NASA Contractor Report 3379 

An Airport Wind Shear 

-__ 

Detectic 

and Warning System Using Doppler 

Radar - A Feasibility Study 

John McCarthy, Edward F. Blick, 

and Kim L. Elmore 

CONTRACT NAS8-33458 

JANUARY 198 1 
TECH LIBRARY KAFB, NM 

” 

NASA Contractor Report 3379 

An Airport Wind Shear Detection 

and Warning System Using Doppler 

Radar - A Feasibility Study 

John McCarthy, Edward F. Blick, 

and Kim L. Elmore 

MCS, Itzc. 

Bozrlder; Colorado 

Prepared for 

Marshall Space Flight Center 

under Contract NAS8-33458 

National Aeronautics 

and Space Administration 

Scientific and Technical 

Information Branch 

1981 

AUTHORS' ACKNOWLEDGEMENTS 

The work reported herein was supported by FWG Associates, Inc. , 

Tullahoma, TN, under Subcontract FWG 6-0510-1. The entire work was 

supported by Mr. Allan R. Tobiason, Aviation Safety Technology, OAST, 

NASA Headquarters, Washington, D.C. 

The authors wish to thank Mr. Dennis W. Camp of Marshall Space 

F1 i ght Center (MSFC) , for his 1 ong-standing and vigorous support of this 

work. An important collaboration with Dr. Walter Frost, of FWG Associates, 

Inc., was a vital part of this study. 

Project SESAME '79, hosted by the NOAA's National Severe Storms 

Laboratory (NSSL) , provided a great deal of support to this work. Dr. Ron 

Alberty, Operations Manager of SESAME '79, Dr. Richard Doviak, Dr. Dusan 

Zrnic, and Mr. J. T. Lee are acknowledged for their support. 

The National Center for Atmospheric Research (NCAR) funded by the 

National Science Foundation, provided research aircraft support to 

Project SESAME '79. 

We are most appreciative to the U.S. Air Force 3rd Mobile 

Communications Group at Tinker Air Force Base for their installation 

and staffing of the TPN-19 for SESAME '79. 

Finally, the assistance of Mr. Randall R. Bensch, now a professor 

at Northeast Louisiana University, has been a vital addition to the 

evolution of this research. 

iii 

.". ...."".". ...... ...-.-.- . ...." ...."..".. _........, ,. .._.. ....._._.. . , .. . -. ~~- 

. 

TABLE OF CONTENTS 

PAGE 

CHAPTER I . INTRODUCTION .................... 1 

I1 . EXPERIMENTAL PLAN ................. 5 

I11 . MEASUREMENT OF WINDS ALONG THE APPROACH PATH .... 11 

1 . Doppler Radar Winds .............. 11 

2 . Aircraft Measured Winds ............ 15 

3 . Comparison Between Doppler Radar. Aircraft 

Winds. and Other Flight Parameters ....... 16 

IV . RESULTS OF FIXED-STICK BLICK NUMERICAL 

SIMULATION MODEL ................ 65 

V . PAR APPROACH QUALITY ASSESSMENT TOOL ........ 71 

VI . COMPARISON OF AIRCRAFT PREDICTED RESPONSE TO 

ACTUAL AIRCRAFT RESPONSE ............ 75 

VI1 . CONCLUSIONS .................... 81 

1 . Summary and Overall Assessment ......... 81 

2 . Prel iminary P1 ans for an Experiment with 

Aircraft F1 ight Simulators ........... 82 

3 . Preliminary Plans for a Field Experiment in 1982 83 

REFERENCES ........................... 85 

V 

.. " ........... . . - 
LIST OF FIGURES 

FIGURE 

1. 

2. 

3a. 

3b. 

3c. 

3d. 

3e. 

3f. 

39. 

3h. 

4a. 

4b. 

4c. 

4d. 

4e. 

A map showing the runways, approach path, location, 

and azimuth scans for comparison experiment ..... 

Photograph of the NSSL display for Queen Air F1 ight 

9Run3 ....................... 

First of 8 data panels for Queen Air approach 

on 16 May 1979, designated as Flight 9 Run 3 .... 

QF9R3M16 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the radar 

QF9R3M16 showing aircraft and model true airspeed 

as a function of time ................ 

QF9R3M16 showing aircraft and model airspeed 

departure nominal approach speed .......... 

QF9R3M16 showing aircraft and model pitch angle 

as a function of time ................ 

QF9R3M16 comparison of aircraft longitudinal wind 

and Lagrangian’Doppler velocity as a function of 

time ........................ 

-QF9R3M16 comparison of aircraft longitudinal wind 

and Eul eri an Doppler velocity ............ 

QF9R3M16 compari son for Eul eri an Doppler vel oci ty 

taken 1 s immediately after the end of the approach . 

First of 8 data panels for Queen Air approach on 

7 May 1979, designated as Flight 9 Run 3 ...... 

QF7R3M07 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the radar 

QF7R3M07 showing aircraft and model true airspeed 

as a function of time ................ 

QF7R3M07 showing aircraft and model airspeed 

departure nominal approach speed .......... 

QF7R3M07 showing aircraft and model pitch angle 

as a function of time ................ 

PAGE 

7 

13 

17 

18 

19 

20 

21 

22 

23 

24 

25 

26 

27 

28 

29 

vi 
FIGURE PAGE 

4f. QF7R3M07 comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

49. QF7R3M07 comparison of aircraft longitudinal wind 

and Eulerian Doppler velocity ............ 

4h. QF7R3M07 comparison for Euleri an Doppler velocity 

taken 1 s immediately after the end of the 

approach ...................... 

5a. SF6RlM07 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ......................... 

5b. SF6RlM07 comparison of aircraft and Lagrangian 

Doppler velocity as a function of time ........ 

6a. SF8RlMl4 showing aircraft and model a1 ti tude 

departure from a 3 deg glide slope path to the 

radar ........................ 

6b. SF8RlM14 Comparison of aircraft and Lagrangian 

Doppler velocity as a function of time ........ 

7a. SF8R2M14 showing aircraft and model departure from 

a 3 deg glide slope path to the radar ........ 

7b. SF8R2Ml4 comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

8a. SF8R3M14 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ........................ 

8b. SF8R3Ml4 comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

9a. QF5RlA25 showing aircraft and model a1 ti tude 

departure from a 3 deg glide slope path to the 

radar ........................ 

9b. QF5RlA25 comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

1 Oa. QF5R3A25 showing aircraft and model a1 ti tude 

departure from a 3 deg glide slope path to the 

radar ........................ 

30 

31 

32 

35 

36 

37 

38 

39 

40 

41 

42 

43 

44 

45 

vi i 
FIGURE PAGE 

lob. 

lla. 

llb. 

12a. 

12b. 

13a. 

13b. 

14a. 

14b. 

15a. 

15b. 

16a. 

16b. 

QF5R3A25 comparison of ai rcraft 1 ongi tudi nal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

QF8RlM14 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ........................ 

QF8RlM14 comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

QF8R2M14 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ........................ 

QF8R2M14 comparison of ai rcraft 1 ongi tudi nal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

QF8R3M14 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ........................ 

QF8R3M14 compari son of ai rcraft 1 ongi tudi nal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

QF9RlM16 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ........................ 

QF9RlM16 comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

QF9R2M16 showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ........................ 

QF9R2416 comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a. function of 

time ......................... 

QF16RlJl showing aircraft and model altitude 

departure from a 3 deg glide slope path to the 

radar ........................ 

QF16RlJl comparison of aircraft longitudinal wind 

and Lagrangian Doppler velocity as a function of 

time ......................... 

46 

47 

48 

49 

50 

51 

52 

53 

54 

55 

56 

57 

58 

viii 
FIGURE PAGE 

17a. QF16R2J1 showing aircraft and model altitude 

departure from a 3 deg glide slope path tothe 

radar ......................... 59 

17b. QF16RZJ1 comparison OT aircraft longitudinal wind 

and Lagrangi,an Dopeler velocity as a function of 

time. ........................... 60 

18a. QF17R2J4 comparison of aircraft longitudinal wind 

and Lagrangian .Doppler velocity as a function of 

time .......................... 61 

19. NSSL processor spectral display for 10' Doppler radial 

velocity spectra .................... 63 

20. Typical input and output of B1 i ck model ........ 66 

21a. Pilot approach quality assessment evaluation form, 

questions 1 through 6 ................. 72 

21b. Questions 7 through 12 ................. 73 

22. Diagrammatic illustration of wind shear detection and 

warning system .................... 76 

ix 
LIST OF TABLES 

TABLE PAGE 

1. Summary of PAR cases under analysis . . . . . . . . . 10 

2. Approach deterioration parameters for Baeing 727 

class airplane . . . . . . . . . . . . . . . . . . . 68 

3. Approach deterioration parameters for 16 Blick 

Fixed stick simulations . . . . . . . . . . . . . . . 70 

4. Summary of approach quality assessment tool . . . . . 74 

5. Linear regression slope, intercept, correlation 

coefficient, and explained variance for u' and h' 

ADP values, for four tests . . . . . . . . . . . . . . 78 

X 
CHAPTER I 

INTRODUCTION 

During the past few years, both the aviation and atmospheric science 

communities have been examining the presence of severe wind shear situated along the approach or departure path of aircraft in the terminal 

environment. Numerous investigations have been made in an attempt to 

better understand the situations that can lead to serious aircraft accidents or incidents. Fujita and Caracena (1977), Frost and Crosby (1978), 

Frost and Reddy (1 978) , and McCarthy et al. (1979) have provided insight 

into conditions pertinent to accidents. Tinsley et al. (1978) has out1 ined the FAA's operational or planned solutions to the problem. 

Fujita (1980) has documented seven accidents or incidents related 

to thunderstorm wind shear, the most recent of which was a near-accident 

of Eastern Air Lines Flight 693 at Atlanta Airport on August 22, 1979. 

Although the FAA has been examining and implementing solutions to the wind 

shear problem, the authors believe there is still room for improvement. 

Our work, and the work of Fujita (1980), indicate clearly that new systems 

must be developed to provide improved safety for civil air carriers. 

