December 2011 

NASA/TM-2011-217321 

NESC-RP-11-00692

 

Doppler Radar Profiler for Launch Winds at the 

Kennedy Space Center (Phase 1a) 

Daniel G. Murri/NESC 

Langley Research Center, Hampton, Virginia 
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December 2011 

NASA/TM-2011-217321 

NESC-RP-11-00692

 

Doppler Radar Profiler for Launch Winds at the 

Kennedy Space Center (Phase 1a) 

Daniel G. Murri/NESC 

Langley Research Center, Hampton, Virginia 
Available from: 

NASA Center for AeroSpace Information 

7115 Standard Drive 

Hanover, MD 21076-1320 

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Technical Assessment Report

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NESC Request No.: TI-11-00692 (Phase 1a) 

Doppler Radar Profiler for Launch Winds at

the Kennedy Space Center (Phase 1a) 

October 27, 2011

 
NASA Engineering and Safety Center 

Technical Assessment Report

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NESC Request No.: TI-11-00692 (Phase 1a) 

Report Approval and Revision History

NOTE: This document was approved at the October 27, 2011, NRB. This document was 

submitted to the NESC Director on November 16, 2011, for configuration control. 

Approved: Original Signature on File 11/17/11 

 NESC Director Date 

Version Description of Revision Office of Primary 

Responsibility Effective Date 

1.0 Initial Release Mr. Daniel G. Murri, 

NASA Technical 

Fellow for Flight 

Mechanics, Langley 

Research Center 

10/27/11 
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Table of Contents 

Technical Assessment Report 

1.0 Notification and Authorization ........................................................................................ 4

2.0 Signature Page ................................................................................................................... 5

3.0 Team List ........................................................................................................................... 6

4.0 Executive Summary .......................................................................................................... 7

5.0 Assessment Plan ................................................................................................................ 9

6.0 Problem Description and Proposed Solutions ................................................................ 9

7.0 Data Analysis ................................................................................................................... 10

8.0 Findings, Observations, and NESC Recommendations .............................................. 18

8.1 Findings............................................................................................................................. 18

8.2 Observations ..................................................................................................................... 19

8.3 NESC Recommendations.................................................................................................. 19

9.0 Alternate Viewpoints ...................................................................................................... 19

10.0 Other Deliverables .......................................................................................................... 19

11.0 Lessons Learned .............................................................................................................. 19

12.0 Definition of Terms ......................................................................................................... 19

13.0 Acronyms List ................................................................................................................. 20

14.0 References ........................................................................................................................ 21

List of Figures

Figure 7.0-1. Google Earth Image of the KSC DRWP Network. Each 915-MHz DRWP is 

Shown by a Purple Marker and is Labeled Accordingly. The 50-MHz DRWP 

is Shown by a Yellow Thumbtack. ....................................................................... 12 

Figure 7.0-2. Number of Measurements from the KSC 915-MHz DRWP Network for Each 

Month over the 2000-2009 POR .......................................................................... 13 

Figure 7.0-3. Number of KSC 915-MHz DRWP Profiles that Reach the Ideal Minimum 

50-MHz DRWP Altitude for Each Month over the 2000–2009 POR ................. 14 

Figure 7.0-4. Number of Concurrent KSC 50-MHz and 915-MHz DRWP Profiles for Each 

Month over the 2000–2009 POR ......................................................................... 15 

Figure 7.0-5. Number of Concurrent and Overlapping 50-MHz and 915-MHz DRWP 

Profiles for Each Month over the 2000–2009 POR ............................................. 16 

List of Tables

Table 7.0-1. Characteristics of the Wind Distributions Used to Calculate Percent Reduction 

in Vector Wind Change from the February Mean ............................................... 18
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NESC Request No.: TI-11-00692 (Phase 1a) 

Technical Assessment Report 

1.0 Notification and Authorization 

The NASA Engineering and Safety Center (NESC) received a request from Mr. Daniel Murri, 

NASA Technical Fellow for Flight Mechanics at Langley Research Center (LaRC), to develop a 

database from multiple Doppler radar wind profiler (DRWP) sources and develop data 

processing algorithms to construct high temporal resolution DRWP wind profiles for day-oflaunch (DOL) vehicle assessment. The request was received on February 9, 2011. The 

development of capability was planned to be conducted in four phases (1a, 1b, 2, and 3). An 

initial evaluation for these phases was presented at the March 10, 2011, NESC Review Board 

(NRB). The assessment was deferred, pending further development of phases and identification 

of potential future partners. An assessment plan was approved by the NRB on May 26, 2011. 

