NASA/CR-2012-216311 

Vandenberg Air Force Base Upper Level 

Wind Launch Weather Constraints 

Jaclyn A. Shafer 

ENSCO, Inc., Cocoa Beach, Florida 

NASA Applied Meteorology Unit, Kennedy Space Center, Florida 

Mark M. Wheeler 

ENSCO, Inc., Cocoa Beach, Florida 

NASA Applied Meteorology Unit, Kennedy Space Center, Florida 

July 2012 
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NASA/CR-2012-216311 

Vandenberg Air Force Base Upper-Level 

Wind Launch Weather Constraints 

Jaclyn A. Shafer 

ENSCO, Inc., Cocoa Beach, Florida 

NASA Applied Meteorology Unit, Kennedy Space Center, Florida 

Mark M. Wheeler 

ENSCO, Inc., Cocoa Beach, Florida 

NASA Applied Meteorology Unit, Kennedy Space Center, Florida 

National Aeronautics and 

Space Administration 

Kennedy Space Center 

Kennedy Space Center, FL 32899-0001 

July 2012 
Acknowledgements 

The author would like to thank Dr. William Bauman and Ms. Winnie Crawford of the Applied 

Meteorology Unit and Dr. Lisa Huddelston and Dr. Frank Merceret of the Kennedy Space 

Center Weather Office for lending their time, data management, and statistical expertise to this 

task. 

2 

Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 

This report is also available in electronic form at 

http://science.ksc.nasa.gov/amu/ 
Executive Summary 

The 30th Operational Support Squadron Weather Flight (30 OSSWF) provides 

comprehensive weather services to the space program at Vandenberg Air Force Base 

(VAFB) in California. One of their responsibilities is to monitor upper-level winds to ensure 

safe launch operations of the Minuteman Ill ballistic missile. The 30 OSSWF tasked the 

Applied Meteorology Unit (AMU) to analyze VAFB sounding data with the goal of 

determining the probability of violating (PoV) their upper-level thresholds for wind speed 

and shear constraints specific to this launch vehicle, and to develop a tool that will calculate 

the PoV of each constraint on the day of launch. 

In order to calculate the probability of exceeding each constraint, the AMU collected and 

analyzed historical data from VAFB. The historical sounding data were retrieved from the 

National Oceanic and Atmospheric Administration Earth System Research Laboratory 

archive for the years 1994-2011 and then stratified into four sub-seasons: January-March, 

April-June, July-September, and October-December. 

The maximum wind speed and 1 000-ft shear values for each sounding in each subseason were determined. To accurately calculate the PoV, the AMU determined the 

theoretical distributions that best fit the maximum wind speed and maximum shear 

datasets. Ultimately it was discovered that the maximum wind speeds follow a Gaussian 

distribution while the maximum shear values follow a lognormal distribution. These results 

were applied when calculating the averages and standard deviations needed for the 

historical and real-time PoV calculations. In addition to the requirements outlined in the 

original task plan, the AMU also included forecast sounding data from the Rapid Refresh 

model. This information provides further insight for the launch weather officers (LWOs) 

when determining if a wind constraint violation will occur over the next few hours on day of 

launch. 

The interactive graphical user interface (GUI) for this project was developed in Microsoft 

Excel using Visual Basic for Applications. The GUI displays the critical sounding data easily 

and quickly for the LWOs on day of launch. This tool will replace the existing one used by 

the 30 OSSWF, assist the LWOs in determining the probability of exceeding specific wind 

threshold values, and help to improve the overall upper winds forecast for the launch 

customer. 

