139
Calhoun: The NPS Institutional Archive Theses and Dissertations Thesis Collection 1971 Calculation of levels of relative contribution of the carbon-dioxide channel radiance from TIROS VII in the case of a large-scale stratospheric warming in January 1964. Giaque, Larry Lee. http://hdl.handle.net/10945/15595

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Page 1: Calculation of levels of relative contribution of the carbon-dioxide … · 2016. 6. 2. · Calhoun: The NPS Institutional Archive Theses and Dissertations Thesis Collection 1971

Calhoun: The NPS Institutional Archive

Theses and Dissertations Thesis Collection

1971

Calculation of levels of relative contribution of the

carbon-dioxide channel radiance from TIROS VII in

the case of a large-scale stratospheric warming in

January 1964.

Giaque, Larry Lee.

http://hdl.handle.net/10945/15595

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CALCULATION OF LEVELS OF

RELATIVE CONTRIBUTION OF THE

CARBON -DIOXIDE CHANNEL RADIANCE

FROM TIROS VII IN THE CASE OF A

LARGE SCALE STRATOSPHERIC

mumc ARY IQfi,

monmni

LARRV LEE GIAUQUE

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^Zj0c^

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UnitedNavai Postgra

tatesuate School

SlfpOSTG—,

^SCHOOL

MONTEREY, CALIF. 9394U

T.H E k "i JL k

CALCULATION OF LEVELS OF RELATIVE CONTRIBUTIONOF THE CARBON- DIOXIDE CHANNEL RADIANCE FROM

TIROS VII IN THE CASE OF A LARGE-SCALESTRATOSPHERIC WARMING IN JANUARY 1964

by

Larry Lee Giauque

Thesis Advisor: F. L. Martin

September 1971

Approved box public Mdlzait; dlbViibuutLon uiilLniutzd.

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Calculation of Levels of Relative Contribution of theCarbon-dioxide Channel Radiance from TIROS VII in the Case of

a Large-scale Stratospheric Warming in January 1964

by

Larry Lee GiauqueLieutenant Commander, United States Navy

B.A. , University of Colorado, 1961

Submitted in partial fulfillment of therequirements for the degree of

MASTER OF SCIENCE IN METEOROLOGY

• LV>iJi

NAVAL POSTGRADUATE SCHOOLSeptember 1971

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ABSTRACT

A case study of a winter stratospheric warming in the western

hemisphere in January 1964 between 60 and 40 north latitudes was

conducted. Utilizing TIROS VII radiance data and analyzed height

fields, a stepwise regression equation was determined to specify lowerI

stratospheric layer temperatures. These temperatures were used with

standard atmospheric temperatures to construct a sounding for use in a

radiance computer program. Finally, this computed radiance was com-

pared to regression values to determine if prediction and study of

stratospheric warmings are valid and useful.

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TABLE OF CONTENTS

I. INTRODUCTION 9

II. DATA PROCESSING 12

III. STATISTICAL PROCEDURES AND INTERPRETATIONS . c 14

A. DEFINITION OF DATA SETS 14

B. TEST OF AN INDEPENDENT DATA SAMPLE 16

C. STATISTICAL INFERENCES OF THE TEST 18

D. CONSTRUCTION OF WARM AND COLD MODEL STRATOSPHERES ... 21

IV. A NUMERICAL RADIATIVE COMPUTATION 26

V. CONCLUSIONS 37

APPENDIX - Computer Program . . c . . . .38

LIST OF REFERENCES 59

INITIAL DISTRIBUTION LIST '^

FORM DD 1473 61

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LIST OF TABLES

I. Substratifications of sample data 14

II. Stepwise order of entry of variablesin the regression equation 4, including F

upon-entry at step k, the test statisticCritical F, , and multiple correlation co-efficient R, at each step 16

III. Comparison of explained variance betweenthe dependent sample and independent sample .... 17

IV. Means and standard deviations of 15-jj.

temperatures and predictor thicknessesfor samples S (15) and S (15) 20

W K.

V. Layer mean statistics for the warm andcold cases S

TT (15) and 3^(15) 21W K.

VI. Comparison of 10 mb temperatures of thewarm and cold models to those of thestandard atmosphere 22

VII. Comparison of I5-jj temperature compuccJfrom the sample mean and the modelatmosphere radiance calculations 30

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LIST OF FIGURES

1, Warm and cold model atmospheres 23

2. Proposed model warm atmosphericsounding 28

3. Proposed model cold atmosphericsounding 29

4. Carbon-dioxide channel radiancecontributions for equal incrementsof In p (warm model atmosphere) 32

5. Carbon-dioxide channel radiancecontributions for equal incrementsof In p (cold model atmosphere) 33

6. Warm case equal area weighting curvecorresponding to Figure 4 34

7. Cold case equal area weighting curvecorresponding to Figure 5 35

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TABLE OF SYMBOLS AND ABBREVIATIONS

A. Regression coefficients

B(X,T) Planck intensity function at wave length X and

temperature T

Carbon dioxide

Degrees Celsius

F-ratio upon entry at step k

Acceleration of gravity

Greenwich Mean Time

Outgoing monochromatic radiance

Degrees Kelvin

Kilometer

Meter

Millibars

Detected radiance

Atmospheric pressure

Specific constituent mixing ratio

Multiple regression coefficient

Dry air gas constant

Warm hemisphere sample of 10 January 1964

Cold hemisphere sample of 10 January 1964

Warm hemisphere sample of 15 January 1964

Cold hemisphere sample of 15 January 1964

T Temperature

X. Regression predictors

Y Regression predictand

co2

c

Fk

g

GMT

hK

km

m

mb

N

P

q

R

Rd

sw(io)

sK(io)

V 15)

SK(15)

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Y Regression predictand test values

t Weighting function as a function of In p

h Height above mean sea level

T(h) Transmittance of the atmosphere to the outgoing15-(J. band of C0

? , between the levels Z = h andZ = 00

§ Filter function centered at wavelength X,

spanning the increment AX

X Wavelength

-4|j Microns, identical to 10 cms

AZ Thickness of atmospheric layer

1-CC The significance of the predictor addedexpressed as a probability

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ACKNOWLEDGEMENTS

The author wishes to express his appreciation to his advisor,

Professor F. L. Martin, for his suggestions, advice, guidance and

support in this research.

