coherent dial measurement of range-resolved water vapor concentration

Coherent DIAL measurement of range-resolved water vaporconcentration

R. Michael Hardesty

A pulsed coherent CO2 lidar was employed to measure water vapor profiles by the differential absorption

lidar (DIAL) technique. Measurements were obtained to ranges of 10 km along horizontal paths and 6 km

when the lidar beam angle was elevated. Comparisons with nearby rawinsonde soundings showed fairly

good agreement, although a tendency for the lidar to overestimate relative to the sonde was observed.Uncertainties in the individual measurements were attributable primarily to speckle, quantum noise, andatmospheric nonstationarities. The DIAL data set was also used to obtain radial wind velocity measure-ments at ranges beyond the maximum range of the concentration measurement.

1. Introduction

Since 1981 the Wave Propagation Laboratory of theNational Oceanic and Atmospheric Administration hasoperated a pulsed coherent CO2 lidar system for remotemeasurements of winds1' 2 and aerosol backscattercoefficients34 in the troposphere and lower strato-sphere. By taking advantage of the sensitivity gainedby the use of heterodyne detection, measurements havebeen obtained from ranges exceeding 20 km using thenaturally occurring aerosol as a backscatter source.Such sensitivity is also potentially advantageous forrange-resolved differential absorption lidar (DIAL)measurements of atmospheric gaseous species concen-trations, especially in the X = 10.6-,um wavelength re-gion where quantum-noise limited operation is difficultto achieve using direct detection. To examine thisconcept, the NOAA lidar was operated in a coherentDIAL mode to estimate atmospheric water vapor pro-files. The choice of water vapor as the target specieswas a matter of convenience; the primary objective ofthe measurement program was to demonstrate thecapabilities of heterodyne detection in DIAL mea-surements employing CO2 lasers.

Because the wavelength region between 9 and 11 ,gmis particularly rich with respect to absorption lines ofvarious pollutants, such as ethylene, ammonia, ozone,perchloroethylene, trichloroethylene, and Freon 12,several groups have attempted DIAL measurementsusing incoherent CO2 lidar systems.5-9 Althoughtransmit pulse energies in some of these systems were

The author is with NOAA Environmental Research Laboratories,Wave Propagation Laboratory, Boulder, Colorado 80303.

Received 25 January 1984.

>1 J, maximum ranges attainable using aerosol targetswere typically in the 2-3-km range. Because of theexponential increase in total extinction with range,significantly extending the range capabilities of inco-herent CO2 DIAL systems probably necessitates sub-stantial increases in laser pulse energy. Employmentof coherent detection provides an alternative means ofincreasing the maximum range capability of such DIALsystems. One obvious potential application for suchsensitivity is battlefield detection of chemical agents,where one would like to detect the presence of a haz-ardous substance at as long a range as possible. Otherapplications might include pollution monitoring overmetropolitan areas where the maximum range wouldbe of the order of 20-30 km.

Since the detector current in a coherent system con-tains information on the amplitude and phase of thebackscattered radiation, the capability also exists tomeasure the wind velocity as well as the species con-centration. This could be a valuable asset on a battle-field since the rate of transport of the hazardous sub-stance toward the lidar could be monitored. Anotherapplication of combined species and velocity measure-ments might be measurement of atmospheric watervapor fluxes in and out of severe storms for use in en-trainment studies.

Although these potential applications provide goodreason to consider using coherent DIAL, the techniqueis not without its drawbacks. Coherent systems aretypically more sensitive to speckle and refractive-indexturbulence effects than direct detection systems are;hence, the advantage in mean SNR does not fullytranslate into improved measurement capability. Also,because coherent systems are more complex, their ad-vantages have to be fairly significant to justify the addedoperational effort they require.

1 August 1984 / Vol. 23, No. 15 / APPLIED OPTICS 2545

TransmitterPulse energyPulse durationPulse repetition frequencyFrequency control

TelescopeTypePrimary diameterFocal length

ReceiverDetectorLocal oscillatorBandwidthIntermediate frequency

Computer-controlled scanner2-axisPointing accuracy

100 mJNominal 2 psec10HzHybrid-TE configuration;

closed loop servo control

Off-axis paraboloid28 cm202 cm

HgCdTe photodiodeDischarge-excited CO 2 laser10 MHz20 MHz

0.10

In the experiments described, the NOAA lidar systemwas used to measure water vapor along both horizontaland slant paths. Because the lidar has been designedprimarily for measuring winds, certain system charac-teristics such as transmit pulse duration and wave-length-switching techniques were suboptimal for theDIAL measurements. Despite this, water profiles wereobtained to ranges of 10 km along horizontal paths and6 km along slant paths. To the best of our knowledge,these are the first range-resolved coherent DIAL mea-surements. Previous coherent measurements havebeen reported which used ground-based or airborne cwsystems 1 0 -1 2 or a ground-based pulsed lidar.13 Each ofthese systems, however, utilized returns from topogra-phical or retroreflective targets.

