A-1g567 DETERMINATION OF STABIIT FRTOM TEMPERATURE PROFILES II()NAVAL OCEANOGRAPHIC OFFICE NST STATION MS

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NATIONAL BUREAU OF STANDARDS 1 %3 A

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DE ERM INATIOOF STABILITY FROMTEMPERATURE PROFI LESRtoH rJ. Wahl 20A 2 ) DPhysical Ocean~oph Branch

OCAN MEASUREMNTS PROGRAM

AUGUST 19S2

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FOVThis report etplores the feasability of deriving profiles of

Brunt-Vaisala frequency from measurd tedperature profiles andregional temperature-salinity relationships. Detailed knowledgeof the Brunt-Vaisala frequency, which is the controlling factorfor internal waves, is critical in addressing Ocean MeasurementsProgram requirements for characterizing the upper ocean environ-ment. Analyses uti.lizing the techniques described herein forderiving Brunt-Vaisala frequency from XBT temperature profileswill be performed for areas of principal interest to the OceanMeasurements Program.

C. H. BASSMTCaptain, USKlCommanding Officer

NO

SECURITY CLASSIFICATION OF THIS PAGE f~hon Data EnIors___________________

REPORT DOCUMENTATION PAGE DtEAD COMPETING ORMIREPORT NUMBER 2.GOVT ACCESSION NO: 7. RECIPIENT'S CATALOG MUMuER

4. TITLE (Cid Subtitfl S. TYPE OF REPORT & PERIOD COVERED

Determination of Stability FromTemperature Profiles Technical Report

S. PERFORMING ORG0. REPORT MUMMER

7. AUTNOR(a) 0. O4TRACT OR GRANT MUMBER(s)

Robert J. Wahl

9. PERFORMING ORGANIZATION NAME AND ADDRESS 1.PROGRAM KLEMENT. PROJECT, TASK

Naval Oceanographic Office AE OKUI UMR

NSTL StationBay St. Louis, MS 39522

11. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATEAugust 1982IS. NUMBER OF PAGES

14. MONITORING AGENCY NAME & ADDRESS(If different from Controllingd Office) 1S. SECURITY CLASS. (of this report)

UNCLASS IFI EDIlsa. DEC ASI FICATION/ DOWNGRADING

16. DISTRIBUTION STATEMENT (of this Report)

Approved for public release; distribution unlimited

17. DISTRIBUTION STATEMENT (of the asract entered in Block 20, It different frea Report)

IS. SUPPLEMENTARY NOTES

Is. KEY WORDS (Comirno an, reverse side if necessary and Identify by block number)

Brunt-Vaisala Frequency, XBT, Temperature Profiles, T-S Diagrams, CTD,Vertical Stability, Sargasso Sea, Northeast Atlantic

20. ABSTRACT (Coniine an reverse side it noesamp and Idat5* b1 blea ole* Vertical profiles of Brunt-Vaisala (By) frequency derived from measured temp-erature and constructed salinity data were compared to BV frequency profilescalculated from CTD data. The salinity profiles were constructed usingaveraged CTD or historical data from relatively quiet and active areas. Themethods used in deriving salinity are based on: an averaged temperature-salinity relationship, pressure averaged salinity, and constant salinity pro-files. The quality of the derived BV frequency was found to depend on themethod used and amount of local variability.jDD Fjo~m 1473 EDITION OF 1 NOV es is ossoLsTa

S/N 0102. LF. 014- 6601 SECURITY CLASSIFICATION OF TMIS PAGE euVaeItr

Acknowledgements

The assistance of Dr. Thomas Kinder in reviewing this paperis gratefully acknowledged. Special thanks are extended to Dr.Ortwin von Zweck and William Teague. Their suggestions andcriticisms were most valuable and much appreciated. The illus-trations were prepared by Ms. Donna Waters, who also assembled thereport for publication. The final manuscript was typed by Ms.Donna Skipper.