Appreciation is also expressed to the W. R. Church Computer

Facility of the Naval Postgraduate School.

8

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I. INTRODUCTION

The launch of the TIROS VII meteorological satellite on 19 June 1963

led to the remote sensing of stratospheric temperatures on a quasi-

global scale. The orbits of TIROS VII were almost circular and had an

average height of 635 km. The plane of the satellite orbit was inclined

to the equitorial plane at an angle 58 , which resulted in scan-coverage

between 60 north and 60 south latitudes. TIROS VII was equipped with

a five-channel scanning radiometer, one of which measured the filtered

thermal radiation of CO in the half-power wavelength range 14.8 to

15.5(a [Staff members, 1964]. The C09

in the stratosphere should emit

at the same temperature as the air (of which it is a part), thus the

observed intensities can be interpreted in terms of a weighted-mean,

equivalent black-body cempcraLure in the stratosphere. Radiation

transfer theory leads to the radiance from the 15-(j band [Warnecke,

1967] as

x2

p=0.1

r r <H(X, In p)N15

=J J

$(X) d(ln P)~ B(X » T(ln p)) d (ln p) dX (1)

X1

p=1000

In (1), the 15 -|j band is assumed opaque to the surface radiation. If

the weighting function ty (In p) is defined as

x2r dT(X,ln p)

% (In p) =J

$(\) B(X,T(ln p)) ^ (ln p)d\ (2)

the integral (1) reduces to

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p=1000.

N15

=J

[l|» (In p)] d (In p) (3)

p=0.1

Thus the contribution of each layer to the radiance, N, sensed by the

radiometer can be determined as a function of pressure. Radiative

transfer theory applied to model atmospheres by Nordberg et al. [1965]

indicates that maximum radiation, \[f (In p), in the 15-|d range is

emitted by the low stratosphere. The maximum weighting contribution at

small nadir angles originates at about 25 km but the 15-(j. temperature

corresponds to different heights from time to time because the tempera-

ture structure in the stratosphere changes with time [Belmont et al.,

1968]. Radiance should also then be statistically related to the mean

temperature or thickness between various pressure levels in the stratos-

phere. The latter conjecture was the originating hypothesis of this

investigation.

Several studies have appeared in the literature which strongly

support a relationship with 15-|j temperatures at pressure levels in

the stratosphere. Belmont et al. [1968], Nordberg et al. [1965],

Warnecke [1967] and Teweles [1966] indicated that 15-[j temperatures

depict some of the large scale horizontal wave activity in the thermal

fields of the lower stratosphere. In addition, Kennedy [1966], has

compiled an atlas of ten-day mean isotherm charts recorded by the

15-|j channel of TIROS VII for the period June 1963 through July 1964.

These charts were presented by Kennedy as indicative of the spatial

temperature distribution of the lower stratosphere during the total

period of analysis of TIROS VII. Between 60 north and 60 south

10

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latitudes these charts depict, for example, the proper seasonal

distribution of stratospheric isotherms at about 25 km.

Dense cloud bands will cause a decrease in the 15-p temperature

and will raise the peak elevation of its radiance weighting function.

Although data presented in the Kennedy Atlas were not corrected for

cloud contamination, nevertheless, the reduction to ten-day mean 15-|j

temperatures was considered by Kennedy to have eliminated the cloud

contamination effect. This atlas served as a source for grid point

15-p. temperature data for the case studies investigated in this

dissertation.

Since the 15 -p. temperatures are weighted over an indefinite thick-

ness range in the stratosphere, Belmont et al. [1968] has raised the

question, "which pressure level in the stratosphere does the 15-[a

temperature best represent?" Moreover, Shen et al. r 1968] have shown

the usefulness of 15-(J temperature fields in detecting stratospheric

warming events in the Southern Hemisphere polar winter. This paper

seeks tc relate statistically the various layer-contributions to the

15-|j temperature in the case of a winter stratospheric warming in the

polar latitudes of the Western Hemisphere. This case was centered

time-wise on 15 January 1964.

11

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II. DATA PROCESSING

The 15—Jj temperatures were extracted from the Kennedy Atlas [1966]

of stratospheric mean 15-|j isotherms, using charts 42 (10 January 1964)

and 43 (15 January 1964). Grid points values for 60 , 50 , and 40

north and every 5 of longitude around the globe were carefully inter-

polated to the nearest whole degree Kelvin. These 216 grid points

were further divided into two hemispheres : that between 70 west and

110 east longitude corresponding to the "cold" sample since it

approximated the sector of the winter cold vortex. The "warm" hemisphere

between 110 east and 70 west longitude (the "Western" Hemisphere) con-

tained the warm stratospheric anticyclone. There were 108 grid points

located in each sample.

Thickness values at each o£ the 216 grid points were noted and tor

both dates of interest were determined from the Northern Hemisphere

analyses of 10, 30, 50, 100 and 300 mb contour charts. These charts

were found in the January 1964 series of map analyses of the Institute

of Meteorology and Geophysics of the Free University of Berlin [1964],

Contour values from each pressure level and at each grid point were

differenced to determine four thicknesses in the stratosphere and upper

troposphere:

10 - 30 mb thickness, denoted X, (i, j)

30 - 50 mb thickness, denoted X~(i,j)

50 - 100 mb thickness, denoted X„(i,j)

100 - 300 mb thickness, denoted X, (i,j)

Finally, the dependent variable is the 15-(j temperature and is denoted

hereafter as Y(i,j).

