NASA Contractor Report 168247 

TEMPERATURE HISTORIES OF COMMERCIAL FLIGHTS 

AT SEVERE CONDITIONS FROM GASP DATA 

W. H. Jasperson and G. D. Nastrom 

Control Data Corporation 

Minneapolis, Minnesota 

October 1983 

Prepared for 

NATIONAL AERONAUTICS AND SPACE ADMINISTRATION 

Lewis Research Center 

Under Contract NAS3-21249 

https://ntrs.nasa.gov/search.jsp?R=19840003084 2018-05-11T19:32:32+00:00Z
7.0 SUMMARY 

This report is a study of the thermal environment of commercial 

aircraft from a data set gathered during the Global Atmospheric 

Sampl ing Program (GASP). The data set covers a four-year period of 

measurements. The report presents plots of airplane location and speed 

and atmospheric temperature as functions of elapsed time for 36 extremecondition flights, selected by minimum values of several temperature 

parameters. One of these parameters, the severity factor, is an 

approximation of the in-flight wing-tank temperature. Representative 

low-severity-factor flight histories may be useful for actual temperatureprofile inputs to design and research studies. Comparison of the GASP 

atmospheric temperatures to i nterpol ated temperatures from National 

Meteor01 ogical Center and Global Weather Central analysi s fields shows 

that the analysis temperatures are slightly biased toward warmer than 

actual temperatures, particul arly over oceans and at extreme conditions. 

2.0 INTRODUCTION 

By most criteria, aircraft fly in a hostile environment. In particular, commercial aircraft typically fly at heights where the outside air 

temperature may be -70% or colder. Present aviation turbine fuels have 

low freezing points to insure flowability at minimum temperatures. However, fuels with higher freezing points can allow better future utilization of 

scarce and changing raw materials and flexibility in meeting changes in 

product demands. 

Engineers have the option of modifying aircraft fuel systems so that 

the fuel is not subjected to as severe a temperature stress. This may be 

done passively by altering the exposure or actively by heating the tanks 

(refs. 1-3). If either of these alternatives is considered, there has to 

be a balance between the effectiveness and the penalties paid in terms of 

cost complexity, maintai nabi 1 i ty, weight and aircraft performance. 
In order to evaluate potenti a1 fuel system modifications, through 

design or experimental studies, representative extreme-envi ronment 

flights must be characterized. Figure 1 presents the average air 

temperature as a function of latitude and height (ref. 4). As expected, 

the temperature decreases poleward in the lower atmosphere. However, 

above approximately 14 km (46000 ft) in winter (figure 1 [a]) and 12 km 

(40000 ft) in summer (figure 1 [b]) , the average temperature decreases 

equatorward with the result that the coldest average temperatures found in 

the atmosphere are at approximately 17 km (54000 ft) over the equator. 

The day-to-day fluctuations in atmospheric temperatures are far 

more important in relationship to minimum fuel temperatures and flowability 

than are the mean temperatures. Previous studies have compiled statistics 

on minimum atmospheric temperatures to determine the probability of occurrence of extremes. In one study, a survey of 8125 flights over 12 commercial routes gave the probability distribution of minimum fuel, total air, 

and static air temperatures (ref. 5). Actual flight histories and the 

time of occurrence of minima were not reported. Flight temperature 

histories were constructed for several military missions in another study, 

usi ng National Meteorological Center analysi s field data over a ten-year 

period with heat transfer model calculations (ref. 6). 

This present study utilizes a set of temperature data collected on 

many routes worldwide. A previous report (ref. 7) presented statistical 

data from each flight and organized the observed atmospheric temperatures 

into probability tables by monthly geographic and altitude grids. The 

current study presents complete temperature histories of selected flights 

determined to be most extreme according to several parameters. One of 

these parameters is a severity factor, an approximation of the wing-tank 

fuel temperature. The analysis of temperatures includes comparisons of 

temperatures measured by the aircraft and temperatures interpolated from 

analysi s fields. 
3.8 DATA 

The NASA Global Atmospheric Sarnpl i ng Program (GASP) ran from March 1975 

to July 1979. During this program four commercial 8747 aircraft in routine 

service were instrumented to obtain measurements sf aerosols, trace constituents and meteorological variables (refs. 8 and 9). The GASP system 

was automated to record data at nominal five-minute intervals during flight 

above FL190 (5.8 km or 19000 ft according to the ICAO Standard Atmosphere). 

When turbulence was encountered, or on entire selected flights, data were 

recorded at four-second intervals (ref. SO), but for this study only onemi nute i nterval data were retained. Temperatures were measured with a 

Rosemount temperature sensor for which the expected rms error is less 

than 1'~ (ref. 11 1. The temperature data, however, were recorded in who1 e 

degrees Cel sius. 

The data set used in this study consists of 6945 flights covering 273 

different routes. Most of these routes are in the United States (including 

Hawai i ) or are from the U. S. to Europe or Japan. However, there a1 so are 

numerous flights from the Northern Hemisphere to the Southern Hemisphere, 

within the Southern Hemisphere, between cities along the southern rim of 

Asia, and even into Africa. Airport codes and locations are listed in 

Table 1. A complete summary of a11 GASP flights is found in ref. 7. 

