Examining Wind Gust Factors with Hurricane Sandy across the Coastal Carolinas

As a follow-up to Bryce’s timely post yesterday, we examined the sustained winds, wind gusts, and gust factors for Hurricane Sandy across coastal North Carolina and South Carolina. Nearly all of the data collection and some of the analysis was completed by Shawna Cokley.

Hourly observations of winds and wind gusts from 12 regular ASOS or AWOS METAR locations impacted by the fringes of the wind field associated with Hurricane Sandy were examined from 26 October through 28 October. The locations contained in the analysis include KCPC, KECG, KEWN, KFFA, KHSE, KILM, KMQI, KMRH, KNBT, KNKT, KOAJ, and KSUT. 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 MPH 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 1,369 gust factors were computed for Sandy.

Note that a previous blog post highlighted the examination of 14,938 gust factors for ten tropical cyclones across the Carolinas and Virginia – A Wind Gust Factor Database from 10 Tropical Cyclones for Use with GFE Tool Development.  This post will provide an update to that database.

The chart below is a scatter plot of the sustained winds in MPH versus gust factors for the 1,369 observations included in the study along with a best fit regression curve (y = -0.307ln(x) + 2.4539). In general, the chart demonstrates an inverse relationship between the wind speed and gust factor as well as a decrease in the number and variability of observations as wind speeds increase.

A histogram of the frequency of gust factors for Sandy across the Carolinas is shown below.  Note the very few occasions of gust factors of less than 1.2 with the most frequent gust factor falling between 1.4 and 1.5. The distribution of gust factors shown in this histogram is consistent with several other studies including Krayer and Marshall (1992), Paulsen and Schroeder (2005), and Conder and Peterson (2000), although our data set has a histogram that is shifted slightly to the right of the large ten storm histogram.

We also generated a regression equation for Sandy (shown in bold red below) and compared it to the curves for the ten other tropical cyclones. A plot of the curves for each of the ten storms and the combined curve for all of the ten original storms (shown in black) is included below.

Some thoughts about the gust factors associated with Sandy are noted below:

  1. The maximum sustained wind contained in the Sandy data set was only 39 MPH and the maximum wind gust was 50 MPH. The data set contained a large number of lower end winds and wind gusts. In fact, more than 72% or 987 out of the 1369 observations contained in this data set, had sustained winds of 20 MPH or less.  Only 58 observations had sustained winds of 30 MPH or more.
  2. The gust factors were extremely variable at low sustained wind speeds but generally converged and decreased with increasing sustained wind speed.
  3. The mean gust factor value for Sandy was 1.58 which was slightly greater than the ten storm mean of 1.47. Both of these values are very similar to several previous studies (see comparison chart from a previous blog post https://cimmse.files.wordpress.com/2012/08/10-storms-table.png). Schroder (2002) found an average gust factor of 1.49 during tropical cyclones at several airport locations while Krayer and Marshall (1992) found an average gust factor of 1.55 in a data set standardized to open terrain.
  4. The regression curve for Sandy was similar to the other storms examined but it tended to be on the higher side of the curves for each storm and slightly higher than the CSTAR  ten storm best fit regression curve, especially for lower end sustained winds.
  5. It is thought that the higher gust factors for Sandy were at least in part due to the observations included in this data set were on the western fringe of the storm as it was beginning the extratropical transition process. More specifically, these locations were away from the core of the storm and during the many of these observations, these observations were in areas of precipitation driven to a large extent, by frontogenetical forcing.
  6. Forecasters at NWS offices in Wilmington, Newport, and Raleigh North Carolina informally tested some new GFE smart tools and procedures during the storm based on research activities associated with the CSTAR project. Additional details on the tools used, the process, and some feedback will be shared in a subsequent blog post.

References
Conder, M. R., and R. E. Peterson, 2000: Comparison of Gust Factor Data from Hurricanes. Preprints, 24th AMS Conf. on Hurricanes and Tropical Meteor. Fort Lauderdale, FL. J53-J54. [Available online at  http://www.atmo.ttu.edu/conder/documents/Hurr-J7.5.PDF]

Krayer, William R., Richard D. Marshall, 1992: Gust factors applied to hurricane winds. Bull. Amer. Meteor. Soc., 73, 613–618.  [Available online at http://dx.doi.org/10.1175/1520-0477(1992)073<0613:GFATHW>2.0.CO;2]

Paulsen, B. M., J. L. Schroeder, 2005: An Examination of Tropical and Extratropical Gust Factors and the Associated Wind Speed Histograms. J. Appl. Meteor., 44, 270–280.[Available online at http://journals.ametsoc.org/doi/pdf/10.1175/JAM2199.1]

Schroeder, J. L., M. R. Conder, and J. R. Howard, 2002: “Additional Insights into Hurricane Gust Factors,” Preprints, Twenty-Fifth Conference on Hurricanes and Tropical Meteorology, San Diego, California, 39-40.

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One Response to Examining Wind Gust Factors with Hurricane Sandy across the Coastal Carolinas

  1. Pingback: Hurricane Arthur’s Wind Gust Factors and a CSTAR Research to Operations Success | CIMMSE

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