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Developing a Dataset of Wind Gust Factors to Improve Forecasts of Wind Gusts in Tropical Cyclones

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Uploaded on Nov 12, 2013

Jonathan Blaes
NOAA/NWS Raleigh, NC
David Glenn
NOAA/NWS Newport, NC
Donald Hawkins
NOAA/NWS Wilmington, NC

Forecasting wind gusts in tropical cyclone environments can be very challenging. NWS forecasters are tasked with creating gridded forecasts of wind gusts that are accurate, while also consistent with guidance from the National Hurricane Center and with adjacent Weather Forecast Offices (WFOs). In support of a Collaborative Science, Technology, and Applied Research tropical cyclone wind project with North Carolina State University, we examined the sustained winds, wind gusts, and wind gust factors for ten tropical cyclones that impacted the Carolinas and Virginia. 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, distance from upstream geophysical changes, boundary layer stability, and the presence of convection.

Gust factors were computed for both land locations from METAR observations and marine locations via buoy observations for the ten tropical cyclones. The diverse set of station locations and tropical cyclones result in a dataset that contains varied sensor types, roughness lengths, exposures, wind trajectories, etc. A mean gust factor for both the land and marine locations will be shown. Given the variability of the gust factor with changes in sustained wind speed, a best fit regression curve was developed for the land locations and will be shown. It will be demonstrated that the distribution of gust factors with wind speeds, the mean gust factor, and gust factor extremes in our dataset is similar to results in other similar studies.

With this dataset we have developed a set of tools and procedures for forecasters to use in the Graphical Forecast Editor (GFE). They include a tool to produce wind gusts directly from the wind based on either the regression equation or the mean gust factor. In addition, a more robust method has been developed to initially populate a WindGustFactor grid based on either the mean gust factor or the regression curve and then allow the forecaster to adjust the grid for local effects, such as boundary layer stability, prior to calculating the wind gust. Benefits of this new method will be shown. Six WFOs across the Southeast will be testing and evaluating these tools during the 2013 hurricane season.

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