1 
Table of Contents 

Executive Summary ................................................................................................................... 1 

List of Tables .............................................................................................................................. 4 

1. Introduction ........................................................................................................................... 5 

2. Previous 30 OSSWF Operational Tool. ................................................................................. 6 

3. Historical Data ...................................................................................................................... 7 

3.1 Collection ..................................................................................................................... 7 

3.2 Processing ................................................................................................................... 7 

3.3 Data Distributions ......................................................................................................... 8 

3.4 Probability of Violation ................................................................................................ 11 

4. Excel Graphical User Interface (GUI) .................................................................................. 13 

4.1 Sounding Data ........................................................................................................... 13 

4.2 Model Data ................................................................................................................ 13 

5. Summary and Future Work ................................................................................................. 18 

6. List of Acronyms ................................................................................................................. 19 

7. References ......................................................................................................................... 20 

2 
List of Figures 

Figure 1. Graphical representation of a northwest wind .................................................................... 6 

Figure 2. The PDFs of the maximum speed observations (blue, left axis and solid grid lines) 

and In of the observations (red, right axis and dotted grid lines) ..................................... 9 

Figure 3. Curves showing the relationship of the z values for the observations (blue) and the In 

of the observations (red) to the theoretical Gaussian z values ..................................... ! 0 

Figure 4. Same as Figure 3 but for wind shear. ................................................................................ II 

Figure 5. Screen shot overview of 30 OSSWF GUI display ............................................................ l5 

Figure 6. Example screen shot of the X 1 00 worksheet tab in GUI ................................................ 16 

Figure 7. Screen shot of the RAP tab in GUI .................................................................................... l7 

3 
List of Tables 

Table 1. Summary of calculations used to determine 1 000-ft shear .............................................. 8 

Table 2. The first four moments including the median value of the observations and 

In( observations) wind speed data for January-March ....................................................... 9 

Table 3. The first four moments including the median value of the observations and 

In( observations) wind shear data for January-March ...................................................... 10 

Table 4. Summary of maximum wind speed PoV statistics per sub-season .............................. 11 

Table 5. Summary of maximum 1 000-ft shear PoV statistics per sub-season ........................... 12 

Table 6. List of Excel's PoV calculations for the maximum wind speed and shear datasets. 

The output values were multiplied by 100 to convert to percentages .......................... 12 

Table 7. Summary of PoV (%)values per sub-season .................................................................. 16 

4 
1. Introduction 

The 30th Operational Support Squadron Weather Flight (30 OSSWF) provides 

comprehensive weather services to the space program at Vandenberg Air Force Base (VAFB) 

in California. One of their responsibilities is to monitor upper-level winds to ensure safe launch 

operations of the Minuteman Ill ballistic missile. The 30 OSSWF tasked the Applied 

Meteorology Unit (AMU) to analyze historical VAFB sounding data with the goal of determining 

the probability of violating (PoV) their upper-level thresholds for wind speed and shear 

constraints specific to this launch vehicle. The result is a tool that will replace their existing one, 

assist the 30 OSSWF Launch Weather Officers (LWOs) in determining the probability of 

exceeding specific wind threshold values, and improve the overall upper-level winds forecast. 

5 
2. Previous 30 OSSWF Operational Tool 

The 30 OSSWF provided the AMU with a Microsoft Excel spreadsheet containing their 

current operational tool used for calculating wind shear and determining the likelihood of 

violating specific upper-level wind constraints. The AMU examined the contents of the file to 

determine how the values were calculated; it is important for the final tool to use the same 

equations as those used by the 30 OSSWF for consistent operational results. Some errors in 

the 30 OSSWF tool were discovered and the AMU informed the 30 OSSWF of the 

inconsistencies. 

The 30 OSSWF tool referenced an incorrect column in the Excel worksheet when 

calculating the 1 000-ft wind shear, and the x (east-west) and y (north-south) wind components 

were miscalculated. As an example, based on compass headings, if the wind direction is 

northwest at 315', the wind is blowing towards 135'. This is represented graphically in Figure 1 

by a green vector beginning at the origin (x = 0, y = 0) and pointing toward the southeast. The 

wind vector is in the bottom right quadrant, resulting in a positive x-component and negative ycomponent. The AMU calculations reflect these signs while the 30 OSSWF tool showed the 

opposite. The existing references and calculations in the 30 OSSWF tool were modified to 

correct these issues. To confirm the new calculations were correct, the AMU output was 

compared to that of the 30 OSSWF tool using sounding data provided by the 30 OSSWF. 

