Influences on Observed Near-Surface Gust Factors in Landfalling U.S. Gulf Coast Hurricanes: 2004–08

Abstract

The deployment of ruggedized surface observing platforms by university research programs in the path of landfalling tropical cyclones has yielded a wealth of information regarding the near-surface wind flow characteristics. Data records collected by Texas Tech University’s Wind Engineering Mobile Instrument Tower Experiment and StickNet probes and by the Florida Coastal Monitoring Program along the Gulf Coast of the United States from 2004 to 2008 were compiled to examine influences on near-surface gust factors. Archived composite reflectivity data from coastal WSR-88D instruments were also merged with the tower records to investigate the influence of precipitation structure. Wind records were partitioned into 10-min segments, and the ratio of the peak moving-average 3-s-gust wind speed to the segment mean was used to define a gust factor. Observations were objectively stratified into terrain exposure categories to determine if factors beyond those associated with surface frictional effects can be extracted from the observations. Wind flow characteristics within exposure classes were weakly influenced by storm-relative position and precipitation structure. Eyewall observations showed little difference in mean gust factors when compared with other regions. In convective precipitation, only peak gust factors were slightly larger than those found in stratiform conditions, with little differences in the mean. Gust factors decreased slightly with decreasing radial distance in rougher terrain exposures and did not respond to radar-observed changes in precipitation structure. In two limited comparisons, near-surface gusts did not exceed the magnitude of the wind maximum aloft detected through wind profiles that were derived from WSR-88D velocity–azimuth displays.

Retrieval of Peak Thunderstorm Wind Velocities Using WSR-88D Weather Radars

“…The fitting method is evaluated based on a harmonic wave, where the amplitude and phase shift of the wave correspond to the wind magnitude and direction, respectively. Considering a full azimuthal range yields a single result per scanned level, which can be combined to construct a vertical profile such as the work done by Giammanco et al (2016) and Krupar et al (2016). A three-dimensional approach, named Volume Velocity Processing (VVP), was proposed by Waldteufel and Corbin (1979).…”

“…Even though progress on wind retrieval has been made over the years, the challenge of retrieving near-surface peak winds for localized events, like thunderstorms, using fixed radars persists. For example, a comprehensive study that compared retrieved hurricane velocities from fixed radars to ground measurements was presented in the work done by Krupar et al (2016). However, hurricanes are more abiding to the VAD linearity assumptions when compared to smaller scale thunderstorm wind events.…”

Influence of a portable near-surface observing network on experimental ensemble forecasts of deep convection hazards during VORTEX-SE

“…The computing hardware and pressure sensor are mounted inside a Campbell Scientific data acquisition box with a small battery for ,12-h deployments. An external battery box can also be deployed that extends the StickNet's sampling lifetime to .24 h (typically less than 5 days), which has been advantageous for prolonged deployments during landfalling hurricanes (e.g., Zachry et al 2013;Giammanco et al 2016;Alford et al 2019;Fernández-Cabán et al 2019). During VORTEX-SE, a 100-W solar panel was attached to each probe (see Fig.…”

A wind tunnel study of the aerodynamic characteristics of a scaled, aeroelastic, model tree

“…Some of these tests have ignored the effects of turbulence in the atmospheric boundary layer (Mayhead, 1973;Aly et al, 2013), which limits the usefulness of the results. However, more recent studies have also included gust effects (Miller et al, 2015;Giammanco et al, 2016). Therefore, the first objective of the study is to develop an approach to constructing an aeroelastic model of a tree with different crown configurations which satisfies the geometric similarity, dynamic similarity and dimensionless parameters including Froude number,…”