II. Experimental Method

The NOAA pulsed coherent CO2 lidar system hasbeen well described in previous works. '1 4 Systemspecifications are listed in Table I. The lidar employsa hybrid-TE configuration to produce pulses containing100 mJ of energy at a maximum pulse repetition fre-quency of 15 Hz. Nominal pulse duration is 2 usec,although 15% of the energy occurs in the pulse tailextending to 5 ,usec. Despite the fact that isolationbetween the lidar transmitter and receiver is 70 dB,some energy from the transmit pulse typically leaks intothe signal detector, causing it to saturate. The mini-mum range of the system is determined by the timerequired for the detector to come out of saturation, plusthe time for the pulse tail to propagate beyond the re-gion immediately in front of the lidar. A typical valuefor the minimum range is 1.6 km.

The lidar is grating tunable across most of the R andP lines of the 00°1-10°0 CO2 transition. Because thesystem employs heterodyne detection, the operatingwavelengths of both the TE laser transmitter and thereceiver local oscillator (LO) laser must be changed bymeans of diffraction gratings. At present, the gratingsmust be changed manually; 2 min is usually requiredto switch the frequency of both cavities.

During lidar operation the aerosol-backscatteredsignal is gathered by the system optics and directed ontothe HgCdTe photodiode, where it is optically mixedwith the radiation from the LO laser. To preserve thesign of the Doppler shift in the backscattered signal, theLO laser frequency is offset by 20 MHz from thetransmit frequency. Following preamplification andfiltering, the detector output signal is fed into a complexdemodulator, which removes the 20-MHz intermediatefrequency (IF) component, producing in-phase andquadrature signals at baseband. For DIAL measure-ments these signals were digitized at a 10-MHz rate for200 yusec following pulse transmission and stored onmagnetic tape. The total system bandwidth is 10 MHz,permitting Doppler shifts in the backscattered signalequivalent to radial wind velocities of as much as ±25m sec-'.

The R(20) line ( = 10.247 um) served as the ab-sorbing line, and the R(18) line ( = 10.260 Aum) as thereference for the DIAL water vapor measurements. Fordata collection the procedure employed was to samplereturns from 1000 shots on one line, tune the laser to theother line, and sample an additional 1000 shots. Toestimate uncertainties in the individual measurements,this sequence was usually repeated at least four times.Each complete DIAL measurement (both wavelengths)required 5-7 min.

The digitized data were processed off-line to obtainthe H20 concentration measurements as follows: First,the total power in the sampled signal for each pulse froma given range was estimated from

(1)

where 5R is the distance traveled by the pulse during theinterval bt between consecutive samples (R = 15.9 mwhen t = 100 nsec), c is the speed of light, and X(i3t)and Y(i5t) are the sampled sequences of the in-phaseand quadrature signals, respectively. Since the het-erodyne power estimate profile P(i6R) from a singleshot has large random uncertainties due to laser speckleand quantum noise,15 power profiles from each indi-vidual return were averaged over the entire 1000-pulsedata set. Signal fluctuations caused by noise andspeckle are independent from pulse to pulse; thus, theaveraging reduced the standard deviation in the meanpower estimate due to these quantities by a factor of1/-/00 - 0.031.

Other fluctuations typically exist in the backscatteredpower estimate which are not independent from pulseto pulse. Such fluctuations are caused primarily bytemporal changes in the extinction along the propaga-tion path between the lidar and the scattering volumeand by changes in the backscatter coefficient within thescattering volume itself. Using a CO2 lidar, Menyukand Killinger16 monitored these long-term fluctuationsin measurements of power backscattered from a harddiffuse surface. They showed that fluctuations of thisnature did not reduce as N-112 when multiple pulseswere averaged, as in the speckle case. Thus, althoughspeckle and noise dominate the single-pulse power es-

2546 APPLIED OPTICS / Vol. 23, No. 15 / 1 August 1984

Table I. NOAA Lldar System Parameters

POR) = X2 WR� + Y2 �2i�b R) ,� c c

timate uncertainty, the ultimate measurement uncer-tainty following multipulse averaging is often deter-mined by the magnitude of the atmosphere-dependentlong-term fluctuations. An analysis of both short- andlong-term signal statistics of aerosol-backscatteredpower estimates was also performed as part of the DIALstudy. Results of this analysis and a discussion of itssignificance relative to DIAL measurements are beingprepared as a separate paper.