0 0 0 

315 360 10 

0 

0 0 

270 90 

Vl 

X 

240 ro 0 

0 

0 

180 135 

Figure 1. Graphical representation of a northwest wind 

6 
3. Historical Data 

The AMU collected, processed, and analyzed VAFB sounding data to determine the PoV of 

their specific wind speed and shear constraints. This included interpolating data to heights 

required for operations and determining how the data were distributed. 

3.1 Collection 

In order to analyze the upper-level thresholds for wind speed and shear and calculate their 

PoV, the AMU had to collect historical sounding data from VAFB. The ideal data for this task 

would have been the soundings collected through the Automated Meteorological Profiling 

System (AMPS) at VAFB. In their initial proposal for this task, the 30 OSSWF expressed 

concern about being able to supply this data set to the AMU. Due to limitations of their AMPS 

system, it would take considerable resources to put the data in a format that could be used in 

the task. The 30 OSSWF sent a sample AMPS file to the AMU in a readable text format, 

however, the file had no header information identifying which variables were listed, and it was 

difficult to discern the variables from the values. 

To circumvent these issues, the 45th Weather Squadron (45 WS) suggested using the 

Range Reference Atmosphere (RRA) data for VAFB. The RRA contains the monthly means and 

standard deviations of the sounding variables every 0.25 km (-820ft) using soundings collected 

in the years 1990-2001 (https://bsx.edwards.af.mil/weather/rcc.htm). Assuming the variable 

values were normally distributed, the means and standard deviations were used in an Excel 

formula to calculate the probabilities of exceeding the desired thresholds. The probabilities 

never exceeded 1%, and were most often much closer to 0%. The AMU determined this would 

not be useful information for the 30 OSSWF. 

The AMU team met and decided that useful results would more likely be found by using 

individual soundings. VAFB soundings were available in the National Oceanic and Atmospheric 

Administration (NOAA) Earth System Research Laboratory (ESRL) archive and in a format that 

was easy to process. These VAFB soundings were downloaded from the NOAA ESRL site 

(http://www.esrl.noaa.gov/raobs/) for the years 1994-2011 . The AMU modified and wrote scripts 

to import the sounding data into TIBCO Spotfire S+ (TIBCO 201 0) for analysis, extracted the 

data needed for the task requirements, and created monthly data files for the maximum wind 

speed and maximum 1 000-ft shear constraints. 

3.2 Processing 

To calculate the PoV for each wind constraint, the data for each sounding needed to be 

interpolated to consistent 1 000-ft height levels. The AMU used Peri scripts to add the required 

levels to each sounding and then interpolated the wind direction and speed to those 1 000-ft 

heights. So that the PoV could be depicted accurately for the different times of the year, the 

soundings were stratified into four different sub-seasons: January-March, April-June, JulySeptember, and October-December. The maximum wind speed and maximum 1 000-ft shear 

values for each sounding per sub-season were then determined. The 30 OSSWF also 

requested the 1 000-ft shear be calculated at multiple intervals. For example, in addition to the 

1 000-2000ft shear, the 1100-21 OOft, 1200-2200ft, etc. values were also calculated. These 

values were used in statistical equations to calculate the PoV for each constraint. All 1 000-ft 

layer shear values were calculated using the equations depicted in Table 1. 

7 
Table 1. Summary of calculations used to determine 1 000-ft 

shear 

Variable Description Formula 

u-component wind u = Wspd*cos(270 - Wdir)*pi/180 

v-component wind v = Wspd*sin(270 - Wdir)*pi/180 

u-component shear u-shear(Layer) = u(Upper) - u(Lower) 

v-component shear v-shear(layer) = v(Upper) - v(Lower) 

Shear of layer Shear(Layer)= Sqrt(u-shea~ + v-shea~) 

Where: Wspd = Wind speed (kt) at given height. 

Wdir =Wind direction (degrees) at given height. 

Upper= top height (ft) of the layer of interest. 

Lower = bottom height (ft) of the layer of interest. 

pi = 3.14159265358979 

3.3 Data Distributions 

In order to accurately calculate the PoV for each wind constraint, the distribution of the 

maximum wind speed and shear datasets had to be determined. The AMU estimated the 

theoretical distributions of the observations with the help of Dr. Frank Merceret of the Kennedy 

Space Center (KSC) Weather office. 