In the last ten years, three basic concepts regarding adverse 

thunderstorm wind shear have emerged: 

a. Gust Front: The concept hat hunderstorm outflow on a scale 

of 10 to 50 km horizontal extent is responsible for producing 

lethal wind shear for an aircraft. Goff (1976) presents this 

1 
case most clearly. Surface sensor techniques being implemented 

by the FAA address this feature with the Low-Level Wind Shear 

A1 ert System (LLWSAS) devel oped by Goff, and hy a microbarograph 

system developed by Bedard et al. (1979); both are becoming 

operational at many major airports. Basically, a gust front, 

or other singular discontinuity, is sensed as surface wind or 

pressure change as it advects across an airport area; upon 

detection an alert is given automatically. The phenomenon is 

identified only as it is "reflected" in surface changes, and 

as a result these surface systems- represent only "secondary" 

observing met.hods. Finally, the phenomenon measured is seen 

only on a scale ranging from 10 to 50 km, and does not appear 

to occur on a scale more closely tied to aircraft operations, 

such as 2 to 5 km. 

b. Downburst. Fujita has proposed the existence of intense 

features in and near thunderstorms, that produce both downdrafts and horizontal outflows, on a scale of 3 to 5 km 

horizontally. An excellent d.escription of this phenomenon is 

given in Fujita (1980). Of particular interest here is the 

fact that a downburst is of a rather small scale, one that 

fi-ts well.inside the approach or departure zone of an aircraft. . In other words, this phenomenon is on the same length 

scale of an aircraft operating in the terminal area. This 

scale 4s in contrast to the gust front feature,,which is 

..characteristically of larger scale. 

c. Phugoidal Waves. Groups represented by McCarthy and Frost 

have been examining the presence of rapidly varying horizontal 

2 
winds in the thunderstorm environment, and more specifically, 

calculating the response of aircraft to such winds. They 

found that long-period phugoidal response characteristics of 

high-performance jet transports could be excited by encounters 

with wave-like perturbations in horizontal wind, which, under 

certain conditions, result in major oscillations in altitude 

and airspeed, possibly leading to premature impact and/or 

stall. In their works , Frost and Crosby (1978), Frost and 

Reddy (1 978) , and McCarthy et a1 . (1 979, 1980a , 1980b) 

found that the vertical component of the wind, as one of the 

consequences of Fujita's downburst, was relatively less 

important than was the horizontal, or headwind, component, 

and proposed the implementation Of airborne systems 

designed to alert pilots of critical headwind/tailwind shear. 

Tinsley et al. (1978) and Foy (1979) best illustrate FAA 

concepts. In another FAA investigation of wind shear, Offi et al. 

(1980) describe a successful attempt to measure headwind 

along the approach path using an FAA ASR-8 surveillance radar. 

The work reported herein has been an application of the phugoidal response 

wind shear work of McCarthy et a1 . (1979) and of Frost and Crosby (1978) 

and Frost and Reddy (1978). We have recognized the importance of the 

longitudinal, or headwind/tailwind, component of wind in the thunderstorm 

environment as being most critical to aircraft performance. Although we 

accept the deleterious effect of the vertical, or downdraft, component, 

we have concentrated on the horizontal component because we believe that 

it can be readily detected. Real-time detection of the vertical component 

is much more difficult than real-time detection of the horizontal component. 

3 
We report on a feasibility study, conducted as part of SESAME '79 

(an intensive research program designed to examine many aspects of severe 

thunderstorms). SESAME '79 was conducted near Norman , Oklahoma, between 

April 1, and June 15, 1979. Details can be found in SESAME (1978, 1979a, 

1979b). Our objective was to examine the feasibi 1 i ty of measuring wind 

along a precision flight path, in the optically clear air, using a groundbased Doppler radar and, once these data were obtained, whether aircraft performance could be predicted using numerical Simulation models. TWO instrumented wind measuring research aircraft were vectored along the approach 

path to verify the accuracy of the ground-based Doppler measurement 

and to verify numerical model-predicted performance characteristics. 

Three means of assessing performance were used, two relying on the airspeed (Au' ) and altitude (Ah') approach deterioration parameters 

identified by McCarthy et al. (1979). The third method utilized 

quantitative pilot assessments of approach quality. 

The overall objective of the study was to gauge the operational 

feasibility of a ground-based Doppler radar, operated in tandem with a 

computerized numerical simulation model of aircraft performance in the 

face of adverse wind shear to predict successfully dangerous situations 

for approaching and departing aircraft. In the sections to follow, we 

will describe the experimental plan in detail, discuss the measurement 

of winds along the approach path, using both Doppler and aircraft 

measurement systems, describe the application of the Blicklfixed stick 

simulation model, discuss the simulation model, discuss the pilot 

assessment tool, look at predicted versus actual aircraft performance, 

and,finally, discuss our overall assessment and recommended plans for 

future work. 

Professor of Aerospace Engineering , University of Okl ahoma , Norman , Okl ahoma. 

4 
CHAPTER I1 

EXPERIMENTAL PLAN 

The following experimental tools were available and utilized in 

this study: 

a. A U.S. Air Force TPN-19 airport terminal area traffic control 

radar, a 10-cm wavelength surveillance radar, and a 

Precision Approach Radar (PAR) radar. The system was manned by 

air traffic controllers from FAA and the Air Force. 

b. A 10.2-cm pulsed Doppler radar located at the National Severe 

Storms Laboratory (NSSL), which could collect wind data in 

the optically clear air. 

c. A meteorologically instrumented Beech Queen Air aircraft and a 

similarly instrumented North American Sabreliner provided by 

the National Center for Atmospheric Research (NCAR). Both 

aircraft had an inertial navigation-based wind measurement 

system, capable of giving u, v and w gust components of the 

wind at high resolution, but we utilized only a 1 Hz resolution. 

Accuracies in the horizontal components are given as 1 m s-l , 

while the accuracy in the vertical can be as high as 10 cm s”. 

From these measurements , the longitudinal (para1 le1 to the 

aircraft axis of flight--or headwind-tailwind component) winds 

were derived. Additionally , a1 ti tude , true airspeed, pitch 

angle, INS position, along with many other parameters not used 

here, were recorded. 

5 
d. A numerical simulation model, developed by Blick, as 

reported in McCarthy et a1 . (1 979) , was used to predict 

performance of the two aircraft. The model included a 

fixed stick assumption (no pilot control or power changes 

were made); Frost and Turkel (1 980) wil report separately model 

results with utilized numerical pilot control functions. 

Figure 1 is a map showing the horizontal placement of the approach 

paths, the runway, and the radar beam positions, used in this study. The 

radar was set to collect time series velocity data along a 3 deg elevation beam, which nearly paralleled the approach path. Data were collected 

from contiguous range locations spaced 150 m apart, which is the closest 

possible for the present system. Minimum range varied from approximately 

2.5 to 6.0 km, limited by the antenna ground clutter return through 

antenna side lobes, while maximum range of data collection was typically 

22.5 km. The azimuth was fixed for each approach direction, in order to 

minimize ground clutter interference. 

The aircraft was vectored along a 3 deg glide path to the runway, 

using the PAR system. With this system, we could maintain the aircraft 

along the path, with a theoretical accuracy of 8 m in the horizontal 

and 2 m in the vertical , utilizing voice commands from the Air Force 

PAR controller, who could monitor the aircraft with a computer tracking 

di spl ay. 

Two types of aircraft and Doppler wind comparisons were 

attempted. The first type we call Lagrangian, because it was an attempt 

to verify most accurately the Doppler winds while an aircraft was moving 

along the beam. In other words, we continuously collected Doppler radial 

velocity data along the 3 deg path while the airplane was moving through 

6 
. " 

MAX WESTHEIMER 

AIRPORT 

NORMAN 

DOPPLlFR 

RADAR 

Figure 1. A map showing the runways, approach path, 

location, and azimuth scans for comparison experiment. 

7 
the range locations where data were collected. For the actual Lagrangian 

comparison, the Doppler radial velocity was computed in the first range 

gate immediately ahead of the airplane, which could easily be seen to 

progress through the Doppler data. This set of Doppler data, collected 

in a progressive space-time framework, was then compared point-by-point 

with the airplane longitudinal wind data. 

A second measurement we termed Eulerian, because it was sampled 

instantaneously, or time-fixed, along the flight path. One sample was 

collected immediately prior to the start of an approach, while a second 

sample was collected immediately after an approach was terminated. 

These two types of Doppler sampling were designed to accomplish 

two things. First , the Lagrangian sample provided our best "ground truth" 

verification of the Doppler's wind measuring accuracy when compared to 

aircraft-measured winds. Secondly, we wanted to know whether the Eulerian 

samples taken before (or after) an approach accurately represented the 

Lagrangian sample. In other words, is the wind shear signal coherent over 

the approximately 4 min. of the approach period? In a real-time test of 

the detection and warning system, only the Eulerian sample could provide 

significant advance warni ng. 

Simultaneously , with a1 1 PAR di rected Doppler wind measuremen'ts , 

aircraft data were collected. Both surface-based and airborne wind data 

were compared; the results of these comparisons are given in Chapter 111. 

Doppler derived winds along the approach path, for both Lagrangian 

and Eulerian modes, were fed into the Blick model, to obtain performance 

predictions. The results of these simulations are given in Chapter IV. 

During the entire experiment, 43 PAR approachs were conducted. 

However, a post-experiment examination of the data indicated complete 

8 
data availability on 16 approaches. A total of 12 Queen Air and 4 

Sabreliner approaches were analyzed fully. Table 1 summarizes certain 

detai 1 s of each of these approaches. 