The key stakeholders for this assessment are the NESC (including the disciplines of Flight 

Mechanics; Guidance, Navigation, and Control (GN&C); and Loads and Dynamics); the NASA 

Space Launch System (SLS) Program; and other current and future NASA and commercial space 

launch vehicle programs that use atmospheric winds to evaluate structural loading and to 

perform trajectory evaluations. 
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2.0 Signature Page 

Submitted by: 

Team Signature Page on File – 12/9/11 

Mr. Daniel G. Murri Date 

Significant Contributors: 

Mr. Robert E. Barbre Date Mr. Douglas C. Brown Date 

Mr. Ryan K. Decker Date Mr. Frank B. Leahy Date 

Signatories declare the findings and observations compiled in the report are factually based from 

data extracted from Program/Project documents, contractor reports, and open literature, and/or 

generated from independently conducted tests, analysis, and inspections. 
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3.0 Team List 

Name Discipline Organization 

Core Team 

Dan Murri 

NESC Lead, NASA Technical Fellow for Flight 

Mechanics LaRC 

Ryan Decker NESC Deputy Lead MSFC 

B.J. Barbre Natural Environments MSFC/Jacobs 

Douglas Brown Statistics LaRC/BAH 

Henry Cordova Mission Operations JSC 

Greg Dukeman GN&C TDT MSFC 

Frank Leahy Natural Environments MSFC 

Frank Merceret KSC Weather Office KSC 

Laura Leybold MTSO Program Analyst LaRC 

Consultants

Neil Dennehy NASA Technical Fellow for GN&C GSFC 

Steve Gentz NESC Chief Engineer MSFC 

Ken Johnson NESC Statistician MSFC 

Curt Larsen NASA Technical Fellow for Loads and Dynamics JSC 

Alden Mackey Loads and Dynamics TDT JSC/ATK 

Steve Minute NESC Chief Engineer KSC 

Administrative Support 

Donna Gilchrist Planning and Control Analyst LaRC/ATK 

Carolyn Snare Technical Writer LaRC/ATK 

Pam Sparks Project Coordinator LaRC/ATK 
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4.0 Executive Summary 

Atmospheric winds are a major factor that must be addressed during launch vehicle design and 

day-of-launch (DOL) operations to maximize flight performance and minimize structural loads. 

Current launch site wind databases at the Kennedy Space Center (KSC), including Cape 

Canaveral Air Force Station (CCAFS), utilize historical balloon measurements, which are 

limited in number of samples and temporal sampling intervals. These database limitations lead 

to uncertainty in predicting wind-induced vehicle loading during the design and certification 

process. These uncertainties result in the use of knockdown factors with unknown conservatism, 

which could result in unneeded structural weight. For DOL operations, wind profile balloon 

measurements have the additional limitations of taking significant time (e.g., approximately 

60 minutes) and potentially drifting a large distance (>80 km) from the launch trajectory. These 

DOL limitations cause more uncertainty in wind-induced loading and can result in more 

stringent wind limitations and reduced launch opportunities. 

This assessment is pursuing the development of a historical Doppler radar wind profiler (DRWP) 

database from 10 years of wind measurements (i.e., 2000–2009) made by KSC/CCAFS 

vertically pointing DRWP systems. This alternate database will provide higher fidelity in sample 

size and temporal wind change, resulting in more accurate quantification of wind effects on 

vehicle loads and the potential for increased performance and DOL flight opportunities for 

launch vehicles. In addition to developing the historical database, the assessment would pursue 

the generation of algorithms to process DRWP measurements to be used for DOL analyses and 

launch decisions. These algorithms would provide a better characterization of winds as 

compared to balloon measurements, which could result in more accurate prediction of ascent 

loading, improved launch opportunities, and reduced system risk. 

KSC/CCAFS employs one 50-megahertz (MHz) DRWP system and a network of 915-MHz 

DRWP systems. KSC operates the 50-MHz system and CCAFS operates the 915-MHz system. 

For the remainder of this report, the system at KSC/CCAFS will be referred to as the KSC 

system. Depending on the amount of backscattering media in the atmosphere, the 915-MHz 

systems measure wind profiles from about 150 to 3,000 meters (m), and the 50-MHz system 

measures profiles from about 2,400 to 18,300 m. If a 915-MHz wind profile extends to at least 

the minimum measurement altitude of the 50-MHz DRWP and exists simultaneously with the 

50-MHz wind profile, then the two profiles can be combined to produce a vertically complete 

wind profile to 18,300 m. Having wind data over this altitude range is usually sufficient for most 

launch vehicles, as they typically are not sensitive to wind-induced loading above 18,300 m. 

Any wind requirements above this altitude would still need to incorporate the use of wind 

profiles from a balloon system, which usually reach an altitude of 30,500 m. 

The proposed assessment to develop the database and the DOL algorithms involves four phases. 

This report describes results from the initial phase — Phase 1a. This initial phase began a 

quality control (QC) process that determined which KSC 915-MHz wind profiles had altitude 

content reaching or overlapping with the 50-MHz wind profiles and then determined which of 
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those sets were concurrent. This process determined the number of potential vertically complete 

profiles from the total number of available profiles. 