The power-vs-range profiles calculated from Eq. (1)contain a bias due to the system noise power. An esti-mate of noise power was obtained by computing thetotal power in the detected signal from a distant rangeinterval (typically -30 km) where negligible backscat-tered energy was present. This method assumes thatthe noise power statistics remain stationary over the200-Iusec interval following pulse transmission. Ex-periments with the lidar have shown this assumptionto be reasonable.

The noise power estimate was subtracted from eachpoint in the range profile to produce an estimate ofbackscattered signal power vs range. The resultingprofile was then filtered using a finite-impulse-response(FIR) digital filter with an equivalent range resolutionof -500 m. This filter, which is approximately matchedto the spatial resolution of the return as determined bythe pulse duration, removed residual speckle- andnoise-induced fluctuations.

The mean water vapor concentration within themeasurement cell of length AR was calculated from

b(R) = 2K ln[iPa(R)] - ln[Pr(R)IJ, (2)

where

Pa (R -

Pa(R) =

Pa R +-)2

Pr (R -

r(R)=Pr R +

2

In Eq. (2), Km is the mean differential absorption crosssection within the measurement volume centered atrange R, and Pa (R) and Pr(R) are the range-filteredbackscattered power estimates on the absorbing [R (20)]and reference [R(18)] wavelengths. For convenience,the quantity i6R in Eq. (1) was replaced by R in Eq.(2).

As seen from Eq. (2), a key parameter in estimatingspecies concentration is the differential absorption crosssection Km. A number of factors can contribute to er-rors in specification of Km; these errors translate di-rectly into equivalent uncertainties in the concentrationestimate p(R). There is significant disagreement in theliterature among the measured and computed values forwater vapor absorption on the R (20) CO2 laser line.17-2 2

As seen from Table II, the absorption cross sectionsmeasured by various groups are greater than thosecomputed from the widely used AFGL absorption

Table 11. Water Vapor Absorption Cross Section on R(20) Laser LineCalculated from Reported Measurements

ConditionsSource (K) K(atm- cm-')

Schnell and Fischer17 360 Torr, 293 1.5 X 10-3Shumate et al. 18 760 Torr, 300 8.6 X 10-4Nordstrom et al. 9 760 Torr, 295.5 7.5 X 10-4Peterson et al.

20 760 Torr, 295.5 7.8 X 10-4Ryan et al.2 ' 760 Torr, 296 4.1 X 10-4McClatchey et al.

2 2 720 Torr, 292a 3.4 X 10-4 a

a Computed from AFGL model (1978 version).

model by factors of from 1.2 to 4. Also, since mostmeasurements to date have estimated absorption inapproximately standard conditions, the values of Kmcomputed from those results cannot, in general, be in-serted into Eq. (2) for water vapor profile measure-ments, but must be adjusted for the temperature andpressure within the remote scattering volume. Thus,specification of absorption cross section is effectivelya three-tiered problem, in which each of the followingmust be well characterized: the value Km in standardconditions, values of temperature and pressure alongthe measurement path, and a change in Km as a func-tion of temperature and pressure. Errors in any ofthese three estimate steps can cause potentially largeerrors in concentration estimates.

Since a majority of the absorption coefficients listedin Table II are close to a value K = 8.6 X 10-4 atm-1cm-l, we used that value for the R(20) absorption crosssection in standard conditions. The temperature de-pendence of the line can then be computed from23

K(T) = KTo ) (TT) exp 1.439E 'ITo TJJ (3)

where T is the temperature, K(TO) is the absorptioncross section in standard conditions, and E" is theground-state energy.