9 
TABLE 1 

SUMMARY OF PAR CASES UNDER ANALYSIS 

~~~ ~ ~- ~ ~~ ~ ~~~ ~- 

Computer 

Ai rcraf t F1 i ght Run Time (CST) Identification 

Date No. No. No. Start Stop Code 

5- 7-79 

5-14-79 

5-1 4- 79 

5-14-79 

4-25-79 

4-25-79 

5- 7-79 

5-14-79 

5-1 4- 79 

5-14-79 

5-1 6-79 

5-1 6-79 

5-1 6-79 

6- 1-79 

6- 1-79 

6- 4-79 

S 

S 

S 

S 

Q 

Q 

Q 

(1 

Q 

Q 

Q 

Q 

Q 

Q 

Q 

9 

6 

8 

8 

8 

5 

5 

7 

8 

8 

8 

9 

9 

9 

16 

16 

17 

1 

1 

2 

3 

1 

3 

3 

1 

2 

3 

1 

2 

3 

1 

2 

2 

11 5247 

09371 3 

095447 

101 651 

100532 

1041 34 

11 4601 

092537 

094725 

100824 

084602 

090649 

09261 7 

085224 

091 41 1 

160009 

11 5447 

094032 

095822 

1021 01 

100739 

104342 

11 4805 

092948 

0951 40 

101219 

08481 1 

090931 

092953 

085634 

091 856 

160257 

SF6R1 M07 

SF8R1 M14 

SF8R2M14 

SF8R3M14 

QF5RlA25 

QF5R3A25 

QF7R3M07 

QF8RlM14 

QF8R2M14 

QF8R3M14 

QF9R1 M16 

QF9R2M16 

QF9R3M16 

QF16R1 J1 

QF16R2Jl 

QF17R2J4 

S = NCAR Sabreliner 

Q = NCAR Queen Air 

10 
CHAPTER 111 

MEASUREMENT OF W-INN ALONG THE APPROACH PATH 

.. 

1. Doppler Radar Winds 

Estimates of the clear-air velocity were obtained interactively 

from the mini-computer system at NSSL. The velocity spectrum, which 

consisted of the average of ten discrete velocity spectra, was displayed 

for each of 64 resolution volumes. Each mean velocity spectrum is displayed by 

64 points or indices spanning an index value from -32 to +31. After making 

a rough visual estimation of the mean Doppler or expected value of the 

clear-air Doppler velocity, an objective estimate of the mean index, 

E(i), is made using 

where M is the number of indices (64), i is the index, and Pi is the 

power density of the spectrum at index i. In the algorithm used, 

spectral noise created by ground clutter is removed by limiting the 

range spanned by the index i to just that required to bracket the clearair velocity spectrum. This is equivalent to reducing the spectral 

density outside of the clear-air velocity spectrum to zero. 

Radial velocity is obtained from (1) by the relation 

where V is the radial veJocity in m s-l (defined as positive away from 

the radar and negative towards the radar) , X is the wavelength ‘of the . - 
radar in meters, i is the index of the mean Doppler, M is the total number 

of indices, and T is the pulse repetition time (PRT) in seconds. Velocity 

values obtained by the algorithm used at NSSL are accurate to better than 

20.25 m s-1. Figure 2 is a photograph of the real-time display, illustrating a wind shear situation. 

During each approach, a Lagrangian data set was collected consisting of the clear-air velocity in the "cleanest" range gate ahead of 

the approaching aircraft. The spectral signature of the aircraft was 

strikingly different from a clear-air signal, so there was no difficulty 

in defining a "clean" range gate just in front of the aircraft. The 

Lagrangian velocity data were, of course, collected as a function of 

time and range. In general, the spatial resolution of the Lagrangian data 

was inferior to that of the Eulerian data. Some time was required to 

gather the Doppler data and average the spectra; depending on the approach 

speed of the aircraft and this data acquisition time, the aircraft may 

have flown completely through one or even two range gates. So, whereas 

we have velocity data with a spatial resolution of 150 m for the Eulerian 

cases, we often may have velocities at only every 300 rn for the 

Lagrangian data. 

Processing of the data consisted first of filtering (smoothing), 

using a simple three-point filter defined by 

which has a response function of 

R( s) = 1 - 2s sin (TAx~L) 2 (4) 

where s is a constant that determines the filter response, j is an index, 

f is the value of the data at some j, and Ax is the interval between 

the data points. For this study, s = S, yielding a response of 

'Private communication with R. Doviak, NSSL. 

12 
Figure 2. Photograph of the NSSL display for Queen 

Air Flight 9 Run 3. Display shows 16 Doppler spectra 

at each 150 m slant range, with closest ranqe 12.9 km 

(bottom) and furthest range 15.3 km (top). Clear air 

velocity values range from + 32 ms-1, with typical 

values for this case near 15 m s-1, shown as integer 

values for each spectrum. 

13 
R(Q = cos2 (~AX/L) (5) 

thus completely removing wavelengths of 2ax. This filter and its response 

function apply only to evenly spaced data. Unfortunately, the Lagrangian 

data are not necessarily evenly spaced in time or space. However, it 

was felt that the deviations from even spacing were not sufficient to 

inval idate use of this fi 1 ter. 

Since data spacing is on the order of 150 m for Eulerian data and 

300 m for Lagrangian data, some method of interpolati.on must be used for 

plotting purposes. Further, our numerical model used requires that wind 

data be supplied every second, which necessitates interpolation. The 

most suitable interpolation scheme for these purposes was a natural 

cubic spline, which has several attractive features: 

1) the spline passes through every data point; 

2) the spline [si(x)] is a cubic on each subinterval (xi, xi+l); 

3) the spline is continuous, i.e., si(xi) = S~+~(X~); and 

4) the first and second derivatives are continuous and the 

is a minimum, yielding the smoothest possible interpolation 

through the data. 

Since there are an indefinite number of cubic splines, defined by 

boundary conditions, which will interpolate a set of points , and since 

nothing was known about the derivatives at the end points, a natural 

cubic spline was defined by setting the first and second derivatives at 

the end points to zero. 

For plots of velocity as a function of range, interpolations were 

performed at 25 m intervals, and for plots of velocity as a function of 

14 
time, interpolations were performed at 0.5 sec. intervals. Eulerian 

data were plotted as a function of time after a space-to-time conversion 

using the mean speed of the aircraft down the approach, defined by 

Rmax min = v -R 

At 

where R is the range of the most distant range gate used in the 

Lagrangian data , Rmi is the range of the closest range gate, and t is 

the number of seconds taken to traversethe distance (Rmax - Rmin). 

max 

2. Aircraft Measured Winds 

For each of the 16 PAR approaches studied in .detai 1 , the aircraft 

wind data were collected at 8 Hz, and examined at 1 Hz after a running 

average was applied. The primary wind variable examined was the longitudinal component (headwind, tailwind) along the flight rack. Aircraft 

position was determined initially by an inertial navigation system (INS). 

Aircraft range from the Norman Doppler radar was calculated from the Doppler 

data, since the aircraft provided a strong radar return, and could 

easily be seen to move along the beam. We found that the aircraft 

position was often between 0.5 and 1.5 km different than the range 

position provided by the Doppler radar. Because of well-known non 

and uncorrectable errors in the INS, we decided to use the Doppler 

as the "correct" 'range for the comparisons. Unfortunately, we cou 

locate the aircraft position lateral to the beam. Since the radar 

and approach paths were not colocated (see Figure 1 ) , there was an 

approximate 1 km average uncorrected lateral position error. 

I NS 

1 i near 

signa 

Id not 

beam 

1 

15 
3. Comparison Between Doppler Radar, Aircraft Winds, and other Flight 

Parameters. 

We have examined 12 Queen Air approaches, and 4 Sabreliner approaches. 

When we compared Doppler radar and aircraft longitudinal wind data, using 

a subjective judgment, 75% of the 16 approaches compared we1 1 , while 25% did 

not. To illustrate this further, we chose two cases to present in detail 

here. 

a. 16 May 1979 - Queen Air Flight 9 Run 3 

On this day, we made three approaches to runway 03 (northnortheast bound) to Westheimer, during a clear-air low-level southerly 

jet situation, in mid-morning. The approach began at 092617 CST and 

ended at 092953, with a start range from the Doppler of 20.5 km, and 

a final range of 3.7 km. The approach lasted 3 min, 36 sec. Figure 3a 

presents a vertical view of the approach, with aircraft height, in 

meters above Norman radar, expressed as a function of time. Figure 3b 

represents the height of the aircraft, expressed as deviation in meters 

from the glide slope as a function of time. Notice the phugoidal-like 

oscillation in the altitude. These oscillations can be seen in the 

airspeed and pitch angle data, as a function of time (Figures 3c-,e). 

Figure 3f represents the Lagrangian comparison between the 

aircraft longitudinal wind and the Doppler radial wind, along the 

glide path, as a function of time. Several interesting points can 

be seen. The resolution/smoothing difference between the aircraft 

and Doppler data is evident. While the absolute comparison appears 

quite good, there are obvious differences, particularly farther 

out from the radar. Finally, small-scale wave-like and turbulent 

16 
20 40 60 80 100 120 140 160 180 30 

TIME (S) BETWEEN 092617 AND 092953 

Figure 3a. First of 8 data panel s for Queen Air 

approach on 16 May 1979, designated as Flight 9 Run 3 

(approach code QF9R3M16 on Table 1 ) . This shows aircraft altitude (m) above the Norman Doppler radar, as 

a function of time. Solid 1 ine is actual aircraft 

altitude, while dashed line represents the calculated 

a1 ti tude as determined by the B1 ick numerical simulation model, applied to the Eulerian Before case; 

results of the model will be discussed in Chapter IV. 

17 
.. . ,. I. 

.. ., 

TIME (S) BETWEEN 092617 AND 092953 

Figure 3b. QF9R3M16 showing aircraft (sol id 1 ine) and 

model (dashed line) altitude (m) departure from a 3 deg 

glide slope path to the radar, with positive values 