The Phase 1a results indicate that between 1,000 and 7,000 vertically complete wind profiles per 

month can be extracted from the historic KSC DRWP data, which is a significant improvement 

in sample size from the historical balloon databases that contain roughly 200 wind profiles per 

month. Two primary attributes of the KSC DRWP database drive the variation in the number of 

vertically complete KSC DRWP wind profiles. First, the KSC DRWP system provides wind 

profiles by measuring the backscatter from index of refraction fluctuations in the atmosphere. 

Since these fluctuations are less abundant in clear, dry air, fewer wind profiles are available in 

the winter months than in the summer months. Second, the sample size of the KSC DRWP 

database depends on whether multiple KSC 915-MHz DRWPs are accepted for a given 

application. When accounting for these attributes, the KSC DRWP database is projected to 

provide an order of magnitude increase of wind profiles for use in flight vehicle loads and 

trajectory assessments. This increase in sample size from the balloon datasets provides a 

reduction in the uncertainty that a wind or wind change represents the universal population at a 

given percentile. This reduction depends on many factors and can be quantified for specific 

cases. For example, a winds database with the projected sample size range of the vertically 

complete DRWP database provides a 55 to 83-percent reduction in uncertainty of the 

99th percentile vector wind change from the February monthly mean, assuming the wind changes 

fit a generalized extreme value (GEV) distribution. The DRWP database of vertically complete 

profiles can be used in other applications (e.g., simulating temporal wind change on DOL, 

projecting the landing footprint of a capsule after a pad abort, and assessing vehicle maneuvers at 

low altitudes), which may improve the reduction in uncertainty to a different degree. 

After the completion of Phase 1a, the Space Launch System (SLS) Program decided to pursue 

the follow-on phases of this assessment to most quickly integrate the results into their launch 

vehicle development program. As a result, the NASA Engineering and Safety Center (NESC) 

has completed its participation in this assessment with the publication of this report. Follow-on 

phases could remove erroneous wind output from the wind profiler network (Phase 1b), develop 

a database of vertically complete profiles (Phase 2), and develop algorithms for use in KSC DOL 

software (Phase 3). Vandenberg Air Force Base (VAFB) has a DRWP system comparable to the 

one at KSC, and a similar effort to develop a historical DRWP database and DOL algorithms 

could be conducted for that launch site. 
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5.0 Assessment Plan 

The proposed assessment to develop the KSC database and the DOL algorithms involves four 

phases (1a, 1b, 2, and 3). For Phase 1a, the objective was to begin QC processing on the KSC 

915-MHz DRWP historic data by determining which 915-MHz wind profiles had altitude 

content reaching or overlapping with the 50-MHz DRWP altitude coverage. Those wind profiles 

were then compared to the KSC 50-MHz DRWP wind profiles to determine which 915-MHz 

profiles were concurrent with the 50-MHz profiles. Assessing the number of concurrent profiles 

that contain overlapping altitude content determined the number of potential vertically complete 

profiles. 

After the completion of Phase 1a, the SLS Program decided to pursue the follow-on phases of 

this assessment to most quickly integrate the results into their launch vehicle development 

program. As a result, the NESC has completed its participation in this assessment with the 

publication of this report. Phase 1b would apply additional QC techniques to the KSC 915-MHz 

DRWP historic data. Phase 2 would develop and apply algorithms to filter KSC data so the wind 

profile would have common energy spectra. The processed data would be used to build 

databases of discrete profiles and temporally variable wind profile sets for use in space flight 

vehicle loads and trajectory simulations. Phase 3 would involve transferring the QC algorithms 

to the KSC DRWP systems to construct the vertically complete wind profiles for DOL loads and 

trajectory assessments. VAFB has a DRWP system comparable to the one at KSC, and a similar 

effort to develop a historical DRWP database and DOL algorithms could be conducted for that 

launch site. 

6.0 Problem Description and Proposed Solutions 

Space launch vehicles have to account for atmospheric wind loading effects throughout multiple 

phases in the lifecycle process to ensure robust structural integrity and optimized trajectory 

during launch operations. The current technique for measuring atmospheric winds for space 

launch vehicle evaluations at KSC is through the use of balloons to loft measurement instruments 

(e.g., to measure wind, temperature, and pressure). Databases of balloon-based discrete wind 

profiles and temporal wind profile pairs to characterize wind variability and define load 

“knockdowns” have been constructed for application in the vehicle design and certification 

process. Because of cost, time, and programmatic requirements, the databases are limited in 

number of samples. Furthermore, balloon-based wind profiling systems require significant time 

to generate a wind profile (e.g., approximately 60 minutes to reach 18 kilometers (km)) and 

balloons potentially drift a large distance (e.g., greater than 80 km) from the launch trajectory. 

These time and distance factors can result in DOL measurements that are not representative of 

the winds that could be experienced by the vehicle during ascent. 

This assessment utilizes another means of measuring atmospheric winds using KSC groundbased DRWP systems. These systems can be used to build higher-fidelity wind databases for 

vehicle analyses and provide more timely wind measurements used in DOL flight vehicle 

analyses. The winds that DRWP systems measure do not directly align with vehicle launch 
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trajectories, but typically are much closer than the balloon measurements. The intent of the 

DRWP systems is not to replace the balloon systems but to provide an increase in the number 

and frequency of available wind profiles. The balloon system is required to provide launch site 

temperature and pressure profiles since the radar systems only measure wind. 