Aaession ForNTIS GRA&I

DTIC TABUannounced r]

Justificatlon_

Distribution/

Availability Codes

Ava 1a --d /o_Dist I Special

A l. Inc-I- -OWN"-

CONTENTS

PAGE

INTRODUCTION 1

METHODS 2

DISCUSSION

A. Average T-S Method

B. Average S-Z Method

C. CS Method 5

D. Model Average T-S Method 6

COMPARISON OF METHODS 7

SUMMARY AND CONCLUSION 8

REFERENCES 10

. ________,

FIGURES

PAGE

Figure 1. CTD survey locations 11

Figure 2. T-S envelope consisting of 31 CTD 12stations from the Sargasso Sea

Figure 3. Average T-S method applied to cast 137 from the Sargasso Sea between 0 and200 meters for 31-station average

Figure 4. Average T-S method applied to cast 7 14from the Sargasso Sea between 200 and500 meters for 31-station average

Figure 5. Average T-S method applied to cast 7 15from the Sargasso Sea between 500 and1000 meters for 31-station average

Figure 6. T-S envelope consisting of 8 CTD 16stations from the Iceland-Faeroefrontal area

Figure 7. Average T-S method applied to cast 1714 from the Iceland-Faeroe frontalarea between 0 and 500 meters for 8-station average

Figure 8. Salinity profiles for 2 stations from 18the Iceland-Faeroe frontal area

Figure 9. Average Salinity method applied to 19cast 100 from the Iceland-Faeroefrontal area between 0 and 500 metersfor 2-station average

Figure 10. Average Salinity method applied to 20cast 101 from the Iceland-Faeroefrontal area between 0 and 500 metersfor 2-station average

Figure 11. T-S envelope consisting of 2 CTD 21stations from the Iceland-Faeroefrontal area

- VI. = , -- = .a = . - i ,.

PAGEFigure 12. Average T-S method applied to 22

cast 101 from the Iceland-Faeroe frontalarea between 0 and 500 meters for2 station average

Figure 13. Constant Salinity method applied 23to cast 84 from the Iceland-Faeroefrontal area between 0 and 700meters

Figure 14. Constant Salinity method applied to 24cast 101 from the Iceland-Faeroefrontal area between 0 and 500meters

Figure 15. Constant Salinity method applied to 25cast 89 from the Iceland-Faeroe areabetween 0 and 500 meters

Figure 16. Constant Salinity method applied 26to cast 7 from the Sargasso Seabetween 500 and 1000 meters

Figure 17. T-S envelope consisting of 35 T-S 27relationships from the GeneralizedDigital Environmental Model for thesummer season between 300-320N,710-74°W

Figure 18. Average T-S method applied to cast 7 28from the Sargasso Sea between 0 and200 meters for 35 model averagedprofiles

Figure 19. Average T-S method applied to cast 7 29from the Sargasso Sea between 200and 500 meters for 35 model averagedprofiles

Figure 20. Average T-S method applied to cast 7 30from the Sargasso Sea between 500 and1000 meters for 35 model averaged profiles

Figure 21. Mean BV frequency profile, mean error 31(N-Ne), and standard deviation of meanerror for 31 CTD stations from theSargasso Sea using the average T-Smethod

i__ I

PAGEFigure 22. Mean BV frequency profile, 32

mean error (N-Ne), and standarddeviation of mean error for 31 CTDstations from the Sargasso Sea usingthe average S-Z method

Figure 23. Mean BV frequency profile, mean 33error (N-Ne), and standard deviationof mean error for 31 CTD stations fromthe Sargasso Sea using the ConstantSalinity method

Figure 24. Mean BV frequency profile, mean error 34(N-Ne), and standard deviation of meanerror for 31 CTD stations from theSargasso Sea using the model averageT-S method

'viiN

L~..

INTRODUCTION

An important measure describing the structure of the ocean is

its vertical stability as expressed by the Brunt-Vaisala frequency

(N) profile. The derivation of these profiles requires a knowledge

of the vertical density profile which is calculated from temperature

and salinity measurements. If expendable bathythermograph (XBT)

temperature measurements could be used in combination with historical

data to estimate Brunt-Vaisala frequency profiles, a better

description of the water structure on shorter time scales or over

larger areas would be obtained.

A similar situation is encountered in the computation of

dynamic topographies from temperature data. Emery (1975) showed

that in regions dominated by a single water mass, or in regions

with very similar Temperature-Salinity (T-S) relationships,

dynamic heights can be estimated from XBT temperature profiles

using salinity values derived from average T-S relationships.

Wyrtki (1978) derived dynamic topographies directly from average

temperature-density relationships and XBT data, since temperature-

density curves have the advantage of being smoother than corresponding

T-S curves. Emery and O'Brien (1978) have shown that in regions

of multiple-valued T-S relationships salinity can be more accurately

inferred for the computation of dynamic heights from mean salinity-

depth curves.