representing a1 ti tude departures above the path, a1 1 as 

function of time. The lack of phasing here and in -3c,d,e, 

is apparently due to the inaccuracy of the model to predict 

precise details in weak shear conditions. 

18 
w 

x 

CL 

c 

Figure 3c. QF9R3M16 showing aircraft and model- true 

airspeed (m s-1) as a function of time. 

19 
TIME (S) BETWEEN 092617 AND 092953 

Figure 3d. QF9R3M16 showing aircraft and model airspeed departu e nominal (or no wind) approach speed 

of 61.77 rn s-T (1 20 knots) ; airspeeds higher than 

norni nal are posi ti ve . 

20 
I 

10 

8 

6 

4 

-4 

-6 

Figure 3e. QF9R3M16 showing aircraft and model pitch 

angle (deg) as a function of time. 

21 
Figure 3f. QF9R3M16 compari s n of aircraft (sol id 

line) longitudinal wind (m s- P ) and Lagrangian 

Doppler velocity (m s-1) (dashed line) as a function 

of time. 

22 
Figure 39. QF9R3M16 comparison of aircraft (sol id 

1 ine) longitudinal wind and Eulerian Doppler 

velocity (dashed line) taken 1 s immediatley before 

the start of the approach. 

23 
20 

18 

16 

14 

12 

lo 

8 

6 

4 

2 

o'~~~'l"""l"'''' I 20 40 64 80 100 120 140 160 180 200 

TIME (SI BETWEEN 092617 AND 092953 

Figure 3h. QF9R3M16 comparison for Eul eri an Doppler 

velocity taken 1 s immediately after the end of the 

approach. 

24 
Figure 4a. First of 8 data panels for Queen Air 

approach on 7 May 1979, designated as Flight 7 

Run 3 (approach code QF7R3M07 on Table 1 ) . This 

shows aircraft a1 ti tude (m) above the Norman Doppler 

radar, as a function of time. Solid line is actual 

aircraft altitude, while dashed line represents the 

calculated a1 ti tude as determined by the B1 ick 

numerical simulation model, applied to the Eulerian 

Before case; results of the mode7 will be discussed 

in Chapter 1V. 

25 
TIME (S) BETWEEN 114601 AND 114805 

Figure 4b. QF7R3M07 showing aircraft (solid line) 

and model (dashed 1 ine) altitude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

26 
-07 m07 1146-1 148 

TIME (S) BETWEEN 114601 AND 114805 

,. ' . . . . . : . . . 

Figure 4c. ' QF7R3M07 showi.ng aircraft. and model true'. -% 

airspeed (m s-1) as a function of time;, i ... "~.., 
- " . - . -. . .... " ... 

-. ...-.. * "+" f""". .. " -t - .. _. .. ........................ 

........ .-..--. . .......... ........................ 

........... - -+-""". '? ....... ............+.,.......'. 

...................... *", ....... 

TIME (SI BETWEEN 114601 AND 114805 

Figure 4d. QF7R3M07 showing aircraft and model airspeed departure nominal (or no wind) approach speed 

of 61.77 rn s-l (120 knots) ; airspeeds higher than 

nominal are positive. 

28 

" 
10 

8 

6 

-4 

-6 

-8 

! 

-10 

TINE (SI BETWEEN 114601 AND 114805 

Figure 4e. QF7R3M07 showing aircraft and model pitch 

angle (deg) as a function of time. 
Sf4 G7R%07 oF7FuH07 1146-1148 

19 

12 

11 

10 

TIME. (SI BETWEEN 114601 AND 114805 

Fugure 4f. QF7R3M07 comparison of aircraft (sol id 

1 ine) 1 ongi tudinal wind (m s-l) and Lagrangian Doppler 

velocity (m s-1) (dashed line) as a function of time. 

30 
20 

19 

18 

- 

.-4 

v, 17 E 

I 

LL 

-1 

3 

w 

w 1s 

12 

11 

10 

Figure 49. QF7R3M07 comparison of aircraft (sol id 

line) longitudinal wind and Eulerian Doppler 

velocity (dashed line) taken 1 s immediately before 

the start of the approach. 

31 
Figure 4h. QF7R3M07 comparison for Eulerian Doppler 

velocity taken 1 s immediately after the end of the 

approach. 

32 
disturbances are evident in the higher-resolution aircraft data. 

Remember, this comparison represents the best comparison, where 

the aircraft and Doppler data were collected in as close a spacetime framework as possible. Of course, to make this comparison 

possible, the aircraft had to make the approach, a situation 

unsuitable for our real-time detection and warning system. In 

that system, we want to be able to monitor the wind shear continuously, to anticipate adverse conditions along the path, prior 

to an airplane actually beginning an approach. 

Figures 3g and 3h represent Euleri an velocity comparisons , 

with the Doppler data collected 1 set. immediately prior to the start 

of the approach, and 1 sec. immediately following the termination of 

the approach, respectively. Two obvious features are apparent. 

The general nature of the comparison does not change. The Eulerian 

profiles are not significantly different from the Lagrangian profile. However, the position of the smaller-scale features do shift 

somewhat, suggesting that waves or turbulent eddies are moving 

through the data. 

b. 7 May 1979 - Queen Air Flight 7 Run 3 

We would be unfair if we failed to describe one of the poor 

cases. The wind shear situation is considerably less dramatic 

than the previous one. The approach began at 114601 at a range of 

14.4 km, and ended at 114805 at a minimum range of 5 km, taking 

2 min 4 sec to complete. The approach was made to runway 35 

(north-bound) at Westheimer field. 

Figures 4 a-h give results presented identically to Figures 

3a - h. No obvious wind shear is evident along the flight path, 

33 
such as a penetration through a low-level jet, as in the previous example. 

However, certain wave-like fluctuations (2 to 3 m s-l vari.ation)' are 

evident. Furthermore, no clear phugoidal oscillation is present in aircraft, altitude, airspeed, and pitch angle data. Unfortunately, the most 

obvious impression is the lack of general or absolute agreement between aircraft and Doppler wind data. However, when we look at the smal ler-scale 

fluctuations, we see a similarity in scale, although seemingly out of phase. 

This impression becomes slightly clearer when we compare the Lagrangian 

case (Figure 4f) to the two Eulerian cases (Figures 4g-h) . Our only 

explanatio'n for the lack of phasing pertains to the model's apparent inability 

to predict weak wind shear situations accurately; we wil discuss this later 

in more detail. 

In Figures 5-1 8 , we present the remainder of the comparisons. We 

give only the altitude variationsfrom the glide slope, similar to panel b 

in Figures 3 and 4, and the comparison between the Lagrangian Doppler and 

aircraft winds, similar to panel f for Figures 3 and 4. Note that the 

altitude deviation was unavaflable for the last case QF17R254, or Figure 18. 

The most obvious feature of these comparisons has been the remarkably 

good agreement between the aircraft and Doppler data. This is particularly 

true for case (a) and for approximately 75% of the cases examined'. Furthermore, we were pleased with the apparent coherence or representativeness of 

the Eulerian profiles over the 3 to 4 min of the approach periods, indicating 

that such a data sample, when processed to provide a quantitative estimate 

of approach deterioration, likely would be suitable. One important caution 

should be considered: the comparisons given here are for essentially nonthunderstorm related shears, so a good 3 to 4 min coherence might be 

expected. In the case of the microburst phenomenon discussed by Fujita 

34 
TIME (SI BETWEEN 115247 AND 115447 

Figure 5a. SF6RlM07 showing aircraft (solid line) 

and model (dashed line), altitude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

35 
W@ 9-R SF6RlH07 SSRlH07 1152-1 154 

Figure 5b. SF6RlM07 comparison of aircraft (solid 

line) longitudinal wind (m s-1) and Lagrangian Doppler 

velocity (m s-1) (dashed line) as a function of time. 

36 
J 

51 

LL 

"0 

s2 

- 150 

-200 

TIME (S) BETWEEN 092537 AND 092948 

Figure 6a. SF8RlM14 showing aircraft (solid line) 

and model (dashed 1 ine) a1 ti tude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

37 
20 

19 

18 

11 

10 20 40 64 Bo 100 120 140 160 180 

TIME (SI BETWEEN 093713 AND 094032 

Figure 6b. SF8RlM14 comparison of aircraft (solid 

line) longitudinal wind (rn s-l) and Lagrangian 

Doppler velocity (rn s-1) (dashed line) as a function 

of time. 

38 
TIME (S) BETWEEN 095447 AND 095822 

Figure 7a. SF8RZM14 showing aircraft (solid line) and 

model (dashed line) altitude (m) departure from a 3 deg 

glide slope path to the radar, with positive values 

representing altitude departures above the path, all as 

function of time. 

39 
16 

2- 

12 

L 

2 

z6 

B 

4 

W 

W 

4 

2 

0 

TIME (S) BETWEEN 095447 AND 095822 

Figure 7b. SF8RZM14 comparison of aircraft (solid 

1 i ne) 1 ongi tudi nal wind (m s-1) and Lagrangian 

Doppler velocity (m s-1) (dashed line) as a function 

of time. 

40 
200 

150 

100 

I 

r 

W 

e -53 

Q 

E 

W 

a 

a 

-1c3 

- 153 

-230 

TIME (SI BETWEEN 101651 AND 102101 

Figure 8a. SF8R3M14 showing aircraft (solid line) 

and model (dashed 1 i ne) a1 ti tude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

41 
TIME (S) BETWEEN 101651 AND 102101 

Figure 8b. SF8R3M14 comparis n of aircraft (solid 

1 i ne) longitudinal wind (m s- P ) and Lagrangian Doppler 

velocity (m s-1) (dashed line) as a function of time. 

42 
TINE (SI BETWEEN 100532 AND 100739 

Figure 9a. QF5RlA25 showing aircraft (solid line) 

and model (dashed line) altitude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

43 
M 

18 

16 

2 

0 

Figure 9b. QF5RlA25 comparison of aircraft (solid 

line) longitudinal wind (m s-l) and Lagrangian Doppler 

velocity (m s-l) (dashed line) as a function of time. 

44 
Figure lla. QF8RlM14 showing aircraft (solid line) 

and model (dashed line) a1 titude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

47 
18 

2 

0 

TIME (SI BETWEEN 092537 AND 092’948 

Figure llb. QF8RlM14 comparison of aircraft (solid 

line) longitudinal wind (m s-1) and Lagrangian Doppler 

velocity (m s-l) (dashed line) a.s a function of time. 

48 
200 

150 

100 

50 

0 

-50 

- 100 

- 150 

-20C 

20 40 60 80 100 120 140 160 180 230 2?0 240 

TIME (SI BETWEEN 094725 AND 095140 

Figure 12a. QF8RZM14 showing aircraft (solid line) 

