M.S. - Meteorology

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https://hdl.handle.net/10125/2099

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Now showing 1 - 10 of 63
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    A study of Hawaiian and Line Islands rainfall
    (1976) Meisner, Bernard N.; Meteorology
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    Synoptic regimes associated with recent floods in the Rewa
    (1976) Krishna, Ram.; Meteorology
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    A Radar-Based Climatology of Thunderstorms in Hawai‘i.
    (2018-08) Ballard, Robert A.; Meteorology
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    A Bioinformatics Approach to Finding Transcriptional Regulatory Motifs in Bacteria
    ([Honolulu] : [University of Hawaii at Manoa], [May 2016], 2016-05) Takebayashi, Taryn
    Differential RNA sequencing has made it possible to determine the transcription start sites (TSS) for many of the genes in a genome. By using the TSS information, this study aimed to take advantage of the relatively simple transcriptional organization in bacteria and determine potential transcription factor binding sites for the cyanobacterium Anabaena sp. PCC 7120. By revealing shared sequences adjacent to known TSS, shared TFBS and unique TFBS were identified. This may make this set of computer applications useful in determining which genes in a given dataset are possibly transcriptionally coregulated. This project made use of the transcriptional map of the cyanobacterium Anabaena sp. PCC 7120 in order to narrow down the areas of the bacterial genome that may contain TFBS. The utilization of transcription start sites in locating TFBS is an additional unique feature of this study. This study culminated in tutorials (as shown in the Appendices) covering the programming involved in this project that may help biology students to begin writing their own computer programs.
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    Large-Scale Weather Patterns Favorable for Vog Occurrences on Oahu, Hawaii
    ([Honolulu] : [University of Hawaii at Manoa], [December 2015], 2015-12) Tofte, Kristine
    Kilauea Volcano is one of the most active volcanoes in the world, and its two vents (Halemaumau and Puu Oo) release more sulfur dioxide (SO2) than major power plants. During the time of this study (April 2009 – December 2014), the two vents released approximately 3,700 tons of SO2 per day. Within the atmosphere, the SO2 is oxidized and converted to sulfuric acid aerosols through reactions with OH radicals and H2O molecules in clear sky and cloud reactions. This sulfuric aerosol is commonly referred to as volcanic smog (vog) in Hawai'i. During prevailing trade winds conditions, the vog emitted from Kilauea volcano is advected towards the southwest of the Big Island of Hawai'i. However, when winds shift to a southeast or southwest direction, then vog can be carried up the island chain affecting all the Hawaiian Islands. This study focuses on the largescale Weather patterns that cause this wind shift and specifically, on conditions that bring the vog to the island of Oahu, the most heavily populated island. In order to identify large-scale weather patterns that bring vog to Oahu, two datasets were used. Firstly, the Hawai'i Department of Health maintains a record of hourly aerosol mass concentrations in size ranges below 10 μm (PM10) and below 2.5 μm (PM2.5). The volcanic plume consists of accumulation mode sulfuric acid aerosols below 1μm in diameter and therefore, the PM2.5 measurements will capture information about vog concentrations. As part of this study, Hawai'i Department of Health PM2.5 measurements were used to identify elevated vog conditions. Secondly, European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis data were used to determine weather patterns occurring prior and during Oahu vog events. As part of this effort, the ERA-Interim reanalysis data, for different weather patterns, were downscaled to a resolution of 3.3 km using the Weather Research and Forecasting (WRF) model. The WRF output was run in the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to produce both trajectory and concentration plots. The HYSPLIT model allowed for a visual representation of how the vog plume follows the large-scale wind patterns. Data from April 2009 throughout 2014 were analyzed and the total number of vog days was found to be 101. These 101 vog days were the result of 57 distinct vog events lasting from hours up to four days. The 57 events were further categorized into three large-scale weather patterns: precold fronts (37 cases), upper-level disturbances (17 cases) and Kona lows (3 cases). The pre-cold front events had variable duration lasting up to four days and it was found that the largest vog concentrations (PM2.5 values) occurred during long duration pre-cold front events.
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    Conditions Favorable for the Occurrence of Trapped Mountain Lee Waves Downstream of O'ahu
    ([Honolulu] : [University of Hawaii at Manoa], [May 2015], 2015-05) Li, Liye
    The purpose of this study is to determine the synoptic conditions necessary for trapped lee wave development over Oʻahu. The study also shows that the high-resolution mesoscale numerical models could possibly provide valuable numerical guidance for the onset, development and dissipation of trapped lee wave events in Hawaiʻi. The occurrence of trapped lee wave clouds is possible in Hawaiʻi, especially downstream of the island of Oʻahu. The Koʻolau and Waiʻanae mountain ranges of Oʻahu are oriented NW-SE. The pre-frontal southwesterly wind in winter has a large wind component perpendicular to these mountain ranges. With the presence of an inversion aloft, trapped lee waves may occur during the wintertime. In the summer time, northeast trade wind is persistent and trapped lee wave event is relatively rare. In this study, environmental conditions related to the development of three trapped lee wave events (27 January, 2010—TRAP1; 24 January—TRAP2, 2003; 26 January, 2014—TRAP3, 25 August, 1977) are analyzed using soundings, charts, satellite images. The available model input datasets for the summer case in 25 August, 1977 is ERA-40 in the resolution of 2.5⁰×2.5⁰, which is not enough to simulate high-resolution model in 1-km. With input analysis datasets in the resolution of 1.25⁰×1.25⁰, the three wintertime events are successfully predicted by the high-resolution WRF model. Among them, TRAP1 and TRAP2 are initialized using the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), and TRAP3 is initialized with NCEP Climate Forecast System Version 2 (CFSv2) output.Results from a WRF model simulation with a horizontal 1-km grid indicate that the trapped lee waves are most significant just beneath the inversion. There are several common factors involved in the occurrence of these trapped mountain wave events: 1) the presence of a well-defined inversion above the ridge tops; 2) abundant low-level moisture; 3) strong low-level winds with Froude Number (Fr) > 1 impinging on the mountain ranges; and (4) wind shear with increasing wind speed with respect to height through the inversion. A strong pre-frontal southwesterly flow is the typical synoptic setting for the occurrence of trapped mountain waves in winter, whereas in the summer months the presence of an upper-level disturbance with easterly winds aloft is a necessary prerequisite. The vertical wind profile is the key element to determine whether trapped lee waves or downslope winds form. None of the trapped lee wave events in winter or summer have a critical level. If a critical level exists between 500 hPa to 300 hPa, and wind decreases with height in the low level, a downslope wind storm or mountain wave may occur instead of trapped lee waves. Sensitivity tests for the 27 January, 2010 case are performed with reduced relative humidity (RH). With lower RH, trapped lee waves have smaller amplitudes and shorter wavelengths suggesting a latent heat release feedback to the environmental flow.