Ae-

In this study several approaches for estimating vertical

stability of the water column from temperature profiles and

averaged in situ or historical salinity data are examined. Some

of these approaches are similar to those used for the computation

of dynamic heights with XBT data.

METHODS

Estimates of Brunt-Vaisala frequencies were calculated from

CTD (Conductivity, Temperature, and Depth) temperature data and

corresponding salinities inferred from averaged in situ CTD

measurements or historical data. These estimated Brunt-Valsala

frequencies were then compared to Brunt-Vaisala frequencies

calculated directly from the in situ CTD measurements.

Salinity profiles were inferred using three methods: average

temperature and salinity relations (average T-S method), average

salinity-depth profiles (average S-Z method), and constant salinity

profiles (CS method). All three methods were evaluated with data

from 31 CTD stations in the Sargasso Sea and 12 CTD stations in

the Iceland-Faeroe frontal area (figure 1). The CTD data consisted

of data at one-meter vertically-spaced intervals, low-pass filtered

with a half-power point at 10 meters. In addition, data from the

Naval Oceanographic Office Generalized Digital Environmental Model

(GDEM) (Colborn, Daubin, Hashimoto, and Ryan, 1980) for the

Sargasso Sea were also :lized ' the average T-S method.

"i ,*~1

In the average T-S method Brunt-Vaisala frequencies are estimated

from in situ CTD temperature measurements and salinity values

inferred from an average T-S relationship. Average T-S relationships

are derived from in situ temperature and salinity station data

ensemble averaged at one-meter depth intervals and also from GDEM

temperature and salinity profiles at standard National Oceanographic

Data Center (NODC) depths. The GDEM data are based on historical

temperature and salinity profiles and were obtained for a 30 by 30

minute quadrant on a seasonal basis.

In the average S-Z method, Brunt-Vaisala frequencies are

estimated using temperatures from an in situ CTD temperature

profile and corresponding salinities from an average salinity

profile. The average salinity profiles are formed by ensemble

averaging individual salinity profiles at one-meter depth intervals.

Finally, in the CS method, Brunt-Vaisala frequencies are

estimated from in situ CTD temperature measurements and a constant

salinity. The constant salinity value must be representative for

the area.

DISCUSSION

A. AVERAGE T-S METHOD

A prerequisite for accurate results in the use of the average

T-S method is a "tight" and "smooth" T-S envelope. In a tight T-S

envelope, the standard deviation in salinity is less than 0.1 ppt

, .3

(Emery, 1975). In a smooth T-S envelope derivatives of the individual

T-S curves are continuous.

CTD data from the 31 stations from the Sargasso Sea (Broome,

Hallock, Karpas, Mulher, and Teague, 1980) present a tight and

smooth T-S envelope at depths greater than 200 meters (figure 2).

High variability of temperature and salinity is found in the Lipper

200 meters. The single anamolous T-S curve is associated with an

eddy reported by Hallock, Teague, and Broome (1981).

Estimates of N to a depth of 1000 meters were calculated for a

representative station from the Sargasso Sea data and were compared

to N calculated from in situ temperature and salinities (figures

3-5). Overall agreement between estimated and in situ Brunt-

Vaisala frequencies were found in areas of reliable salinity

estimates or where temperature dominated density. Less reliable

salinity estimates were found at temperature inversions and

thermocline transitions.

In regions with high mesoscale variability in the temperature

and salinity structures, as encountered south of the Iceland-

Faeroe front (Teague, 1981), the T-S envelope may be tiqht, but

not smooth (figure 6). Salinity estimates from the average T-S

method are unreliable and result in poor agreement between the

estimated and in situ Brunt-Vaisala frequency profiles (figure 7).

B. AVERAGE S-Z METHOD

The average S-Z method provides good estimates of N where the

envelope of the in situ salinity profiles is tight, i.e. the

4

' a' w. .. ....... -"' . . .. __... .... . . .. _ . ' . . . ' l : °- " . . . . ."

standard deviation of salinity is less than .01 ppt. An envelope

formed by two salinity profiles from the Iceland-Faeroe frontal

area illustrates tightness below 300 meters (figure 8). For these

profiles good agreement between N and the estimates of N were found

in the surface layer where density is dominated by temperature, and

below 300 meters where good salinity estimates were found with the

average S-Z method (figures 9 and 10). Poor salinity estimates,

associated with positive temperature gradients between 70 and 300

meters, produced errors on the order to 2 cph in estimating Brunt-

Vaisala frequencies. Better estimates of salinity and Brunt-

Vaisala frequency were obtained with the average S-Z method (figure 8)

than from the average T-S method (figure 11) in depth ranges

associated with multiple-valued average T-S curves (figure 12).

