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The Advanced Multi-Frequency Radar is a three-frequency system designed and built by the University of Massachusetts Microwave Remote Sensing Lab (MIRSL). The radar has three frequencies, Ku-band (13.4 GHz), Ka-band (35.6 GHz), and W-band (94.92GHz). The additional information gained from additional frequencies allows the system to be sensitive to a wide range of atmospheric and precipitation particle sizes, while increasing the ability to derive particle microphysics from radar retrievals. This thesis details the calibration of data from the Canadian CloudSat/CALIPSO Validation Project (C3VP) held during January 2007 in Ontario, Canada. The calibration used internal calibration path data and was confirmed through comparison of precipitation reflectivity with an Environment Canada radar. The calibrated data was then used to estimate the median mass diameter of precipitating snow from a high-priority C3VP data set. This median mass diameter retrieval was compared to the results from a local ground instrument, the Snow Video Imager (SVI), showing good agreement.

The lee shores of the North American Great Lakes are subject to hazardous amounts of snowfall each winter as continental polar air masses are destabilized by the relatively warmer lakes which manifests as pronounced heat and moisture fluxes and subsequent convection and snow generation. This phenomenon, known as lake-effect snow (LES), has been studied by the atmospheric scientific community extensively as the local and mesoscale processes are becoming better understood through the implementation of in situ research projects and high-resolution numerical weather prediction models. However, considerably less research effort has inquired on what large-scale conditions are linked with lake-effect snow. The objective of this dissertation is to develop a more comprehensive understanding of the synoptic-scale conditions associated with lake-effect snowstorms and how they differentiate with non-LES winter storms. Chapter 1 provides a brief introduction to LES and reviews the basic dynamics of LES formation in the form of a comprehensive literature review. Chapter 2 consists of the first synoptic climatologies of lake-effect snowstorms off Lakes Michigan and Superior through statistical analysis of past lake-effect cases off those two lakes. Chapter 3 focuses on developing a synoptic climatology of wintertime cyclonic systems, specifically Alberta Clippers, that traversed the Great Lakes basin but did not result in lake-effect snow formation. Chapter 4 features the development of an objective classification model that differentiates between these two winter weather phenomena by using past LES and non-LES winter storm case repositories to train and test the model. This research effort will focus on wintertime Alberta Clipper systems and LES off Lakes Erie and Ontario. Finally, Chapter 5 reviews the primary results from this research and discusses their significance and implications regarding possible future research.

This thesis deals with an endangered large mammal species - snow leopard, its distribution, population dynamics, landscape genetics and connectivity, trophic ecology and human-snow leopard conflicts in the Nepalese Himalaya (Sagarmatha National Park (SNP), Lower Mustang (LM) and Upper Manang (UM) in the Annapurna Conservation Area, during Wet and Dry seasons in 2014-2016. In the case of snow leopard study, we used data obtained from camera traps, scat's genetic analysis and monitoring of fresh pugmarks and scrapes while direct count method was used to study for its main prey, blue sheep and Himalayan tahr. In study 1, we assessed the determinants of habitat suitability of snow leopards using MaxEnt model and mapped the distribution of suitable habitat for snow leopards in Nepal. Altitude and Annual mean temperature are important common factors contributing to snow leopard habitat suitability within the area studied, which is indicated by both the percentage contribution of environmental variables and Jackknife test from MaxEnt model. Some other uncommon factors also seem to play a role, as they were important in at least one of the analyses. These were: distance from road, and precipitation of driest month but their importance has to be considered with caution. In study 2, we present our...

The Greenland ice sheet is an area of great interest to the scientific community due to its role as an important bellwether for the global climate. Satellite-borne scatterometers are particularly well-suited to studying temporal changes in the Greenland ice sheet because of their high spatial coverage, frequent sampling, and sensitivity to the presence of liquid water. The dry snow zone is the largest component of the Greenland ice sheet and is identified as the region that experiences negligible annual melt. Due to the lack of melt in the dry snow zone, backscatter was previously assumed to be relatively constant over time in this region. However, this thesis shows that a small seasonal variation in backscatter is present in QuikSCAT data in the dry snow zone. Understanding the cause of this seasonal variability is important to verify the accuracy of QuikSCAT measurements, to better understand the ice sheet conditions, and to improve future scatterometer calibration efforts that may use ice sheets as calibration targets.This thesis provides a study of the temporal behavior of backscatter in the dry snow zone of the Greenland ice sheet focusing on seasonal variation. Spatial averaging of backscatter and the Karhunen-Lo`eve transform are used to identify and study the dominant patterns in annual backscatter behavior. Several QuikSCAT instrumental parameters are tested as possible causes of seasonal variation in backscatter in the dry snow zone to verify the accuracy of QuikSCAT products. None of the tested parameters are found to be related to seasonal variation. Further evidence is given that suggests that the cause of the seasonal variation is geophysical and several geophysical factors are tested. Temperature is found to be highly related to dry snow backscatter and therefore may be driving the seasonal variation in backscatter in the dry snow zone.

The purpose of this Thesis has been to write, for the first time, an authentic, unbiased "Biography of Erastus Fairbanks Snow, Missionary, Pioneer, and Colonizer." Biography was chosen at the suggestion of Dr. Lowry Nelson, Professor of Rural Social Economics, of Brigham Young University, and because of a natural fondness for western history, and a sincere appreciation for the men and women who made "The West" liveable. For the particular subject chosen, I am indebted to Dr. William J. Snow, Professor of History at Brigham Young University.

Warren Stone Snow was an early convert to the LDS church who during the Church's first four decades was often involved in defensive roles as Mormonism encountered various conflicts on the American frontier. While he protected the lives of Joseph Smith and Brigham Young and defended Illinois Saints from houseburning mobs and took a leading role in the Battle of Nauvoo, his greatest defensive contributions took place after the Mormons settled in Utah. As commander of the Sanpete Military District, he was one of the leading figures in Mormon defensive efforts during the Utah War in 1857 and later as brigadier general in the Nauvoo Legion he was the single most important Mormon military leader during Utah's longest and most intense Indian War, the Black Hawk War of 1865-1867. This thesis is a biography of Snow's life during his protecting years and examines his background and character as well as his motivations and defensive activities.

The planning of snow removal routes is complicated by the fact that the amount it snows, and thus the amount of resources, that is, vehicles, needed to clear it, varies from year to year. This variation has created a demand for a way to quickly generate efficient snow removal plans that take the resources that are available into account. In this report we describe the development of an ad hoc heuristic algorithm that improves already existing feasible solutions to the snow removal problem. It accomplishes this by reassigning tasks from the vehicles with the longest tours to those with the shortest tours, followed by reordering their tasks to ensure that the solution remains feasible. This algorithm is meant to be implemented in a larger piece of software and it is tested on a set of pre-generated solutions for a given network and number of vehicles, including the best known ones. Over half of the previously best known solutions were improved by this algorithm.