Analysi s fields of terr~perature produced by the National Meteor01 ogi cal 

Center (NMC) and by the Air Force Global Weather Central [GWC) were also 

used in this study. Both data sets are gridded on a 1977-point octagon 

presented in Pig. 2. Both data sets cover the Northern Hemisphere to 

about 18'~ latitude. These gridded data are available twice a day, at 

0000 GMT and 1200 GMT, and the following pressure levels were used: 

500 rnb (50 kPa pressure, corresponding to 5.6 km, F~180) 

400 mb ( 7.2 km, FE240) 

300 mb ( 9.2 km, FL360) 

250 rnb (10.4 km, Ft340) 

200 rnb (17.8 km, FL390) 

150 mb (13.6 km, FL450) 

100 rnb (96.2 km, FL530) 

-3- 
4.0 ANALYSIS OF DATA 

4.1 Sel ecti on Parameters -- - 

Fi ve different temperature severity parameters were def i ned and 

computed for each of the 6945 GASP flights to select flights that met 

criteria for coldest temperatures. These parameters are defined as follows: 

4.1.1 - Minimum Temperature 

The minimum temperature is the minimum or most extreme single 

event ambient (static) temperature recorded at any time during the 

flight. 

4.1.2 Thermal Exposure 

The thermal exposure is the time weighted sum of the ambient 

temperatures encountered over the entire flight, expressed in units 

of degree-minutes. Mathematically it is given by 

where E is the thermal exposure, 

TS is the ambient (static) temperature, 

At is the time interval, 

and t is the number of the time interval from the start of 

cruise (t=l) to the end of cruise (t=n). 

4.1.3 Averaae Temperature 

The average temperature for a flight is the thermal exposure 

divided by the total time duration of the flight. 
4.1.4 Severity Factor 

The severity factor is an estimate of the fuel temperature 

during the flight, not measured by the GASP instrumentation. The 

severity factor is calculated by assuming a time-varying heat transfer 

coefficient. The coefficient is based on Boeing calculations for 

configurations typical of the GASP aircraft (ref. 12). Mathematical ly, 

the severity factor is given by: 

Tsf,i = 'sf,i-~ -r IA~ -K(Tsf,i-~ r9i 

where Tsf,i is the severity factor after time interval i, 

K is the thermal constant (assumed to be 7.84 x 10-~rnin -]I9 

'sf,i -1 is the severity factor after time interval i-1, 

T i s the recovery temperature duri ng time interval i -1 , r,i 

and At is the time interval. 

The recovery temperature is given by 

2 T r9i = (1 + 0.18Mi) Ts,i 

where Mi is the Mach number over interval i, 

and T i s the static air temperature over interval i . Thi s s, i 

equati on assumes an adi abati c recovery of 90%. 

The severity factor at the start of cruise, TSf,O, was assumed to 

be -17'~. 

4.1.5 Mi nimum Averaqe Seqment Temperature 

A flight secjment is defined as a portion of a flight in excess 

of two hours duration during which the flight level changes by less 

than 21 50m (500 ft) . If more than one such segment exists, thi s 

parameter is the one with the coldest average temperature. 
4.2 Coldest Flights 

The computation of each of these parameters for all GASP flights 

resulted in an ordered set of flights from most severe to least severe for 

each parameter. From this set, 36 "most severe" flights were selected. 

These flights are shown in Table 2 along with the values of the selection 

parameter. The flights are ranked in Table 2 in a general order of 

decreasing severity. The order is subjective, but flights were judged more 

severe if they were extreme in more than one of the selection parameters. 

Nineteen different airport pairs are represented in Table 2. The most 

consistently severe route is between Bahrain Island in the Arabian Gulf 

or Dhahrain, Saudi Arabia, and New York. Seven of the 36 flights are 

between these cities. 

5.0 - DISCUSSION OF DATA 

5.1 Fliqht Histories 

Flight histories of the 36 selected flights of Table 2 are presented 

in the order of rank in figs. 3 to 38. Each of these figures is a panel 

with multiple plots of recorded and calculated parameters as common 

functions of flight duration. 

Each panel is labeled across the top with the airports of departure 

and destination, the time of the first data point (time of departure), 

and the date of the flight. Within each panel, there are seven sets of 

plots with separate ordinates alternated between the left and right 

margins. All refer to the common abscissa of elapsed time. From the 

bottom up, the plots show aircraft speed (Mach number), altitude (flight 

level ) , distance from the NMC tropopause (where available) , static air 

temperature, severity factor (approximate fuel temperature), 1 ati tude 

and longitude. Distance may be estimated by the nominal equivalence of 

1700 km, or 1000 statute miles to each 100 minutes of elapsed time. 
All GASP data were measured from Boeing 747 aircraft, and the average 

cruising speeds fluctuate about Mach 0.85. The flight level, or pressure 

altitude of the aircraft, is determined by all of the variables that go 

into the flight plan and ranges from 10 to 13 km (33000 to 43000 ft). 

The height of the NMC tropopause was interpolated to each recorded 

aircraft position from NMC tropopause analysis fields, and the height 

difference between the tropspause and the aircraft is plotted in the panel 

in pressure units (mb]. A positive distance indicates that the aircraft 

is above the Lropopause, Tropupause data were available for most northern 

hemi sphere flights. 

The static air temperature as recorded by the aircraft is presented 

in the next part of the panel. If NMC and/or GWC temperature data were 

also available, they are also included on the same scale as the GASP 

temperatures. The NMC (GWC) temperature curve is distinguished from 

the others by small boxes (triangles) drawn at 100 minute intervals. 

The NMC and GWC temperature data were interpolated from the gridded fields 

to the aircraft position linearly with respect to horizontal distance and 

time and linearly with respect to the logarithm of pressure in the vertical. 