C. CS METHOD

Constant salinity can be a viable method for the determination

of Brunt-Vaisala frequencies under strict conditions: small

salinity gradients in the absence of temperature inversions (figure 13),

or strong temperature gradients (figure 14). Compensating T-S

structures result in poor approximations of Brunt-Vaisala frequencies

such as are evident, for example, near the base of the mixed layer

shown in figure 15. The presence of a salinity gradient error will

cause an offset in estimating Brunt-Vaisala frequencies (figure 16).

5

&ohm

D. MODEL AVERAGE T-S METHOD

Environmental model data may be a useful resource for obtaining

an average T-S curve for the computation of Brunt-Vaisala frequencies

in areas where in situ salinity data are not available. Temperature

and salinity profiles were extracted from GDEM at locations closely

corresponding to the locations of the stations shown in figure 2.

The effect of long-term averaging, not evident in the in situ CTD

data, is evident in the broader model T-S envelope below the 18

degree isotherm (figure 17). The coarser vertically spaced seasonal

averaged GDEM data also yielded a smoother average T-S curve than

obtained from in situ data.

Reliable estimates of Brunt-Vaisala frequencies from the model

average T-S method were found in the upper 200 meters (figure 18).

Between 200 and 500 meters errors in the estimates of Brunt-

Vaisala frequencies approached the magnitude of in situ Brunt-

Vaisala frequencies, especially in the vicinity of poor salinity

estimates and temperature inversions (figure 19). Poor salinity

estimates in regions of highly variable T-S structure arise from

long-term averaging. Although the in situ T-S curve falls within

the bounds of the model T-S envelope, the in situ T-S curve

possesses a different slope from the model average T-S curve

between 500 and 1000 meters (figure 20). As a consequence the

estimates of Brunt-Vaisala frequencies are underestimated where

the slope of the estimated T-S relationship is less than the in

situ slope and overestimated where the estimated slope is greater

than the in situ slope.

_ _-B

COMPARISON OF METHODS

A comparison of the four methods is made using data from the

Sargasso Sea in an area exhibiting "tight" and "smooth" T-S

relationships. The mean Brunt-Vaisala frequency, mean error, and

standard deviation profiles were computed using the data collected

at the 31 CTD stations in the Sargasso Sea. Results are presented

for each method in figures (21-24). Mean N, mean error, and

standard deviation were filtered prior to plotting to suppress

wavelengths less than 10 meters for a clearer presentation.

As expected, the average T-S method produced the best estimates

of N for the Sargasso Sea data followed by model average T-S,

average S-Z and CS methods. The largest mean error and standard

deviation for all methods were found near the surface (about 1 cph

mean error and 1-2 cph standard deviation), where N is largest (max

N of approximately 13 cph), and near the top of the main thermocline

between 450 and 600 meters (about .5 cph mean error and 1 cph

standard deviation). The mean errors for all methods were similar

between 100 and 450 meters (0.0-0.2 cph); standard deviation ranged

from 0.2 cph (average T-S method) to 0.4 cph (average S-Z method).

Below 600 meters, the mean error ranged from 0.2 cph (average T-S

method) to 1.2 cph (average S-Z); the standard deviation ranged

from 0.2 cph (average T-S method) to 1.0 cph (CS Method).

I . .I I I . J

SUMMARY AND CONCLUSION

Various methods for estimating Brunt-Vaisala frequency profiles

from in situ temperature and inferred salinity have been examined.

Most accurate derivations of Brunt-Vaisala frequency profiles are

found when in situ salinity data are used in the methods. In many

circumstances, when in situ salinity data are not available, model

data may be a useful alternative. Estimates of N by all of the

above methods examined in this paper are acceptable under certain

conditions. All methods presented have problems with temperature

inversions and thermocline transition zones. Good estimates of N

by each method were found in regions of temperature dominated

density gradients.

The selection of an appropriate method of estimating Brunt-

Vaisala frequencies from XBT temperature profiles is based on the

T-S structure encountered in the area. If the T-S envelope is

"tight" and "smooth" the average T-S method yields good estimates

of Brunt-Vaisala frequencies. Areas characterized by tight, non-

smooth T-S envelopes may exhibit tight, structured envelopes of

salinity profiles. For these areas the average S-Z method will

give good estimates of N. The derivation of the average T-S

curves from model data results in a smoother curve than a curve

based on synoptic salinity temperature observations. Using model

data instead of in situ data for obtaining T-S relationships may

a _

result in greater uncertainties in estimating Brunt-Vaisala

frequencies. These uncertainties arise from long-term averaging,

highly variable spatial interpolation, and low vertical resolution.

