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dc.contributor.advisorChairperson, Graduate Committee: Lucy Marshall.en
dc.contributor.authorMullen, Randall Scott.en
dc.contributor.otherBrian 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.en
dc.contributor.otherBrian 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.en
dc.contributor.otherBrian 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.en
dc.contributor.otherBrian 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.en
dc.date.accessioned2013-06-25T18:38:01Z
dc.date.available2013-06-25T18:38:01Z
dc.date.issued2012en
dc.identifier.urihttps://scholarworks.montana.edu/xmlui/handle/1/1916
dc.description.abstractSolar 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.en
dc.language.isoengen
dc.publisherMontana State University - Bozeman, College of Agricultureen
dc.subject.lcshSolar radiation.en
dc.subject.lcshSolar activity Forecasting.en
dc.titleModeling the temporal and spatial variability of solar radiation
dc.typeDissertation
dc.rights.holderCopyright Randall Scott Mullen 2012en
thesis.catalog.ckey2076527en
thesis.degree.committeemembersMembers, Graduate Committee: Brian L. McGlynn (co-chair); Megan Higgs; Paul Stoyen
thesis.degree.departmentLand Resources & Environmental Sciences.en
thesis.degree.genreDissertationen
thesis.degree.namePhDen
thesis.format.extentfirstpage1en
thesis.format.extentlastpage223en
mus.identifier.categoryLife Sciences & Earth Sciences
mus.relation.departmentLand Resources & Environmental Sciences.en_US
mus.relation.universityMontana State University - Bozemanen_US


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