Accurate knowledge of the electron density structure of the Earth's upper atmosphere is crucial to forecasting the performance of transionospheric radio signals. For this research, we focus on storm-time structuring in the mid- to high latitude ionosphere where large gradients in electron density can cause severe degradation of communication and navigation signals. We begin in Chapter 2 with a review of the primary data sets and methods used to accomplish the collaborative, multi-instrument studies described in this dissertation. In Chapter 3, we compare observational techniques for tracking polar cap patches during a moderate geomagnetic storm interval. For the first time, we monitor the transportation of patches with high spatial and temporal resolution across the polar cap for 1--2~h using a combination of GPS TEC, all-sky airglow imagers (ASIs), and Super Dual Auroral Radar Network (SuperDARN) HF radar backscatter. Simultaneous measurements from these data sets allow for continuous tracking of patch location, horizontal extent, and velocity even under adverse observational conditions for one or more of the techniques. A focus is placed on the structuring of patches, particularly on the nightside ionosphere as they become wider in the dawn-dusk direction and develop narrow finger-like structures. In Chapter 4, we perform a superposed epoch analysis to characterize the average response of GPS TEC in the North American sector during more than 100 geomagnetic storms over a 13-year interval. For the first time a rigorous approach is used to fully separate storm-time, local time, longitudinal, and seasonal effects at midlatitudes where dense ground receiver coverage is available. The rapid onset of a positive phase is observed across much of the dayside and evening ionosphere followed by a longer-lasting negative phase across all latitudes and local times. Our results show clear seasonal variations in the storm-time TEC, such that summer events tend to be dominated by the negative storm response while winter events exhibit a stronger initial positive phase with minimal negative storm effects. A prominent magnetic declination effect is identified and examined in terms of thermospheric zonal winds pushing plasma upward/downward along magnetic field lines of opposite declination. Finally in Chapter 5 we summarize several co-authored studies which examined various storm-time phenomena utilizing GPS TEC mapping tools developed for this dissertation research, with topics including subauroral polarization stream (SAPS), storm enhanced density (SED), tongue of ionization (TOI), and polar cap patches. / Ph. D.

The low latitude tropical ionosphere has been investigated by various researchers using Global Positioning System (GPS). Presently for many civil aviation applications, the ionospheric modeling of the tropical region has gained importance, in particular for flight safety. Since ionosphere is dispersive in nature, dual frequency (L1 = 1575.42 MHz and L2 = 1227.60 MHz) GPS observations can be used to obtain Ionospheric Total Electron Content (TEC). Since TEC varies with local time and geomagnetic latitude, an Ionospheric Modeling Technique using spatial linear approximation of vertical TEC over receiver station has been implemented following Sardon et al. The effects of all the systematic errors due to the satellite plus the receiver (SPR) instrumental biases can reach upto several nanoseconds. (1 TEC is 1016 electrons/m2, 1 ns = 2.86 TEC and 1 TEC = 0.16 m). Hence, to have an accurate estimation of ionospheric TEC, the instrumental biases must also be estimated. This thesis describes a heuristic adaptive Kalman Filtering scheme developed to estimate the TEC, the constants in the linearisation scheme, as well as the above total instrumental biases. The Kalman filter implementation is basically an optimization problem of minimizing the Cost Function J based on the difference between the model output and the measurement, called as the ‘innovation’, scaled by its covariance. In order to obtain the best possible results using the Kalman Filter approach, it is essential to provide appropriate values for the initial state, process and measurement noise covariances (P0, Q and R) respectively, which in general may not be known. Usually manual tuning of the filter parameter is carried out without using the above cost function J! The filter estimates can be highly sensitive to the above chosen statistics and thus these will have to be estimated carefully. Hence, we have utilized the Adaptive Kalman Filtering procedure of Myers and Tapley extended by Gemson and Ananthasayanam. The minimization is carried out by simultaneously estimating the above statistics and the unknown parameters, which include the TEC and the instrumental bias. In addition, A Constant Gain Kalman Filter approach using Genetic Algorithm (GA) has also been developed for the above requirement. It is observed that the steady state gains in KF and AKF approaches are in good match with the constant gains obtained from Genetic Algorithm. Using the above Adaptive Kalman Filtering technique and Constant Gain Kalman Filter approach, vertical TEC values and SPR biases have been estimated from the IGS receiver observations stationed at ISTRAC/ISRO, Bangalore, India. A diurnal TEC variation over Bangalore for a period of one year for 2003 and January 2004 is estimated and reported in this thesis. This approach has also been applied to study the behaviour of the ionosphere over low latitude IGS station at Fortaleza, Brazil data during the great magnetic storm on the 15th July 2000 and the results were found to be consistent with the results of Basu et al. In addition, Using Constant Kalman filter, the TEC enhancement over Indian region has been estimated for the October 2003 Ionospheric storm, and the results were found to be consistent with the reported results in the literature.