Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Diode-laser-based high spectral resolution LIDAR(Montana State University - Bozeman, College of Engineering, 2021) Colberg, Luke Stewart; Chairperson, Graduate Committee: Kevin S. RepaskyThis thesis describes the design, construction, and testing of a high spectral resolution lidar (HSRL) as a part of a combined HSRL and differential absorption lidar (DIAL) system. The combined HSRL and DIAL instrument is constructed using the MicroPulse DIAL (MPD) architecture and uses distributed Bragg reflector lasers. The MPD architecture is unique because it is eye-safe and cost-effective; therefore, it is ideal for creating a network of ground-based lidars. This instrument is designed for thermodynamic profiling of the lower troposphere. A network of these instruments would be helpful for wide-scale atmospheric monitoring for weather forecasting and climate science. The purpose of the HSRL is to retrieve the optical properties of aerosols in the lower troposphere. The HSRL uses the DIAL offline laser, which has a wavelength of 770.1085 nm, and a potassium vapor cell as the spectral filter. The data retrieved from the HSRL provides the aerosol backscatter coefficient and the backscatter ratio up to an altitude of 7 km during nighttime operation and 5 km during daytime operation. The time resolution for these measurements is 5 minutes, and the range resolution is 150 m. These aerosol optical properties are valuable for aerosol studies and climate modeling; aerosols introduce the most significant degree of uncertainty in modeling the heat flux of the atmosphere. Additionally, these aerosol optical properties can be used to find the planetary boundary layer height (PBLH). The planetary boundary layer controls the exchange of heat, water vapor, aerosols, and momentum between the surface and the atmosphere. It has been demonstrated that the PBLH strongly affects turbulent mixing, convective transport, and cloud entrainment, which makes the PBLH an important parameter for weather forecasting and climate modeling. Despite its significance in atmospheric science, there is no standard method for defining the PBLH. A retrieval method for finding the daytime PBLH using HSRL data is proposed, and data comparisons to radiosonde PBLH retrievals are provided. The algorithm shows a good agreement with the radiosonde retrievals for conditions with a well-behaved boundary layer.Item Results of a micro pulse differential absorption LIDAR for temperature profiling and analysis code(Montana State University - Bozeman, College of Engineering, 2021) Cruikshank, Owen Daniel; Chairperson, Graduate Committee: Kevin S. RepaskyThermodynamic profiling of the lower troposphere is necessary for the study of weather and climate. The micropulse DIAL (differential absorption lidar), or MPD, presented here is designed to fill the need. The MPD is eye-safe and can run autonomously for continuous measurements compared to technologies with similar measurement capabilities like Raman lidar. Using a temperature-sensitive absorption line of O 2, the MPD system can measure the absorption of O 2 in the lower troposphere as a function of range and convert that measurement to temperature as a function of range. This process relies on a perturbative correction to the absorption retrieval to account for the fact that the O 2 absorption spectral linewidth is similar to the molecular Rayleigh scattering linewidth. An ancillary measurement of the ratio of aerosol backscatter to molecular backscatter is required for the correction. The integrated high spectral resolution lidar (HSRL) uses a heated potassium vapor notch filter to make the aerosol-to-molecular ratio measurement. An analysis program in MATLAB was written to take in raw lidar data and produce a temperature product of range and time. Results presented from a campaign at the Atmospheric Radiation Measurements program Southern Great Plains site in Oklahoma in spring 2019 show temperature comparisons with radiosonde measurements with a mean difference between radiosonde and MPD measurements of -1.1K and a standard deviation of 2.7 K. Further results from an instrument on the Montana State University campus in Bozeman and at the National Center for Atmospheric Research in Boulder, Colorado have shown that the MPD instrument can produce measurements autonomously for periods of weeks to months.Item Combining spectral and polarimetric methods to classify cloud thermodynamic phase(Montana State University - Bozeman, College of Engineering, 2019) Tauc, Martin Jan; Chairperson, Graduate Committee: Joseph A. Shaw; David W. Riesland, Laura M. Eshelman, Wataru Nakagawa and Joseph A. Shaw were co-authors of the article, 'Radiance ratios for CTP discrimination' submitted to the journal 'Journal of applied remote sensing' which is contained within this thesis.; Wataru Nakagawa and Joseph A. Shaw were co-authors of the article, 'The SWIR three-channel polarimeter for cloud thermodynamic phase detection' in the journal 'Optical engineering' which is contained within this thesis.Cloud thermodynamic phase--whether a cloud is composed of spherical water droplets or polyhedral ice crystals--is an important parameter for optical communication with space-based instruments, remote sensing of the atmosphere, and, perhaps most importantly, understanding weather and climate. Although some methods exist to detect the phase of clouds, there is still a need for passive remote sensing of cloud thermodynamic phase due to its low-cost, scalability, and ease of use. Two methods for cloud thermodynamic phase classification employ spectral radiance ratios in the short-wave infrared, and the S 1 Stokes parameter, a polarimetric quantity. In this dissertation, the combination of the two methods is realized in an instrument called the short-wave infrared three-channel polarimeter. The coalescence of radiance ratios in the short-wave infrared and polarization channels oriented parallel and perpendicular to the scattering plane provides better classification of cloud phase than either method independently. Despite the improvement, the low-cost system suffered from hardware and software limitations, which caused an increase in noise and polarimetric artifacts. These errors are analyzed and a subset of low-noise data shows even better classification ability. All together, the results attained from the deployment of the polarimeter in early 2019 showed promise that the combination of the two methods is an improvement over past techniques.