The severity factor, or arbitrary fuel temperature, is included above 

the temperature curve. The severity factor, def-ined in section 4.1.4, 

can be seen to represent a damped response to the air temperature (or, 

more specifically, the recovery temperature). The top plots in each 

panel are the flight location, longitude and latitude, as functions of 

elapsed time. 

5.2 Severity Factors 

Temperature patterns in the atmosphere are reflections of meridional 

circulation patterns. Near the earth's surface in midlatitudes, the 

primary circulation features are sequences of high pressure and low 

pressure systems imbedded in the westerly winds. In the upper atmosphere, 
say above 6 km (20000 ft), these pressure systems appear as rneridional 

deviations or waves in a basically zonal (west to east) flow. An aircraft 

will generally encounter, during any season of the year, sequences of 

relatively high and relatively low temperatures. An examination of the 

flight histories presented in figures 3 to 38 shows that cold areas tend 

to have a duration of 100 to 200 minutes (1000 to 2000 miles). What this 

implies is that even though ambient air temperatures may occasionally reach 

-70'~ or colder, they do not remain at that extreme level over an entire 

long flight. It also shows why it is important to look at actual flight 

histories, either measured or inferred from analysis fields, rather than 

simp1 e temperature-a1 ti tude cl imatol ogies when exami ning a thermal 

exposure problem. 

The severity factor is calculated from the air temperature and appears 

as a damped response to the flight temperature variations. The minimum 

value of the severity factor is not directly related to the average air 

temperature along the route. The magnitude and duration of any deviation 

from the average is more important. Furthermore, cold air temperatures 

late in a flight will tend to produce more extreme severity factors than 

cold temperatures early in a flight. 

A demonstration of the relationship of severity factor to wi ng-tank 

fuel temperature is shown by the comparison in figure 39 of calculated 

severity factors for a published flight history of a flight from Seattle 

to Johannesburg (ref. 2). The severity factor assumes an initial fuel 

temperature of -17'~; in the comparison flight, the initial temperature 

was -8'~. l~owever, the influence of initial fuel temperature becomes 

negligible after several hours of flight time (compare ref. 12). Both 

the severity factor and the Boeing prediction model approximate the 

measured fuel temperature well. The severity factor is based on the 

Boeing technique with an arbitrary initial temperature and other 

simplifications. 

The severity factors presented in the flight hi stories were calculated 

from the GASP temperatures. Table 3 compares the minimum severity factors 
from Table 2 for the selected flights as calculated from the GASP temperatures with the factors calculated from the NMC and/or GWC data, if available. 

It is significant to note that in only one case was the severity factor 

computed from analysis fields colder than the severity factor computed from 

the aircraft measured temperatures, and this was by only 0.03'~ (flight 

rank 11 ). In general, the severity factors computed from the analysis 

fields were 3 to 5'~ warmer than the GASP severity factors. The differences 

appear to be due primarily to the fact that the analysis fields tend to be 

consistently biased toward warmer temperatures during the coldest portions 

of the flights. Because ~ost of the flights are over water, it is difficult 

to judge if this bias is due to the fact that there are less input data 

over the oceans or due to a damping or averaging bias. One of the few 

flights completely over land (rank 13) also shows a bias between the temperatures. In any case, one should be aware of the magnitude of the differences 

in mininium severity factor that can result from different types of input 

data. 

On the basis of severity factor and the other parameters, five routes 

that were generally the coldest were identified from among the 19 represented by the selected flights. These routes and the number of flights 

available are: 

Los Angeles (LAX) - Tokyo (HND,NRT) 234 

San Francisco (SFO) - Hong Kong (HKG) 57 

San Francisco (SFC) - Auckland (AKL) 36 

New York (JFK) - Bahrain Is. (BAH) 43 

New York (JFK) - Rio de Janeiro (GIG) 30 

She average temperature and severity factor were computed for each 

flight, and the empirical probabilities of occurrence for several 

sel ected probabi l i ti es were determi ned . These empi ri cal values are 

presented in Table 4. 

A criterion of extreme temperature conditions often used for design 

and research is that of a one-day-a-year probabi 1 ity (refs. 5 and 12). 
Two of the coldest routes, JFK-BAH and LAX-Tokyo, do have minimum 

severity factors and average temperatures which are normally distributed. 

With an assumption cf normality, the one-day-a-year probability on these 

two routes can be estimated: 

Mi nimum 

Route 0 Severity Factor, C Average Temperature, 'C 

JFK, BAH 

LAK, Tokyo 

Thus the rank 1 temperature history (figure 3) corresponds closely to a 

one-day-a-year flight profile with respect to the minimum severity factor. 

Other temperature histories of figures 3 to 38 may also be useful as 

representative of actual 1 ow-probabi l i ty, extreme-condi ti on f l i ghts, 

adapted and modified as necessary. 

5.3 Further NMC, GWC and GASP Temperature Comparisons 

It should be noted that changes in flight level produce corresponding 

changes in the distances from the tropopause, the temperatures, and 

occasionally the aircraft speed. Apart from the near discontinuities in 

these flight histories due to flight level changes, the plots of the distance from the NMC tropopause and the NMC and GWC temperature curves 

should be snlooth. The distance between analysis field grid points is 

equivalent to about 25 minute; of flight time at normal cruise speeds. 

This implies that features in the temperature field with wave lengths 

smaller than about 50 minutes of flight time cannot be represented by 

the NMC/GWC analysis fields. Much more structure is resolvable in the 

GASP data which are taken, for the most part, at five-minute intervals. 

