date: 1983

American meteorology was synonymous with subjective weather forecasting in the early twentieth century. Controlled by the Weather Bureau and with no academic programs of its own, the few hundred extant meteorologists had no standing in the scientific community. Until the American Meteorological Society was founded in 1919, meteorologists had no professional society. The post-World War I rise of aeronautics spurred demands for increased meteorological education and training. The Navy arranged the first graduate program in meteorology in 1928 at MIT. It was followed by four additional programs in the interwar years. When the U.S. military found itself short of meteorological support for World War II, a massive training program created thousands of new mathematics- and physics-savvy meteorologists. Those remaining in the field after the war had three goals: to create a mathematics-based theory for meteorology, to create a method for objectively forecasting the weather, and to professionalize the field. Contemporaneously, mathematician John von Neumann was preparing to create a new electronic digital computer which could solve, via numerical analysis, the equations that defined the atmosphere. Weather Bureau Chief Francis W. Reichelderfer encouraged von Neumann, with Office of Naval Research funding, to attack the weather forecasting problem. Assisting with the proposal was eminent Swedish-born meteorologist Carl-Gustav Rossby. Although Rossby returned to Stockholm to establish his own research school, he was the de facto head of the Meteorology Project providing personnel, ideas, and a publication venue. On-site leader Jule Charney provided the equations and theoretical underpinnings. Scandinavian meteorologists supplied by Rossby provided atmospheric reality. Six years after the Project began, meteorologists were ready to move their models from a research to an operational venue. Attempts by Air Force meteorologist Philip D. Thompson to co-opt numerical weather prediction (NWP) prompted the academics, Navy, and Weather Bureau members involved to join forces and guarantee that operational NWP would remain a joint activity not under the control of any weather service. This is the story of the professionalization of a scientific community, of significant differences in national styles in meteorology, and of the fascination (especially by non-meteorologists) in exploiting NWP for the control of weather. / Graduation date: 2003