For areas characterized by negligible salinity gradients, the

constant salinity method will yield good estimates of Brunt-

Vaisala frequencies; a selection of a nonrepresentative salinity

value will bias the estimates of Brunt-Vaisala frequencies.

The choice of the method for determining Brunt-Vaisala frequencies

depends upon the salinity structure characteristic of the area,

and ultimately on the available salinity data. In some regions, a

combination of methods may result in best estimates of Brunt-

Vaisala frequencies.

i I II I

REFERENCES

Broome, R. D., Z. R. Hallock, R. M. Karpas, F. F. Mulher, andW. J. Teague, CTD Profiles in the Western North AtlanticOcean August-October 1979, TN 7210-6-80, U. S. Naval Oceano-graphic Office, Bay St. Louis, MS, 1980.

Colborn, J. G., S. C. Daubin, Jr., E. Hashimoto, and F. J. Ryan,Evaluation of Standard Ocean Candidates, Report 922, Pacific-Sierra Research Corporation, 1980.

Emery, W. J., Dynamic Height from Temperature Profiles, J. ofPhysical Oceanography, 5, 369-375, 1975.

Emery, W. J., and A. O'Brien, Inferring Salinity from temperatureor depth for dynamic height computations in the North Pacific,Atmosphere-Ocean, 16(4), 348-366, 1978.

Hallock, Z. R., W. J. Teague, and R. D. Iroome, A deep, thick,isopycnal layer within an anticyclonic eddy, J. of PhysicalOceanography, 11, 1674-1677, 1981.

Teague, W. J., CTD Profiles in the Northeast Atlantic and NorwegianSea September-November 1980, Data Summary, U. S. NavalOceanographic Office, Bay St. Louis, MS, 1981.

Wyrtki, K., Monitoring the Strength of equatorial currents fromXBT sections and sea level, J. of Geophysics Res., 83(C4),1935-1940, 1978.

10

.- ,..i

OSURVEY AREA

Figure 1 CTD survey locations

SALINITY34.8 35.0 35.2 35.4 35.6 35.8 36.0 36.2 36.4 36.6 36.8

2581

26-

24-

22-

S20-

CLJ

16-

14-

12

10-

8-

Figure 2 T-S envelope consisting of 31 CTD stations from the Sargasso Sea

12

X< ESTIMATED SALINITY34 343 346 349 3 2 3f) 3.5 361 364 36 ? 37

SAL NI TY34 34 3 34 6 3,49 3'5 2 3, 3;3 e2 361i 36 4 367? 37

-o TEMPERATURE0 3 6 9 1U 15 le 21 24 27 3.

ESTI MATED N3 6 9 12 15 le -11 24 2?

, 3 6 9 12 11) i2 J1 J4 27

EST SAL- ,SAL

TEMP-

N /

ESTN

*113

... /

I 2,/

1< 7

Figure 3 Average T-S method applied to cast 7 from the Sargasso Seabetween 0 and 200 meters for 31-station average

_ _ _ 1

ESTIMATED SALINITY:3620 36 45 36-30 36.35 3640 3645 3650 3655 3660 36.65 3670

+ SALINITY36A0 3625 3630 .3636 364-0 3645 36.50 3655 .3660 3665 367?0

A TEMPERATURE17 V7.3 V 6 17.9 162a 186 18. 19.1 19.4 19.7 20

I I II IJ

0 ESTIMATED N0 1 2 3 4 5 6 7 9 10

I -I I I _j

O N0 1 2 3 4 5 6 7 a 9 10

200 I

N SAL

260 TEMP,..

290-. -,,,-EST N

320 ,j~EST SAL

410 -.

440

500-

530.