The absorption cross-section temperature depen-dence as predicted by Eq. (3) agrees closely with ex-perimental observations when the AFGL model valueof E" = 1557.8 cm-' is used in the expression.23 Thus,the AFGL model parameters yield good agreement withobservations in terms of temperature dependence but,as shown in Table II, rather poor agreement when ab-solute specification of the cross section is considered.We modified the AFGL model to correct for this dis-crepancy by reducing the separation between the CO2R (20) line center and the water vapor line center suchthat the model yielded a value for K at standard con-ditions consistent with our assumed value. The ratio-nale for such an adjustment comes from observationsby Shumate et al. 1 8 and Zuev2 4 that lack of precision inrelative frequency of line centers is a potential sourceof error in models that compute species absorption.Adjusting the value of Av in the AFGL model producedpredicted absorption cross-section estimates that agreewell with observed measurements of both absolute crosssection and temperature dependence.25

Because water vapor profiles were often measured to5.5-km heights, where atmospheric pressure is one-half


that of sea level, Eq. (3) must, in general, be modifiedto include narrowing of the linewidth due to reducedpressure. Given the temperature and pressure, theabsorption cross section on each line is estimatedfrom

K(Tp) = K(To po) (Tp)[-(Av) 2 + Ca2(To'po)]

a(To,po)[ir(Av)2 + a2(Tp)]

X exp [1.439E" ( 1 -1]

where a(Tp) is the collisional halfwidth given by

a(Tp) = a(Topo) (k) ( To)0-.

The AFGL model parameters were used for (Topo)and E" to compute K for both lines. Because K on theR(18) line is relatively small, no attempt was made tomodify the AFGL parameters to conform with obser-vations at that wavelength.

Figure 1 shows the estimated variation in R (20) ab-sorption cross section K vs temperature for threepressures, calculated by using K(Topo) = 8.6 X 10-4atm-' cm-' from Eq. (4). A strong temperature de-pendence is seen, as expected due to the rather highvalue of E". On the other hand, the predicted depen-dence of Km on pressure is almost nonexistent becauseof the assumed close proximity of the CO2 transmitwavelength to the center frequency of the water vaporline.

When vertical water vapor profiles are being esti-mated, obtaining appropriate values for temperatureand pressure to insert into Eq. (4) is generally not easy.In these measurements the U.S. standard atmospherewas used to estimate pressure vs height; typical pressuredeviations from the standard atmosphere producenegligible absorption coefficient errors.26 Tempera-tures were estimated from whatever sources wereavailable. In situ readings taken at the lidar site pro-vided the temperature data for the horizontal DIALmeasurements. When profile measurements were at-tempted, we used temperature data from rawinsondesoundings. Although some soundings were takenconcurrently with the lidar measurements, in general,the temperature data came from the National WeatherService (NWS) Denver sounding. Because of the spa-tial and temporal separations, the potential for tem-perature estimation errors existed for these measure-ments, especially in rapidly changing atmosphericconditions.

Ill. Results

The DIAL measurements were performed in the vi-cinity of Boulder, Colo., through the winter and springof 1983. Typically, the winter atmosphere along thefront range of the Rocky Mountains is extremely dry;mean absolute humidities range from 2 g/m3 at thesurface to 0.4 g/m3 at 500-mbar pressure (4 km aboveground level).27 Because of such low water vapor con-centrations aloft, measurements during winter monthswere performed with the lidar directed horizontally soas to maximize the water vapor encountered by the

0x

(4) E

0)

0.8k

0.6-

1.'I I

---- p = 0.85 atm.1.0p = u.7 atm.-- p=0.5atm. /

/~~~~~~~

0.4k-

I I I I I_ _

0.21-

240 250 260 270

Temp (K)

280 290 300

Fig. 1. Estimated variations in absorption cross section on the R(20)laser line vs temperature calculated from Eq. (4) for three

pressures.

5000 II3/23/83

14:30

500 R(l18)

)

- 50-

R(20)

2 4 6 8 10Range (km)

Fig. 2. Profiles of backscattered power at R(20) and R(18) wave-lengths for horizontal DIAL measurements made on 23 Mar. 1983.

beam. Horizontal measurements also permit the useof ground-based sensors to obtain necessary tempera-ture measurements (for absorption cross-section ad-justment) and water vapor comparison data.

One such horizontal measurement was performed on23 Mar. 1983. Figure 2 shows the 1000-pulse averagedpower vs range profiles for returns on the R(18) andR(20) laser lines. The differential absorption is ob-vious; the R(20) return is 17 dB down in power at the8-km range relative to the R (18) return. During thesemeasurements, the lidar was pointed west toward theRocky Mountain foothills. In this case, the return fromthe foothills is evident at -8-km range. For horizontalmeasurements where no obstruction was present, themaximum range was >10 km.


