Gust Factors from Five Tropical Cyclones Reveal Similarities and May Lead to New GFE Tools

In support of the CSTAR tropical cyclone wind project and an outgrowth of an event summary on Hurricane Irene, we examined the sustained winds, wind gusts, peak winds, and gust factors for five tropical cyclones that impacted the Carolinas and Virginia. The five storms include Irene (2011), Hanna (2008), Ernesto (2006), Charley (2004), and Isabel (2003). Student Volunteer Dan Brown completed the data retrieval and analysis for four of the five tropical cyclones examined as well as the statistical analysis and most of the heavy lifting with this study. NC State student volunteers Rebecca Duell and Lindsey Anderson developed the overall methodology and completed the analysis of Hurricane Irene.

Hourly observations of winds and wind gusts from approximately 30 regular ASOS or AWOS METAR locations impacted by the various storms were collected. The locations varied for each storm and were selected to capture the variations in the wind field.  Observations from routine hourly METARs were used (special observations and observations not at the top of the hour were excluded. Some desired observations were unavailable due to perceived communication or power problems.

A table of the tropical cyclones examined along with a map of their tracks is shown below. The track map was generated from the excellent Historical Hurricane Tracks web site.

Tropical Cyclones Examined
Storm Name
Date
Landfall Location
Max Sustained Winds at Landfall
Track  Map
NHC Report
Irene
27-Aug-11
NC
85 MPH
Link
Link
Hanna
6-Sep-08
NC/SC border
70 MPH
Link
Link
Ernesto
30-Aug-06
South FL
70 MPH
Link
Link
Charley
13-Aug-04
FL
75 MPH
Link
Link
Isabel
18-Sep-03
NC
105 MPH
Link
Link

For the five tropical cyclones examined, the hourly wind gust factor for each METAR location was computed as the ratio of the wind gust to the sustained wind speed. A total of 6464 total gust factors were computed for all of the storms with the number of gust factors for each storm varying considerably: Irene (1055), Hanna (917), Ernesto (1107), Charley (290), and Isabel (3095).  It should be noted that the diverse set of station locations and storms result in a data set influenced by sensor type, roughness length, varied exposure, wind trajectory, etc.  The impact of these variables can be seen in the gust factor data presented below.

The chart below shows the sustained winds versus gust factors for the 6464 observations included in the study along with a best fit regression curve. In general, the chart demonstrates an inverse relationship between the wind speed and gust factor as well as a decrease in the number of observations as wind speeds increase.


A histogram of the frequency of gust factors for the five tropical cyclones examined is shown below.  Note the very few occasions of gust factors of less than 1.2 with the most frequent gust factor falling between 1.3 and 1.4.


Some details about the scatter plot and histogram are noted below:
1) The minimum gust factor observed was generally 1.2 with only 9.2% or 596 out of 6464 observations accompanied by a gust factor of less than 1.2.
2) The gust factor is quite varied at low sustained wind speeds but generally converges and decreases with increasing sustained wind speed.
3) A one size fits all gust factor does not apply given the various mesoscale, microscale , and observation specific variables involved.
4) There is a large variation in gust factors with changes in sustained winds:
Sustained winds of 20 MPH or less – gust factors typically range from 1.2 to 2.5.
Sustained winds of 20-30 MPH or less – gust factors typically range from 1.2 to 1.8.
Sustained winds of 30 MPH or greater – gust factors typically range from 1.2 to 1.6.
5) A fairly large fraction (43%) of gusts factors occur in the 1.3 to 1.6 range and 66% of gust factors occur in the 1.2 to 1.7 range.  The average gust factor among the 6464 observations was 1.58 with a median value of 1.51.

The distribution of gust factors and the tendency for them to decreases and become more consistent with increasing wind speed is likely explained by the reduced frequency of stronger winds, the tendency of the stronger winds to be located near the coast with on-shore exposure or reduced surface roughness, and reduced mixing near the core of the storm.

We also generated regression equations for each of the storms individually and then combined them into one equation. A plot of the curves for each storm and the combined curve for all storms is shown below.

Several studies have examined the gust factor while exploring important local influences such as surface roughness and exposure while considering the influence of time averaging periods.  The average gust factor we found during our 5 storms was 1.58 which is similar to other studies. Conder and Peterson (2000) noted an average gust factor of 1.62, while Krayer and Marshall (1992) found an average gust factor of 1.55. The distribution of gust factors with sustained winds in our initial study is fairly consistent with these studies as well. While we have not broken down the gust factors with respect to exposure and surface roughness, other studies provide some guidance. One study from Harper et al. (2008) noted the different gust factors for the peak 3 second gust occurring within a one minute period for various exposures; in-land (roughly open terrain) 1.49, off-land (offshore winds at a coastline) 1.36, off-sea (onshore winds at a coastline)  1.23, and at-sea (offshore > 20km) 1.11

The next steps for this project are to add 5 more storms to the database including Floyd, Bertha, Fran, Dennis, and Gaston and update the various scatter plots, histograms, and other statistics. In addition, these results will be used to demonstrate and train forecasters about the varied distribution of wind gusts associated with tropical cyclones. Finally, we have already developed a tool for GFE that will use a regression equation to produce gust factors and/or wind gusts based on the sustained wind speed. With a larger data set and more testing, we feel that this tool can be shared and experimented with.

Harper, B. A., J. D. Kepert, and J. D. Ginger, 2008: Wind speed time averaging conversions for tropical cyclone conditions. Proc. 28th Conf. Hurricanes and Tropical Meteorology, Orlando, FL, Amer. Meteor. Soc., 4B.1. [Available online at  http://ams.confex.com/ams/28Hurricanes/techprogram/paper_138064.htm%5D

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%5D

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

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4 Responses to Gust Factors from Five Tropical Cyclones Reveal Similarities and May Lead to New GFE Tools

  1. bptyner says:

    Thanks for adding this post and conducting the gust factor analysis. I think this supports some of our preliminary findings, particularly with the increase in gustiness as wind speeds decrease. I hope to piggy back on this gust factor analysis and show plots of gust factors at each individual station and separate by wind direction. I think this can help in the development of a simple gust factor model to be used by each WFO. Great work, Dan, Rebecca, and Lindsey!

  2. Pingback: Gulf Coast Rising News | Gust Factors from Five Tropical Cyclones Reveal Similarities and …

  3. hurricanebob says:

    Our summer Hollings student, Ryan Kramer, just completed a wind gust climatology for our CWA that used all data (not just tropical) since 2007 and found an average gust factor of 1.51 for land sites (excluding those along the immediate coast) and 1.21 for marine/coastal land sites with a similar inverse relationship between sustained winds and gusts and some variation based on wind direction.

  4. Jonathan Blaes @ WFO RAH says:

    Bob, we’ll be in touch about this.

    JB

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