Even if allowance is made for the damping of temperature details, there 

are often significant differences between the GASP temperatures and the 

NMC/GWC analysis fields. Furthermore, there are also instances where 

there are large differences between the NMC and the GWC temperatures. 
Upper air data have historically been much more readily available 

over land than over the oceans. With satellites, more data have been 

made available over the oceans, but it is still generally conceded that 

the quality and detail of the data over land exceeds that of data over 

the oceans. For this reason, two routes, one over land and one over 

the ocean, were selected to compare the temperature analysis fields with 

the GASP temperatures. The land route was between New York and San 

Franci sco (146 flights), and the oceanic route was between San Francisco 

and Tokyo (1 08 f l ights) . 

Figure 40(a) presents the distribution of the differences between 

GASP and NMC temperatures for the oceanic flights and the continental 

flights. The continental flight temperature differences have a mean 

almost equal to zero and a standard deviation of 1.65'~. The oceanic 

flights, on the other hand, have a mean difference bias of 0.85'~ and 

a standard deviation of 3.55'~. The mean difference is such that the 

NMC temperatures are warmer than the GASP temperatures, thereby understating the severity. Figure 40(b) shows the distribution of the 

probability that the absolute value of the temperature difference will 

be exceeded. The greater spread of the oceanic flight differences is 

apparent. 

Figure 41 presents a comparison between GASP/NMC temperatures and 

GASP/GWC temperatures for both oceanic and continental routes. Only 

flights for which both NMC and GWC temperature data were available were 

used. Statistical differences between the NMC and GWC temperatures for 

either route are small. The positive temperature bias for the oceanic 

route and the slight negative bias for the continental route are evident. 

Figure 42(a) presents the distribution of the GASP and NMC temperature differences for the oceanic flights (same as figure 40[a]) and the 

distribution of the GASP and NMC temperature differences for the 

selected flights of Table 2 for which NMC data were available. This 

figure is interesting in two respects. First, a much larger mean 
temperature difference bias (1.65°~) is apparent in the coldest flight 

data set. This fact reiterates the point that the temperature analysis 

fields wi 11 underestimate the thermal severity of an actual flight. 

Secondly, the bias difference is not reflected in fig. 4Z(b) which shows 

the distribution of the probability that the absolute value of the 

temperature difference wi 11 be exceeded. Cumulative di stri butions 1 ike 

fig. 4Z(b) are often used to estimate error bounds, and the fact that 

these two are nearly identical occurs in this case by chance. This 

example serves to illustrate that care must be taken in interpreting 

results when absolute values are used in transforming a probability 

distribution to a cumulati ve distribution. 

6.0 SUMMARY OF RESULTS 

This report has presented a study of the thermal environment of 

commercial aircraft from a data set gathered during the Global Atmospheric 

Sampling Program. This data set consists of 6945 flights covering 273 

routes over most of the world. 

From the analysis of this data set, the following results are 

obtai ned. 

1. Thirty-six flights, representing 19 different routings, were 

selected by several temperature parameters as the most severe. This 

report includes plots of airplane position, speed, and atmospheric 

temperature as functions of elapsed time for each of the selected 

flights. A table shows the various minimum temperature parameters for 

each sel ected f 1 i ght . 

2. A severity factor is defined as one of the representative 

extreme temperatures. This factor may be used to select worst case lowprobability flights for design and research modeling. The severity 

factor is an approximation of the wing-tank temperature, related to the 

minimum enroute temperatures, their duration, and t.ime of occurrence 

during flight. 
3. Ambient temperatures as measured from the aircraft were compared 

with the temperature interpolated from National Meteorological Center 

(NMC) and Global Weather Central (GWC) analysis fields, and it was found 

that the interpolated temperatures were slightly biased towards warmer 

than actual temperatures. This was particularly true over the oceans and 

for the thermally severe flights. NMC and GWC gridded data appeared 

statistically similar. 
7.0 REFERENCES 

Pasion, A. J.: Design and Evaluation of Aircraft Heat Source 

Systems for Use with High-Freezing Point Fuels. 

NASA CR-159568, 1979. 

Thomas, I.: Broadened Jet Fuel Specifications: Their Effect 

upon Commerci a1 Ai rpl ane Desi gn and Operat i on. 

Shell Aviation News, No. 450, pp. 32-35, 1978. 

McConnell, P. M., L. A. Desmarais, G. N. Peterson, and C. L. 

Del aney: Operational Effects of Increased Freeze Poi nt 

Fuel s i n Mi l i tary Ai rpl anes. AIAA Paper AIAA-83-1139, 

June 1983. 

Byers, H. R.: General Meteorology. New York: McGraw Hill, 1959. 

Pasion, A. J.: In-flight Fuel Tank Temperature Survey Data. 

NASA CR-159569, 1979. 

McConnell, P. M., L. A. Massmann, G. N. Peterson, and F. F. Tolle: 

Fuel /Engi ne/Ai rpl ane Trade Off Study, Operational Effects of 

Increased Freeze Point Fuels. AFWAL-TR-82-2067, 1982. 

Nastrom, G. D., and W. H. Jasperson: Flight Summaries and 

Temperature Cg imatol ogy at Ai rl i ner Crui se A1 ti tudes from 

GASP Data. NASA CR-168106, 1983. 

