A Wind Gust Factor Database from 10 Tropical Cyclones for Use with GFE Tool Development

In support of the CSTAR tropical cyclone wind project, we examined the sustained winds, wind gusts, peak winds, and gust factors for ten tropical cyclones that impacted the Carolinas and Virginia. A table of the tropical cyclones examined along with a map of their tracks is shown below. Nearly all of the data collection and analysis was completed by student volunteer Dan Brown.

Hourly observations of winds and wind gusts from between 21 and 45 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. A summary of the METARS used with each storm is available in this file. Only observations from routine hourly METARs were used (special observations and observations not at the top of the hour were excluded). For the ten tropical cyclones examined, the hourly wind gust factor for each METAR location 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. It is a relatively simple statistic that is dependent on numerous factors, including the roughness length (exposure), distance from an upstream terrain change, stability, height, and the presence of convection. More information on gust factors in tropical cyclones can be found in Krayer and Marshall (1992), Vickery and Skerlj (2005), and Powell et al. (1996).

A total of 14,938 gust factors were computed for all of the storms with the number of gust factors for each storm varying considerably. The number of gust factor observations for each storm (GF Obs) is included in the table below along with maximum sustained winds at landfall, location, etc. It should be noted that the diverse set of station locations and tropical cyclones result in a data set that contains varied sensor types, roughness length, exposure, wind trajectory, etc.

Tropical Cyclones
Storm Name
Wind at Landfall
GF Obs
Track  Map
NHC Report
85 MPH
NC/SC border
70 MPH
South FL
70 MPH
75 MPH
75 MPH
105 MPH
105 MPH
105 MPH
115 MPH
105 MPH

The chart below is a scatter plot of the sustained winds in MPH versus gust factors for the 14,938 observations included in the study along with a best fit regression curve (y = -0.173ln(x) + 1.9506). 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 the ten tropical cyclones examined is shown below.  Note the very few occasions of gust factors of less than 1.1 with the most frequent gust factor falling between 1.3 and 1.4. 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 toward lower gust factor values.

The histogram below shows a plot of wind speeds with the occurrences of gust factors. The chart highlights the trend of larger gust factors observed with weaker wind and smaller gust factors in area of stronger winds.  For the 10-20 MPH wind range, the largest bin of gust factors is 1.3-1.4. As the winds increase to 20-30 MPH, the largest bin of gust factors is 1.2-1.3 while at winds of 30-40 MPH the largest bin of gust factors is 1.1-1.2.

The chart below shows a plot of sustained wind speeds and wind gusts for all of the storms examined. The average gust factor calculated for all ten storms is 1.47 and is shown with the red line in the chart below. The  black line is the best fit trend line which is similar to the mean value indicating that the mean value is a got fit with the whole data set.

Some details about the scatter plots and histograms are noted below:
1) The minimum gust factor observed was generally 1.1 with only 17.9% or 2,678 out of 14,938 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 10-20 MPH – gust factors typically range from 1.2 to 1.6
Sustained winds of 20-30 MPH – gust factors typically range from 1.1 to 1.4
Sustained winds of 30-40 MPH – gust factors typically range from 1.1 to 1.3
5) A fairly large fraction (41.5%) of gusts factors occur in the 1.2 to 1.6 range and 48.4% of gust factors occur in the 1.1 to 1.6 range.  The average gust factor among the 14,938 observations was 1.47.

The distribution of gust factors and the tendency for them to decrease 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.

The mean gust factor value for the 10 storms examined was 1.47 which is very similar to several previous studies. Those studies examined the gust factor while exploring important local influences such as surface roughness and exposure while considering the influence of time averaging periods. 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.  The chart below compares our data set with five other studies and notes the mean Gust Factor (GF) , whether the study compared Tropical Cyclones (TC) or Extratropical Cyclones (EC), the wind and wind gust measuring period, the exposures, and the standard deviation (σ).

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.

We feel rather confident that this data set is of sufficient quality and the distribution of gust factors is adequately similar to other studies to utilize the data set in additional work.  The mean gust factor we found was very similar to several other studies and the general distribution of gust factors as shown in the histogram is likewise similar. One limitation of the data set is the minimal number of very strong wind observations. This is not terribly surprising given the localized nature of hurricane force winds and the limited spatial density of the ASOS/AWOS network. This limitation was also noted in many of the other studies. Finally, this data set was composed of observations exclusively over land and did not include any marine observations. This deficiency still needs to be addressed.

With a workable dataset available, we are developing a couple of tools for use in the Gridded Forecast Editor (GFE).  Reliable and fully documented versions of these tools should be available by late August and will be introduced on the CIMMSE blog.  The tools will in part use the regression equation based on the 14,938 gust factor points to create WindGust grids based on the Wind grids and to create a new “GustFactor” grid which we are experimenting with. Other options to create WindGust grids will also be available. In addition, the CSTAR project is investigating an improved vortex model for use in the GFE TCMWindTool. Other complimentary tools are also under development. A snap shot of the tool interface is shown below.


Durst, C. S., 1960: Wind speeds over short periods of time. Meteor. Mag., 89, 181–186.

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]

Powell, Mark D., Samuel H. Houston, Timothy A. Reinhold, 1996: Hurricane Andrew’s Landfall in South Florida. Part I: Standardizing Measurements for Documentation of Surface Wind Fields. Wea. Forecasting, 11, 304–328. [Available online at http://dx.doi.org/10.1175/1520-0434(1996)011<0304:HALISF>2.0.CO;2]

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.

Vickery, P.J., and P.F. Skerlj, 2005,: Hurricane gust factors revisited, J. Struct. Eng., 131, 825-832. [Available online at http://www.asce.org/uploadedFiles/Communications-NEW/Hurricane/Hurricane_Gust_Factors_Revisited.pdf]

Yu, Bo, Arindam Gan Chowdhury, 2009: Gust Factors and Turbulence Intensities for the Tropical Cyclone Environment. J. Appl. Meteor. Climatol., 48, 534–552. [Available online at http://dx.doi.org/10.1175/2008JAMC1906.1]

This entry was posted in CSTAR, TC Inland and Marine Winds. Bookmark the permalink.

5 Responses to A Wind Gust Factor Database from 10 Tropical Cyclones for Use with GFE Tool Development

  1. Pingback: Hurricane Sandy Provides an Opportunity to Test and Develop New Tropical Cyclone Wind and Wind Gust Tools | CIMMSE

  2. Pingback: CIMMSE

  3. Pingback: Examining Wind Gust Factors with Hurricane Sandy across the Coastal Carolinas | CIMMSE

  4. Pingback: Wind, Wind Gusts, and Gust Factors Observed Over Marine Locations with Hurricane Irene | CIMMSE

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

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s