Ground-based DRWP systems derive wind velocity and direction at discrete range intervals 

through transmission of radio signal to measure backscattered signal generated by index of 

refraction irregularities and the presence of objects (e.g., moisture and dust) within the 

atmosphere. There are two DRWP systems at KSC operating at different frequencies 

(50 MHz and 915 MHz) to sample the atmospheric winds from 150 to 18,300 m. Depending on 

the amount of backscattering media in the atmosphere, the 915-MHz systems typically measure 

wind profiles from about 150 to 3,000 m, and the 50-MHz systems typically measure profiles 

from about 2,400 to 18,300 m. Wind profiles are generated every 5–15 minutes based on the 

DRWP system configuration. An advantage of the DRWP systems over the balloon-based 

system is the ability to operate continuously. Continuously operating systems produce thousands 

of wind profiles that can improve the statistical characterization of temporal wind variability 

over the balloon-based database. The DRWP system can provide increased flexibility in 

defining time intervals to assess wind variability, which could result in improved confidence in 

vehicle loads analyses. However, data from both DRWP systems (and balloons) are susceptible 

to error and the effective vertical resolution of the two DRWP systems is not the same. 

Therefore, to construct a complete wind profile resolving the same energy spectra, an extensive 

QC process is required to remove erroneous data and a common wavelength filter must be 

applied. 

This report describes results from Phase 1a. This initial phase began a QC process that 

determined which KSC 915-MHz wind profiles had altitude content reaching or overlapping the 

50-MHz wind profiles and then determined which of those sets were concurrent. Assessing the 

number of concurrent KSC profiles that contain overlapping altitude content determined the 

number of potential vertically complete profiles. 

7.0 Data Analysis 

An analysis was performed to examine the number of potentially available, vertically complete 

wind profiles from the KSC DRWP network. An extensive database of quality-controlled 

50-MHz DRWP profiles is available for use in launch vehicle loads and trajectory assessments 

[ref. 1]. Data from the KSC 915-MHz DRWP for the 2000–2009 period of record (POR) were 

obtained through the Tropical Rainfall Measurement Mission archive (http://trmm.ksc.nasa.gov), 

but the data had not been subjected to the QC process. Integrating the DRWP profiles requires 

an extensive screening of the 915-MHz DRWP data. This section documents Phase 1a, which 

determined the number of profiles that can be expected when generating vertically complete 

DRWP wind profiles and examined the potential benefit of performing the 915-MHz data QC. 

 
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Four analyses were performed to determine the number of available vertically complete profiles: 

1. Determine the number of KSC 915-MHz DRWP profiles. 

2. Determine the number of KSC 915-MHz DRWP profiles that reach or overlap the 

minimum altitude of the 50-MHz DRWP. 

3. Determine the number of concurrent KSC 50-MHz and 915-MHz DRWP profiles. 

4. Determine the number of concurrent KSC 50-MHz and 915-MHz DRWP profiles that 

contain overlapping altitude content. 

All analyses were performed using the 2000–2009 POR. Analysis 1 is the least restrictive. 

Analyses 2 and 3 are independent of each other, but are more restrictive than Analysis 1. 

Analysis 4 is the most restrictive. Note that Analysis 4 counted the number of profiles that met 

the criteria for Analyses 2 and 3 simultaneously. 

Each analysis was performed two ways. One way assumed that an individual 915-MHz DRWP 

was combined with the 50-MHz DRWP to generate vertically complete profiles. The other way 

assumed that any 915-MHz DRWP was combined with the 50-MHz DRWP to generate 

vertically complete profiles. Figure 7.0-1 displays the KSC DRWP network locations. Four 

915-MHz DRWPs are located in a diamond-shaped pattern surrounding the 50-MHz DRWP and 

the Merritt Island 915-MHz DRWP. The 50-MHz DRWP is located near the north end of the 

Shuttle Landing Facility, about half way between the Mosquito Lagoon and the Merritt Island 

915-MHz DRWPs. This DRWP network has the capability of providing up to five 915-MHz 

DRWP measurements and one 50-MHz DRWP measurement at a given time. Data can be 

accumulated from a single 915-MHz DRWP, a combination of 915-MHz DRWPs, or any 

915-MHz DRWP. Therefore, each analysis was performed examining each 915-MHz DRWP 

individually and all 915-MHz DRWPs at a given time to envelope the potential sample size of a 

database generated by a given 915-MHz DRWP combination. 
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Figure 7.0-1. Google Earth Image of the KSC DRWP Network. Each 915-MHz DRWP is Shown by a 

Purple Marker and is Labeled Accordingly. The 50-MHz DRWP is Shown by a Yellow Thumbtack. 