Perkins, P. 3.: Global Measurements of Gaseous and Aerosol Trace 

Species in the Upper Troposphere and Lower Stratcsphere 

from Daily Flights of 747 Airliners. NASA TM X-73544, 1976. 

Perki ns, P. J . , and L. C. Papathakos: Global Sensi ng of Gaseous 

and Aerosol Trace Species Using Automated Instrumentation on 

747 Ai rl i ners . NASA TM-73810, 1977, 
10. Holdeman, J. D. and E. A. Lezberg: NASA Global Atmospheric Sampling 

Program (GASP) Data Report for Tape VL0001. NASA TM X-71905, 

1976. 

11. Stickney, T. M., M. W. Shedlov, D. I. Thompson and F. J. Yakos: 

Rosemount Total Temperature Sensors Technical Report 5755, 

Revision A. Rosemount, Inc., Mpls., MN, 1981. 

12. Pasion, A. J., and I. Thomas: Preliminary Analysis of Aircraft 

Fuel Systems for Use with Broadened Specification Fuels. 

NASA CR-135198, 1977. 
TABLE 1 

Ai rport/Ci ty Codes and Locations 

- CITY 

ACA - Acapulco, Mexico 

AKL - Auckf and, New Zeal and 

AMS - Amsterdam, Nether7 ands 

ANC - Anchorage, Alaska 

ATH - Athens, Greece 

%AH - Bahrain Is., Arabi an Gulf 

BDA - Bermuda, Atlantic Ocean 

BEG - Belgrade, Yugoslavia 

BEY - Beirut, Lebanon 

BGR - Bangor, Maine 

BKK - Bangkok, Thai 1 and 

BNE - Brisbane, Australia 

BOM - Bombay, India 

BOS - Boston, Mass. 

BRU - Brussels, Belgium 

CCS - Caracas, Venezuela 

CGN - Cologne, Germany 

CHC - Christchurch, New Zealand 

CLE - Cleveland, Ohio 

CPH - Copenhagen, Denmark 

CPT - Capetown, South Africa 

CTS - Sapporo, Japan 

CUN - Cancun, Mexico 

CUR - Curacao, Neth. Antilles 

DAM - Damascus, Syria 

DEL - Del hi, lndi a 

DEN - Denver, Colorado 

DFW - Dallas/Ft. Worth, Texas 

DHA - Dhahrain, Saudi Arabia 

DRW - Darwin, Australia 

DTW - Detroit, Michigan 

DUB - Dublin, Ireland 

EZE - Buenos Aires, Argentina 

FA1 - Fairbanks, Alaska 

FCO - Rome, Italy 

FRA - Frankfurt, Germany 

GIG - Rio de Janeiro, Brazi 1 

GUA - Guatemala City, Guatemala 

GUM - Guam Island, Mariana Islands 

HKG - Hong Kong, Hong Kong 

HND - Tokyo, Japan 

HNL - Honolulu, Hawaii 

IAD - Washington, D.C. 

IAH - Houston, Texas 

IST - Istanbul, Turkey 

- LAT . LONG. 
TABLE 1 (cont'd) 

