UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    Photochemistry of Exoplanet Atmospheres: Modelling alien chemistry accurately and self-consistently
    (2023) Teal, Dillon James; Kempton, Eliza; Astronomy; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Exoplanets offer unique physical and chemical laboratories experiencing entirely alien environments compared to the Solar System planets. Their atmospheres, governed by the same laws of physics, display remarkable diversity and complexity. They serve as the most complex planetary phenomena we can directly observe, coupled to the planet's interior processes, formation environment, the properties of the host star, and complex chemical ecosystems. The art of modelling these systems is a rich field of study, and in this work I study the nature of photochemical models and what understanding they can provide for us based on the quality and breadth of their inputs. By characterizing the implicit uncertainty chemical models have without a well-characterized host star, I quantify the importance of host star characterization to chemical modelling, showing their sensitivity under different reaction schemes and microphysical models. I then apply this to recent observations of known exoplanet host stars LHS 3844 and AU Microscopii. Finally, I cover work to model sub-Neptune atmospheres across a wide parameter space aimed at understanding the influence of a planet's environment and unknowns on haze formation and observational prevalence in emission and transmission spectroscopy.
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    ASSIMILATION OF PASSIVE MICROWAVE BRIGHTNESS TEMPERATURES FOR SNOW WATER EQUIVALENT ESTIMATION USING THE NASA CATCHMENT LAND SURFACE MODEL AND MACHINE LEARNING ALGORITHMS IN NORTH AMERICA
    (2017) Xue, Yuan; Forman, Barton A.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Snow is a critical component in the global energy and hydrologic cycle. It is important to know the mass of snow because it serves as the dominant source of drinking water for more than one billion people worldwide. To accurately estimate the depth of snow and mass of water within a snow pack across regional or continental scales is a challenge, especially in the presence of dense vegetations since direct quantification of SWE is complicated by spatial and temporal variability. To overcome some of the limitations encountered by traditional SWE retrieval algorithms or radiative transfer-based snow emission models, this study explores the use of a well-trained support vector machine to merge an advanced land surface model within a variant of radiance emission (i.e., brightness temperature) assimilation experiments. In general, modest improvements in snow depth, and SWE predictability were witnessed as a result of the assimilation procedure over snow-covered terrain in North America when compared against available snow products as well as ground-based observations. These preliminary findings are encouraging and suggest the potential for global-scale snow estimation via the proposed assimilation procedure.