Analysis 1 counted the number of observations from the 915-MHz DRWP network, ignoring 

data from the 50-MHz DRWP. The number of observations from each 915-MHz DRWP and the 

number of 15-minute periods containing at least one 915-MHz DRWP measurement were tallied. 

Figure 7.0-2 shows the results of Analysis 1. Ideally, approximately 29,000 profiles per month 

would be generated from each 915-MHz DRWP if it took a measurement every 15 minutes over 

the POR. From the data, if any of the five 915-MHz DRWPs was chosen at a given time, it was 

found that approximately 14,000–18,000 profiles were actually generated for a given month. 

Roughly 9,000–16,000 measurements were generated per month from an individual 915-MHz 

DRWP. 
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Figure 7.0-2. Number of Measurements from the KSC 915-MHz DRWP Network for Each Month over 

the 2000–2009 POR 

Analysis 2 counted the number of 915-MHz DRWP profiles, which reached the ideal minimum 

altitude of the 50-MHz DRWP and showed the number of 915-MHz DRWP profiles that would 

be available to generate vertically complete profiles (with no interpolation) if a 50-MHz DRWP 

measurement existed at the same time and contained data to its minimum altitude. First, the 

maximum altitude of each 915-MHz DRWP was found for profiles starting at approximately 

150 m. Next, a threshold (T) was derived as 

 Eq. (7.0-1) 

where min(z50) is the ideal minimum 50-MHz DRWP measurement altitude and gs50 and gs915

are the gate spacing (i.e., vertical sampling interval) of the 50-MHz DRWP and 915-MHz 

DRWP, respectively. During the 2000–2009 POR, gs915 remained constant at 101.0 m. 

However, a system upgrade [ref. 2] caused min(z50) and gs50 to change in July 2004 from 

2011.0 to 2666.0 m, and from 150.0 to 145.0 m, respectively. Inserting these values into 

Equation (7.0-1) produced thresholds of 1885.5 m and 2543.5 m for 915-MHz DRWP profiles 

taken before August 2004 and from August 2004 to the end of the POR, respectively. The 

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

5000

10000

15000

20000

KSC 915-MHz Profiles

Month

Number of Profiles

South Cape

False Cape

Merritt Island

Mosquito Lagoon

TI-CO

Any Profiler
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number of 915-MHz profiles that extended to at least the threshold was tallied for each 915-MHz 

DRWP and for any 915-MHz DRWP at a given time. Figure 7.0-3 shows results from 

Analysis 2. Approximately 2,000–12,000 profiles from an individual 915-MHz DRWP reached 

the minimum altitude, and roughly 7,000–15,000 profiles from any 915-MHz DRWP at a given 

time reached the minimum altitude, depending on the month. A seasonal variation is shown 

from Analysis 2, with fewer 915-MHz DRWP profiles reaching the altitude threshold during the 

winter months. This attribute exists because the air exhibited lower absolute humidity (less 

scattering off index of refraction fluctuations) in the winter months for the 915-MHz DRWP to 

record a wind measurement successfully. 

Figure 7.0-3. Number of KSC 915-MHz DRWP Profiles that Reach the Ideal Minimum 50-MHz 

DRWP Altitude for Each Month over the 2000–2009 POR 

Analysis 3 counted the number of concurrent 50-MHz and 915-MHz DRWP measurements and 

showed the number of vertically complete profiles that would exist if all concurrent 915-MHz 

DRWP profiles reach the minimum altitude of the 50-MHz profile. An averaging method was 

implemented for this analysis to account for the two DRWP systems not having the same 

sampling periods [refs. 3 and 4]. The 50-MHz DRWP recorded measurements every 

3–5 minutes and the 915-MHz DRWP winds were averaged over a given period of time (usually 

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

5000

10000

15000

20000

KSC 915-MHz Profiles Reaching Minimum 50-MHz Altitude

Month

Number of Profiles

South Cape

False Cape

Merritt Island

Mosquito Lagoon

TI-CO

Any Profiler
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11–14 minutes) at each altitude during the sampling period. Wind components from the 

50-MHz DRWP were averaged over the 915-MHz DRWP averaging window at each altitude to 

best simulate the 915-MHz DRWP measurement process. The window is defined as 

T915-1 minute  T50  T915 + Tap + 1 minute, where T915 and T50 are the timestamps in the 

915-MHz and 50-MHz DRWP databases, respectively, and Tap is the averaging time period used 

to derive the given 915-MHz profile. If T50 fell within the bounds provided, then the profile at 

T50 was included in the process to generate an averaged profile from the 50-MHz DRWP. Note 

that the averaging window included a 1-minute buffer on either side to account for the nonidentical timestamps between the 50-MHz and 915-MHz DRWP databases. The minimum 

altitude of each averaged 50-MHz DRWP profile was then found. For Analysis 3, the number of 

minimum altitudes was tallied since the existence of a minimum altitude indicated that data exist 

in the 50-MHz DRWP averaged profile. Figure 7.0-4 shows the results of Analysis 3. 

