Examining Gust Factors at the Land-Water Interface More Closely

A recent CSTAR project with NC State and over a half dozen WFOs in the Southeast, examined ways to improve inland wind and wind gust forecasts associated with tropical cyclones. The CSTAR project produced three primary improvements including a bias correction of the TCM wind vortex, using collaborated wind reductions over land, and using collaborated wind gust factors for wind gust grids across the domain.

Fig. 1. Example wind gust forecast as viewed in GFE showing wind gusts at land locations in southeast VA are greater than the wind gusts at adjacent marine areas.

Fig. 1. Example wind gust forecast as viewed in GFE showing wind gusts at land locations in southeast VA are greater than the wind gusts at adjacent marine areas.

Feedback from project participants noted that at times, the use of gust factors near the land-water interface can produce undesirable wind gusts in some scenarios. In an example described in this previous blog post (Examples of Gust Factor at Water-Land Interface), wind gusts at land locations in southeast VA are greater than the adjacent marine areas.  It is worth noting that the processes governing wind gusts at the land-water interface can be quite complicated and occur on very small spatial scales, including those smaller than current forecast grid lengths in GFE. Still, project participants desired a more seamless transition between the land and marine wind gust values.

Fig. 2. The location of the 9 oceanfront locations examined and a table noting the approximate location of the observational platform with the closest surf zone.

Fig. 2. The location of the 9 oceanfront locations examined and a table noting the approximate location of the observational platform with the closest surf zone.

compare.table

Fig. 3. A table comparing data from the 5 locations examined including all locations, non-oceanfront (inland) locations, oceanfront locations, Hatteras, NC (KHSE), and all marine locations.

In order to examine this, NC State student Victoria Oliva, examined the sustained winds, wind gusts, and GFs for 15 tropical cyclones that impacted the Carolinas, Virginia and Maryland. Routine hourly METAR observations with sustained wind speeds of 10 kts or more were used to calculate the hourly GF for each location.  For land locations, the METAR locations varied for each storm and were selected to capture the variations in the wind field with a total of 13,121 GFs computed. In order to examine the land-water interface more closely, we examined gust factors at 9 locations in which the METAR is located in close proximity to the coast, specifically within at least 2 miles from the surf zone. We labeled these locations as “oceanfront.” The METARs included in the oceanfront data set include KCRE, KFFA, KHSE, KMQI, KMRH, KMYR, KNBT, KNJM, and KSUT and their locations are shown in Figure 2. A total of 2,289 GFs from the 9 locations for the 15 storms were examined. In addition, the Hatteras, NC observation (KHSE) was singularly examined as it is located on an island just 0.2 miles from the surf zone. A total of 488 GFs were computed from 15 storms that impacted KHSE. Finally, GF were computed for more than two dozen buoys with an anemometer height of 5 meters that were impacted by the 15 storms. Hourly marine observations with wind speeds of 10 knots or more and wave heights less than 5 meters were used to compute 3,026 gust factors.

Fig. 4. Regression curves for the various locations examined including all locations, non-oceanfront (inland) locations, oceanfront locations, Hatteras, NC (KHSE), and all marine locations.

Fig. 4. Regression curves for the various locations examined including all locations, non-oceanfront (inland) locations, oceanfront locations, Hatteras, NC (KHSE), and all marine locations.

A table comparing the gust factors from the various locations is shown above in Figure 3. The locations include: all gust factors, non-oceanfront (inland) locations, oceanfront locations, Hatteras, NC (KHSE), and all marine locations. The results were surprising with the oceanfront gust factors having a slightly larger average and larger mean value than the non-oceanfront land locations. We had expected the oceanfront gust factors to be considerably smaller than the non-oceanfront or inland gust factors.  The KHSE average and mean gust factors were slightly lower than the average and mean oceanfront gust factor. Still, we expected the KHSE gust factor would be much lower.  The KHSE average gust factor of 1.50 was still significantly higher than the average marine gust factor average of 1.23. A plot of regression curves from the various locations is shown in Figure 4. Note the similarity in the curves for all of the land locations, whether inland, oceanfront, or KHSE which is located on an island. The land locations differ considerably with the gusts factors for the marine locations shown in the blue curve.

It was hoped that the gust factor values for the oceanfront locations would show a transition from the non-oceanfront or inland values where gust factors average 1.53 to the much lower marine values that average 1.23. Since the oceanfront observations were unable to capture a gradual change between the land and marine gust factors, some sort of blended approach could provide the transition that forecaster’s desire.
Additional investigation of oceanfront gust factor based on wind direction would be instructive. In addition, examining observations right at the shore and near the dunes might provide the expected transition. It is worth noting however, that KHSE is located on an island and is well offshore from the mainland, and that wind from just about any direction would provide a long fetch marine exposure.

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