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It has been shown in ionospheric research that modelling total electron content (TEC) during storm conditions is a big challenge. In this study, mathematical equations were developed to estimate TEC over Sutherland (32.38⁰S, 20.81⁰E), during storm conditions, using the Empirical Orthogonal Function (EOF) analysis, combined with regression analysis. TEC was derived from GPS observations and a geomagnetic storm was defined for Dst ≤ -50 nT. The inputs for the model were chosen based on the factors that influence TEC variation, such as diurnal, seasonal, solar and geomagnetic activity variation, and these were represented by hour of the day, day number of the year, F10.7 and A index respectively. The EOF model was developed using GPS TEC data from 1999 to 2013 and tested on different storms. For the model validation (interpolation), three storms were chosen in 2000 (solar maximum period) and three others in 2006 (solar minimum period), while for extrapolation six storms including three in 2014 and three in 2015 were chosen. Before building the model, TEC values for the selected 2000 and 2006 storms were removed from the dataset used to construct the model in order to make the model validation independent on data. A comparison of the observed and modelled TEC showed that the EOF model works well for storms with non-significant ionospheric TEC response and storms that occurred during periods of low solar activity. High correlation coefficients between the observed and modelled TEC were obtained showing that the model covers most of the information contained in the observed TEC. Furthermore, it has been shown that the EOF model developed for a specific station may be used to estimate TEC over other locations within a latitudinal and longitudinal coverage of 8.7⁰ and 10.6⁰ respectively. This is an important result as it reduces the data dimensionality problem for computational purposes. It may therefore not be necessary for regional storm-time TEC modelling to compute TEC data for all the closest GPS receiver stations since most of the needed information can be extracted from measurements at one location.

A substantial segment of the error in numerical weather prediction and climate projections comes from the intrinsic uncertainties of General Circulation Models of the atmosphere. Stochastic physics schemes are one of the preferred methods to represent the model uncertainty in Ensemble Prediction Systems, where different realizations of the same forecast are created to quantify the probabilities of different outcomes in the atmospheric flow. Stochastic physics schemes have been successfully employed in medium-range and seasonal forecasting systems, as they increase the skill of probabilistic forecasts. Similarly it has been demonstrated than these schemes can improve certain aspects of the model's climate. However, it is still not clear whether they are a truthful representation of the model uncertainties they aim to represent. In this thesis, a collection of stochastic physics schemes are evaluated using a seamless approach. It is found that they can improve the representation of the tropical climate and extra-tropical cyclones, but they degrade the individual representation of these processes deteriorating the deterministic skill of the model. Some important features of the model can be degraded by the stochastic physics schemes, like energy and moisture conservation on climate scales. Some closures to the schemes are proposed and successfully tested to remove or reduce some of the problems found. Alternative approaches in the development of stochastic parametrizations are also investigated. Stochastic physics schemes have some benefits but still require further development to produce a realistic representation of model error. It is also recommended that evaluation methodologies must be expanded to include process-based diagnostics to display the realism of its perturbations.

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Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. Bibliographical references: p. 275-293.

Thesis (Ph. D.)--University of Washington, 2007. / Vita. Includes bibliographical references (p. 103-107).

Thesis (Ph. D.)--University of Missouri-Columbia, 2008. / 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.

Thesis (Ph. D.)--University of Oklahoma, 1950. / Includes bibliographical references (leaves 273-311).

Thesis (Ph. D.)--College of William and Mary. / Typescript (photocopy). Vita. Includes bibliographical references (leaves 130-137).