Approximately 7,000–10,000 averaged 50-MHz DRWP profiles were concurrent with individual 

915-MHz DRWP profiles, and roughly 9,000–12,000 50-MHz DRWP profiles were concurrent 

with any 915-MHz DRWP profile. Although similar results existed when compared to 

Analysis 2, the seasonal variation disappeared since the 915-MHz DRWP profiles were not 

required to meet an altitude threshold. 

Figure 7.0-4. Number of Concurrent KSC 50-MHz and 915-MHz DRWP Profiles for Each Month over 

the 2000–2009 POR 

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

5000

10000

15000

20000

Month

Number of Profiles

Number of Concurrent 50-MHz and 915-MHz Profiles

South Cape

False Cape

Merritt Island

Mosquito Lagoon

TI-CO

Any Profiler
NASA Engineering and Safety Center 

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Analysis 4 provided the end result of Phase 1a. In addition to interrogating the DRWP 

databases, it provided the number of DRWP profiles that are available for generating a database 

of vertically complete profiles prior to the 915-MHz DRWP QC process. All cases where the 

50-MHz DRWP minimum altitude from Analysis 3 is at or below the 915-MHz DRWP 

maximum altitude from Analysis 2 were tallied for each 915-MHz DRWP individually and the 

entire 915-MHz DRWP network at a given time. Figure 7.0-5 shows the results of Analysis 4. 

Approximately 1,000–5,000 and 3,000–7,000 concurrent, overlapping profiles exist when using 

an individual 915-MHz DRWP and any 915-MHz DRWP at a given time, respectively. These 

results present the number of profiles that can be combined into a database of vertically complete 

profiles prior to the 915-MHz QC process. The QC process to be applied to the 915-MHz data in 

Phase 1b would consist of automated and manual checks to remove unrealistic data and would 

reduce the number of available, vertically complete DRWP profiles. The extent to which the 

sample size would be reduced is unknown. However, for application to a specific flight vehicle 

program, allowances could be made to consider profiles over a narrower vertical range and/or 

allow a small number of data gaps in the profiles. Winds would be linearly interpolated over 

these data gaps. If either the altitude range is narrowed or a tolerance for a small number of data 

gaps is accepted, then the resulting sample size would increase. In comparison, the historical 

balloon databases contain approximately 200 wind profiles per month. 

Figure 7.0-5. Number of Concurrent and Overlapping 50-MHz and 915-MHz DRWP Profiles for Each 

Month over the 2000–2009 POR 

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

0

5000

10000

15000

20000

Month

Number of Profiles

Number of Overlapping 50-MHz and 915-MHz Profiles

South Cape

False Cape

Merritt Island

Mosquito Lagoon

TI-CO

Any Profiler
NASA Engineering and Safety Center 

Technical Assessment Report

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NESC-RP11-00692

Version:

1.0

Title:

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NESC Request No.: TI-11-00692 (Phase 1a) 

The increase in sample size provided by the database of vertically complete DRWP profiles 

reduced the uncertainty that a sample’s distribution of winds and wind changes represents its 

universal population. However, a single quantification of uncertainty reduction was not feasible 

as many different subsets can be formed from the vertically complete DRWP profiles and 

multiple balloon databases exist. These two factors lead to different amounts of uncertainty 

reduction when comparing DRWP and balloon databases. The extent to which the width of the 

95-percent confidence bounds (CB) decreases, using a large sample of vector wind changes from 

the February mean wind versus using a smaller sample of wind changes in the region of 

maximum dynamic pressure, is presented as an example of quantifying one possible uncertainty 

reduction. The vector wind difference from the February mean in the 8,000–10,000 m altitude 

region is assumed to fit a GEV distribution with the computed shape parameter (K), location 

parameter (ȝ), and scale parameter (ı). The 99th percentile estimates were found using the 

inverse of the GEV distribution with these parameters. Low and high CBs were obtained using 

the Asymptotic Distribution of Percentiles theorem [ref. 5], which states that the distribution of a 

variable at a specified percentile is Gaussian. The upper and lower CBs were calculated using: 

 

Eq. (7.0-2) 

where İp is the estimate from the distribution at percentile p, and p ranges from 0 to 1. The GEV 

probability density function is expressed by GEV(İp, K, ȝ, ı), n is the sample size, and za/2 is the 

standardized Gaussian variable. Because the estimates of the 99th percentile at the 95-percent 

confidence level are of interest, p and za/2 are set to 0.99 and 1.96, respectively. The upper and 

lower CBs were subtracted to obtain the confidence width. 

