To evaluate the performance of CSTAR related research to operations activities, the sustained winds, wind gusts, and gust factors for Hurricane Matthew (2016) were examined across coastal and eastern Georgia, South Carolina, North Carolina, and Virginia. The image above or to the right is the tropical cyclone best track and wind radii data for Hurricane Matthew which shows the track of the storm near and along much of the southeast U.S. coast. The track data is a subjectively smoothed representation of a tropical cyclone’s history over its lifetime, based on a post-storm analysis of all available data. The data also contains wind radii information which is the farthest distance from the cyclone’s center where sustained winds of 34-, 50-, and 64-kts are occurring in each of four quadrants about the storm (NE, SE, SW, and NW).
The map below is a subjective analysis of the maximum wind gusts observed across NC during Hurricane Matthew. Many locations across the immediate coast observed wind gusts in excess of 70 MPH with a few locations across the Outer Banks reporting wind gust greater than 80 MPH. Wind gusts of 50 MPH or more extended inland to the southern and central I-95 corridor.
NWS Raleigh volunteer Victoria Oliva, examined the sustained winds, wind gusts, and gust factors for Matthew across coastal and eastern Georgia, South Carolina, North Carolina and Virginia. Hourly observations of winds and wind gusts from 60 regular ASOS or AWOS METAR locations impacted by the over land wind field associated with Tropical Storm Matthew were examined. The locations examined in this analysis extended from KSVN (Hunter Army Airfield near Savannah, Georgia) northeast along and just inland of the coast to KWAL (Wallops Island, Virginia).
Only observations from routine hourly METARs were used (special observations and observations not at the top of the hour were excluded). In addition, gust factors were only calculated for sustained winds of 10 kts or greater. For each observation, the hourly wind gust factor was computed. The gust factor is defined as the ratio between the wind gust of a specific duration to the mean (sustained) wind speed for a period of time. A total of 979 gust factors were computed for Matthew.
The maximum sustained wind contained in the Matthew data set was only 53 kts and the maximum wind gust was 70 kts with both observations from KHXD (Hilton Head, SC). The data set contained a large number of lower end sustained winds and wind gusts. Nearly 79% or 769 out of the 979 observations, contained in this data-set had sustained winds less than 25 kts. Only 85 observations, or around 9% of all observations, had sustained winds of 40 kts or more and only 8 observations had sustained winds of 40 kts or more.
The chart to the right is a scatter plot of the sustained winds in kts versus gust factors for the 979 observations included in the study along with a best fit regression curve (y = -0.231ln(x) + 2.2498). In general, the chart demonstrates an inverse relationship between the wind speed and gust factor. Not surprisingly, the gust factors with Matthew were rather variable at low sustained wind speeds and generally converged and decreased with increasing sustained wind speed. This chart is similar to the database of 15 storms used to develop the CSTAR TCM wind technique.
A histogram of the frequency of gust factors for Matthew is shown to the right. The average gust factor for Matthew was 1.58 which is somewhat higher than the average of 1.53 for the database of 15 tropical cyclones used to develop the CSTAR TC wind technique. The histogram data noted that the gust factors were most frequently noted between 1.5 and 1.6.
We generated a regression equation using the gust factor data set associated with Matthew and compared it to the regression equation used in the 15 storm database used to develop the CSTAR TCM wind technique. The figure to the right compares the Matthew regression equation (shown in red) to the 15 storm equation (shown in blue). They show a similar trend but the gust factors with Matthew are consistently a little higher than the 15-storm dataset.