12

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The statistical model is then to be expressed in the multiple-

regression form

Y = A + A..X- + A_X_ + A_X_ + A.X. (4)oil 22 33 44

where the coefficients A , A.. , A^, A« and A, are to be determined by

the least squares techniques. All of the variables for input into

equation (4) were encoded onto punched cards in a format consistent

with the requirements of the stepwise regression program, BMD02R

[Dixon, 1966], This program is available in the Library of the W. R.

Church Computer Center of the Naval Postgraduate School.

13

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III. STATISTICAL PROCEDURES AND INTERPRETATIONS

A. DEFINITION OF DATA SETS

As noted previously, it was necessary to stratify the data for the

two map-times into cold and warm stratospheric "hemispheres". According

to the stratospheric contour and temperature analyses of the Free

University of Berlin, the warming anticyclone had reached its peak

intensity in the Western Hemisphere on 15 January 1964, with a well-

defined cold hemisphere adjacent. The stratospheric warming was still

in a developing stage on 10 January 1964. This led to the four sub-

stratifications of sample data, which for simplicity will be denoted in

Table I.

TABLE I

Substratifications of Sample Data

Date Warm Cold

10 January STT (10) S HO)

15 January ST7 (15) S (15)

Actually the last two, S (15) and S (15) were used to generate the

multiple regression equations of type applicable to the warm and cold

hemispheres, respectively. These equations were then to be tested for

diagnostic significance by applying them to the independent samples

S (10) and S (10). Each of the four stratifications had 108 data samplew K.

sets.

The BMD02R regression analysis not only generates a multiple

regression equation similar to (4) but also performs a step-wise

14

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screening in the process: it first determines that independent variable

X. which explains the highest percentage variance of Y. Then at step

two, it determines the X. in the remaining predictor set that explains

the largest percentage of the residual variance unexplained by the

first variable, and so forth, for steps three and four.

The BMD02R program also computes for each step the F-statistic

upon-entry of the kth variable selected, where F, is expressible at

step k as [Dixon, 1966]

F. (l,n-k-l) = (fo cum. expl.var. , step k) - ($ cum, expl. var. , step k-1)

(Jjo unexplained variance at step k)

In the present problem, two tests were to be made using X, , X , X_ and

X. with a total sample size of n=108 in the warm and cold cases STT (15)4 W

and S (15), respectively. Based upon the magnitude of F, of (5), Table

II indicates tlie order of entry of the predictors selected and the

corresponding F, -statistic with which they entered.

For each predictor tested, its significance at step k may be

cassessed by comparison of its F, value with a Critical F

Tdefined

after Miller [1962] as

Fk

= Fa/P-k+l

a,n-k-l), a = 0.05 (6)

in order that the over all regression be assured of significance at the

1-CC confidence level. The set of Critical F. values to be used fork

comparison are adjoined to Table II.

The four-predictor regression equations having the form of (4) are

as follows:

S (15), Y=112.213 - .04842X1+ .03686X

2+ .18648X + .07498X

4(7)

15

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TABLE II

Stepwise order of entry of variables in

the regression equation (4), including F,

upon-entry at step k, the test statisticCritical F , and multiple correlation co-

efficient R, at each step

Sample--Warm, Sw(15), n=108 Sample-•Cold, S„(15), n=108

Criti-cal

Values

<StepNo.

Vari-ableenter-

Fk

Mult.Corr.

Coeff.

Vari-ableenter-

Mult.Corr.

k Coeff.ing ing

k=l X3

179.13 .7926 X3

14.81 .4252 6.51

2 Xl

54.20 .8688 Xl

8.42 .4905 6.00

3 X4

39.20 .9066 X4

4.21 .5083 5.19

4 X2

4.36 .9106 X2

1.72 .5201 3.96

S_,(15), Y=171.927 + .04872Xn+ .06728X_ + .10750X_ - .07642X. (8)

K i 2. 5 h

Table II shows that all thickness predictors entered at a confidence

level of 95 percent for each entry in equation (7). On the other hand,

for the cold case, the order of entry was identical to that of S (15)w

but the levels of significance for X, and X9were subcritical. How-

ever, in the cold case, the standard error of estimate continued to

decrease from step three to step four, so the full four predictor

equation (8) was retained for testing against the independent sample

S (10). A more complete justification for retaining the full set ofJs.

predictors can be found at the end of III-C.

B. TEST ON AN INDEPENDENT DATA SAMPLE

In order to test the validity of equations (7) and (8) developed

from S (15) and S (15) , the coefficients from these samples wereW Js.

16

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combined through the matrix multiplication (9) to form the

estimator-predictand of the independent data

Y - (A , A^, A , A~, A.) (9)

using the sets S (10) and S (10). The regression between (Y,Y) forW K

the independent sample gave the results listed in Table III as com-

pared to the dependent case.

TABLE III

Comparison of explained variance betweenthe dependent sample and independent sample

Dependent Sample

"/? Exp 1

«

Variance

Independent Sample

£Expl.

R(Yj Y) Fn(1,106)

Variance 1

W

K

82.92

27.05

47.11 .6864

76.61 .8753

94.426

347.266

There was a sizeable shrinkage in explained variance in the warm

case when applying the regression from the SI7 (15) case to the inde-

pendent data set. However, in this case the F-test still indicated

confidence well over the 95 percent level of belief in spite of the

shrinkage. The result of the regression for the cold case showed a

significant improvement in the explained variance of T in the

independent sample, an unexpected result which will be discussed

below.

