Theses and Dissertations at Montana State University (MSU)
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Item The influence of solar radiation in snow on near surface energy balance in complex topography(Montana State University - Bozeman, College of Engineering, 2015) Curley, Patricia Glatz; Chairperson, Graduate Committee: Edward E. AdamsOnce snow reaches the ground it begins to metamorphose. It may thermodynamically metamorphose into a weak layer, which could lead to slab avalanches. The effect of local weather, topography and snow depth on this process can be estimated with a first principle one-dimensional energy balance equation in conjunction with a mesh topographic model. To do this, the commercially available software RadThermRT (RTRT) was used. This work focused on the effect of solar radiation on surface and near surface temperatures as well as the effect of varying the resolution of the topographic model. Three main components were completed. A solar radiation attenuation coefficient was developed based on wavelength, snow grain size, and snow density from published literature. Then this code was used to calculate results from twelve hour radiation recrystallization experiments carried out in a cold lab with homogenous snow. Finally, conditions for metamorphic events were calculated and qualitatively affirmed in the field at the Yellowstone Club ski area. This work demonstrates that solar radiation has a significant effect on the surface temperature as well as temperature at depth, and weak layer metamorphic events can be modeled. Based on RTRT calculations with 100 kg/m 3 density snow, shortwave radiation increased the temperature at the surface by approximately 5°C and at 2.5 centimeters below the surface by 9°C. During the 2013/14 and 2014/15 seasons, diurnal weather data was collected at the Yellowstone Club ski area, and events around the mountain were recorded with the help of the Yellowstone Club ski patrol and thermal imaging. For radiation recrystallization events, strong positive-knee-shaped gradients were successfully modeled on congruous slopes. RTRT and measured results agreed within 2°C. Spring events were also calculated and measured but there were some false positives. In the winter, spatial variation over the mountain was greater than in the spring where snow temperatures were ubiquitously high. Overall, this work is useful for modeling snow surface and depth temperatures to project the occurrence of weak layer metamorphic events. Going forward from this work, projecting longevity of weak layers and including a layer history of the snow would further improve the model.Item The development and validation of a snow/icepack pavement temperature thermodynamic model(Montana State University - Bozeman, College of Engineering, 2002) Bristow, Jeffrey RyanItem 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.