The simplest distribution in classical statistics, and with many applications in the 

atmospheric sciences, is the Gaussian distribution (Wilks, 2006). If the mean and standard 

deviation of each dataset can be calculated, the probability of exceeding any value X can be 

obtained directly from Gaussian distribution tables, including those in standard software 

packages like Excel (Merceret, 2009). Similarly, the lognormal distribution is often observed in 

nature, particularly with wind features (Smith and Merceret, 2000). Based on this previous work, 

the AMU first created the probability density functions (PDFs) of the maximum speed 

observations and the natural log (In) of the observations, shown in Figure 2, to help determine if 

the data distribution was Gaussian or lognormal. The observation curve was noisy and 

positively skewed, and the In curve was smooth and negatively skewed. Table 2 shows the four 

moments (mean, standard deviation, skewness, kurtosis) of the data sets and their median 

values. The mean and median are similar for both sets of values. For Gaussian and lognormal 

distributions, skewness and kurtosis are 0. The values for the observed distributions in Table 2 

are not 0, but have absolute values of less than 1. The observations have smaller magnitudes of 

skewness and kurtosis than the In values, indicating they may be more Gaussian distributed 

than lognormal. 

8 
0.025 

II) .2 0.02 

... 

ru i:: 0.015 

~ 

II) 

~ 0.01 

0.005 

0 

Probability Density Functions for the 

January-March Sub-Season Max Speeds 

Max Speeds (8-178 kt} 

-.-observations - ln(Observations) 

0.8 

0.7 

0.6 u; 

c 

0 0.5 ·~ 

ru 

0.4 ~ II) 

0.3 ..a 

0 

0.2 :5 

0.1 

0 

Figure 2. The PDFs of the maximum speed observations (blue, left axis and solid 

grid lines) and In of the observations (red, right axis and dotted grid lines). 

Table 2. The first four moments including the median value of the 

observations and In( observations) wind speed data for January-March 

Values Mean Median Standard Skewness Kurtosis Deviation 

Observations 71 .71 69 29.57 0.51 -0.06 

In( Observations) 4.18 4.23 0.45 -0.62 0.44 

Dr. Merceret transformed these datasets to normalized values used in standard Gaussian 

probability tables: 

x- x 

z=--, 

s 

where x is the observed or In value, x is the mean, and s is the standard deviation of the 

sample. The value z is dimensionless. Figure 3 compares the z values for the observations and 

In of the observations to the theoretical value of z for the Gaussian cumulative distribution. For 

both curves, z increases as speed increases on the x-axis. A straight line would indicate a 

Gaussian or lognormal distribution for the corresponding set of values. Neither curve is straight 

from end to end, but the observations curve becomes straight close to x=-1 and y=-1 in the 

graph. That corresponds to a wind speed of 42 kt; above this speed, the data appear to be 

Gaussian distributed. The In curve is straight below 42 kt. Since the speeds of interest are 

above 42 kt, the AMU assumed a Gaussian distribution when calculating PoV for the maximum 

wind speeds. 

9 
Theoretical vs Observed Wind 

Speed Z Distributions 

4 ~--~--~----~--~--~--~----~--. 

• 

2 

Nl +----+---.,_---+-----1f-----..11 

"C 

CD 

i! 0 -+-----+-----+----1-- CD 

~ 

0 -1 +----+---.,.._ __ ___. ---+---+----+----+----1 

-2 • 

-4 +--- ----+----1---+----+----+----1-~ 

-4 -3 -2 -1 0 1 2 3 4 

Theoretical Z 

Figure 3. Curves showing the relationship of the z values for 

the observations (blue) and the In of the observations (red) to 

the theoretical Gaussian z values. 

The AMU performed a similar analysis for the wind shear values. Table 3 shows the first four 

moments and median values for the two data sets. The values for the observations data set 

indicate it is not likely Gaussian distributed. The mean and median values are somewhat close, 

but skewness and kurtosis are far from 0. The values for In of the observations are more 

indicative of a Gaussian distribution. The curve for the observations in Figure 4 is not straight at 

any point, but the In curve becomes straight at x=-2.5 and y=-3 where the shear is 1.9 kt/1 000 ft 

and remains quasi-straight through the point x=2.5 and y=2 where the shear value is 45 kt/1 000 

ft. The shear value of interest is well within the linear portion of the LN curve, leading the AMU 

to assume a lognormal distribution for the shear values. 