17

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C. STATISTICAL INFERENCES OF THE TEST

The stratospheric warming which seemed to reach its maximum

magnitude over the entire "warm" hemisphere on 15 January, had also

spread to some extent into the "cold" hemisphere. The fact that the

warming process had encompassed the entire warm sector and a part of

the cold sector may explain the wide range of explained variance

between the two sectors on 15 January including the rather low

explained variance in S (15).K.

A statistical reason for the observed shrinkage in explained

variance in passing from the dependent equation (7) to the inde-

pendent sample of 10 January may be ascribed to the incomplete

development of the full warm hemisphere as of this date, so that the

sample of 10 January actually consisted of a mixture of warm and cold

data points. In other words, the warm hemisphere of 10 January seems

not to have been as clearly stratified as a warm hemisphere as that

of 15 January.

The phenomenon of an increased percentage explained variance in

passing from equation (8) to the independent cold sample of 10

January was subject to a similar conjecture. The relatively small

multiple regression coefficient resulting from S (15) seemed toK

indicate that a stratospheric warming effect had also begun to

spread into the "cold" hemisphere, and in consequence only 27.05

percent of the variance of Y was explained by the specification

equation (8). On the other hand, the much larger percentage of the

variance explained by (8) applied to S (10) seems to indicate that

the cold stratification for the 10 January case was more uniform

than the dependent case chosen for 15 January.

18

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In retrospect, a more flexible sampling procedure which might

have improved the results should have involved more care in deline-

ating the stratifications of the areas of warm and cold stratospheres,

respectively. For example, it now seems reasonable to limit the

warm area sample to those stratospheric grid points having anti-

cyclonic contour curvature and not necessarily assigning an entire

hemisphere to the sample. Similar considerations, with regard to

cyclonic curvature might well have afforded a better criterion for

the cold stratification in both the dependent and independent cases.

It was now possible to offer a more complete statistical reason

for retaining all four predictors in the right side of equation (8).

Even though the dependent cold sample from which equation (8) was

derived seems to have been not uniformly stratified, the use of the

resulting predictand was well verified (R(Y,Y) = .8753) on the more

stable stratified cold hemisphere of 10 January.

It was also noteworthy that a choice of S (10) as the dependentK

cold sample gave the same order of entry for variables as indicated

in Table II, with all individual predictors significant at well above

the 95 percent confidence limit.

With Y based upon equation (8), the ensuing regression between

Y and Y for 10 January was

Y = -95.3142 + 1.4298Y, R(Y,Y) = .8753 (10)

so that by equation (10) all predictors would have had the same

coefficient matrix apart from the constant multiplier, 1.4298.

Thus equations (7) and (8) are adopted as the representative

regression equations for the warm and cold stratospheric samples,

respectively.

19

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Since the regression equations just listed must be satisfied

by the sample means, it is useful to list the mean properties of

these two atmospheric samples S IT (15) and S Tr (15). Table IV is aW K

compilation of the means and standard deviations of all variables

which appear in equations (7) and (8) for 15 January 1964.

TABLE IV

Means and standard deviations of 15-|a

temperatures and predictor thicknessesfor samples S TT (15) and Sv (15)

Sw (15) S

K (15)

Vrbl. Mean Std. Dev. Mean Std. Dev.

T15

226. 16K 3.68923 217. 96K 4.79275

h 7298.1 gpm 327.7286 6796.5 gpm 268.4886

h 3356 .

1

126.8544 3149.4 100.4864

h 4520.6 165.8544 4221.9 162.5060

X4

7017.0 125.0733 6998.1 138.5645

Y 226. 16K 217. 96K

The standard deviation of X.. (the 10 to 30 mb thickness) was

considerably larger than the other levels; however, it is a layer

subject to more radiosonde error than those below it. Also inter-

polation of contour height to grid points was more subjective at

10 mb due to stronger gradients than existed at lower levels in the

stratosphere.

Because of the equivalence of thickness to mean temperature of

an isobaric layer through the integrated form of the hydrostatic

equation

20

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Rrf

p1 -

AZ = — In — T (11)g P 2

it is possible to ascribe a mean temperature to each of the four

isobaric layers of thicknesses hitherto denoted X.. , X , X_ and X, .

These mean temperatures corresponding to the mean thicknesses already

listed in Table IV are given in Table V for the warm and cold stratos-

pheres respectively, along with other relevant statistics used in the

specification of the 15-|j, temperature. The statistic R(Y,X.) is the

simple correlation between T1

,. and the ith layer- thickness.

TABLE V

Layer mean statistics for the warmand cold cases S

T7 (15) and S H5)

"arm Case Cold Case

7~ Mid- ~R(Y,x7) Layer R(Y,X.) LayerLayer . x J 1 J

point mean mean(nib)

press. temp. temp.

xr 10 - 30 17.32 mb .195 226. 96K

X2

: 30 - 50 38.73 .663 224.40

X3

: 50 - 100 70.71 .793 222.82

X, : 100 - 300 173.20 .656 218.22

.750 211. 36K

.281 210.56

.161 208.09

-.340 217.63

D. CONSTRUCTION OF WARM AND COLD MODEL STRATOSPHERES

From the mean temperatures listed in Table V, stratospheric model

temperature-pressure distributions were constructed for the warm and

cold cases in Figure 1: A-B-C-D showing the lower stratosphere tempera-

tures in the warm case and A'-B'-C'-D' showing the lower stratosphere

temperatures in the cold case at 17.3, 38.7, 70.7 and 173.2 mb

21

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respectively. The lowest points D and D' lie within a half degree

Celsius of one another, at the 173.2 mb level.