and model (dasned line) altitude (m) departure from a 

3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

49 
20 40 64 80 100 120 140 164 180 200 240 

TINE (SI BETWEEN 094725 AND 095140 

Figure 12b. QF8R2M14 comparison of aircraft (sol id 

1 ine) longitudinal wind (m s-l) and Lagrangian 

Doppler velocity (m s-’) (dashed line) as a function 

of time. 

50 

I 
" " 

TIME (S) BETWEEN 100824 AND 101219 

Figure 13a. QF8R3M14 showing aircraft (solid line) 

and model (dashed 1 ine) a1 ti tude (m) departure from 

a 3 deg glide,slope path to the radar, with positive values representing a1 ti tude departures above the 

path, all as function of time. 

51 
bN) 4R oFWFt14 ml4 1008-1012 

18 

2 

0 

Figure 13b. QF8R3M14 compariTon of aircraft (solid 

1 i ne) longitudinal wind (m s- ) and Lagrangian Doppler 

velocity (m s-l) (dashed line) as a function of time. 

52 
Figure 14a. QF9RlM16 showing aircraft (solid line) . 

and model (dashed line) altitude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

53 
TIME (S) BETWEEN 084602 AND 084811 

Figure 14b. QF9RlM16 compari on of aircraft (sol id 

1 ine) longitudinal wind (m s-?) and Lagrangian 

Doppler velocity (m s-1) (dashed line) as a function 

of time. 

54 
200 

1% 

100 

50 

0 

-X 

-100 

-lx 

"0 

20 40 60 80 100 120 140 160 

TINE (S) BETWEEN 090649 AND 090931 

Figure 15a. QF9RZM16 showing aircraft (sol id 1 ine) 

and model (dashed 1 ine) a1 titude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the 

path, all as function of time. 

I 

55 

.~ .
20 40 60 80 100 120 140 

TIME (S) BETWEEN 090649 AND 090931 

Figure 15b. QF9R2416 comparison of aircraft (sol id 

1 ine) lon i tud'nal wind (m s-1) and Lagrangian Doppler velocity ym s-1) (dashed line) as a function of time. 

56 
TIME (SI BETWEEN 085224 AND 085634 

Figure 16a. QF16RlJ1 showing aircraft (solid line) 

and model (dashed 1 ine) a1 titude (m) departure from a 

3 deg glide slope path to the radar, with positive 

values representing a1 ti tude departures above the 

path, all as function of time. 

57 
Figure 16b. QF16R1 Jl comparison of aircraft (sol id 

1 ine) 1 ongi tudinal wind (m s-l) and Lagrangian Doppler 

velocity (m sdl ) (dashed line) as a function of time. 

58 
TIME (S) BETWEEN 091411 AND 091856 

Figure 17a. QF16RZJ1 showing aircraft (solid line) 

and model (dashed line) altitude (m) departure from 

a 3 deg glide slope path to the radar, with positive 

values representing altitude departures above the path, 

all as function of time. 

59 
Figure 17b. QF16RZJ1 compari on of aircraft (sol id 

line) longitudinal wind (m s- ? ) and Lagrangian Doppler 

velocity (m S-l) (dashed line) as a function of time. 

60 
TIME (SI BETWEEN 160009 AND 160257 

Figure 18a. QFl7R2J4 compari on of aircraft (solid 

1 ine) 1 ongi tudinal wind (m s- 4 ) and Lagrangian Doppler 

velocity (m s-l) (dashed line) as a function of time. 

NOTE: Altitude deviation data was not available. 

61 
(1980) , we believe Doppler scans on the order of once each minute might 

be requi red. 

We were less pleased with the lack of phasing in the smaller 

scale features , particularly in 25% of our sample, as represented by 

case (b). We decided to look more carefully at the spectra which were 

used to obtain the Doppler wind profile, to see if a more satisfactory 

explanation could be obtained. Figure 19 represents ten such spectra, 

ranging from 9.55 to 8.2 km from the Norman-radar. .. Although the spectra are 

not exactly clean, those at 8.2', 8'.35, 8.5, and 9.55 km are single-moded, 

suggesting that our .averaging technique using equations (1 ) and (2) was 

suitable. However, for the spectra at 8.65, 8.8, 8.95, 9.1,. 9.25, and 

9.40 km, a clear bimodal distribution is evident. Consequently, our 

radial velocity esti'mates at these latter ranges are probably inaccurate, 

a fact consistent with.Figure 4f. The causes for such spectra are many, 

and there is no' unique way to single out any one. For instance, strong 

point targets in the side lobes can spi 11 enough power into contiguous 

range bins to .create such.spectra.. Yet we. cannot discard the possibility 

that meteorological"signa1s on 'small scales are responsible for these 

bimodal veloci'ty spectra. The presence of turbulent vortices or eddies, 

coupled with our lack of colocation in our comparisons, particularly in 

.. .. 

.. 

., I .. 

.. ,. 

azimuth, could certainly account for some of the differences in aircraft 

and Doppler data. If the radar and aircraft sampling had been precisely 

colocated, we would expect these variations to be considerably less obvious. 

Finally, we know that even if this were the case, the two measurements 

differ in that the aircraft is providing a series of point velocity measurements, while the Doppler radar presents a reflectivity and resolution 

volume weighted mean values. 

62 
I 

-32 -28 -24 -20 -16 -12 -8 -4 0 

DOPPLER RADIAL VELOCITY (m S-9 

Figure 19. NSSL processor spectral display for 

10 Doppler radial velocity spectra, ranging from 

8.2 to 9.55 km, expressed as a function of spectral 

intensity (dB below peak). For each spectrum displayed, three spectral data samples were averaged. 

Time of sample was 11 471 9 CST on 7 May 1979--refer 

to Figure 4a-h for comparison. 

63 
The following conclusions are justified: 

1. For 75% of the cases examined to date, excellent agreement is 

obtained. 

2. Certain small-scale disturbances were not verified in the 

comparisons, due to the following problems: 

a. a lack of Doppler resolution, 

b. a lack of colocation of the two sampling systems, 

c. the possible presence of eddy or vortex-like disturbances 

within the pulse volume, as well as point targets in 

antenna side lobes. 

3. If a Doppler radar were to obtain clear-air radial wind data 

precisely along the intended approach path , problems 2a and 

2b would be greatly reduced. Furthermore, we believe that 

if the antenna was shrouded to reduce side lobes, the problem 

with point targets would be practically eliminated. 

4. Use of a Doppler radar to provide the measurement component 

of an Airport Wind Shear Detection and Warning System appears 

justified. 

64 
CHAPTER IV 

RESULTS OF FIXED STICK BLICK NUMERICAL SIMULATION MODEL 

The model of aircraft performance developed by Blick, and reported 

in McCarthy et a1 . (1979) , was appl ied to the 16 approaches studied in 

detai 1. Airplane transfer functions for the Queen Air and Sabrel iner 

were developed and tested. All model runs were made with the fixed stick 

assumption, while a pilot-in-the-loop edition was run by Frost 

and Turkel (1 980). A1 1 runs were begun at th.e initial range indicated 

in the figures of Chapter 111, with the nominal airspeed for the Queen Air 

and Sabrel iner 61.77 m s-l (120 knots) and 66.92 m s-l (1 30 knots) 

respectively. A typical example of the Blick model output is given in Figure 20. 

As in McCarthy et a1 . (1979) , we computed approach quality by two means: 

1 /2 

Au' = [d tL u2 dt] (8) 

Ah' = [k/ tL(h - hn)* dt] (9) 

1 /2 

0 

Where Au' is the root-mean-square value of airspeed (m s -' ) deviation 

from the nominal or equilibrium airspeed, Ah' is the root-mean-square 

value of a1 ti tude deviation from the 3 deg glide slope , tL is the total 

approach time (s) to landing, u is airspeed (m s"), h is aircraft altitude (m), hn is nominal aircraft altitude (m) along a 3 deg glide slope, 

and t is time (s). From the equations and as discussed in McCarthy et a1 . 

(1979), we can see that 1 arge values of Au ' and Ah' represent serious 

I 
IJG 

000020 

WG 

000020 

TRS 

000020 

THE 

000020 

Figure 20. Typical input and output of Blick model. 

Case is for Boeing 727 airplane. Input, shown as 

top two panels on left, are horizontal (UG) and 

vertical (WG) wind; output are true airspeed (TAS) 

and pitch angle (THE). Trace shows glide slope and 

0.7 deg missed approach limits (solid lines) and 

aircraft position (1's). 

66 
deteriorations of the approach. Consequently , we call Au' and Ah' 

approach deterioration parameters (ADP). 

To gain further insight into the importance of the horizontal 

phugoid wave, we have examined the approach deterioration parameters of 

a B-727 class airplane, when full, half, and one-quarter sinewaves of 

horizontal (longitudinal) winds, precisely at the airplane's phugoid 

frequency, are inputted into the controlled-fixed simulation model. 

Results are shown in Table 2 in terms of Au', Ah', and DTD; here DTD 

represents the distance long or short of aircraft nominal touchdown. 

... .. 

Our work suggests that Au' may be the most useful indicator, since 

airspeed fluctuations may be .the most difficult for the pilot and 

airplane to handle. Note that the Au' parameter is rms velocity, and 

not the instantaneous airspeed. It is clear that an aircraft encounter 

with a full wave can be most serious, as can the half wave situation. 

The one-fourth wave situation, representing a simple ramp or step shear 

which may be encountered in a gust front, is considerably less serious 

than an encounter with a phugoidal wave. Another interesting point is 

seen when the ADP values for Eastern Air Lines Flight 66, as reported 

in McCarthy et al. (1979) , are considered in the context of Table 2. 

Notice that this crash occurred when the airplane encountered a re1 atively 

low 1/2 wave amplitude. Recent studies of the phugoidal waves associated 

with severe thunderstorms show amplitudes in the 15 to 25 m s-' range 

(see Wilson et al., 1980) , and implies' that the Eastern Flight 66 of 

wind shear accident may be associated with relatively non-severe storms, 

a fact we1 1 documented by Fuj ita and Caracena (1977). Pi lots have long 

,. 

.. 

I avoided severe thunderstorms; this work shows the extreme danger associated with weak thunderstorms that have phugoidal waves. 

67 

I . .. " " 
TABLE 2 