IT0 - Wilo, Hawaii 

JFK - New York, Wew York 

JNB - Johannesburg, South Africa 

KHI - Karachi, Baki stan 

KUL - Kula Lumpur, Malaysia 

LAS - Las Vegas, Nevada 

LAX - Los Angeles, California 

LHR - London, England 

LPA - bas Palmas, Canary Island 

MEL - Melbourne, Australia 

MEX - Mexico City, Mexico 

MIA - Miami , Florida 

MIQ - Caracas, Venezuela 

MNL - Manila, Philippines 

MRU - Mauritius, Indian Ocean 

MUC - Munich, Germany 

NAN - Nandi, Fiji Island 

NCE - Nice, France 

NOU - Nournea, New Caledoni a 

NRT - Tokyo, Japan 

OKA - Okinawa, Japan 

OMA - Omaha, Nebraska 

ORD - Chicago, Illinois 

OSA - Osaka, Japan 

ORY - Paris, France 

PDX - Portland, Oregon 

PER - Perth, W. Australia 

PHL - Phi 1 adel phi a, Pennsyl vani a 

PJK - Glasgow, Scotland 

PPG - Pago Pago, Samoa 

PPT - Papeete, Tahiti 

PTY - Panama City, Panama 

SEA - Seattle, Washington 

SF0 - San Francisco, California 

SIN - Singapore, Singapore 

SNN - Shannon, Ireland 

STL - St. Louis, Missouri 

STR - Stuttgart, Germany 

SYD - Sydney, Australia 

THR - Tehran, Iran 

TPE - Taipei , Taiwan 

VIE - Vienna, Austria 

YQX - Gander, Newfoundland, Canada 

YVR - Vancouver, 8.C. Canada 

YYZ - Toronto, Ontario, Canadz 
Table 2 

Selected Extreme Condition Fliqhts 

DepartureDestination 

Rank Ai rports 

1 BAH-JFK 

2 CPT-AKL 

3 BAH-JFK 

4 JFK-DFW 

5 SIN-HKG 

6 SNN-JFK 

7 FRA-JFK 

8 SFO-HNL 

9 NRT-SF0 

10 JFK-DHA 

11 JFK-HND 

12 BOM-BAH 

13 DFW-JFK 

14 HND-LAX 

15 HND-LAX 

16 JFK-BAH 

17 LAX-HND 

18 LHR-JFK 

19 ORD-HNL 

20 JFK-HND 

21 BAH-JFK 

22 GIG-JFK 

23 SYD-SF0 

24 PPT-PPG 

25 HKG-SIN 

26 SFO-HKG 

27 DHA-JFK 

28 HND-LAX 

29 HKG-SF0 

30 SFO-AKL 

31 SFO-HKG 

32 SYD-SF0 

33 LAX-HND 

34 DHA-JFK 

35 HND-JFK 

36 JFK-HND 

Date 

1 Parameter Values 

Thermal 

Exposure 

OC-~i n

Mi n 

Avg Severity 

Temp ,OC Factor ,'c 

---+ 

Avg Segment 

Tem~ OC 
Table 3 

Com~arison of Minimum Severitv Factors of Selected Fliahts 

* * * 

Rank SF GASP SF NMC SF GWC 

* SF^^^^, SF^^^, and SFGWC are the minimum severity factors 

as computed from the GASP temperature and the NMC and GWC 

analysis fields, respectively. 
Table 4. 

Probability of Occurrence for Two Temperature Parameters on Five Coldest Routes 

Severity Factor. 'C 

Probabi 1 i ty 1 % 5 % 10% 25% 50% 75% 90% 95% 99% 

Route 

JFK, BAH - -38.0 -35.5 -33.7 -31 .5 -29.0 -26.3 -25 -0 - GIG, JFK - -35.5 -34.7 -31.7 -29 .O -23.8 -18.6 -17.5 - I HKG, SF0 - -35.5 -34.6 -33.2 -30.0 -26.8 -24.2 -21.9 - 

AKL, SF0 - -34.8 -33.0 -31 .O -28.4 -27.0 -26.1 -25.2 - 

' LAX, HND(NRT) -37.2 -35.4 -34.2 -31.9 -29 -0 -26.2 -24.1 -22 -8 -18.4 

Average Temperature, OC 

Probability 1% 5 % 10% 25% 50% 75% 90% 95% 99% 

Route 

JFK, BAH - -59.9 -58.7 -57.2 -53.8 -52.1 -50.0 -49.1 - 

GIG, JFK - -58.8 -57.5 -55.8 -53.5 -48.2 -41.5 -39.8 - 

HKG, SF0 - -55.8 -54.6 -53.8 -50.8 -48.8 -47.5 -45.2 - 

AKL, SF0 - -56.3 -55.3 -54.3 -52.4 -50.4 -49.2 -49.0 - 

LAX, HNDINRT) -60.9 -58.9 -57.9 -56.1 -53.5 -51.4 -49.8 -47.2 -46.1 
(a) Winter (b) Summer 

Figure 1. Vertical cross-sections of the meridional distribution of temperatures 

(adapted from ref. 4, fig. 4.1 1. 
Figure 2. Grid points for National Meteorological Center (NMC) 

and Global Weather Central (GWC) analysis fields. 
Figure 3. Flight history for flight rank 1. 

-23- 
Figure 4. Flight history for flight rank 2. 
180 

BRH Tll JFK DEPARTURE 2323 GMT 3 JAN 79 1 I 1 I I I I 1 I 

x 

0 

a 

x 

0.ei I 

a 100 200 300 uoo 500 600 700 eao 

ELCIPSED nne tnr N) 

Figure 5. Flight history for flight rank 3. 
W 

0 

3 + - 0 

u 

x 

D 

.a 

-180 

50 

IP 

-4 

40 2 

C 

0 

m c. 

--UO 30 

a 

m 

b 

U 

Q: 

LL -30 

* 

L 

a 

W -28 W -70 2 V) 31 

D 

m 

50 

f, 

-60 2 

;O 

rn 

- 

C) 

-50 ' 

U 

x- 100 XLP X: 

x- 

&w 

LLV) 

3 0 

WgI: 

UO 

ZD 

CfL 

ke3 7 U)D: 

-+ -100 o 500 I 

--I 

r 

m 

UOO 5 

C4 

7 

-4 

0.9 300 2 

2 

0 z 

a 

t 

0.8 

0 100 200 300 YO0 500 600 700 000 BOO 

ELC)PS€D TIHE [HlNl 

Figure 6. Flight history for flight rank 4. 
Figure 7. Flight history for flight rank 5. 

-27- 
160 SNN T8 ;PF# DEPARTURE 16 19 GMT 27 JAN 76 

W 

0 

3 

t - 0 

0 

Z 

C) 

3 

-180 

8 0 

ID 

--I 

so : 

c 

u 

m 

- 

--UO '40 

a 

0 

tU 

a 

IL -30 

* 

C 

0 

a 

Lrl 

w -20 

W -70 2 en x 

D 

m 

w 

D 

-60 2 

w 

m 

- 

n 

-50 - 

2- 100 zm r 

x0 

E*W 

LV) 

3 0 

WCK 

un 

20 

a& 

I-D 7 

V)QT 

-k- -100 5 

0 500 " 

x 

-4 

Im 

'00 5 

- 

T 

4 

0.9 300 2 

I 

U c a 

L 

0.8 

0 100 200 300 YO0 500 600 700 800 900 

ELAPSED TlllE (WIN1 

Figure 8. Flight history for flight rank 6. 

-28- 
Figure 9. Flight history for flight rank 7. 
1 QO 

SF0 TO HNL 

LAJ 

0 

3 

t- - o 

U 

a: 

D 

2 

-100 

UD 

Irn + 

30 2. 