Since no mean temperatures were available from this study below

173.2 mb, the cold and warm cases were adjoined to the Cold and Warm

Supplemental Standard Atmospheres [Dubin et al., 1966] at latitude

60 north in January. The cold and warm January standard profiles

below 300 mb were vitually identical and for the purpose of the

modeling done here were taken as the unique curve E-F-G in Figure 1.

This led to a minor inconsistency in the mean temperatures to be

expected in the layer 100-300 mb in the cold and warm cases,

respectively.

The expected temperature at 10 mb for the warm and cold models were

obtained by extrapolating the lines B - A and B 1 - A 1 in Figure 1 to

the 10 mb level. This techniaue led to the results listed in Table VI:

TABLE VI

Comparison of 10 mb temperatures of the warm and coldmodels to those of the January Supplemental StandardAtmosphere (60 north)

Warm Cold

10 mb, model -43.65C -61.15C

Jan. 60N Supp. -43.75C -73.50C

It is clear that the lower stratospheric temperatures from the warm

sample are in good agreement with the January warm standard, while the

cold sample was not as clearly definitive of the cold standard for the

reasons already cited in III-C.

The remainder of the model above the 10 mb level was fitted in both

models by extending linearly the T-ln p profile from 10 mb upward to

22

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X

£ 10

30

50

100

300

1000 mb «-

210 220 230 240Temperature

Fig. 1. Warm and cold model atmospheres

250 260

23

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the listed stratopeaks of the Warm and Cold Supplemental Standards

[Dubin et al., 1966]. These peaks occur over the range:

p = 0.7 to 0.423 mb where T = -5C

p = 0.44 to 0.26 mb where T = -17C

Above the top of these levels, the listed lapse rate above the

stratopeak was used to extend the T-ln p models to the level p=0.1

mb, which is commonly taken as the top of the atmosphere in

radiative-transfer theory.

The simple correlation coefficients listed in Table V give some

indication of the layers contributing most heavily to the specification

of T-.C-. The results in the warm case (Table V) indicate a maximum

influence or weight from the layer 50-100 mb centered at 18.1 km

(70 mb). However, there is considerable additional influence from

the 30-50 mb and 100-300 mb layers (at 26.4 and 12.2 km, respectively).

Note that the influence from the layers X~, X„ and X, as indicated by

R(Y,X.) seem significant,, This will be discussed further in IV.

On the other hand, the cold model atmosphere has the maximum

influence detectable from this study in view of the high correlation

coefficient R(Y,X ), (Table V), attributable to the layer 10-30 mb and

this influence decreases systematically below this level. The signifi-

cant negative correlation in the lowest level (100-300 mb) is appar-

ently due to the low warm tropopause which is synoptically expected

with a cold stratospheric vortex situation. The overlying deep cold

layer (100-10 mb) apparently acts as an effective absorber, and

relatively low-emittance re-radiator of the CO radiation started in

the high troposphere. In other words, this negative correlation in

the lowest layer is apparently related to the relatively steep lapse

24

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rate between the lowest part of the stratosphere and the warm

tropospheric layer immediately below.

25

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IV. A NUMERICAL RADIATIVE COMPUTATION

A brief discussion of the upwelling radiance from an arbitrary

planetary atmosphere having a temperature distribution T = T(p) and

constituent distributions q. = q.(p), i=l, .»., 3, is given. V. Kunde

[1967] prepared a detailed theoretical study of a number of planetary

atmospheres detailing the necessary theoretical computations for the

upwelling radiances sensed by various medium resolution infrared radio-

meters. Kunde 1

s theory [Kunde, 1967] made use of spherically hori-

zontal symmetry of all sounding properties in the atmosphere, and

computed the transmitted radiative contributions from each level p to

p+dp. Thus he made use of the generalized formula for outgoing radiance

dl, = B, [A,T(ln p)] ,,?T

, d(ln p) (12)

in the case of a satellite sensor having optical filter response

§, = 1.0. In equation (12), the transmittance T is the constituentA

product-transmissivity at pressure p, and T must be a decreasing

function of pressure. The Curtis-Godson approximation is used for

correcting the vertical absorber mass distribution, and for deducing

the resultant pressure-effect upon line broadening.

When CO is the main emitter and the earth's 15-|a band the main

source of outgoing radiation, the surface may be considered black in

the terrestrial spectrum (reflectivity zero). The problem was further

simplified by assumed constancy of the mixing ratio of CO at

q = 0.477 gm/kg. The details of the vertical variation of water

vapor and ozone mixing ratios, which are highly variable for each gas,

were supplied in the form of a sounding distribution of each. These

26

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gases are distributed relative to height or, equivalently to the

pressure p = p(h,T).

Based on the results of III-D, two model vertical profiles T(p)

were determined from Figure 1 with sufficient vertical resolution

(about thirty significant levels) to cover the entire range of pressure

from p = 1013.5 mb to p = 0.1 mb, for both the warm and cold cases in

Figures 2 and 3.

The vertical distributions of water vapor and ozone enter the com-

putation of N, ,. only in a very secondary manner since there is only

slight overlap between the water vapor rotational band wings and the

14.0-16.3|J. response function placed upon the sensors of the 15-\1

channel of TIROS VII. The sensor response function $(X.) associated

with the jth subinterval, £\. ., of the 15—jj. channel are listed in the

TIROS VII Radiation Data Catalog and Users' Manual [Staff. 1965].

The water vapor and ozone mixing ratio distributions with height

actually used were listed for Maniwaki, Quebec (46N, 76W) based upon

the real time radiosonde observations taken on 29 September 1958 at

1200 GMT. The Maniwaki surface values (at 996.0 mb) of mixing ratio

were considered identical to those at 1013.5 mb of the present models

atmospheric base level.

The integral i|/(ln p) of equation (2) represents the contribution

2to the total filtered radiance at a point in space in watts /m /ster of

depth and includes the Planck-Kirchhof f transmittance attributed to a

small pressure increment dp, as essentially specified by the radiosonde

(including the constituent mixing ratios).

