Summary: | Complex magnetosphere-ionosphere coupling mechanisms result in high latitude irregularities that are difficult to characterize. Until recently, the polar and auroral irregularities remained largely unexplored. Inadequate infrastructures to deploy and maintain advanced dual frequency Global Navigation Satellite System (GNSS) receivers at high latitudes, especially in the Southern hemisphere, makes such an investigation a formidable task. Additionally, the complicated geometry of the magnetic field lines in these regions pose challenges in designing global scintillation models. This dissertation takes some steps towards bridging these gaps while advancing the state-of-the-art high latitude irregularity studies. In the first part of this dissertation, we briefly describe the Autonomous Adaptive Low-Power Instrument Platforms (AAL-PIP) experimental setup. These space science instrument platforms are being deployed in remote locations in Antarctica, improving the coverage of GNSS data availability. We explain in detail the method developed for analyzing high rate (typically 50 Hz) data from a novel dual-frequency Global Positioning System (GPS) receiver called Connected Autonomous Space Environment Sensor (CASES). We also report first observations from CASES at high latitudes. From this study, we established that CASES can be reliably used as a science grade GPS scintillation monitor. Following this, a novel three dimensional (3D) electromagnetic (EM) wave propagation model called "Satellite-beacon Ionospheric-scintillation Global Model of the upper Atmosphere" (SIGMA) was developed to simulate GNSS scintillations on ground. GPS scintillation simulations of significantly high fidelity are now possible with this model. While the model is global, it is the first such model which accounts for the complicated geometry of magnetic field lines at high latitudes. Using SIGMA, a sensitivity study is presented to understand the effect of geographical, propagation and irregularity parameters on the phase scintillations. This ...
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