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Item Modeling the temporal and spatial variability of solar radiation(Montana State University - Bozeman, College of Agriculture, 2012) Mullen, Randall Scott; Chairperson, Graduate Committee: Lucy Marshall; Brian L. McGlynn (co-chair); Brian L. McGlynn and Lucy A. Marshall were co-authors of the article, 'Use of intensity- duration- frequency curves and exceedance- frequency curves for quantifying solar radiation variability' in the journal 'Renewable energy' which is contained within this thesis.; Brian L. McGlynn and Lucy A. Marshall were co-authors of the article, 'A beta regression model to obtain interpretable parameters and estimates of error for improved solar radiation predictions' in the journal 'Journal of applied meteorology and climatology' which is contained within this thesis.; Brian L. McGlynn and Lucy A. Marshall were co-authors of the article, 'Modeling solar radiation using the spatial auto-correlation of the daily fraction of clear sky transmissivity' in the journal 'Theoretical and applied climatology' which is contained within this thesis.; Brian L. McGlynn and Lucy A. Marshall were co-authors of the article, 'Evaluating a beta regression approach for estimating fraction of clear sky transmissivity in mountainous terrain' in the journal 'Hydrology and earth system sciences' which is contained within this thesis.Solar radiation is fundamental to ecological processes and energy production. Despite growing networks of meteorological stations, the spatial and temporal variability of solar radiation remains poorly characterized. Many solar radiation models have been proposed to enhance predictions in areas without measurement instrumentation. However, these models do not fully take advantage of the increasing number of data collection sites, nor are they expandable to incorporate additional metrological information when available. In this dissertation we: 1) developed a method of statistical analysis to summarize and communicate solar radiation reliability, 2) applied a beta regression model to leverage auxiliary meteorological information for enhanced solar radiation prediction, 3) refined the beta regression model and considered spatial auto-correlation to better predict solar radiation across space, 4) extended and evaluated these methods in a mountainous region. These advancements in the characterization and prediction of solar radiation are detailed in the following chapters of this dissertation.