Table 7.0-1 displays results of this exercise. The fit parameters were assumed to be constant and 

only n was varied. An initial sample size of 200 was selected to represent the balloon databases, 

and sample sizes of 1,000 and 7,000 were selected to represent the projected sample size range of 

the vertically complete DRWP database. The confidence width at the 99th percentile for 

n = 200 is 13.3 meters/second (m/s). Increasing n to 1,000 yields a confidence width of 6.0 m/s, 

which is a 55.3-percent reduction in uncertainty. Increasing n to 7,000 yields a confidence width 

of 2.3 m/s, or an 83.1-percent reduction in uncertainty. It is important to note that this exercise is 

presented only as an example. Comparing actual distributions of wind and wind change from 

separate databases is more complex for two main reasons. First, much of the wind data applied 

to vehicle assessments does not fit a particular distribution. Second, if data were to fit a 

distribution, different wind variables can be examined and the same variable can be examined for 

different months, which will change the distribution and/or fit parameters leading to different 

reductions in uncertainty when compared to a given database with a smaller sample size. 
NASA Engineering and Safety Center 

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NESC-RP11-00692

Version:

1.0

Title:

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Table 7.0-1. Characteristics of the Wind Distributions Used to Calculate Percent Reduction in 

Vector Wind Change from the February Mean 

8.0 Findings, Observations, and NESC Recommendations 

8.1 Findings

The following findings were identified: 

F.1. Historical KSC balloon databases contain approximately 200 wind profiles per month.

F.2. There are 3,000–7,000 vertically complete profiles that potentially exist if any 915-MHz 

DRWP were of interest, and 1,000–5,000 profiles that potentially exist for an individual 

915-MHz DRWP. 

• These profiles would increase the database sample size used in current and previous 

flight vehicle programs by an order of magnitude. 

• Uncertainty reduction depends on many factors, but a hypothetical case of comparing 

wind deviations from the February mean reduces the range by 55 to 83 percent.

F.3. Fewer profiles exist during the winter months due to lower absolute humidity (less 

scattering off the index of refraction fluctuations) at the higher 915-MHz measurement 

altitudes. 

F.4. The DRWP systems produce vertically complete profiles up to an altitude of about 

18,300 m. If wind data is required above this altitude, the use of a balloon system will 

then be needed, which typically provides wind profiles up to about 30,500 m. 

F-5. Stating confidence for wind profiles requires the calculation of confidence intervals for 

an extreme percentile (i.e., 99th) of the wind profile population. 

F-6. Distributions of wind data from any measurement system change as a function of the data 

being examined and time of year, and much of the wind data applying to loads and 

trajectory assessments does not fit a theoretical distribution. Although confidence of a 

sample representing the universal population will improve using the DRWP database, 

quantifying confidence on a mixed distribution has not yet been investigated. 

n K ʅ ʍ 99% (m/s) Low CB High CB Width

200 -0.85133 7.1057 17.222 44.271 37.614 50.927 13.313

1000 -0.85133 7.1057 17.222 44.271 41.294 47.248 5.954

7000 -0.85133 7.1057 17.222 44.271 43.145 45.396 2.251

GEV Distribution Parameters Confidence at 99th percentile (m/s)
NASA Engineering and Safety Center 

Technical Assessment Report

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NESC-RP11-00692

Version:

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Title:

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8.2 Observations

The following observations were identified: 

O.1. The 915-MHz DRWP data used in this analysis were not subjected to the QC process. 

Applying the QC process to this data will reduce the number of available vertically 

complete DRWP profiles, but the extent to which the sample size will be reduced is 

currently unknown. 

O.2. VAFB has a DRWP system comparable to the one at KSC, and a similar effort to develop 

a historical DRWP database and DOL algorithms could be conducted for that launch site. 

8.3 NESC Recommendations 

The following NESC recommendations were identified and directed toward the SLS Program, 

which will be pursuing the future phases of this assessment. 

R.1. Future phases of this assessment should address implementing the QC process on 

915-MHz data from KSC. (F-2, O-1)

R.2. Future phases of this assessment should determine the most accurate methods for 

calculating confidence intervals on wind percentiles. (F-6)

9.0 Alternate Viewpoints 

There were no alternate viewpoints identified during the course of this assessment by the NESC 

team or the NRB quorum. 

10.0 Other Deliverables 

No unique hardware, software, or data packages, outside those contained in this report, were 

disseminated to other parties outside this assessment. 

11.0 Lessons Learned 

No applicable lessons learned were identified for entry into the NASA Lessons Learned 

Information System. 

12.0 Definition of Terms 

Corrective Actions Changes to design processes, work instructions, workmanship practices, 

training, inspections, tests, procedures, specifications, drawings, tools, 

equipment, facilities, resources, or material that result in preventing, 

minimizing, or limiting the potential for recurrence of a problem. 

Finding A conclusion based on facts established by the investigating authority. 
NASA Engineering and Safety Center 

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NESC-RP11-00692

Version:

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NESC Request No.: TI-11-00692 (Phase 1a) 

Lessons Learned Knowledge or understanding gained by experience. The experience may 

be positive, as in a successful test or mission, or negative, as in a mishap 

or failure. A lesson must be significant in that it has real or assumed 

impact on operations; valid in that it is factually and technically correct; 

and applicable in that it identifies a specific design, process, or decision 

that reduces or limits the potential for failures and mishaps, or reinforces a 

positive result. 