The Kunde radiative transfer theory [Kunde, 1967] was applied to

both of the model atmospheres as input, and with the model-invariant

27

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10

CL,

30

50

100

300

1000 mb220 230 240 250

Temperature K.

260

Fig. 2. Proposed model warm atmospheric sounding

28

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.1

a,10

30

50

100

300

1000 mb210 220 230 240

Temperature K.

250 260

Fig. 3. Proposed model cold atmospheric sounding

29

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mixing ratio distributions of q n (p) and q_ (p). The Kunde computerH2° °3

program is listed in the Appendix. The program was designed to give the

total filtered N and the corresponding T, - computed by five-point

interpolation from the laboratory calibration of N vs ^-.c- In this

theoretical program no instrument degradation need be considered.

Finally the first important output of the program gives N and the

effective T.. _ for the model atmospheres. It also gives a pressure-

height weighting function essentially equivalent to ijj(ln p) = dN/d(ln p)

appropriate to the contribution to N for equal increments of In p.

The results of the model -atmosphere radiance computation after Kunde

[1967] applied to the warm and cold models (and the implied soundings,

Figures 2 and 3) led to the following results for calculated N and the

resultant 15-|a temperatures.

TABLE VII

Comparison of 15-(j temperature computedfrom the sample-mean and the modelatmosphere radiance calculations

2 —N (watts /m /ster) T [Kunde] T = Y

S I7 (15) 3.048 228. 9K 226. 2Kw

SK(15) 2.460 218. IK 217. 9K

In Table VII the corresponding values are in columns 3 and 4, whereas

the contrast between the model atmospheres is to be seen by comparing

row 2 against row 3. It is to be noted that the warm case emits a

greater N than the cold sample, and that the model atmospheres adopted

reproduce the respective sample mean T1

,. temperatures effectively.

30

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Another important output of the Kunde program is the percentage of

total N associated with increments of In p between p = 0.1 and

p = 1013.5 mb. This output was listed in the Kunde program by kilo-

meter intervals and at equivalent pressure levels for the warm and cold

model atmospheres and the results summed to give the weight functions

ill (In p) in the form of block-diagrams on a In p scale (Figures 4 and

5). These block diagrams were subsequently smoothed preserving equal

areas of \|f (In p) from block-to-block and the results appear as Figures

6 and 7.

It is now useful to reconsider the simple correlation coefficients

between T.. ,. (and therefore N) , and the layer thicknesses given in Table

V. For the cold atmosphere, the negative correlation attributable to

the layer 100-300 mb has been explained by the compensating cool

shielding layer C'B 1 which occurs even when a temperature rise occurs

at or near 300 mb. However, the correlation coefficient of 0.750

between the 10-30 mb thickness and the total radiance was due to

sampling variations in temperature of B'A' about the mean profile T(p)

of Figure 1, with a warmer than average upper layer able to contribute

more radiance to space than if the layer were sampled as relatively

cold. This result verifies the positive correlation R(T 1C.,X, ) = 0.750

found for the cold case.

A similar argument was applied to the warm case where the lapse rate

from the upper troposphere to the stratopeak was continuously of an

inversion nature. Any layer sampled in S (15), if warmer than the mean,w

tends to have greater emittance to space, whereas it will have smaller

emittance when cooler than normal accounting for the positive correlations

in Table V. This effect is especially prominent near the level of

31

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1.25

2.5

5.0

10

20

(X40

80

160

320

640

lOOOmb .1 .2 .3 .4 .5 .6 .7 .8 .9

ty(In p) watts /m /ster

Fig. 4. Carbon-dioxide channel radiance contributions for

equal increments of In p (warm model atmosphere)

32

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.6

1.25

2.5

5.0

a.

10

20

40

80

160

320

640

lOOOmb • JL * -< • O • t • J IT ^7 .8 .9

\Jj(In p) watts /m /ster

Fig. 5. Carbon-dioxide channel radiance contributions for

equal increments of In p (cold model atmosphere)

33

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.6

1.25

2.5

5.0

ex

10

20

40

80

160

320

640

1000 mb1 .2 .3 .4 .5 .6 .7 .8 .9

2ty

(In p) watts/m /ster

Fig. 6. Warm case equal area weighting curve correspondingto Fig. 4

34

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(X

«-.J

.6

1.25

2.5

5.0

10

20

40

80

160

320

640

1000 mb .7 .8 .9

\|f (In p) watts/m /ster

Fig. 7. Cold case equal area weighting curve correspondingto Fig. 5

35

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maximum weighting functionty

(In p), which occurs in the range

50-100 mb.

36

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V. CONCLUSIONS

The results of this study of a northern hemisphere stratospheric

warming indicate that a polar-orbiting satellite with a 15-^ sensor

can be used as a tool to study stratospheric warming processes. The

layers of the lower stratosphere which are initially affected can be

identified by comparison of regression values to normal soundings for

that of the anticyclonic area or the vortex area. Although this study

was concerned only with one stratospheric warming, the correlation

coefficients are large enough to seem significant. This was especially

true in the S (15) sample which was particularly well stratified withw

respect to the warmingo

A daily synoptic analysis of the C0_ channel radiance information

from a polar-orbiting satellite should provide initial indications u£

when a stratospheric warming is beginning. The development of such a

warming may easily be followed as it progresses around the glode.

Future operational study in this area by use of smaller sectors, using

successive-day swath continuity might allow enough data-definition to

follow such a warming as it develops in the vertical and could become

a tool for the study of stratospheric warmings.