< l 9

I

1.0 _

lU

7.5EI- -I

a: -c +

<EL CCun

<EL

.2_

5.01-

2.5F-

2 4 6

Range (km)

Fig. 3. Ratios of backscattered power from two ran23 Mar. measurements.

0 - -- - I I

3/23/83 Individual--- -Mean8_

BAO Surfh

E06

4 -

C\

0

Range (km)

Fig. 4. Water vapor concentration estimates vs rameasurements. Long-dashed line shows mean con

sured at ground station -25 km awa

Two independent concentration measumade on 23 Mar. Figure 3 shows the rat:at both wavelengths calculated frompower-vs-range profiles. MeasurementFig. 3 was 1 km. The two measurementssonable consistency; the R (20) ratio was-lent to 4.1 dB/km) compared with 1.9 (eqtdB/km) for the R (18) measurement.

The two water vapor concentration (

shown in Fig. 4, along with the mean of Iand an in situ temporally averaged wabcentration measurement taken simultanBoulder Atmospheric Observatory (-2The two profiles agree reasonably well wmeasurement and with each other. Both'.show a slight increase in concentration

Although there are no data available for comparison toindicate whether this is real or the result of some mea-

3/83 surement artifact, the concentration might reasonablybe expected to increase toward the west as the beamcomes closer to the higher-elevation surface.

Since tropospheric moisture increased significantlyin May and June, DIAL measurements during these

_ months were taken with the lidar elevated at anglesranging from 00 to 900. For profiling purposes, verticalpointing provides the best maximum range capability;however, height resolution (equal to range resolution

_ times the sine of the elevation angle) is limited to 500m by the long transmit pulse. Approximately 75% ofthe total atmospheric water vapor usually exists withinthe first 2 km above the surface; therefore, we generally

8 10 ) lowered elevation angles to increase the vertical reso-lution of the measurements in that region.

Figure 5 shows 1000-pulse averaged backscatteredges vs range for power vs range profiles taken at R(20) and R(18)

wavelengths during the afternoon of 4 May 1983, withthe lidar pointing 200 above the horizontal. Becauseof a sharp backscatter discontinuity between the 1- and2-km range, the minimum measurement range on thisday was a rather large 2.5 km. Five measurements weretaken over a 50-min time interval. The measurementsexhibited good consistency, as shown in the profiles of

ice adjacent range-power measurement ratios calculatedfor each wavelength (Fig. 6). Since the R(18) ratio isrelatively constant, the decreasing R (20) ratio vs rangeis indicative of decreasing water vapor concentration.

A profile of K. necessary to convert the ratio profilesof Fig. 6 to concentration profiles was calculated usingthe temperature readings from the NWS Denver raw-insonde sounding at 4:00 p.m. The rawinsondesounding was taken -2 h after the DIAL measurements;horizontal separation between the rawinsonde site andthe lidar site was -50 km.

10

inge for 23 Mar.centration mea-Y.

rements wereio terms P(R)the filtered

cell length ins showed rea--2.6 (equiva-

divalent to 2.8

estimates arethe estimateser vapor con-eously at the5 km away).vith the pointDIAL profiles

with range.

5000

C,,C

CE>.

.n0

1.5 2.0Height AGL (km)

4 6- - ~~~~~~~~~

Range (km)

Fig. 5. Profiles of backscattered power for DIAL measurementsmade 4 May 1983 with lidar pointing 20° above horizontal.


I I

R(20) 3/2

R(1 8)

I.I

I I\uE X Xv?

8

7.51

cc5.0< -If5

2.5

"l1.0

4


6

2.5

8Range (km)

Fig. 6. Ratios of backscattered powers for four of the 4 May mea-surements. Measurement gate length was 1 km.

Figure 7 shows the estimated water vapor concen-tration profiles for the five individual measurements,as well as the mean profile. Also shown in Fig. 7 arewater vapor profiles calculated from the 6:00 a.m. and4:00 p.m. Denver soundings. As in the 23 Mar. data setthe individual measurements showed good internalagreement. Each indicated a water vapor concentra-tion that decreased rapidly between the 1.5- and 2-kmheight. Although indicating the same basic trend, thelidar-measured concentrations were higher than thosemeasured by both the morning and evening rawin-sondes. Comparisons with rawinsondes are of ques-tionable validity, especially when the spatial and tem-poral differences between the lidar and the sonde areconsidered. Typical uncertainties in the onboard dewpoint measurements yield an expected concentrationerror of 1-2 g/m3 in rawinsonde soundings,2 8 which isof the order of the observed lidar-sonde discrepancy.Because the two rawinsonde soundings agree rather wellhowever, it is more likely that the discrepancy seen inFig. 7 is indicative of either a measurement bias betweenthe sensor estimates and/or some effect of the spatialseparation. Additional measurements made duringJune seemed to confirm the apparent tendency for thelidar to overestimate concentration relative to therawinsonde. On two occasions lidar measurementswere compared with those from rawinsondes launchedimmediately adjacent to the lidar site. As in the 4 Maycomparison, the lidar concentration estimates werehigher than the rawinsonde measurements.