Table 3. The first four moments including the median value of the 

observations and In( observations) wind shear data for January-March. 

Values Mean Median Standard Skewness Kurtosis Deviation 

Observations 13.93 12.29 8.55 1.79 8.49 

In( Observations) 2.45 2.51 0.64 -0.49 0.32 

10 
7 

6 

5 

4 

3 

N 2 "a 

Cll 

c: 1 

Cll 

ut 

.a 0 0 

-1 

-2 

-3 

-4 

-5 

Theoretical vs. Observed 

Shear Z Distributions 

.. ,. 

~ 

.. ---1 • ObsZ • LnObsZ I .. 

I .... ~~ ~ 

IJIIII"""" 

t' 

--4 -3 -2 -1 0 1 2 3 

Theoretical Z 

Figure 4. Same as Figure 3 but for wind shear 

3.4 Probability of Violation 

4 

For the maximum wind speed PoV calculation, the mean and standard deviation of the 

maximum wind speed values were determined in each sounding within a given sub-season. The 

results for each sub-season are shown in Table 4. 

Table 4. Summary of maximum wind speed PoV statistics per subseason 

Sub-Season Mean Max Wind Standard Deviation 

Speed 

January-March 71 .713 29.565 

April-June 57.441 27.187 

July-September 44.433 18.491 

October-December 65.310 28.328 

Since the distribution of the 1 000-ft shear values was found to be lognormal, the AMU 

calculated the In of the maximum shear values. The mean and standard deviation of these 

values were then determined to use in the PoV calculation. The results for each sub-season are 

11 
shown in Table 5. The respective PoV values were calculated for each wind constraint per subseason using the equations containing the Excel functions shown in Table 6. The "TRUE" option 

was selected to use the cumulative distribution function since it returns the probability of 

exceeding the variable constraint. The "FALSE" option would have returned a probability that 

the variable would be exactly equal to the constraint. 

Table 5. Summary of maximum 1 000-ft shear PoV statistics per subseason 

Sub-Season Mean ln(Max Shear) Standard Deviation 

January-March 2.446 0.643 

April-June 2.064 0.712 

July-September 1.935 0.682 

October-December 2.271 0.692 

Table 6. List of Excel's PoV calculations for the maximum wind speed and shear 

datasets. The output values were multiplied by 100 to convert to percentages. 

Dataset Excel PoV Formula 

Maximum Wind Speed - PoV = (1- NORM.S.DIST((X-x)/cr, TRUE))*100 Gaussian distribution 

Maximum ShearPoV = (1- LOGNORM.DIST(Y,LN (y),LN(cry),TRUE))*100 Lognormal distribution 

Where: X = maximum wind speed constraint 

x = mean maximum wind speed values shown in Table 4. 

a = standard deviation values shown in Table 4. 

Y = maximum shear constraint 

y = mean ln(max shear) values shown in Table 5. 

crv = standard deviation values shown in Table 5. 

12 
4. Excel Graphical User Interface (GUI) 

The primary goal of this project was to develop a tool to determine the PoV for the upperlevel wind constraints specific to the Minuteman Ill ballistic missile launch vehicle at VAFB. This 

tool was developed in Excel using Visual Basic for Applications (VBA) to create a GUI that 

displays critical sounding data easily and quickly for the launch weather officers (LWOs) on the 

day of launch. Figure 5 shows the main page of the GUI which consists of 13 worksheet tabs; 

each with their own displays. 

4.1 Sounding Data 

Information for the soundings is in the first 12 worksheet tabs of the GUI. The "REVIEW" tab 

summarizes the essential launch constraints for the latest sounding and associated sub-season. 