37

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APPENDIX

KUNDE RADIANCE PROGRAM FOR 15 -(J BAND OF C02

<(•>•••> x — o so cr_j oo X _i X m o — • II C

<t x x uj r*~ »-< «-o Is- L'.;

2 O •"• -« QC •-" ""* *** —O— • h-«j m m m q. r*- — o «-*>- oir»o i-« cm z:

h~ •• X -J •« (— LT.LTi OliJ 0»~-0 >-* (J —*->0 MM — h-»-OX HrflH U.». i— m m o — w.cm _(.-. wrc>w x a:^ » ^s — o mmo «-,-.. o >l|ij x ». i*- mo o o o r-i r-Hu ^o in ujUuu vGin 3•Z X O O w ~Hl- 30 *~ >QT3 • X O„ „_ r-{ i-h X nO »-uj »..nn tr --fi- • r*-co ro _j

LO XO •— — —^ H--*X—X •» cr 3* .-— »LL X_j xo O v: Oai • in *o »-o a. •>—o Ma c\i soO <th I— h- OCX— — f*-—0->m 5 —om -HO • cm~z 5 «•" <c <a. oa o tnwO'-'O*-' m oocr> u^ •> >r ••

<c xo 00 »- r-K ^o Mvtlo^-o^- I— oin—• »x u x•• »-h-co . •• o w—o w-H>-nr-(5 ,-iwf-) xin ro

4- I—<C>-C .V O C\IOr-i LOI— OJii—-<S - —-rO<M -O •• II••

h- ICi<X X O—CO*- y- -rM>_lCi- — 3«d-^ »IT> CMX •> ^-J*-" »-t r-( <J (_> ,-1 r-i •"^X«tril-- O Dl)W I*" • •

•• ouiv m w »»q _»x —.ini— 3"-_j » in l— err) »c\i f-i coXXt-O */. >0 *2: •- inr-.U««X~- — vj.h- •• fN--1 O U-

r\i _<•—< »m m •«r r^ •-— <—• »~ —i*~wx—» t-o cy c •— <—ii ,:

i_ i»j Vs. <\!m **. _j »Oio—o^ro *- f,< — u" 01 »•—*0 :i — . J_ 1:— > ooxooo-4- --^—oo—- cc —om •>,-< r» xODhO OOini-|-OHO> sr 000 x - 7

o oo *-"-•'-* 1—1m— .-m.— r-<;7' x otn*-' ox x •—<

c\j ^<iv^o—wc\j—..^.wc! — <r •- r-i'-^Q »m ro 2:^^t-ovioX-oOLniriMiHlo' — «-^(MOsi <\j •• ». x^"oxo--4 a^orv-r-o> — h- o X'^^ .in 1*- xt—o •o—«-»ooc:*-"»'0<i

r _j •• m x>xid r- •— • r^-

^i.O—DlCij-h- ro r\|C? 2: x-, «— _.irV •> ncMO -) »• —

.

c><-<^t •xoi— ••h-'-ic •• ^o •-< xi 'r-i • f-i x r<~i

%—•—— o *--~ •(— »—»^o x *• ••o XLuro u_ ro »-<

^JHO^-i— C'«— »••—OO 00 Q- ~-—~\£\ vOan » »-XhVOO^OC^-OOO^" * OOO • r—iijU II CM C\la'•—X—joo—1 mi*- inm f-< —<c ^0^ 00— o »-ci. • »u..'

^X •*"—D-ZM'-OOIl h-U'in *-<—x OJxO •• X — U- U 5"

MOO— r—d.XfOD(— <-HC\J UDZ_I*- X>0 ^ "X <" Is- »-X

v. ^c>r «-oc> ^x>-imOo. 1— Xoo LLvom ^»u ox— »•«" rr 1 • —X g —.(-coxTri/) <th- x> ••»• x ro — .

O— crcvH-oct'h-m o« •> •><?> o<t •• xmO »t *-* iu — r\iui

oo^^ »-o(- *r,~— •• »'~— ^-c »-o— Or-< • •> uj _j sc-~<i/>hoj »^o f ^win-»-<oo jt •— »-o »u ro ^-lj *- o »!U<t^-Oti '»CH'*OHhOOOO'« *• O— in c\j +f~* *~cnj » T" O «-<J? -h 00-COI-«'OOhccO'v OO0-* »X;jj ini CO «n.— .-iCMXI—— -~c >-i—10m. •.o—'•-<*— *- C'Jin r-<o—• ooor »X •-< im u »rvj

iD^C'""!- in*-—Hv-wj zrmrvj *-r-o^- u »•—< ^i*-ro • cd • *-^^-<ci— «-»t-<oox—'H-mt— 2 u.".^- -.-"— x*-x »c\j »• ^a •> ro »-r- ^ »u»-x<r*-oo »•? o>-< »-l< i.ij>o:< |- u»>o x «x cm »-x •-< xll mm »-x5"S.i^CMu ^-^'-a .*——»h- >«;.»-- 3 C'"' >XX Of*-

I

s- • 1—to • O hh*OCXX_J|— CT OIld rt.LTil 13? «U:CQ «-i _J » <-<ll CM LT> »f-l f<1 *- i-l || <-* *J" •fit—'i/)CLX(J-Oh-H-3 (*-'J '3 "+-3I—-3X—*•—— »• *•**-. Li rO •» •— ^ •» CM »~CMCM ••

•*^ «—x »- «"' ••ooroox*t——'U- ••<£ f— • «h?2Z?Zh?Z.7L&7:'?. OZZZ'hz^COh X r~- .roO^x ro cx^X »-inx O'- 1 X<rl—o^.mmom—nCC cOwUcr-i-r 0000c —uomn roi-i cm cm—• .—1 in,-t >-*f-if-4^\\. HtLrOHMM —SNOSOSmmMi-,0 1—••—•»--• •(.-•—«,-<»—!!—-• C-^'O *-»•-'— *-»M.'-t ,»-'«-'*—«-» *-• *-—-

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LIST OF REFERENCES

Belmont, A. D. , G. W. Nicholas and W. C. Shen, 1968: Comparison of15-(j TIROS VII Data with Radiosonde Temperatures. Journal ofApplied Meteorology , 7_, 284-289.