The five independent measurements shown in Fig.7 provide a limited data set to estimate uncertainty ina single concentration measurement. The standarddeviation of the individual measurement set is plottedin Fig. 8 as a function of range. Although the standarddeviation estimate is noisy because of the limited data

set, it shows that the variability among the measure-ments was -0.75 g/m3 or less out to a range of -6 km.This indicates quite good repeatability, considering thatthe on-line and off-line measurements were taken -2-3min apart.

Also plotted in Fig. 8 is the expected error due onlyto speckle and receiver noise effects, calculatedfrom2 6

8

0

0c., 0)Ir-

6

4

2

01 I I I 0.5 1.0 1.5 2.0 2.5

Height AGL (km)I l l2 4 6 8

Range (km)Fig. 7. Water vapor concentration profiles calculated from 4 Maymeasurements. The long-dashed line is the mean of the five indi-vidual measurements. Moisture readings from NWS rawinsondes

are plotted for comparison.

2.01

Fnl§)

1.51

1.0

.5

5/4/83

- -- -

1.0 1.5 2.0 2.

Height AGL (km)

I I I~~~~~~~~~~~~~~~4

Range (km)Fig. 8. Comparison of concentration measurement standard de-viation estimated from 4 May measurement set (solid line) with thepredicted standard deviation due only to speckle and quantum-noiseeffects (dashed line). Ringing in measured standard deviation is due

to effect of 0.5-km smoothing filter used in the data analysis.

5


5/4/83 ---- R(20)0= 200 - R(18)

i"I

I I

5/4/83 individualmean

-------- DEN rawinsonde 6 a.m.- - - DEN rawinsonde 4 p.m.-

onII

l

us - -

A _

l

514/83(O = 20°)

8

I I

R(l18)

.. ~13:30 -

R(20)13:19

2/4/83

I I I

I I

R (18)13:35

R(20) \13:43

2/4/83

I I I I

R(l 8) -R(l18)

,w- 13:59 * 14:02 -

13:51R - 1:16 -

2/4/83 2/4/83

I l I I I I I I2 4 6 8 10 2 4 6 8 10

Range (km)

Fig. 9. Sequence of measurement profiles showing growth and dis-sipation of apparent backscatter inhomogeneity at the 6-km range.

1 [ 1 2 1 \1 /0-b = 2mARN11 _+_ . + II (5)

2KmARN' 12 l Sm mc* SNR m SNRi '(

where N is the number of pulses averaged, SNR is themean signal power divided by mean noise power, i = 1,2refers to measurements on the R(20) and R(18) wave-lengths, respectively, and m, m, and mc are theequivalent number of independent samples of fluctu-ations due to speckle, detection noise, and a speckle Xnoise cross term given by

f Rf ()d T

Go R'2(-)R((T6dT

f Rt (T)d T

Mn = (6)

R"2(T)Rf (T)d-r

f Rf (r) d

L Rf(T)Rr(T)Rr(T)dT

In Eq. (6), R'(i-) and R' (r) are the normalized auto-covariance functions of the signal and noise compo-nents, and Rf (r) is the self-convolution of the digitaltemporal filter.

From Fig. 8, we see that the observed uncertainty of"0.75 g/m3 was approximately twice as large as the es-

timated speckle- and noise-induced uncertainty of -0.3g/m3 . This indicates that other sources of error becomesignificant over 1000-pulse averaging intervals. Themost probable source of additional uncertainty overthese intervals is atmospheric nonstationarity. Duringthe time required to change wavelengths, new volumesof air with potentially different backscatter and ex-

tinction properties are advected into the lidar beam. Incalculating concentration, Eq. (4) assumes that the ra-tios of backscatter coefficients at the two extremes ofthe range cell are equal and that differential backgroundabsorption by interfering species is negligible. Thecloseness of agreement between the observed uncer-tainty and the uncertainty attributable to speckle andnoise is one indication of the validity of that assumption.Generally, this incremental increase was within 1.0 g/m3

of the speckle- and noise-produced error, indicating thatatmospheric nonstationarity produced a relativelyminor effect.

