A. H. Weber, M. J. Parker, and J. H. Weber
Westinghouse Savannah River Company
Aiken, SC 29808

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The Atmospheric Technologies Group (ATG) of the Savannah River Technology Center (SRTC) collects meteorological data for many purposes at the Savannah River Site (SRS) including weather forecasting. Wind gust forecasting is of special importance since many outdoor tasks are planned with the expectation that wind gusts will remain below about 4.5 m/s (10 mph). Typical work activities last for 4-8 hours, and a wind forecast is provided either one day or a few hours prior to an activity. Projects take place both day and night but not during inclement weather conditions such as thunderstorms with high wind gusts. This study focuses on wind gusts and also, to a lesser degree, turbulence intensities that occur in fair weather conditions near the surface over time periods from 1 hour to one week (168 hours).

Wind speed is monitored at nine 61-m tower sites across the SRS (Parker and Addis, 1993). One tower, Central Climatology (CC), is instrumented with sensors at 4, 18, and 36 m in addition to the SRS standard 61-m level. Cup anemometers are used to measure the mean wind speed and instantaneous wind gusts. Collocated with the cup anemometers, ATG uses bi-directional wind vanes (bivanes) to measure horizontal and vertical wind direction, and the standard deviations about these means are calculated. The standard deviation of the horizontal wind direction (s_A) and the standard deviation of the mean vertical wind direction (s_E) are good approximations to the turbulence intensities s_v/ and s_w/ (Weber, et al, 1975).

Ten years of meteorological tower data collected by ATG were available to analyze. Fifteen-minute averages of archived data were used to study the relationship between the mean wind speed, maximum instantaneous wind gust, and turbulence intensities expected during a typical work activity. Linear regression equations were used to establish the relationship between the mean wind speed and maximum gust for different atmospheric conditions.

Fifteen-minute averages of wind speed, turbulence intensities (s_A and s_E) , and the maximum wind gust over the corresponding fifteen-minute period for a 10-year period between January 1991 – December 2000 were extracted from the data archives for analysis. Simple quality assurance tests were applied to the data during the data extraction process. These tests mainly consisted of rejecting data that violate instrument capabilities. Additional outlying data points were rejected after examining time series and scatter plots.

It should be emphasized that it was not the objective of this study to examine extreme gusts as might exist during severe weather such as thunderstorms, hurricanes, tornadoes, etc. (for those see Weber, et al, 1998). Rather, the study was directed at examining wind speeds, gusts and turbulence that could occur when employees were not prohibited from working outdoors.

The distributions of one-hour scalar-averaged wind speed, maximum wind gust, s_A and s_E at the 4-meter height are shown in Figs. 1-4. Fig. 1 shows a distribution with two peaks, one near 1.5 m/s and a second near 0.75 m/s. The lower peak may be caused by the anemometer’s increased starting threshold due to occasional dew accumulation. Double peaks in the wind speed distribution do not occur for any of the other (higher) tower levels.

Figure 3. The frequency distribution of one-hour scalar averages of the standard deviation of
wind azimuth s_A at the 4-meter height during the 10-year period 1991-2000.

The distribution of the standard deviation of elevation angle s_E is shown in Fig. 4. This distribution also contains double peaks, one near 10 degrees and the second near 1.5 degrees. The lower peak may be due to a higher starting threshold caused by occasional dew accumulation. The distribution for s_E at the 18-meter level is shown in Fig. 5. The double peaks are no longer present (this is also true for the 36-m and 61-m levels)

After screening the data and examining the statistical distributions, one-year averages of the 15-minute wind speeds and gusts were plotted over the entire 10-year span and are shown in Figs. 6-9. The time series for wind speed in Fig. 6 shows no significant changes over the ten-year period. The mean wind gusts for the ten-year period also show no significant changes except for a small increase (at all four levels) in the first 2-3 years.

The 4-meter turbulence intensities (s_A and s_E) for 4 and 18 meter heights are shown in Figs. 7 & 9. Fig 7 for s_A shows a reasonably steady behavior over the 10-year period. The plot of s_E in Fig. 7 shows a significant increase during 1999-2000, however this increase is not present in Fig. 9 for the 18-m level. The increase in s_E after 1998 at 4-meters is quite likely due to changes in roughness (obstacles placed upstream) of the low-level wind instruments.

One would expect the mean wind speed and maximum gust to be highly correlated. The turbulence intensities s_A and s_E should be correlated as well. In order to examine correlation among variables at the 4-m height the 15-minute averages for wind speed, maximum gust, s_A and s_E were averaged over a one-hour time period and the Pearson correlation coefficient was computed. (The wind gust is the maximum gust in the one-hour period.) Table 1 shows the correlation among the variables for the one-hour averaging time. The Pearson correlation coefficient between wind speed and gust is 0.95. None of the other correlation coefficients are nearly this high. The second highest correlation in Table 1 is 0.54 between maximum gust and s_E. The correlation coefficient between the turbulence intensities s_A and s_E is only 0.17.