Figure 4 Average T-S method applied to cast 7 from the Sargauso Seabetween 200 and 500 meters for 31-station average

14

x ESTIMATED SALINITY336 338 *34.1 34.4 34.7 36 363 35.6 36.9 362 36.6II I I I I I I I I

+ SALINITY336 3Je 341 344 347 36 3.3 36.6 30.9 362 365I I I I I I I ,, I I I -

A TEMPERATURE0 2 4 6 e t0 12 14 16 18 20SIII I I I I I I

C ESTIMATED N0 1 2 3 4 5 6 ? 9 0

Q N0 1 2 3 4 5 6 7 e 9 10

500 I I I I I I

-EST N_ I5N TEMP

660 OZZSAk

7W EST SAL

850

900

950-

1000-

Figure 5 Average T-S method applied to cost 7 from the Sargasso Seabetween 500 and 1000 meters for 31 -station average

15

" - . - .... ..... . .- - . ... -..-- , i .:.E+_., -I- - ,' Z A. - -. , ,

SALINITY34.90 34.95 35.00 35.05 35.10 35.15 35.20 35.25 35.30 35.35 35.40

16-

14-

12-

UJ 10-

CL

S6-

0-

-2-

Figure 6 T-S envelope consisting of 8 CTD stations from theIceland-Faeroe frontal area

ESTI MATED SALI NI TY~. 3i~ 4 O 34% q-) Y)5 3151 Y1.30 3")25 3

'14 91 3" Or I I P3

SALINITYi-i e- 4 34 90 349' 3", 3AOf 3C) C 3"115 Y)_ Y 321) Y) 30

TEMPERATU. REe 9 11 It 12 13 14 15,

ESTI MATED N

-~3 6 9 12 11 le 21 24 2

_NN

LZZ .~-ESTNEST SAL-~

TEMPSAL>

C-0,

4 2I

450-

.ju00%

Figure 7 Average T-S method applied to cast 14 from the Iceland-Faeroefrontal area between 0 and 500 meters for 8-station average

SALINITY34.5 34.6 34.7 34.8 34.9 35.0 35,1 35.2 35.3 35.4 35.5

0*

100

200

300

400

L 500

L/)Lj 600

700

800

900

1000

1100

Figure 8 Salinity profiles for 2 stations from the Iceland-Faeroe frontal area

ESTIMATED SALINITY3.5 32. 331 33.4 337 34 34.3 34.6 349 352 35

' II ______ _____

SALINITY32.,S 32P 331 33.4 33.7 34 34 3 346 349 35 2 3)

______________ L J __ _-.. J

TEMPERATURE-1 0 1 3 4 6 7 V 9

I - J J .L....L. I I

ESTI MATED N-3 0 3 6 9 1 S le 1 44 2I IL I I I I I - I i I

r N-3 6 9 L2 S e 21 24 27

. I I I I I

Z EST N i EST SAL.-- 9 )

1001 -, _ .. SAL

- -- TEMP150 /

I-

P504 ';I

Figure 9 Average Salinity method applied to cast 100 from the Iceland-Faeroefrontal area between 0 and 500 meters for 2-station average

19l

ESTIMATED SALINITY321 32 E 33.1 33.4 337 34 34-3 346 349 3 2 3 ,

J- ~J I I I I 1 I

SALINITY32.I 328 331 34 33.7 34 34.3 346 349 3.)2 355

A TEMPERATURE-t 0 1 2 3 4 6 7 E 9

ESTIMATED N-3 0 3 6 9 12 IF I" 21 24 27

L , I _ _ _ _ 1 I I

-3 0 3 6 9 12 1 e 21 ?4 270- I I I I I I 4

:, ,SAL

.,EST N EST SAL"'!00 .... - ES A L j

" 0

S N-TEMP

3-101

/

41Figure 10 Average Salinity method applied to cast 101 from the Iceland-Foeroe

frontal area between 0 and 500 meters for 2-station average

20 -

0

SALINITY34.5 34.6 34.7 34.8 34.9 35.0 35.1 35.2 35.3 35.4 35.5

8 i iii I i I

7-

6

LJ 4

C", 3

ILJ2-

Ij..

-

0-

-1

-2

Figure 11 T-S envelope consisting of 2 CTD stations from the Iceland-Faeroe frontal area

21

x ESTIMATED SALINITY32 ' 32 E 331 334 337 34 343 346 349 Y) 2 3i

I IiI I *I.. .. ......... ......

+ SALINITY32A 32P 331 334 337 34 343 346 349 3 2 3Y

I I I I I

,3 TEMPERATURE-1 0 1 2 3 4 I 6 7 e 9I_ _ _ ______ ______ I I i__

ESTIMATED N-3 0 3 6 9 W2. 1 e 21 24 2?

I. I I I i I I _ j

Q, N-3 0 3 6 9 12 . I' 21 24 27

Ii I I I I I

0I

/

EST N--- 0--N---TEMP E.T..