C 

0 nl A 

-UO 20 rn 

0 

CU 

a 

L -30 

* 

bm 

IY; 

W 

> -20 W -70 A v, 1 

'D 

m 

;D 

3 

-60 2 

;P 

m 

- 

-50 ' 

0 

r- 100 

2m r xa 

QCW 

LLV) 

3 0 

wu 

OL 

zm 

a& 

to 7 WE I- 

-+ -100 P 500 2; x 

I 

r 

IT 

9" 

- 

7) 

I 

0.9 300 2 I 

0 

Ot: E? 

x 

0.8 

0 100 200 300 UOO 500 600 700 800 800 

ELRPSED TIHE CHIN1 

Figure 10. Flight history for flight rank 8. 

-30- 
180 

NRT TO SFC¶ 

0 

180 

50 

rm 

-4 

uo r; 

C 

0 

m 

-UO 30 

- 30 

-20 -70 ;;1 

3C 

3 

m 

1D 

m 

-60 2 

XI 

rn 

- 

C) 

-50 - 

100 

0 

'+I 

!- 

500 2; 

t 

4 

r 

m 

voo 

- 

-n 

-i 

0.9 300 2 

z 

0.8 

0 180 200 300 400 500 600 700 800 900 

ELRPSED TfHE ~HIN1 

Figure 11. Flight history for flight rank 9. 
0 100 200 300 400 500 600 700 800 800 

ELAPSED TIME (MINI 

Figure 12. Flight history for flight rank 10. 

-32- 
Figure 13. Flight history for flight rank 11. 
180 

W 

0 

3 

#- - 0 

0 

4 

D 

A 

-1 00 

30 

r 

D 

-I 

20 r; 

C 

0 

m LI 

-40 10 

a 

0 

to 

CL 

LL -30 

* 

- C 

z 

W -20 w -70 4 V) r 

7 

m 

;P 

m -80 2 

a 

m 

CCL 

C) 

-50 ' 

U 

XA 100 zm r x0 

ew 

urn 3 Q wa 

00, 

ZO 

a0 Pa '*I 

U)QT r- ub- -100 Q so0 ; 

I 

-I 

r 

m 

YO0 2 

r 

A 

-I 

-4 

0.9 300 2 

x 

0 

ac E! L 

0.8 

0 100 200 300 400 500 600 700 800 900 

ECRPSED TIHE lHINl 

Figure 14. Flight history for flight rank 12. 

-34- 
Figure 15. Flight history for flight rank 13. 

-35- 
Figure 16. Flight history for flight rank 14. 
DISTRNCE FROM NHC 

TROPOPRUSE 1HBI t 

SEVERITY FACTOR (C1 
ELAPSED TIHE [MINI 

Figure 18. Flight history for flight rank 16. 
Figure 19. Flight history for flight rank 17. 
Figure 20. Flight history for flight rank 18. 

-40- 

180 JFK TO HND DEPQRTURE 1628 GMT 18 OCT 76 

8 

,160 

-VO 

-30 

-28 

100 

I) 

100 

0.9 

0.6 

0 100 200 300 UOO 500 600 700 800 90 

ELAPSED TIHE CHIN1 

Figure 22. Flight history for flight rank 20. 
Figure 23. Flight history for flight rank 21. 
Figure 24. Flight history for flight rank 22. 

-44- 

180 PPT TCJ PPG DEPARTURE 1842 GMT 10 MAY 77 

0 

180 

a 

r 

D 

4 

-10 7 

C 

0 

m 

-20 

-30 

-20 -70 2 

I 

w 

m 

3 

t) 

-60 2 

;F) 

m 

- 

C, 

-50 - 

100 

0 

+1 

r 

f 00 so0 : 

I 

4 

r 

m 

MOO 2 

I- 

- 

'? 

I 

0.9 300 2 

z 

0.8 

0 100 200 300 MOO 500 600 700 000 000 

ELAPSED Tl HE CHIN1 

Figure 26. Flight hi story for fl ight rank 24, 

-46- 

Figure 28. Flight history for flight rank 26. 

-48- 
180 DHA TCI JFK OEPRRTURE 2132 GMT 24 FEB 79 

w 

E 0 

8 

.J 

-180 

80 

r 

m + 

uo : 

c 

0 

m 

C 

= -U0 20 

e 

a + 

U 

a 

1L -30 

* 

C 

C) 

w 

W -20 w -70 2 

tn 5 

m 

a 

r, 

-60 2 

m 

m 

- 

n 

-50 - 

Y- roo Lrn 

1: 

x0 

OLW 

LLV) 

3 8 

uc 

VO 

ZD aL -l 

Wb: I- 

-+ -100 m 500 x 

4 

L 

400 i% 

ICI 

+I 

I 

0.9 300 2 

E E 

Q: 

L 

0.8 

0 100 200 300 UO0 500 600 700 800 000 

ELRPSED TIRE tNlN1 

Figure 29. Flight history for flight rank 27. 

-49- 
800 BOO 

ELFIPSED TIRE (MINI 

Figure 30. Flight history for flight rank 28. 

-50- 
Figure 31. Flight history for flight rank 29. 
Figure 32. Flight history for flight rank 30. 
Figure 33. Flight history for flight rank 31. 
10 

In 

4 

-10 =, 

C 

I=I 

m 

-30 

-70 2 

3 

3 

m 

;O 

m 

-60 2 

ZO 

t7 

C4 

D 

-50 ' 

tl 

r 

so0 ; 

x 

4 

r 

m 

400 2 

r 

A 

+I 

I 

300 2 

z 

200 300 UUO 500 600 700 800 900 

ELAPSED TIHE ttIIN1 

Figure 34. Flight history for flight rank 32. 
Figure 35. Flight history for flight rank 33. 
UOO 500 600 700 800 800 

ELRPSED TIME CHIN1 

Figure 36. Flight history for flight rank 34. 