~~~~ ~ 

Approach deterioration parameters for Boeing 727 class airplane, for simulated sinusoidal full, half and one-fourth wave longitudinal wind inputs 

at airplane phugoid frequency of 0.026 Hz, for control-fixed model , with 

both initial headwind and initial tailwind cases, for 5, 10, 15, 20, 

m S-l amp1 i tudes. DTD (km) is airplane touchdown distance from nominal 

(runway), with negative being short, positive long,* 

Initial Headwind Initial Tailwind 

Wave Amplitude (m s-') 

5 10 15 20 I 20 15 10 5 I I I 

I I I 

Au'! Full Wave 4.8 10.2 16.6 23.9 23.0 16.0 9.9 4.7 I I I 

I Half Wave f 2.3* 4.6 6.9 9.3 I 9.8 7.3 4.7 2.3 I I I I 

! One-Fourth I .5 I Wave 

I I 

I 3.0 4.6 6.1 I 7.5 5.2 3.4 1.6I 

I I 

I I I I 

I I I 

I I I 

I I I 

Ah1! Full Wave f 47.6 129.6 237.5 350.4 I 318.6 209.1 109.0 39.5 

I Half Wave I 17.0* 36.1 61.5 95.2 139390.7 52.1 22.2 

I I I I I 

I I I I I 

f One-Fourth 

I Wave I 

I 

I 

I 

I 

DTD! Full Wave 

i Half Nave 

I 

I 

One-Fourth 

I Wave I 

I 

! 32.2 57.8 75.3 85.0 I 

I 

I 

I 

I 

-0.93 -3.39 -6.65 -9.98 I 

+0.01 -0.17 -1.02* -2.16 I 

I 

+0.53 +1.01 +1.30 +1.36 I 

I 

! 212.2 149.6 93.5 43.3 I 

I 

I 

I 

I 

I 

I -9..26 -5.95 -2.78 -0.40 I 

I -2.27 -1.87 -0.72 -0.17 I 

I 

f -4.57 -2.59 -1 -91 -0.89 I 

I I I I I I I 

*Represents approximate values for Eastern Air Lines Flight 66. 
Table 3 gives Au' and Ah' for our 16 simulations. Shown are values 

for the Lagrangian and two Eulerian estimates, as defined in Chapter 111. 

The most obvious feature seen in the table is the absence of large values 

of model output Au' and Ah'. This is particularly true for Au' , where rms 

airspeed variations (Eulerian Before--1 sec before test) from nominal 

never exceed 2.1 m s-l, with the average being only 1 .O m s-'. Remember 

that the Eastern Air Lines Flight 66 value was 3.5 m s-'. Note too, that 

the Sabre1 iner average is 2.0 m 5-l while the Queen Air average is 0.7 m s-l. 

The Sabreliner has a higher phugoidal response than does the Queen Air, 

as may be suggested in these data. 

- 

With regard to Ah', for a fixed stick model, certain altitude 

I departures from the glide slope readily can be corrected were pilot con- 

! trols included. Consequently less importance is attached to Ah' values. 

More discussion of this point can be found in McCarthy et al. (1979). 

We have plotted the results of the Blick output as a dashed line 

on Figure 3a-e, 4a-e, and 5 to 18, for the Eulerian Before case (1 sec after 

test). Results are quite similar for the Eulerian After and Lagrangian 

and consequently are not shown. 

It is clear from Table 3 and the plotted figures that we did not 

encounter significantly adverse wind shear. We attribute this to the 

fact that our pilots, controllers, and SESAME '79 Aircraft Coordinator 

did not want to attempt PAR approaches in dangerous wind shear conditions. This serious limitation in the planned test of feasibility will 

be discussed in detail in Chapter VII. 

1 

'Lead author, John McCarthy. 

69 
TABLE 3 

Approach deterioration parameters (ADP, Au' and Ah')for 16 Blick Fixed sticK simulations. Also include 

ADP are estimates of actual aircraft performance, to be discussed in Chapter VI. 

I Approach Au I Au I Au I Au I Ah I Ah I Ah I Ah I 

Before After Before After 

ms ms ms ms 

Code Lagrangian Eulerian Eulerian Aircraft Lagrangian Eulerian , Eulerian Aircraft 