"SAL I': - EST SA--

Ix250 /

400~

450

Figure 12 Average T-S method applied to cast 101 from the Iceland-Faeroe frontalarea between 0 and 500 meters for 2-station average

22

× ESTI MATED SALI NI TY325 32e 3.31 334 33? 34 34.3 34.6 34.9 362 36 5

+ SALINITY3X.6 32,8 3J1 3J4 337 34 343 34.6 349 362 36.AI 2 2 I i I I 2 1 .,2

A TEMPERATURE0 2 4 6 8 10 12 14 16 18 20

C ESTIMATED N-3 0 3 6 9 12 15 18 21 24 27| I 2 2 2,. I.,...,......1 2

C, N-3 0 3 6 9 12 16 18 21 24 2?

?0 2

-TEMP EST SALK AL

140

210

Z Pun..- EST N

420

40

'560

?00

Figure 13 Constant Salinity method applied to cast 84 from the Iceland-Faeroefrontal area between 0 and 700 meters

2S

ESTIMATED SALINITY3a5 328 33.1 33.4 33.7 34 34,3 34.8 349 35 2 366

I A A II I A

+ SALINITY3.;o 32,8 3.31 .33.4 33.7 34 34.3 34.6 34.9 352 355

I ' I I - _ i - - II

TEMPERATURE-1 0 1 2 3 4 5 6 7 8 9

I I I I I I t I I _

0 ESTI MATED N-3 0 3 6 9 12 15 18 21 24 27

D N-3 0 3 6 9 12 15 18 21 24 Z7

50 I

EST SAL

200 -

350I

24

ESTIMATED SALINITY32 32r .331 334 337 34 343 346 34 3,2 3"W

1- -- I - --- A _ I _A -

+ SALINITY32-" 32tk 3J31 .33. 337 34 343 346 34-1 3-2 T-

TEMPERATUREO 2 4 6 e to 12 14 16 le 201 __L .... L .dJ _ _J L A.. .

ESTIMATED N-3 0 3 6 9 12 115 18 ?.1 24 27I I 1 L J_ _ 1 _--____A. J

N-3 0 3 6 9 12 15 le 21 24 _n

I 0 I I

SAL-i

,) N -TEMP

I ---i -EST SAL-

:--1901 EST N, ..

300 -

31o]

400 -450

.i~c

Figure 15 Constant Salinity method applied to cost 89 from the lcelond-Foeroearea between 0 and 500 motors

25

ESTIMATED SALINITY33') 33e 34 L 344 347 3.1 3",.3 3" 3.)q 3"

t SALINITY33" 33l 341 34 4 347 .3 3"3 3'C( 3.9 362 36- _____J . . ... J ,1 1 1 -- J I . - -- 1

TEMPERATURE0 1 4 6 .0 1.2 14 16 I. e0

L _ _ .- _ _ _ __- ---- J

C ESTIMATED No 1 2 3 4 6 7 e. 9 10

0 1 4 3 4 ' 6 7 e9 1'3 0I I I I IIiI I

/ f I

--: :: . EST N EST SAL-

N-

600 - -!_.

TEMP -SAL

750

elio - -- --

900 :._1 .

91O '-- ., -

1000 - . -. .

1050o

Figure 16 Constant Salinity method applied to cast 7 from the Sargasso Seabetween 500 and 1000 meters

t ! __. " __ + .....+2

SALINITY34.8 35.0 35.2 35.4 35.6 35.5 36.0 36.2 36.4 36.6 3.

28-

26-*

24-

22-

u~20-

I--

CL

S16-

14-

12-

10-

Figure 17 T-S envelope consisting of 35 T-S relationships from theDigital Environmental Model for the summer season between30"-320N, 710-74OW

x ESTIMATED SALINITY34 34.3 346 349 3152 3tj 5 3k e 36 1 364 3( ? 37' 1 1I I L - L I I I+ SALI NIr

34 343 346 349 352 31 . 35 L 361 364 36? 3?I ! _ - k LI I -j

- TEMPERATURE0 3 6 9 12 1 1 21 24 2? 30I I I __ _ I 1

C ESTIMATED N-3 0 3 6 9 2 1% 1tL 21 24 ->7

' . J J I I

N-3 0 3 6 9 12 15 IF 41 24 270 II I I I

N

--------- \.__.......... .

2 1 0 - --------

'I

40- EST N

460 -

TEMP-..

180

eo EST SAL!

r 100 ,

120 I

0.