In order to determine the effect of solar heating on the correlations, the 24-hour day was divided into four 6-hour time periods as follows: afternoon (12 £ EST £ 17), late evening (18 £ EST £ 23), pre-sunrise (0 £ EST £ 5), and morning (6 £ EST £ 11). The results for the 4-m height are shown in Tables 2-5. The correlation between mean speed and maximum gust is about the same throughout the day 0.91-0.95.

The correlation between the remaining variables at 4-m is not strong (all less than 0.65). However, it is interesting to note that the turbulence intensity s_E has the strongest correlation (around 0.60-0.65) with both wind speed and maximum gust during the late evening and pre-sunrise hours, rather than during the hours when solar heating would normally be taking place. The turbulence intensities s_A and s_E are positively correlated during the daytime and negatively correlated at night. (The averaging for the standard deviation of wind direction s_A is done with simple scalar addition rather than taking into account wind meandering during the course of the hour.)

Near the ground during the nighttime hours when the wind speeds are light, the bivanes cease to function reliably due to drooping tails. The result is that s_E is erroneous (large). This can be appreciated by examining how the correlation coefficient between s_A and s_E increases with height. Table 6 shows that at the 61-m height the correlation coefficient between s_A and s_E has risen to 0.75. Correlation among the variables could be investigated further by establishing some wind speed threshold at 4-m and subsetting the data set (this is planned for future work).

Since the wind speed and maximum gust are highly correlated, it is useful to provide the linear regression model between the two variables. Using the one-hour scalar averages of the wind speed, the linear regression equation for the 1-hr wind gust is

G_01-hr = 2.19S_01-hr – 0.11 (m/s),

where G is wind gust and S is wind speed.

Similarly the regression equations for 4-hr, 8-hr, 24-hr, 48-hr, and 168-hr averages are:

G_04-hr = 2.07S_04-hr + 0.13 (m/s)
G_08-hr = 1.84S_08-hr + 0.57 (m/s)
G_24-hr = 1.62S_24-h + 1.03 (m/s)
G_48-hr = 1.41S_48-hr + 1.45 (m/s)
G_168-hr = 1.41S_168-hr + 1.34 (m/s)

It should be noted that the correlation coefficient between the wind speed and maximum gusts drops significantly (less than 0.50) for all time averages greater than 8-hours. However, the linear regression equations for 1, 4, and 8-hour averaging times provide a reliable means of forecasting the maximum wind gust for outside work during fair weather conditions at SRS.

Similar regression equations can be developed for the heights 4, 18, 36, and 61-meters on the CC tower for the 4-hour averaging times. These are

G_04-m = 2.07S_04-m + 0.13 (m/s). (04-m)
G_18-m = 1.77S_18-m + 0.39 (m/s). (18-m)
G_36-m = 1.67S_36-m + 0.20 (m/s). (36-m)
G_61-m = 1.44S_61-m + 0.54 (m/s). (61-m)

Predicting the maximum wind gust from the average wind speed near the surface, for a work-period of 4 hours during fair weather at SRS can most simply be accomplished by doubling the wind speed. The 95% confidence interval about the regression line is

G_04-hr(95%-reg. line) ± 1.96[Var(S_04-hr)]^1/2; where
Var(S_04-hr) = 4.42E-4 + 2* S_04-hr (-1.82E-4)
+ (S_04-hr)²(9.64E-05)

The 95% confidence interval for an individual point in the scatter plot is

G_04-hr(95%-point) ± 1.96 [Var(S_04-hr) + 2.02]^1/2.

The confidence intervals are shown in Fig. 10 for a random sample of 10% of the total data.

The 1-hr and 4-hr averaged wind speeds near the ground in fair weather conditions are highly correlated to maximum wind gusts during the same period. A useful approximation is that the maximum surface wind gust can be predicted by doubling the average wind speed for either a 1 or 4 hour period. Similarly, aboveground (up to 61- m) wind gust forecasts can be simply applied from regression equations (Section 4). Synoptic or mesoscale models that predict the mean wind speed can then be used as a starting point to forecast the working conditions for gust-sensitive activities at the SRS.

The 4-m turbulence intensities s_A and s_E are not highly correlated during the day and are even negatively correlated at night. As the height is increased the correlation coefficient between s_A and s_E increases to 0.75 at the 61-m level (all hours of the day included).

1. Parker, M. J. and R. P. Addis. 1993: Meteorological Monitoring Program at the Savannah River Site. WSRC-TR-93-0106. Westinghouse Savannah River Company, Aiken, SC 29808.
2. Weber, A. H., J. S. Irwin, J.P. Kahler, and W. B. Petersen, 1975: Atmospheric turbulence properties in the lowest 300 meters. EPA-600/4-75-004, North Carolina State University, Raleigh, NC. (Available through the U.S. Dept. of Commerce, Superintendent of Documents, NTIS, Springfield, VA 22161).
3. Weber, A. H., J. H. Weber, M. J. Parker, C. H. Hunter, C. O. Minyard, 1998: Tornado, maximum wind gust, and extreme rainfall event recurrence frequencies at the Savannah River Site. WSRC-TR-98-00329. Westinghouse Savannah River Company, Aiken, SC 29808.