Although a majority of the DIAL concentrationmeasurements were characterized by reasonably lowatmospheric variability, as in the 5 May measurementset, the potential effects of differential backscatter wereevident in measurements taken 4 Feb. 1983, with thelidar pointing horizontally. Figure 9 shows a sequenceof received power profiles encompassing -35 min. Alarge perturbation in the power profile at the 6-kmrange is obvious in the 13:59 R(18) measurement. Byfollowing the time sequence, one can clearly note theappearance and dissolution of the perturbation. Theperturbation first appears in the R(20) measurementat 13:43, reaches a maximum value at 13:59, then ap-pears to dissipate rapidly. The concentration mea-surement in this case was strongly affected by thetransient nature of this perturbation, which probablyresulted from an isolated region of strong backscatter.As noted earlier, errors result when the atmosphericbackscatter conditions change during the interval be-tween the measurements at the two wavelengths.Concentration measurements calculated from the dataof Fig. 9 showed large fluctuations in the region aroundthe 6-km range. This case was not typical of the ma-jority of the measurements, which, for the most part,showed consistencies more of the order of the 4 Maydata set.

An indication of the feasibility of making combinedspecies and wind velocity measurements can be ob-tained from Fig. 10, which plots mean radial velocityestimates derived from R (20) and R (18) returns in the4 May data set. The radial velocity from the R(18)returns is measurable to beyond 7 km, which is past thecutoff range for the DIAL measurements. Also plottedin Fig. 10 are the error bars for the single-pulse mea-surements. Whereas the DIAL measurements requiredaveraging 1000 pulses on each line to obtain measure-ments with reasonable uncertainty, velocity estimatesobtained from the R (18) returns were acceptable afteronly a single shot. Velocity measurements from theR(20) returns were much poorer at the longer rangesbecause of decreased signal strength. This illustratesthe relative difficulty in measuring concentration usinga system optimized for wind velocity measurements. Acombined DIAL/Doppler system would almost certainlyemploy wider bandwidth transmit pulses than theNOAA system to give better speckle averaging capa-bility for the DIAL measurement. Any resulting deg-radation in the single-pulse wind velocity estimate couldeasily be reduced by multiple-pulse averaging.


500

501

5us

C

E D

En6l.

5000

50C

50

5

-h( Xl All l w Quu

E

.62:0a)

:5L'a,co


4 I 66

88

Range (km)

Fig. 10. Mean and standard deviation of single-shot radial windspeed estimates calculated from R(20) and R(18) returns in 4 Maydata set. Observed differences in mean values for the two cases aredue primarily to atmospheric variability (measurements were sepa-

rated by 4 min).IV. Discussion

These results demonstrate the potential of coherentCO2 DIAL for range-resolved species concentrationmeasurements at longer ranges. Using a suboptimalsystem, we simultaneously measured water vapor con-centrations and radial wind velocities to horizontalranges beyond 10 km and to vertical heights ap-proaching 5.5-km ASL. The measurements, obtainedusing a transmit-pulse energy of 100 mJ, illustrate thesensitivity advantage of heterodyne detection in the X= 10.6-bum portion of the spectrum. Similar DIALexperiments employing direct detection resulted inmaximum ranges of 2-3 km despite the use of order ofmagnitude more powerful laser transmitters. 59 Atshorter ranges (2 km) direct detection is probablypreferable to heterodyne detection for DIAL measure-ments, since the systems are less complex and less sus-ceptible to speckle and turbulence effects. However,many potential species-monitoring applications, suchas detection of chemical-biological agents in a tacticalbattlefield environment, may require a longer rangecapability. Given that suitable absorption lines for thespecies of interest exist in the infrared, heterodyneDIAL techniques should be considered for such situa-tions.

Our measurement capability was ultimately limitedby lidar system operational parameters and by apparentuncertainty in the water vapor absorption cross sectionon the R (20) laser line. The long pulses produced bythe lidar transmitter limited the range resolution to-500 m. Since most of the interesting atmosphericwater vapor structure occurs within a few kilometers ofthe surface, use of shorter pulses would provide betterresolution over this region. Assuming energy was heldconstant, pulses could be shortened to 1 usec without

affecting the SNR of the backscattered returns.Shortening the pulse duration and reducing the energyin the tail of the pulse would also reduce the systemminimum range. The 1.6-km minimum range valuenecessitated directing the lidar at shallow elevationangles to obtain well-resolved vertical profiles near thesurface.