140 }IeQ I

200

Figure 18 Average T-S method applied to cast 7 from the Sargasso Sea between0 and 200 meters for 35 model' averaged profiles

"28..

,,,- .. .... .....;. . .... .. a.. .. . .. .. .. . k ..,AIL.-..-"

K< ESTIMATED SALINITY3620 362") 3630 3636 3640 3646 3650 3655 3660 3666 36701 I I I , - I - I I I

+ SALINITY3620 3621. 3630 3636 3640 3645 3650 36 56 3660 36615 3670

1 I I I I I I I

A TEMPERATURE17 173 176 V.9 162 1e,5 lee 191 194 t? 20

S1I I I I I 1 I I I

C ESTIMATED N0 1 a 3 4 5 6 e . 9 t0

tIII1I I I I

N0 1 a 3 4 5 6 7 e 9 t0200 ii I i l I

430 -SAL

_C -EST NTE P

260

ago " ESTSAL-,,

3'i0

410 -

440

1100~I/

530

Figure 19 Average T-S method applied to cast 7 from the Sargasso Sea between200 and 500 meters for 35 model averaged profiles

29

ESTIMATED SALINITY335 33.t 341 344 34.7 35 353 3')6 3.9 362 36.'i

I I I I I I

+ SALINITY336 33.8 34.1 34.4 34. 35 353 35.6 359 362 36.1

A TEMPERATUREo 2 4 6 e 10 12 14 16 e e

{ - I I I I I I I

C ESTIMATED N0 1 2 3 4 0 6 7 e. 9 10I I I I I I I

No 1 2 3 4 6 7 8 9 10.ioo I ii I I i i

~~~~0 -~ TEMP-

EST N60 - "'A

8d750

,-EST SAL900 -

9150 -

Figure 20 Average T-S method applied to cast 7 from the Sargasso Sea between500 and 1000 meters for 35 model averaged profiles

30

~~ ES N . -. '

t MEAN N PROFILE (CPH)0 2 4 6 e 10 12 14 16 e 20

- I I I I i I I I I

C MEAN ERROR (CPH)-16 -14 -12 -10 -8 -6 -4 -2 0 2 4

0 I

100

MEAN ERROR200 + STAN DARD

(""'MA NDEVIATION"MEAN N

400

Ion"

90 01

lc

Figure 21 Mean BV frequency profile, mean error (N-Ne), and standard deviationof mean error for 31 CTD stations from the Sargasso Sea using the

average T-S method

31

+ MEAN N PROFILE (CPH)o 2 4 6 e IC 12 14 16 18 20

C MEAN ERROR (CPH)-16 -14 -12 -10 -8 -6 -4 -2 0 2 4

0-

100

MEAN ERROR (±STANDARD

3000 -M E N ND EV IA TIO N

400

7 .00 -)

900

1000

Figure 22 Mean BV frequency profile, mean error (N-Ne), and standard deviationof mean error for 31 CTD stations from the Sargasso Sea using theaverage S-Z method

32

MEAN N PROFILE (CPH)0 . 6 e 10 123 14 16 IF 0z

C MEAN ERROR (CPH)16 -14 -12 -10 --e -6 -4 -2 0 2 4

(MEAN NMEAN ERRO3 0+ STA NDARD

DEVIATION

ix 500i

eoc

90101

100\ -

* Figure 23 Mean BV frequency profile, mean error (N-Ne), and standard deviationof mean error for 31 CTD stations from the Sargasso Sea using theConstant Salinity method

33

MEAN N PROFILE (CPH)o 2 4 6 a 10 12 14 16 18 20

0 MEAN ERROR (CPI-)-16 -14 -12 -10 -e -6 -4 -2 0 2 4

0

.DOC MEAN ERROR+STANDARD

,MEAN NDEVIATION300

4700

Ix oo

W900

1000

1100

Figure 24 Mean BV frequency profile, mean error (N-Ne), and standard deviationof mean error for 31 CTD stations from the Sargasso Sea using themodel average T-S method

34

DISTRIBUTION LIST

ASN, R, E&S 1CNO (OP-02, -21, -95, -952) 8COMNAVOCEANCOM 2CNR (Code 103T, 480) 2NI SC 1NORDA 2NRL 3NUSC 2NAVPGSCOL 2NFOIO 1DARPA 1DIRSSP (SP-202, -2025) 4OT IC 12APL/JHU (STE) 6NAVEASTOCEANCEN 1NAVOCEANCOMFAC Keflavi k 1