Once the LWOs click the "LOAD NEW BALLOON DATA" button they should check the 

"CURRENT DISPLAYED BALLOON DATA" box to ensure the correct sounding has loaded into 

the GUI. To easily compare the current sounding data to the climatology for the present subseason, the "CURRENT SUB-SEASON INFO" box displays the average maximum wind speed 

and 1 000-ft shear values for the time period and the sub-season PoV of each wind constraint. 

The PoV results for each sub-season are shown in Table 7. 

The "LAUNCH CONSTRAINTS AT A GLANCE" box focuses on the latest sounding data. It 

shows the maximum wind speed and its height, the maximum 1 000-ft shear and its layer, plus 

calculates the PoV for each constraint. The PoV for the current sounding is calculated using the 

same equation as the historical data however the mean maximum wind speed value is replaced 

with the current maximum wind speed in the layer of interest. The climatological standard 

deviation is still used. This is true for both the maximum wind speed and maximum shear wind 

constraint PoV. The PoV calculation assumes the standard deviation for the sounding is similar 

to that of the sub-season, and as such, is climatological in nature. The 30 OSSWF could not 

provide launch day soundings that occur within a few hours of each other therefore the AMU 

could not determine the PoV for some future time. Instead, the calculation best indicates the 

PoV of exceeding the given threshold in the current sounding assuming the level of peak value 

was not sampled. 

Below the summary boxes are the "Maximum Wind Speed" and "Maximum 1 000-ft Shear" 

graphs that display the current sounding data every 100-ft. The 10 worksheet tabs labeled 

"XOOO", "X 1 00" . . . "X900" contain data for the additional 100-ft interval shear levels the 30 

OSSWF requested and is mentioned in section 3.2 Processing. Figure 6 shows an example 

screen shot of the "X 1 00" worksheet tab. This includes the wind speed and shear values at the 

25,100-26,100 ft, 26,100-27, 1OOft, etc. heights. Each worksheet tab displays the sounding data 

at the respective heights, calculates the shear and then graphs the wind speed and shear 

values within the range of interest. The "RAW DATA" worksheet tab displays the latest raw data 

for the current sounding loaded in the GUI as shown in Figure 5. 

4.2 Model Data 

Although not part of the original task plan, the AMU and 30 OSSWF discussed adding 

model point forecast sounding data to the GUI. This will provide additional insight to the LWOs 

on launch day when determining if a wind constraint violation will occur over the next few hours. 

The 30 OSSWF agreed this would be valuable information and so the AMU added this to the 

tool. The Rapid Refresh (RAP) model was selected for the 30 OSSWF application. This model 

was developed for users needing frequently updated short-term weather forecasts. It replaced 

the Rapid Update Cycle (RUC) as the operational NOM hourly-updated assimilation/modeling 

system at the National Centers for Environmental Prediction (NCEP) on 1 May 2012. The latest 

RAP sounding data are available from Iowa State University Archive Data Server 

13 
(http://mtarchive.geol.iastate.edu) every hour and normally updated by 1 hr and 45m after the 

hour. The "RAP" tab in the GUI displays two sounding graphs: one for wind speed and one for 

wind direction (See Figure 7). Each graph displays the respective variable for the current 

sounding profile plus 12 1-hour RAP forecast soundings. The RAP initialization time is based on 

the current UTC time. 

14 
A '--- '"'--~c D E G H K M 

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

45 

46 

47 

48 

49 

50 

51 

52 

Figure 5. 

CURRENT DISPLAYED BALLOON 

DATA 

LOAD NEW BALLOON DATA 

DATE: 

TIME: 

12/15/2011 

11:32 UTC 

CURRENT SUB SEASON INFO 

•• % Probability of Violations based on -Oct-Dec - sub season data •• 

Mean Max Wspd: 65.31 Mean Max 1000ft Shear: 12.15 

Stdev of Max Wspd: 28.328 Stdev of Max lOOOft Shear: 9.16 

% Probability of Violating Max Wind constraint: 0 % Probability of V'10lating Shear constraint: 5 

LAUNCH CONSTRAINTS AT A GLANCE 

• • % Probability of Violat ions based on current balloon max and sub season stdev •• 

Max Wind Soeed Con-straint 

Maximum Wspd: 88.2 Max Wspd occurred at: 35400 

%Probability of Violating constra int: 3 

Max Shear Constraint 

Maximum Shear: 30.281 Max Shear occurred between: 36600 

%Probability of Violating Shear constra int: 51 

Maximum Wind Speed 

:::,;::. 