Although rawinsonde moisture measurements canhave fairly sizable measurement errors, the observationthat the lidar concentration measurements were con-sistently higher than those from the rawinsonde is astrong indication that a probable bias exists in the lidarestimate. The most probable sources of the apparentbias observed are uncertainties in the differential ab-sorption cross section and effects of the long lasertransmit pulse. As pointed out in a previous analysis,9the tail of the transmit pulse can, in some cases, causean apparent range offset in the estimated concentrationprofile. Thus, when concentration decreases withrange, as is usual in vertical measurements, the estimateat a given range may be higher than the actual value.Although this effect may explain some of the bias, the4 May moisture profiles do not exhibit sufficient gra-dient to account for the total error. Because of both thewide discrepancies in the values of experimentallymeasured R (20) absorption cross sections and the dif-ficulties in adequately estimating temperature, im-precise specification of Km in Eq. (2) must also beconsidered as a potential source of the bias. However,to determine more exactly the extent of the error dueto cross-section uncertainties, more extensive infor-mation describing the variation in Km as a function oftemperature and pressure is needed. Also worthwhilewould be an investigation of DIAL water vapor mea-surements at wavelengths where the absorption crosssection exhibits less temperature sensitivity. Onepossibility for the absorbed wavelength is the P(40) lineat X = 10.81 /im. Because the nearby water line hasone-half of the ground-state energy of the water linenear X = 10.247, its absorption cross section should beless temperature dependent. Operation on this linewould require less precision in the remote estimate oftemperature within the measurement volume.

A number of differential effects can also contributeto errors in DIAL measurements such as these. Be-cause the on-line and off-line measurements were nottaken simultaneously, the most significant error isprobably due to temporally changing backscattercoefficients vs range. The expression in Eq. (2) forcalculation of the concentration assumes that2 9

[ /3a(R) /3r(R) + ( - )AR °

L8,,(R AR)3r(R + AR) (7)

where (R) is the mean backscatter coefficient in thegate at range R, ;7 is the mean absorption coefficientacross the measurement volume due to backgroundgases, and the subscripts a and r indicate effects at theabsorbed and reference wavelengths, respectively. Incases such as that shown in Fig. 9, where the backscatterprofile apparently changes during the wavelength-switching interval, Eq. (7) does not hold, and errors are


introduced into the measurement. It is interesting tonote that the longer transmit pulses were generallyadvantageous in situations where significant back-scatter inhomogeneities were present. Long pulsesprovide effective spatial filtering of smaller-scalebackscatter inhomogeneities, such that for the most partonly inhomogeneities with scale sizes greater than theeffective pulse length have a serious effect on the mea-lsurement. The large fluctuating inhomogeneities seenin Fig. 9 were not typical of our data set; for the mostpart the R (18) and R (20) backscattered signal profilesshowed fairly consistent power profiles. More repre-sentative of our results were the generally low-leveloscillations in the concentration profile of Fig. 7; theyprobably resulted from small fluctuations in backscatterfrom measurement to measurement. Errors such asthese would tend to be unbiased and should not be aprimary cause for the apparent measurement bias in theconcentration estimates, The bias is also not likely tobe attributable to differential absorption by backgroundspecies. Simulations using the AFGL model indicatedthat biases caused by background gas absorption onthese wavelengths should not be sufficient to producethe observed result.

Measurements of radial wind profiles on either theR (20) or R (18) line had relatively low errors comparedwith the species measurements. The implication hereis that some changes in system design parameters toimprove DIAL capability, such as shortening thetransmit pulse and broadening its bandwidth, could bemade without seriously affecting the system's capabilityto make combined DIAL/Doppler measurements. Anyincrease in the single-pulse velocity measurement un-certainty as a result of such changes could easily bemade up by averaging over the multiple-pulse data setthat is required in coherent DIAL measurements.

This paper is based on one presented at the Second Topical Meetingon Coherent Laser Radar, Aspen, Colo., 1-4 Aug. 1983.

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The author gratefully acknowledges the assistance of L. A. Vohsand D. L. Davis in operation of the lidar during these experiments andof K. Schmitz for her help in reducing the data.


coherent dial measurement of range-resolved water vapor concentration

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