-56- 
HND 7'8 JFK DEPARTURE 1201 GMT 14 FEB 77 

70 

r 

m 

-4 

so =i 

C 

w 

m 

30 

-70 

3 

'D 

m 

a 

s 

-80 2 

;D 

m 

c. 

CS 

-50 - 

-n 

500 k =L 

4 

r 

m 

uoo 5 

c... 

'TI 

I 

300 2 

z 

100 200 300 UOO SO0 600 700 800 800 

ELRfSED TINE [HIMI 

Figure 37. Flight history for flight rank 35. 
Figure 38. Flight history for flight rank 36. 

-58- 
e, -8 MASUREB FUEL TEMP. ., 

w 80EONG PREDICT ED FUEL TEMP. " 3 -16 --- $EVEWllfY FACTOR 

ed 

Q: 

-24 a 

z 

W 

t- 

-32 

9 

W 

3 

LL -40 

0 2 4 6 8 10 12 14 

FLIGHT TIME. HOURS 

Figure 39. Comparison of calculated severity factor and Boeing-model 

predicted fuel temperature with measured fuel temperature 

on a flight from Seattle to Johannesburg. 
- OCEANIC 

0- CONTINENTAL 

AT, *C IbTl, 'c 

(a) Probabi l i ty (b) Probability of Exceedance 

Figure 40. Distribution of differences between the GASP and NMC analysis field temperatures 

'aT'Tanalysi s field - TGASp) for an oceanic and a continental route. The number 

of observations (N 1, the average temperature difference BY), and the standard 

deviation (s.d.) for each route are given in the figure. 
N 

20 - NMC OCEANIC 3949 

GWC OCEANIC 3949 

WMC CON?. I451 

.-*GWC CONT. 1451 

0246810 

Figure 41. Distribution of differences between the GASP and the NMC 

and GWC analysis field temperatures (AT=TanalYsi field - 

TGASp) for anoceanic and a continental route. Only 

observations which are common to all three data sets are 

included, and the numberof observations (N), the average 

temperature difference (AT), and the standard deviation 

(s.d.1 for each curve are given in the figure. 
N AT s.d. 

NMC OCEANIC 10037 .85 3.55 r5 ..-. NMC COLD FLIGHTS 4035 1.65 3.14 

AT, eC lb~I. *C 

(a) Probability (b) Probabi l i ty of Exceedance 

Figure 42. Distribution of differences between the GASP and NMC analysis field temperatures 

(AT- Tanalysis field - TGASp) for an oceanic route and for seTected extreme 

fahts. The number of observations (N) , the average temperature difference 

(OT), and the standard deviation (s.d.) are given in the figure. 
1 Reoorr No. 

NASA CR- i68247 

2. Government Accession No. I 3. Recipient's Catalog No. 

4 Tttle and Subtttle 

Temperature Histories of Commercial Flights at Severe 

Conditions from GASP Data 

5. Report Date I October 1983 

I 6. Performing Organ~zation Code 

W. H. Jasperson and G. D. Nastrom 1 None 

1 

7. Aurhorls) 

- 13. Type of Report and Period Covered 

8. Performing Organization Report No. 

, 

9. Perform~ng Organization Name and Address 

Control Data Corporation 

BOX 1249 

Minneapol is, Minnesota 55440 

12 Sponsor~ng Agency Name and Address 

:iational Aeronautics and Space Administration 

Washinqton, D. C. 20546 

10. Work Unit No. 

- 

1 1. Contract or Grant No. 

NAS3-21249 

I Contractor Re~ort 

1 14. Sponsoring Agency Code 

535-06-12 

15. Supplementary Notes 

Final report. Project Manager, Robert Friedman, Aerothermodynamics and Fuels Division, NASA Lewis 

Research Center, Cleveland, Ohio 44135. 

! 6 Abstract 

This report is a study of the thermal environment of commercial aircraft from a data set 

gathered during the Global Atmospheric Sampling Program (GASP). The data set covers a fouryear period of measurements. The report presents plots of airplane location and speed and 

atmospheric temperature as functions of elapsed time for 36 extreme-condition flights, 

selected by minimum values of several temperature parameters. One of these parameters, the 

severity factor, is an approximation of the in-flight wing-tank temperature. Representative 

low-severity-factor flight histories may be useful for actual temperature-profile inputs to 

design and research studies. Comparison of the GASP atmospheric temperatures to interpolated 

temperatures from National Meteorological Center and Global Weather Central analysis fields 

shows that the analysis temperatures are slightly biased toward warmer than actual temperatures, 

particularly over oceans and at extreme conditions. 

17. Key Words (Suggested by Author(s)) 

Atmospheric temperature; Aircraft fuels; 

Aircraft measurements; Fuel temperature; 

Temperature climatology 

NASA-C-168 (Rev. 10-75) 

18. Distribution Statement 

Unclassified - unlimited 

STAR Category 03 

I 

19. Security Clanif. (of this report1 

Unclassified 

A Foi sale by the National Technical Information Service, Springf~eid Virgrnra 22161 

20. Security Classif. (of this page) 

Unclassified 

21. No. of Pages 

6 3 

22. Price' 

A04