-1 -1 -1 -1 

m m m rn 

S F6R1 M07 

SF8R1 M14 

SF8R2M14 

SF8R3M14 

QF5RlA25 

QF5R3A25 

QF7R3M07 

QF8R1 M14 

QF8R2M14 

QF8R3M14 

QF9R1 M16 

QF9R2M16 

QF9R3M16 

QF16R1 J1 

QF16R2J1 

U 

0 

2.1 

0.7 

1.6 

2.1 

0.4 

0.4 

0.8 

0.5 

0.7 

0.4 

0.3 

0.4 

0.4 

0.5 

0.8 

2.6 

2.4 

1.4 

1.4 

0.5 

0.5 

1 .o 

0.7 

0.7 

0.7 

0.9 

0.8 

0.8 

0.6 

0.4 

1.3 

1 .o 

2.0 

1.4 

0.5 

0.8 

1.1 

0.6 

0.6 

0.8 

1 .o 

0.8 

1 .o 

0.6 

0.5 

~~ ~~~ 

1.9 

4.3 

7.2 

2.4 

1.4 

3.2 

2.9 

3.8 

3.0 

4.5 

1.7 

4.8 

4.9 

2.9 

8. D 2 

~ ~ ~~ 

20.3 

29.7 

36.0 

20.9 

25.3 

10.9 

9.1 

23.5 

27.1 

24.8 

36.9 

46.7 

19.9 

15.6 

12.9 

~ ~ ~~ ~ ~~~ 

24.8 

37.6 

34.7 

16.3 

23.6 

13.4 

7.6 

26.6 

20.5 

22.3 

39.1 

35.9 

39.3 

26.2 

13.9 

~~~ ~ ~ ~ 

15.7 

28.7 

33.3 

16.3 

25.6' 

29.7 

15.2 

24.8 

24.3 

26.0 

46.1 

40.6 

47.0 

26.2 

13.1 

40.6 

149.2 

73.4 

108.4 

75.6 

32.2 

69.6 

69.9 

74.4 

41.5 

51.3 

39.3 

71.7 

20.3 

54.0 

I 

QF17R2J4 0.8 0.9 0.8 1.7 9.1 13.2 11.5 18.7 
CHAPTER V 

PAR APPROACH QUALITY ASSESSMENT OOL 

As an independent method of assessing the quality of the approach, 

an-approach quality assessment tool, designed to be completed by the 

pilot, was developed by Mr. A. L. Fincher. Figure 21 is a copy of this 

evaluation sheet. Table 4 presents the results of its use for 15 of the 

16 approaches studied (the evaluation for Sabreliner Flight 6 Run 1 was 

not available). As a means of estimating the quality of the approach, 

we have totalled questions 7 through 12, by assigning a numerical value 

of 1 for a, 2 for b, and 3 for c. These totals indicate that Queen Air 

approaches 16-2, 9-3, 8-3, and 5-3 were considered by the pilots to be 

the most adverse. However, as is clear from the last chapter, none of 

our approaches were conducted in truly dangerous shear conditions. We 

believe, however, that the usefulness of this tool wil be more meaningful in an experiment where a greater range of shear is encountered. 

71 
Date 

Pilot's Name 

Aircraft I.D. 

Approach Start Time 

Approach Stop Time 

APPROACH QUALITY 

(PILOT) 

1. 

2. 

3. 

4. 

5. 

6. 

Approximately how many power adjustments were required on 

this approach? 

a. Less than five (5) 

b. More than five (5) but less than ten (10) 

c. More than ten (10) 

Concerning the magnitude of power changes: In your opinion, 

were the power adjustments required on this approach? 

a. Only minor 

b. Moderate c. Major Power Corrections 

Approximately how many pitch adjustments were required on 

this apDroach? 

a. Less than five (5) 

b. More than five (5) but less than ten (10) 

c. More than ten (10) 

Pitch corrections on this approach k-re: 

a. Slight and predominantly less than five (5) dearees. 

b. Moderate - between five (5) and ten (10) deqrees. 

c. Significant - more than ten (10) degrees. 

Concerning azimuthal deviations from the final aporoach course, 

on this approach there were: 

a. Only "minor" deviations 

b. Significant deviations 

c. Extreme deviations 

Concerning vertical deviations from the alide path on this 

approach, there were: 

a. Minor deviations 

b. Significant deviations. 

c. Extreme deviations 

Figure 21 a. Pilot approach quality assessment eval uation form, questions 1 through 6. 

72 
"" . 

7. 

8. 

9. 

10. 

11. 

12. 

Turbulence experienced on this approach could be categorized as: 

a. None 

b. Liqht 

c. Moderate 

d. Severe 

Airspeed deviations on this approach were: 

a. Less than five (5) knots 

b. More than five (5) knots c. More than ten (10) knots 

rdaximum chan es in vertical velocity (WI) indications re- quired t&*is approach were: 

a. 250 FPM or less 

b. More than 250 FPX but less than 500 FPM 

c. More than 500 FPM 

How would you evaluate the final controller's performance 

on this approach? 

a. Excellent 

b. Average c. Below average 

How would you characterize the "safety" of this approach? 

a. Completely safe 

b. Marginally safe c. Unsafe 

What was your "overall impression" of this approach? 

a. Easily flown, only minor inflight deviations, and comb. Required a good deal of concentration with some infliTht 

c. Required significant concentration and above averaqe 

pletely safe. 

deviations. 

piloting skills to successfully comDlete the approach. 

Please add any additional Dertinent comments: 

Figure 21.b. Questions7 through 12. 

73 
TABLE 4 

Summary of Approach Quality Assessment Tool 

SF8R1 M14 

S F8R2M14 

SF8R3M14 

QF5R1 A25 

QF5R3A25 

Q F7 R3MO 7 

QF8R1 M14 

QF8R2M14 

QF8R3M14 

QF9RlM16 

QF9R2M16 

QF9R3M16 

QF16R1 J 1 

QF16R2J2 

QF17R2J4 

1 

2 

2 

2 

2 

3 

2 

2 

2 

2 

2 

2 

2 

2 

2 

1 

1 

1 

1 

2 

1 

1 

2 

2 

2 

1 

3 

2 

3 

2 

1 

3 

1 

3 

2 

1 

2 

2 

2 

2 

2 

3 

1 

3 

1 

1 

2 

2 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

1 

3 

1 

1 

1 

3 

1 

1 

3 

1 

3 

1 

1 

1 

1 

1 

2 

1 

1 

1 

2 

1 

1 

2 

1 

2 

1 

6 

10 

8 

9 

12 

8 

8 

9 

12 

9 

8 

14 

8 

14 

8 

74 
CHAPTER VI 

COMPARISON OF AIRCRAFT PREDICTED RESPONSE 

TO ACTUAL AIRCRAFT RESPONSE 

A major objective of this feasibility study was to test the ability 

of our numerical simulation model to predict actual aircraft performance 

on the PAR approach course. The sequence of this prediction is illustrated 

in Figure 22, which depicts our concept of a real-time detection and 

warning system, as previously presented in McCarthy et al. (1980a). In 

the real-time concept, we would derive an approach deterioration parameter 

by using a Doppler wind profile which approximates our Eulerian Before 

profile used in this feasibility study. Decisions by the air traffic 

controller, or by the pilot, with the ADP data uplinked to the cockpit, 

would be made prior to executing an approach. 

In our study, we had the benefit of comparing predicted performance 

to that actually encountered by the instrumented aircraft. Table 3 gives 

the results of model (or predicted) approach parameters , as well as a 

calculation of actual aircraft values. All calculations used equations (8) 

and (9). An independent assessment of the approach quality was obtained 

from the pilot evaluation tool, as given in Figure 21 and Table 4. 

As is obvious from the discussions in the preceding two chapters, 

essentially all of our approaches were conducted in weak shear conditions. 

This is seen clearly when model-derived ADP values of Table 3 are compared to much more intense shear, seen in the theoretical values given in 

Table 2. However, actual aircraft ADP values are considerably higher 

75 
1 FOR SPECIFIC AIRCRAFT TYPE I (4) APPL.Y RESPONSE FUNCTION 

RESPONSE TO WIND FUNCTION I' 116) DETERMINE APPROACH 

DETERIORATION PARAMETER I 

Figure 22. Diagrammatic illustration of wind shear 

detection and warning system. Process is sequential, 

starting from Doppler radar measurement of winds 

along the precision approach path, and ending with 

a prediction of approach deterioration for a particular class of airplane. In a real-time system, steps 

1-6 would take place within several seconds by use 

of a computer slaved to the Doppler. 

76 
than model estimates. This discrepancy may be due to imprecision in 

vectoring our SESAME aircraft precisely onto the PAR course. Furthermore it was not always possible to maintain a fixed stick mode, due 

to traffic, shear conditions, and controller instructions. 

Inspection of Table 3 for an estimate of the prediction skill of 

the Blick model gives the impression of a rather inadequate capability. 

More specifically, we are testing the Aut or Ah' ADP for the Eulerian 

Before case as a predictor of the Au' and Ah' for the real Aircraft 

data results case. We find the case for a good predictive ability less 

than convincing. 

To examine the predictive ability further, we computed linear 

regressions, where the independent variable was the actual aircraft 

response, and the dependent variable was the Blick model response. The 

results are given in Table 5. Actual values of Aut and Ah' approach 

deterioration parameters were taken from Table 3. Some rather interesting 

but tenuous conclusions can be drawn. First of all, when all 16 

approaches are included, no significant correlations result (Case a); 

the same holds true when just Queen Air approaches are considered (Case b). 

We see a little more correlation when only the Sabreliner approaches are 

examined (Case c). Surprisingly the altitude variation ADP, Ah', appears 

to be better correlated than Au'. However, as in our earlier inspection, 

the most obvious conclusion is that actual aircraft approach deterioration 

parameters a're not well correlated to model predictions. 

We tried one additional'correlation to see if our independent 

approach quality assessment, discussed in Chapter V, could provide a 

means of stratifying the more adverse wind shear situations. In Table 5, 

Case (d) represents the correlation between model predicted and actual 
TABLE 5 

Linear regression slope, intercept, correlation coefficient, and explained variance for Au' and Ah' 

ADP values, for four tests: (a) all 16 approaches, (b) for 12 Queen Air approaches, (c) for 4 

Sabreliner approaches, and (d), for the four most adverse approaches identified in Table 4 as 

QF16R2J1, QF9R3M16, QF8R3M14, and QF5R3A25. 

Li near Explained Sample Correlation Variance 

Case Variable Aircraft Number S1 ope Y-Intercept Coefficient (a 

(a) Au I S/QA 16 0.03 0.93 0.00 6 

Ah ' 0.08 19.79 0.07 26 

(b) AIJ I QA 12 -0.02 0.76 0.01 11 

4 Ah I 0.06 20.24 

(4 Au I S 4 -0.11 2.38 

a7 

0.02 

0.16 

12 

40 

Ah I 0.06 22.71 0.08 29 

(dl au ' QRlmos t 4 0.17 -0.12 

adverse 

Ah I 0.56 -5.87 

0.46 

0.63 

68 

80 
aircraft ADP values. In this case the correlations seem to approach significant values, with 68% and 80% of the variance explained between predicted and verified values of Au' and Ah', respectively. 

We do not want to overemphasize the importance of these simple 

stratifications. However, we might draw the following conclusions: 

1. Most of the approaches were made through weak wind shear. 

2. For the total sample of 16 approaches, which are heavily 

weighed toward weak shear situations, the Blick fixed stick 

model does a poor job of predicting aircraft performance. 

Looking at it another way, the atmospheric shear signal and 

the aircraft response, when examined by the model, are in 

the ''noise," where presumably other factors such as 

occasional pilot hands-on periods, moments of aircraft being 

out of trim, inadequacies of the Doppler radar wind measuring system, etc., cause errors in the predictive abilities 

of the model. 

3. The capabilities of the model to predict the response of the 

Sabreliner somewhat more accurately may lie in the fact that 

this aircraft is more sensi tive to changes in the wind than 

is the Queen Air. 

4. As the atmospheric signal contains more shear, and hence has 

a more deleterious effect on aircraft performance, the model's 

capability to predict aircraft performance is enhanced. Or 

in other words, the strength of the shear brings the model 

predictive power out of the "noise. 'I 

79 
80 
CHAPTER VI1 

CONCLUSIONS 

1. Summary and Overall Assessment 

A feasibility study was conducted to determine whether ground-based 

Doppler radar could measure the wind a1 ong the path of an approaching ai rcraft with sufficient accuracy to be used to predict aircraft performance. 

A severe storm research program, SESAME '79, provided the tools for this 

test, including two instrumented research aircraft, a Sabreliner and 

Queen Air from NCAR, a Doppler radar at NSSL, and an Air Force PAR unit 

for precision approaches to the Doppler radar. 

Forty-three PAR approaches were conducted, with 16 exam 

detail. In each, Doppler-derived longitudinal winds were comp 

ined in 

ared to 

aircraft measured winds; we concluded that in approximately 75% of the 

cases, the Doppler and aircraft winds were in acceptable agreement. In 

the remaining cases, errors may have been due to a lack of Doppler 

resolution, a lack of colocation of the two sampling volumes, the 