<: 

- 40000 

39000 

38000 

37000 

36000 .._ 

- 35000 

34000 

.. 33000 

..c 

liD 32000 

"ii 31000 ::I: 

30000 

29000 

28000 

27000 

26000 

25000 

0 10 

~ 

~ 

} 

/ ~ 

-:> 

.) 

) 

r 

} 

) 

30 40 50 60 70 80 90 

Wind Speed (kt) 

Maximum 1000 ft Shear 

37600 

100 

RAW DATA A RAP . 

Screen shot overview of 30 OSSWF GUI display 

15 
Table 7. Summary of PoV (%)values per sub-season 

Sub-Season 

January-March 

April-June 

July-September 

October-December 

A C 0 E 

1 Hel1hts(ft) Temp(C) RH WDir WSpd(kt) 1000 ft Shear 

25100 -37.6 293 

26100 -40.1 288 

27100 -42.5 281 

28100 -45.1 283 

29100 -47.9 288 

30100 -50.3 287 

31100 -51.5 11 287 

32100 -52.5 13 290 

33100 -55.3 17 291 

34100 -58.2 22 291 

35100 -61.2 27 291 

36100 -60.7 23 305 

37100 -59.1 16 316 

38100 -61.6 11 306 

l!HOO -63 287 

40100 -6L3 284 

62.2 

62.6 

63 

65.7 

67.3 

69.4 

66 

74.7 

79.6 

81.1 

86.4 

81 

62.3 

46.8 

48 

., 

5.458 

7.678 

3.512 

6.018 

2.415 

3.4 

9.445 

5.081 

1.5 

5.3 

21.141 

28.447 

18.134 

15.691 

3.863 

Max Wind Speed 1 000-ft Shear 

1 7 

0 3 

0 2 

0 5 

M N 0 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

30 

31 

32 

33 

34 

35 

36 

37 

38 

39 

40 

Maximum Wind Speed Maximum 1000 ft Shear 

40000 40000 

39000 I 39000 38000 

37000 

- 38000 

36000 I 37000 ........... 35000 

~ 34000 L ~ 36000 

~ 33000 I 

f. 32000 ./ t 35000 

~ 31000 

- "ii 34000 

::r 30000 " :I: ...,...,...... I :BOOO 29000 I ............. 28000 , 32000 

-- 27000 

26000 

25000 

0 10 20 30 40 50 60 70 80 90 100 

31000 

30000 

0 

~ 

5 10 15 20 

Wind Speed (let) Shear (kt/kft) 

Figure 6. Example screen shot of the X1 00 worksheet tab in GUI 

16 

Q 

---

---

25 30 
10 

11 

u 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

2!J 

30 

31 

32 

33 

34 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

45 

46 

B c 0 G H 

Maximum Wind Speed 

-- Soundlni --RAPOOHour --RAP01Hour --RAP02Hour 

--RAP 03Hour --RAP 04Hour --RAP05Hour --RAP06Hour 

--RAP07Hour --RAP08Hour--RAP09Hour --Rap 10 Hour 

--RAP 11 Hour -- RAP 12 Hour 

40000 

39000 

38000 

37000 

36000 

35000 

34000 

g 33000 

.E 

110 Gi 32000 

:I: 

31000 

30000 

2!1000 

28000 

27000 

26000 

25000 

0.0 5.0 

I iJ 

rt 

~ 

I\, I 

J 

I 

I 

I 1\ 

!/ \1 

10.0 15.0 20.0 25.0 30.0 35.0 40.0 

Wind Speed (lets) 

Figure 7. Screen shot of the RAP tab in GUI 

M N 0 Q 

Wind Direction 

-- Soundina: --RAPOOHour--RAP01Hour --RAP02Hour 

--RAP 03Hour --RAP 04Hour--RAPOSHour --RAP 06Hour 

--RAP 07 Hour --RAP 08Hour--RAP09Hour --RAP lOHour 

--RAP llHour 

40000 

39000 

38000 

37000 

36000 

35000 

34000 

g 33000 

.E 

110 Gi 32000 

:I: 