Dixon, W. J., (Ed.), 1966: Biomedical Computer Programs , HealthSciences Computing Facility, University of California at LosAngeles, 585 pp.

Dubin, M. , Sissenwine, N. and Teweles, S., 1966: U. S. StandardAtmosphere Suppliments, 1966 , National Science Services Admin-istration, National Aeronautics and Space Administration andUnited States Air Force, 289 pp.

Kennedy, J. S. , 1966: An Atlas of Stratospheric Mean Isotherms DerivedFrom TIROS VII Observations , 85 pp.

Kunde, V. G. , 1967: Theoretical Computations of the Outgoing InfraredRadiance from a Planetary Atmosphere , 117 pp.

Meteorological Analyses , Institute for Meteorology and Geophysics of theFree University of Berlin, January-March 1964.

n.iiler, k.. C», i^oz: ^tanistiical ircvIj.ct!i.on by L/iscriruznanL Analysxs,Meteor. Monogr ., 4, No. 25, Boston, Mass., Amer. Meteor. Soc,53 pp.

Nordberg, W. , 1966: Satellite Radiation Measurements in SpectralRegions. Satellite Data in Meteorological Research , NationalCenter for Atmospheric Research, NCAR-TN-11, Boulder, Colo.,199-213.

Shen, W. C, G. W. Nichols and A. D. Belmont, 1968: Antartic Stratos-pheric Warming During 1963 Revealed by 15-u. TIROS VII Data e

Journal of Applied Meteorology, 7_, 268-283.

Teweles, S., 1966: Radiometer data in the 15-u band. Satellite Datain Meteorological Research , National Center for AtmosphericResearch, NCAR-TN-11, Boulder, Colo., 251-257.

Staff Members. 1965: TIROS VII Radiation Data Catalog and Users'Manual . National Space Science Data Center, Greenbelt, Md.,

269 pp.

Warnecke, G,, 1967: The Remote Sensing of Stratospheric Temperaturesand Some Results From the Nimbus II Satellite Experiment , GoddardSpace Flight Center, Greenbelt, Md., 24 pp.

59

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INITIAL DISTRIBUTION LIST

No. Copies

1. Lieutenant Commander Larry L. Giauque 2

Fleet Weather CentralBox 2 COMNAVMARIANASFPO San Francisco, 96630

2. Professor Frank L. Martin 6

Department of MeteorologyNaval Postgraduate SchoolMonterey, California 93940

3. Department of Meteorology 3

Naval Postgraduate SchoolMonterey, California 93940

4. Library, Code 0212 2

Naval Postgraduate SchoolMonterey, California 93940

5. Defense Documentation Center 2:

Cameron StationAlexandria, Virginia 22314

60

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Security Classification

DOCUMENT CONTROL DATA -R&D'Security c las si lie alion of title, body ol abstract and indexing annotation must be entered when the overall report is classified)

1 originating activity (Corporate author)

Naval Postgraduate School

Monterey, California 93940

2*. REPORT SECURITY CLASSIFICATION

Unclassified2b. GROUP

3 REPOR T TITLE

Calculation of Levels of Relative Contribution of the Carbon-dioxideChannel Radiance from TIROS VII in the Case of a Large-scaleStratospheric Warming in January 1964

4 DESCRIPTIVE NOTES (Type of report and. in c lus ive dates)

Master's Thesis; September 19715 tj THORISI (First name, middle initial, last name)

Larry Lee Giauque

6 REPOR T D A TE

September 1971

7a. TOTAL NO. OF PAGES

62

76. NO. OF RE FS

12ea. CONTRACT OR GRANT NO.

6. PROJEC T NO

9a. ORIGINATOR'S REPORT NUMBER(S)

96. OTHER REPORT NO(S) (Any other numbers that may be assignedthis report)

10 DISTRIBUTION STATEMENT

Approved for public release; distribution unlimited.

II. SUPPLEMENTARY NOTES 12. SPONSO RING MILI TAR Y ACTIVITY

Naval Postgraduate SchoolMonterey, California 93940

13. ABSTRACT

A case study of a winter stratospheric warming in the westernhemisphere in January 1964 between 60° and 40 north latitudes wasconducted. Utilizing TIROS VII radiance data and analyzed heightfields, a stepwise regression equation was determined to specify lowerstratospheric layer temperatures. These temperatures were used withstandard atmospheric temperatures to construct a sounding for use in

a radiance computer program. Finally, this computed radiance wascompared to regression values to determine if prediction and study ofstratospheric warmings are valid and useful.

DD, NOV 68 I "T / >*J

S/N 0101 -807-681 1

PAGE I )

61Security Classification

A-31408

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Security Classification

key wo R OSLINK A

ROLELINK C

ROLE

Stratospheric Warming

Channel Radiance

Stratospheric layer temperatures

TIROS VII radiance data

DD ,

F

„r.,1473 (

S/N 0101-607-6321

BACK62

Security Classification A - 140a

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. IUDERY

ThesisG35c.l

.131315iauque

Calculation of lev-els of relative con-tribution of the car-bon-dioxide channelradiance f rom : TEROS -'

VII in the case. Ofa if

large-scale stfitt&rtYspheric warm^rttf^^YJanuary 1964? l TJDERY

Thes

G35c.l

131315Giaque

Calculation fo lev-els of relative con-tribution of the car-bon-dioxide channelradiance from TIROSVII in the case of a

large-scale strato-spheric warming in

January 1964.

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