presence of eddy or vortex-like disturbances within the pulse volume, 

or the presence of point targets in antenna side lobes. It was further 

concluded that shrouding techniques would have reduced the side lobe 

problem. The work left little doubt that a ground-based Doppler radar, 

operating in the optically clear air, would provide the appropriate 

longitudinal winds along an aircraft's intended flight path. 

The study went on to attempt to test whether, given the winds 

along the intended approach path taken immediately prior to the start 

81 
of an approach, a fixed stick numerical simulation model could predict 

aircraft performance. We found that most of our cases occurred in 

extremely weak wind shear conditions, and the resulting model calculation 

was unable to quantify precisely the aircraft performance, in terms of 

shear conditions. However, for the four approaches identified by an 

independent quantitative pilot assessment, the model was more successful. 

This led to the conclusion that as the shear became more severe, the 

model's capability improved. However, we were not able to verify this in 

a convincing manner. Finally, we obtained some field indications that a 

high performance jet transport (Sabre1 iner) was more adversely affected 

by shear than was a light piston transport (Queen Air) , presumably 

operating in similar conditions. 

2. Preliminary Plans for an Experiment With Aircraft Flight Simulators 

In our feasibility study we were unable to encounter shear of a 

magnitude to cause a major effect on our aircraft performances, due' to our 

unwillingness to endanger our crews and equipment. This was fortunate 

for our crews, but unfortunate for an adequate test of the concept. We now 

believe that any subsequent field test of wind shear detection and warning 

should always avoid intentionally placing aircraft in even remotely 

dangerous situations. Consequently we believe that the final "calibration" 

of the theoretical results given in McCarthy et al. (1979) must' be conducted in manned aircraft flight simulators. Shears covering a range of 

wavelengths and profiles, both those measured in the atmosphere and the 

theoretical ones such as those given in Table 2, can be studied with 

real pilots manning flight simulators such as the Boeing 727, 747, L-1011, 

and DC-10. 

82 
We have had preliminary discussions with one airline regarding a 

possible operational/experimental program. We believe that a full flight 

simulator program with an air carrier would be both beneficial to our work, 

and to the air carrier, providing pilots with experience in encountering 

wind shear containing high energy at the phugoidal wavelength. We will 

continue to pursue the establishment of a program with an air carrier. 

Anticipating such an arrangement, we will be identifying and refining 

appropriate wind shear profiles, and preparing them in the correct format 

for input into flight simulators. 

3. Preliminary Plans For a Field Experiment In 1982 

As we discussed in Chapter I, several concepts regarding wind 

shear and its detection and warning have been advanced. To identify gust 

front and other singularities, the low level wind shear alert and microbarograph systems have been developed. To measure actual shear along a 

quasihorizontal approach or departure path, groups represented by 

McCarthy and Offi have investigated ground-based Doppler radar techniques 

and Tinsley (FAA) has called for airborne systems utilizing the airspeed/ 

groundspeed difference technique. Finally, Fujita has identified the 

downburst mechanism, but has not established a technique for their realtime detection and warning. 

We propose that a major field program be planned and executed, 

possibly during the summer of 1982, at Denver's Stapleton Airport. We 

envisage this program to be a test of the existing and anticipated technology designed to detect and warn of wind shear. By that time the FAA's 

operational wind shear program will have in place at Stapleton the 

83 
low-level wind shear alert (already in place) and microbaragraph systems. 

NCAR's 5 and 10-cm Doppler radars could be made available on request, as 

could PAM I and/or PAM I1 surface mesonet systems, and several instrumented 

research aircraft. Mesoscale observing and display systems of the 

Prototype Regional Observing and Forecast System (PROFS) of NOAA may be 

available, and remote probing techniques of NOAA's Wave Propagation 

Laboratory would be important. One or more air carriers with major 

operations at Stapleton could be stimulated into participating. Finally 

it is anticipated that the FAA will have prototype airborne wind shear 

detection systems available for testing by 1982. Persons who have 

expressed interest include the authors, Dr. Robert Serafin, NCAR-FOF, 

Dr. Walter Frost, University of Tennessee, Dr. Ted Fujita, University 

of Chicago, Dr. Richard Doviak, NSSL, Dr. A1 Bedard, NOAA-WPL, 

Dr. Fernando Caracena , NOAA-APCL, and Dr. Ron A1 berty of NOAA - PROFS. 

We see this program to be a comprehensive test of how wind shear affects 

aircraft approach and departure operations, its detection , and its 

warni ng. 

84 
I 

REFERENCES 

Bedard, A. J., Jr., F. H. Merrem, D. Simms, and M. M. Cairns, 1979: 

A Thunderstorm Gust-Front Detection System Part I. System 

Operation and Significant Case Studies Part I1 Statistical 

Results. Federal Aviation Administration Report No. FAA-RD-79-55, 

Washington, D.-C.-.., 1.30. pp. 

Foy, W. H., 1979: Airborne Aids for Coping with Low-level Wind Shear. 

Federal Aviation Administration Report No. FAA-RD-79-112, 

Washington, D.C. .-, 96 pp. 

Frost, W., and B. Crosby, 1978: Investigations of Simulated Aircraft 

F1 ight Through Thunderstorm Outflows. NASA Contractor Report 3052, 

Washington, D.C., 110 pp. " 

Frost W., and K. R. Reddy, 1978: Investigation of Aircraft Landing in 

Variable Wind Fields. SA Contractor Report 3073, Washington, 

D.C., 84 pp. -. .~~ - 

Frost, W., and B. Turkel, 1980: Pilot-Aircraft System Response to Wind 

Shear. Draft Interim Report, Contract NAS8-33458, FWG Associates, 

Inc., Tullahoma, TN, 80 pp. 

Fujita, T. T. , 1980: Downbursts and Microbursts--An Aviation Hazard. 

Preprints , 19th Conf. on Radar Meteor. , Miami Beach Fla. , Am. Meteor. SOC., Boston, Mass., 94-101. 

Fujita, T. T., and F. Caracena, 1977: An Analysis of Three WeatherRelated Aircraft Accidents. Bull. Am. Meteor. SOC. , 11 , 1165-1181. 

Goff, R. C., 1976: Vertical Structure of Thunderstorm Outflows, &J. 

Wea. Rev. , 104, 1429-1440. 

McCarthy, J., E. F. Blick, and R. R. Bensch, 1979: Jet Transport 

Performance in Thunderstorm Wind Shear Conditions. Final 

Contractor Report NASA CR-3207, Washington, D.C., 53 pp. 

McCarthy, J., W. Frost, B. Turkel, R. J. Doviak, D. W. Camp, E. F. Blick, 

and K. L. Elmore, 1980a: An Airport Wind Shear Detection and 

Warning System Using Doppler Radai-. Preprints, 19th Conf. on Radar 

Meteor. , Miami Beach, Fla. , Am. Mete.or. SOC., Boston, Mass. , 135- 

142. 

McCarthy, J. , K. L. Elmore, R. J. Doviak, and D. S. Zrnic, 1980b: 

Instrumented Aircraft Verification of Clear-Air Radar Detection of 

Low-Level Wind Shear. Preprints, 19th Conf. on Radar Meteor., 

Miami Beach, Fla., Am. Meteor. SOC., Boston, Mass., 143-149. 

85 
Offi , D. L., W. Lewis, and T. Lee, 1980: Wind Shear Detection with an 

Airport Surveil lance Radar. Preprints , 19th Conf. on Radar 

Meteor., Miami Beach, Fla., Am. Meteor. SOC., Boston, Mass., 

130-134. 

Severe Environmental Storms and Mesoscale Experiment, 1978: SESAME 1979 

Working Group Reports and Field Plans, NOM Environmental Research 

Laboratories, Boulder, Colorado, 63 pp. 

Severe Environmental Storms and Mesoscale Experiment , 1979a: SESAME 1979 

Plans for Operations and Data Archival. NOAA Environmental 

Research Laboratories, Boulder, Colorado, 66 pp. 

Severe Environmental Storms and Mesoscale Experiment, 1979b: SESAME 1979 

Operations Summary. NOAA Environmental Research Laboratories, 

Boulder, Colorado, 253 pp. 

Tinsley, H. G., F. G. Coons, L. W. Wood, 1978: Possible Near-Term 

Solutions to the Wind Shear Hazard. Preprints, Air Transportation 

Meeting, Boston, Mass., Society of Automative Engineers, Inc., 

Warrendale, Penn. 

Wilson, J. W., R. E. Carbone, and R. J. Serafin, 1980: Detection and 

Display of Wind Shear and Turbulence. Preprints, 19th Conf. on 

Radar Meteor., Miami Beach, Fla., Am. Meteor. SOC., Boston, Mass., 

150-156. 

86 
1. REPORT NO. 2. GOVERNMENT ACCESSION NO. 

~ .. ~~ 

3. R?CGIEF'S CATALOG NO. 

NASA CR-3379 -- 1 4. TITLE AND SUBTITLE 

.. 

An Airport Wind Shear Detection and Warning System Using January 1981 

Doppler Radar - A Feasibility Study 6. PERFORMING ORGANIZATION CClDE 

5. REPORT DATE 

~" ~~~ 

7. AUTHOR(S) 

I_ = ~. . .. 

8. PERFORMING ORGANIZATION REPOR r # 

9. 

John McCarthy, Edward 

PERFORMING ORGANIZATION NAME AND ADDRESS 

F. Blick, and Kim L. Elmore ~" 

110. WORK 

" 

UNIT NO; 

! 

-1 

MCS, Inc. 

239 Cedarbrook Road 

Boulder, Colorado 80302 

12. SPONSORING AGENCY NAME AND ADDRESS 

~ - 

National Aeronautics and Space Administrat ion 

Washington, D.C. 20546 

"326 

1 1. CONTRACT OR GRANT NO. 

NAS8-33458 

ub. FWG 6-0510-1) 12 rYPE OF REPOR-,' B: PERIOD COVERED 

7"' I Contractor Report I 

14. SPONSORING AGENCY CODE 

J 

. -. . . . . 

15. SUPPLEMENTARY NOTES 

_I_" ~ . - "I 

Marshall Technical Monitor: Dennis IJ. Camp 

____~."~. ~~ .. . 

16' ABzT%aslblllty study was conducted to determine whether ground-based Doppler radar 

could measure the wind along the path of an approaching aircraft with sufficient accuracy 

to predict aircraft performance. A severe storm research program, Severe Environmental 

Storms and Mesoscale Experiment (SESAME '79), provided the tools for this test, including 

two instrumented research aircraft, a Sabreliner and Queen Air from NCAR, a Doppler radar 

at NSSL, and an Air Force PAR unit for precision approaches to the Doppler radar. 

Forty-three PAR approaches were conducted, with 16 examined in detail. In each, Dopplerderived longitudinal winds were compared to aircraft-measured winds; in approximately 75 

percent of the cases, the Doppler and aircraft winds were in acceptable agreement. In th 

remaining cases, errors may have been due to a lack of Doppler resolution, a lack of COlocation of the two sampling volumes, the presence of eddy or vortex-like disturbances 

within the pulse volume, or the presence of point targets in antenna side lobes. It was further concluded that shrouding techniques would have reduced the side lobe problem. 

The work left little doubt that a ground-based Doppler radar operating in the optically 

clear air, would provide the appropriate longitudinal winds along an aircraft's intended 

flight path. The study also attempted to test whether, given the winds along the intende 

approach path taken immediately prior to the start of an approach, a fixed stick numeric 

simulation model could predict aircraft performance. Most of the test cases occurred in 

extremely weak wind shear conditions, and the resulting model calculation was unable to 

quantify precisely the aircraft performance, in terms of shear conditions. However, for 

the four approaches identified by an independent pilot assessment to be most severe, the 

model was more successful. This led to the conclusion that as the shear became more 

seveSe, the model's capability improved. However, this could not be verified in a con- vincmg manner. Finally, some field results indicated that a high-performance jet transport (Sabreliner) was more adversely affected by shear than was a light piston transport 

(Queen Air), presumably operating in similar conditions. 

CT.. . 

- 

17. KEY WORDS 18. DISTRIBUTION STATEMENT 

~~ 

Aviation safety 

Wind shear 

Unclassified - Unlimited 

Wind shear simulation Doppler radar 

Aircraft response 

Subject Category 47 

19. SECURITY CLASSIF. (of thh rapa-tl 20. SECURITY CLASSIF. (of thla paw) 

Unclassified Unclassified 

For sale by National Technical Information Service, Springfield. Virginia 22 16 1 

NASA-Langley, 1981 

."_ . . " ". ... .. . . .. ..