Browsing by Subject "Wind science"
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Item An observational study of tropical cyclone low-level wind maxima(2010-08) Giammanco, Ian Matthew; Schroeder, John L.; Powell, Mark D.; Smith, Douglas A.Over the last decade substantial improvements have been made in one’s ability to observe the tropical cyclone boundary layer. Mean wind profiles computed from GPS dropwindsonde data have shown a “jet-like” wind speed maximum located near 500 m above ground level however measurements from individual GPS dropwindsondes (GPS sondes) exhibit variability. Tropical cyclone low-level wind maxima represent a source of momentum available for vertical transport; however little is known regarding their characteristics over open ocean conditions or at landfall. In order to thoroughly characterize low-level wind maxima, over 1080 GPS sondes were employed. Given the lack of GPS sonde data at landfall the National Weather Service’s network of Doppler radar systems was used to mitigate the data void. Over 380 velocity azimuth display wind profiles were derived in order to evaluate the structure and evolution of the boundary layer wind profile at landfall. These data were processed to investigate low-level wind maxima as well to separate the influence of turbulence from quasi-steady low-level jet features described in previous studies. Analysis of the GPS sonde dataset revealed a decrease in the height of the wind maximum with radius and mean boundary layer wind speed. An azimuthal dependence was also observed as the left-front storm-relative sector contained the lowest mean wind maximum. Low-level jet features were observed within more than half of all GPS sondes their mean and variance mirrored the statistics associated with low-level wind maxima. The characteristics of the jet features were in good agreement with previous numerical studies. Logarithmic and power law profiles were also found to perform quite well for composite vertical wind profiles; however when used for individual GPS sondes they were somewhat less effective. The use of velocity azimuth display (VAD) wind profiles proved to be effective in resolving the boundary layer wind vertical wind profile. The height of the wind maximum was found to be radially and azimuthally dependent. Persistent low-level jet features were identified primarily within the off-shore flow regime. The passage of rainbands was also found to influence the vertical wind profile. Log and power law profiles also performed well for VAD derived wind profiles.Item Development of a statistical relationship between ground-based and remotely-sensed damage in windstorms(2010-08) Brown, Tanya Michelle; Liang, Daan; Womble, James A.; Seo, Byungtae; Lin, ZhangxiWith rapid growth in technology, new methods of wind engineering research are being explored and new tools are being utilized. In the past, ground-based surveys of windstorm damage were frequently performed with the aid of aerial photographs in some cases. Researchers have recently begun using remote-sensing data such as digitized satellite, aerial, and LIDAR imagery to assess damage following natural and man-made disasters, in addition to, or instead of employing the older method of walking houses-tohouse for surveys. This research investigates the relationship between the windstorm damage states of residential structures observed at ground level and those observed from space using remote-sensing data. The ground-based datasets utilized in this research include georeferenced digital photographs from VIEWSTM from the coastal counties of Mississippi following Hurricane Katrina and from Madison County, TN following the “Super Tuesday” tornado outbreak of February, 2008. The remote-sensing datasets include Pictometry (15 cm spatial resolution) and NOAA (37 cm spatial resolution) aerial images captured after Hurricane Katrina, and QuickBird (61 cm spatial resolution) and WorldView 1 (50 cm spatial resolution) satellite imagery. Ground-based damage states were rated by the “Degree of Damage” (DOD) according to the Enhanced Fujita Scale. Remotely-sensed damage states were rated by Womble’s Remote-Sensing (RS) Damage Scale. Various types of single variable regression models using various datasets and various statistical transformations were used to parameterize models in which the remotely-sensed damage state was used as a model input to predict the ground level damage state. Several of these models were then validated using additional data. Multiple linear regression models using statistical transformations were also fitted and some were selected for validation. These models used the remote-sensing damage state and imagery spatial resolution both as model inputs to predict the ground level damage state. Recommendations are provided to aid in selecting the appropriate model for use in future damage studies.