31000 

30000 

2!1000 

28000 

27000 

26000 

25000 

260 270 

RAP 12 Hour 

280 2!10 300 310 

Wind Direction (degrees) 

320 

17 
5. Summary and Future Work 

The 30 OSSWF tasked the AMU to develop a tool that will calculate the PoV of the upperlevel wind speed and shear constraints specific to the Minuteman Ill ballistic missile on the day 

of launch. In order to calculate each PoV, the AMU first collected historical sounding data from 

VAFB. The data were retrieved from the NOAA ESRL archive for the years 1994-2001 and 

stratified into four "sub-seasons" for analysis: January-March, April-June, July-September, and 

October-December. The maximum wind speed and 1 000-ft shear values in increments of 100-ft 

for each sounding per sub-season were then determined. To accurately calculate the respective 

PoVs, the AMU determined the distribution of the maximum wind speed and maximum shear 

datasets by fitting these datasets with theoretical distributions. The AMU discovered that the 

maximum wind speeds followed a Gaussian distribution while the maximum shear values 

followed a lognormal distribution. 

The AMU then developed a GUI in Excel using VBA that calculates the PoV for each wind 

constraint and displays current sounding data easily and quickly for the LWOs on launch day. In 

addition to the requirements outlined in the original task plan, the AMU also included forecast 

sounding data from the RAP model. This information provides further insight for the LWOs when 

determining if a wind constraint violation will occur over the next few hours. The AMU-developed 

tool will replace the existing one used by the 30 OSSWF, assist the LWOs in determining the 

probability of exceeding specific wind threshold values, and help to improve the overall upperlevel winds forecast. 

Another way to determine if a wind constraint violation will occur over the next few hours 

would be to conduct a statistical wind change study using 50 MHz wind profiler data similar to 

the calculations done in Merceret (1997). The results provided probabilities of exceeding a 

magnitude of wind vector change over 0.25, 1, 2 and 4 hours. The LWOs would determine what 

wind change between the last sounding and the launch time would pose an operational threat, 

then use pre-calculated values to determine the PoV of the constraint. The VAFB 50 MHz wind 

profiler is not yet functioning. Once it becomes operational, the AMU suggests that the data be 

archived in order to create these values for the 30 OSSWF. 

18 
6. List of Acronyms 

30 OSSWF 

45WS 

AMPS 

AMU 

ESRL 

GUI 

KSC 

In 

LWO 

NCEP 

NOAA 

PDF 

PoV 

RAP 

RRA 

RUC 

VAFB 

VBA 

30th Operational Support Squadron Weather Flight 

45th Weather Squadron 

Automated Meteorological Profiling System 

Applied Meteorology Unit 

Earth System Research Laboratory 

Graphical User Interface 

Kennedy Space Center 

Natural-log 

Launch Weather Officer 

National Centers for Environmental Prediction 

National Oceanic and Atmospheric Administration 

Probability Density Function 

Probability of Violation 

Rapid Refresh 

Range Reference Atmosphere 

Rapid Update Cycle 

Vandenberg Air Force Base 

Visual Basic for Applications 

19 
7. References 

Merceret, F. J., 1997: Rapid temporal changes of midtropospheric winds. J. Appl. Meteor., 36, 

1567-1575. 

Merceret, F. J., 2009: Two empirical models for land-falling hurricane gust factors, National 

Weather Digest, 33(1), 27-36. 

Smith, B. and F. J. Merceret, 2000: The lognormal distribution. College Math. J., 31, 259-261. 

Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed. Academic Press, 

Inc., San Diego, CA, 88 pp. 

20 
NOTICE 

Mention of a copyrighted, trademarked or proprietary product, service, or document does 

not constitute endorsement thereof by the author, ENSCO Inc., the AMU, the National 

Aeronautics and Space Administration, or the United States Government. Any such 

mention is solely for the purpose of fully informing the reader of the resources used to 

conduct the work reported herein. 

21