Observation A factor, event, or circumstance identified during the assessment that did 

not contribute to the problem, but if left uncorrected has the potential to 

cause a mishap, injury, or increase the severity should a mishap occur. 

Alternatively, an observation could be a positive acknowledgement of a 

Center/Program/Project/Organization’s operational structure, tools, and/or 

support provided. 

Problem The subject of the independent technical assessment. 

Proximate Cause The event(s) that occurred, including any condition(s) that existed 

immediately before the undesired outcome, directly resulted in its 

occurrence and, if eliminated or modified, would have prevented the 

undesired outcome. 

Recommendation An action identified by the NESC to correct a root cause or deficiency 

identified during the investigation. The recommendations may be used by 

the responsible Center/Program/Project/Organization in the preparation of 

a corrective action plan. 

Root Cause One of multiple factors (events, conditions, or organizational factors) that 

contributed to or created the proximate cause and subsequent undesired 

outcome and, if eliminated or modified, would have prevented the 

undesired outcome. Typically, multiple root causes contribute to an 

undesired outcome. 

13.0 Acronyms List 

ATK Alliant Techsystems, Inc. 

BAH Booz Allen Hamilton 

CB Confidence Bounds 

CCAFS Cape Canaveral Air Force Station 

DOL Day-of-Launch 

DRWP Doppler Radar Wind Profiler 

GEV Generalized Extreme Value 

GN&C Guidance, Navigation, and Control 
NASA Engineering and Safety Center 

Technical Assessment Report

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NESC-RP11-00692

Version:

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Title:

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NESC Request No.: TI-11-00692 (Phase 1a) 

GSFC Goddard Space Flight Center 

JSC Johnson Space Center 

km kilometers 

KSC Kennedy Space Center 

LaRC Langley Research Center 

m meters 

m/s meters/second 

MHz megahertz 

MSFC Marshall Space Flight Center 

MTSO Management and Technical Support Office 

NESC NASA Engineering and Safety Center 

NRB NESC Review Board 

POR Period of Record 

QC Quality Control 

SLS Space Launch System 

TDT Technical Discipline Team 

VAFB Vandenberg Air Force Base 

14.0 References 

1. Decker, R. and R. Barbré, “Quality Control Algorithms and Proposed Integration Process 

for Wind Profilers Used by Launch Vehicle Systems,” Paper 9.5, Proceedings of the 

15th Annual Conference on Aviation, Range, and Aerospace Meteorology, 3 August 2011. 

2. Pinter, D.J., F.J. Merceret, and C.V. Hatley, “Performance Validation of Upgraded 

Eastern Range 50-Megahertz Doppler Radar Wind Profiler,” J. Spacecr. Rockets, 

43(3), pp. 693-695, May 2006. 

3. Schumann, R.S., Taylor, G.E., Merceret, F.J., and T.L. Wilfong, “Performance 

Characteristics of the Kennedy Space Center 50-MHz Doppler Radar Wind Profiler using 

the Median Filter/First – Guess Data Reduction Algorithm,” J. Atm. Ocean. Tech, 

16, pp. 532-549, 30 June 1998. 

4. Lambert, W.C., Merceret, F.J., Taylor, G.E., and Ward, J.G., “Performance of five 

915-MHz Wind Profilers and an Associated Automated Quality Control Algorithm in an 

Operational Environment,” J. Atm. Ocean. Tech., 20, pp. 1488-1495, 7 May 2003. 

5. DasGupta, A., Asymptotic Theory of Statistics and Probability, Springer Science and 

Business Media, New York, New York, p.693, 2008.
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Technical Memorandum

 4. TITLE AND SUBTITLE

Doppler Radar Profiler for Launch Winds at the Kennedy Space Center 

(Phase 1a)

5a. CONTRACT NUMBER

 6. AUTHOR(S)

Murri, Daniel G.

 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES)

NASA Langley Research Center

Hampton, VA 23681-2199

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National Aeronautics and Space Administration

Washington, DC 20546-0001

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L-20107 NESC-RP-11-00692

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13. SUPPLEMENTARY NOTES

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Unclassified - Unlimited

Subject Category 15 Launch Vehicles and Launch Operations

Availability: NASA CASI (443) 757-5802

19a. NAME OF RESPONSIBLE PERSON

STI Help Desk (email: help@sti.nasa.gov)

14. ABSTRACT

The NASA Engineering and Safety Center (NESC) received a request from the, NASA Technical Fellow for Flight Mechanics 

at Langley Research Center (LaRC), to develop a database from multiple Doppler radar wind profiler (DRWP) sources and 

develop data processing algorithms to construct high temporal resolution DRWP wind profiles for day-of-launch (DOL) 

vehicle assessment. This document contains the outcome of Phase 1a of the assessment including Findings, Observations, 

NESC Recommendations, and Lessons Learned.

15. SUBJECT TERMS

Doppler Radar Wind Profiler; Guidance, Navigation, and Control; Generalized Extreme Value; NASA Engineering and Safety 

Center; Quality Control

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