rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Parameterization and Statistical Analysis of Hurricane Waves
  name:
    name part: Mclaughlin, Patrick William
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Kaihatu, James M.
    role:
      role term: thesis advisor.
  name:
    name part: Texas A & M University
    role:
      role term: degree granting institution.
  type of resource: text
  genre: bibliography
  origin info:
    place:
      place term: txu
    date issued: 2015
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  abstract: Recently, Gulf coast communities have experienced significant damage from landfalling hurricanes. While the effects of hurricane surge on coastal communities have been examined and better defined, risk of damage due to hurricane waves is less quantified. This thesis presents the Wave Response Function (WRF) methodology. Hurricanes are parameterized in the form of non-dimensional equations incorporating key physical hurricane parameters. The non-dimensional equations are then combined with a fully developed sea state cap (Young and Verhagan 1996) to form the open coast and bay methodologies. This approach yields root mean square errors (RMSE) ranging from 0.01-0.46 m, with the majority of points below 0.3 m. This approach yields small bias values. The WRF method was compared to Hurricane Ike data (Kennedy et al. 2011) and yielded RMSE of 0.67 meters despite the higher depths of the recording stations. The WRF method was also compared to Taylor's (2012) parameterized wave equations, with mean RMSE improvements ranging from 0.13-0.32 m. Once WRF coefficients are adjust to minimize RMSE at each station under consideration, extreme value analysis via the Joint Probability Method with Optimal Sampling (JPM-OS) was conducted. When applied to Panama City, FL the JPM-OS methodology yielded extreme value statistics for 179 stations of interest. Maps detailing the spatial extents of the 100 and 1000 year maximum wave event were created using ArcGIS. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/152673
  note: by Patrick William Mclaughlin.
  note: "Major Subject: Ocean Engineering."
  note: Includes vita.
  note: Master of Science Texas A & M University 2014 http://hdl.handle.net/1969.1/152673
  note: Includes bibliographical references.
  note: Text (Thesis)
  subject:
    topic: Major Ocean Engineering
  subject:
    topic: hurricanes
  subject:
    topic: waves
  subject:
    topic: extreme value statistics
  subject:
    topic: joint probability method
  subject:
    topic: parameterization
  identifier: http://hdl.handle.net/1969.1/152673
  record info:
    record content source: TXA
    record creation date: 150204
    record change date: 20151206125710.0
    record identifier: in00003519661
    language of cataloging:
      language term: eng