Theses and Dissertations at Montana State University (MSU)
Permanent URI for this communityhttps://scholarworks.montana.edu/handle/1/732
Browse
4 results
Search Results
Item Infrared cloud imaging systems characterization(Montana State University - Bozeman, College of Engineering, 2016) Riesland, David Walter; Chairperson, Graduate Committee: Joseph A. ShawInfrared cloud imaging (ICI) is a useful tool for characterizing cloud cover for a variety of fields. Clouds play an important role in free-space high frequency (optical and mm-wave) terrestrial communications. Ground-based infrared imagers are used to provide long-term, high resolution (spatial and temporal) cloud data without the need for sunlight. This thesis describes the development and characterization of two ICI systems for deployment at remote field sites in support of Earth-to-space mm-wave and optical communication experiments. The hardware upgrades, calibration process, sensitivity analysis, system validation, and algorithm developments are all discussed for these systems. Relative spectral response sensitivity analysis is discussed in detail, showing as much as 35% calibrated scene radiance uncertainties when using generic manufacturer data in comparison with measured spectral responses. Cloud discrimination algorithms, as well as cloud phase (ice or water discrimination) algorithms are also discussed.Item Deployment of the third-generation infrared cloud imager : a two-year study of Arctic clouds at Barrow, Alaska(Montana State University - Bozeman, College of Engineering, 2016) Nugent, Paul Winston; Chairperson, Graduate Committee: Joseph A. ShawCloud cover is an important but poorly understood component of current climate models, and although climate change is most easily observed in the Arctic, cloud data in the Arctic is unreliable or simply unavailable. Ground-based infrared cloud imaging has the potential to fill this gap. This technique uses a thermal infrared camera to observe cloud amount, cloud optical depth, and cloud spatial distribution at a particular location. The Montana State University Optical Remote Sensor Laboratory has developed the ground-based Infrared Cloud Imager (ICI) instrument to measure spatial and temporal cloud data. To build an ICI for Arctic sites required the system to be engineered to overcome the challenges of this environment. Of particular challenge was keeping the system calibration and data processing accurate through the severe temperature changes. Another significant challenge was that weak emission from the cold, dry Arctic atmosphere pushed the camera used in the instrument to its operational limits. To gain an understanding of the operation of the ICI systems for the Arctic and to gather critical data on Arctic clouds, a prototype arctic ICI was deployed in Barrow, AK from July 2012 through July 2014. To understand the long-term operation of an ICI in the arctic, a study was conducted of the ICI system accuracy in relation to co-located active and passive sensors. Understanding the operation of this system in the Arctic environment required careful characterization of the full optical system, including the lens, filter, and detector. Alternative data processing techniques using decision trees and support vector machines were studied to improve data accuracy and reduce dependence on auxiliary instrument data and the resulting accuracy is reported here. The work described in this project was part of the effort to develop a fourth-generation ICI ready to be deployed in the Arctic. This system will serve a critical role in developing our understanding of cloud cover in the Arctic, an important but poorly understood region of the world.Item Thermal infrared imaging of the atmosphere : the infrared cloud imager(Montana State University - Bozeman, College of Engineering, 2004) Thurairajah, Brentha; Chairperson, Graduate Committee: Joseph A. ShawClouds play an important role in regulating the radiation budget of the atmosphere and are responsible for altering or maintaining the global climate. Understanding the interaction between clouds and radiation is necessary for accurate models that predict future climate and weather changes. The present cloud instruments are either zenithviewing, single-pixel instruments that calculate cloud amount using Taylor's hypothesis (spatial statistics are equal to temporal statistics), which do not work under certain atmospheric conditions, or are imagers that operate in the visible spectrum, thereby operating only in the daytime. Other imaging instruments use completely different techniques for daytime and nighttime detection of clouds and have problems detecting clouds at sunrise and sunset. The Infrared Cloud Imager (ICI), a ground based, thermal infrared imager was developed with funding from the Communications Research Laboratory (CRL), Japan, to provide continuous 24-hour cloud measurement without difference in daytime or nighttime sensitivity. The ICI is a spatially resolving instrument that measures the downwelling atmospheric radiance in the 8-14 aem region of the electromagnetic spectrum. The data collected are used to compute spatial and temporal cloud statistics. Although the ICI was initially developed to measure Arctic clouds, it has been successfully deployed in both Barrow, Alaska in the Spring of 2002 and in Lamont, Oklahoma (mid-latitude plains) in Spring 2003. I have developed algorithms for processing the ICI data based on Microwave Radiometer (MWR) water vapor data, for identifying and classifying clouds, and have demonstrated that ICI is capable of determining cloud statistics. From the radiative transfer analysis of the ICI data, weekly and monthly cloud statistics show a general trend of mostly clear and/or mostly cloudy skies with very small transition periods. Sky cover histograms from Oklahoma show predominantly thick clouds in March and thin clouds in April with a significant amount of variability in sky condition. The comparison of cloud statistics obtained from the entire ICI image and from a single pixel in the ICI image illustrates that zenith-viewing instruments generally tend to underestimate cloudiness. The correlation between ICI percent cloudiness (using different thresholds for Oklahoma data) with the Micro Pulse Lidar (MPL) cloudiness has also been analyzed.Item Wide-angle infrared cloud imaging for cloud cover statistics(Montana State University - Bozeman, College of Engineering, 2008) Nugent, Paul Winston; Chairperson, Graduate Committee: Joseph A. ShawThe Infrared Cloud Imager (ICI) is a radiometrically calibrated thermal infrared imaging instrument currently in development at Montana State University to measure cloud cover statistics. This instrument was developed originally as part of a joint U.S.-Japan effort to study the arctic atmosphere. The ICI provides localized high-resolution data relative to satellites images and, in contrast to visible imaging systems, provides continuous day and night operation. While the original instrument proved the capabilities of using radiometrically calibrated thermal infrared images to produce cloud coverage measurements, this instrument was limited. These limits were primarily the instrument's large size, relatively high cost, narrow field of view, and need to recalibrate the camera for each image. The work presented here covers work conducted to develop two prototypes of a second-generation ICI instrument, and the work which laid the groundwork for the development of a fully deployable version of these systems. These systems are to be used to measure cloud cover statistics for the characterization of optical communication paths by the Optical Communication Group at NASA JPL.