JOURNAL
OF GEOPHYSICAL
RESEARCH,
VOL. 97, NO. D1, PAGES 899-916, JANUARY
20, 1992
AtmosphericWater Vapor Measurements'Comparisonof Microwave
Radiometry and Lidar
MARTIN
N. ENGLAND •
lnterferometricsInc., Vienna, Virginia
R. A. F ERRARE
Universin'es
SpaceResearchAssociation,Washington,D.C.
S. H. MELFI
Laboratoryfor Atmospheres,NASA/GSF½,Greenbelt,Maryland
D. N. WHITEMAN, T. A. CLARK
Laboratoryfor TerrestrialPhysics,NASA/GSFC,Greenbelt,Maryland
The NASAJGSFC Crustal Dynamics Project microwavewater vapor radiometer 003) is evaluatedin terms
of measurements
of the integratedprecipitablewater vapor contentof a particular column of the troposphere.
The measurementswere taken during the AtmosphericMoisture IntercomparisonStudy (ATMIS) held at
Wallops Island, Virginia, during April 1989. Various water vapor sensinginstrumentswere used during
ATMIS, includingradiometers,radiosondes,and the NASA/GSFC Raman lidar. Comparisonsbetweenwater
vapor measurements
by the radiometerand the lidar yielded a correlationcoefficient of 0.998 and rms
differencesfor three nightsof -0.2+0.2 mm (April 11-12, 1989), -0.8-t-0.5 mm (April 16-17, 1989), and
-0.4+0.3 mm (April 17-18, 1989). The integratedprecipitablewater vapormeasurements
for thesethreenights
were approximately
5, 10, and21 mm, respectively.The first two periodshad clearmeteorological
conditions,
while cloudswere presentduringthe third period.The lidar resultsduringthe third periodare augmentedwith
radiosondemeasurementsabove the cloud base. This study shows that the radiometerprovides accurate,
continuousmeasurements
of the water vapor integratedthroughthe depthof the atmosphere.
1. INTRODUCTION
microwave radiometersto measure troposphericbrightness
temperaturesand from thesederive the integratedwater vapor
TheCrustal
Dynamics
Project
(CDP)
atNASA/Goddard
Spacecontent
ofthetroposphere
and
theassociated
"wet"
portion
ofthe
Flight Centerutilizesvery longbaselineinterferometry(VLBI) to
measure tectonic plate motions worldwide by observing
extragalacticradio sources(quasars)[Clark et al., 1985]. The
observedsignal electricalpath lengtherror due to tropospheric
constituents
is a major error sourcein measuringthe components
of an observingstation'sposition [e.g., Shapiro, 1976; Resch,
1980; Clark et al., 1985; Elgeredet at., 1991]. The extra signal
delayintroducedby the troposphere
is usuallyseparatedinto two
terms: the hydrostatic(or "dry") term and the "wet" term [Davis
et al., 1985]. The "wet" term is dominatedby the dipole
componentof the water vapor refractivity,while the "dry" term
is dominatedby 0 2 andN2andthe nondipolecomponent
of water
vapor refractivity.As a resultthe "dry" term can be estimated
from the barometric pressure. Profiles of meteorological
quantitiessuch as temperature,pressureand humidity can be
measuredin situ by radiosondes,and the water vapor content
delay.
The "fundamental" quantities produced by the J series
microwavewatervapor radiometer(WVR) are measurements
of
the line-of-sightbrightnesstemperaturesat three frequencies,
20.7, 22.2, and 31.4 GHz (wavelengths,X, of 1.45, 1.35, and
0.95 cm). The brightnesstemperaturesare converted into
opacitiesat these frequencies
andcombinedto produceestimates,
via the useof a retrievalalgorithm,of the integratedprecipitable
watervaporcontentof thatparticularcolumnof the atmosphere.
Becausethe performanceof the WVR in measuringthe absolute
brightnesstemperaturesis critical for subsequent
VLBI data
reduction, some method is needed to calibrate the absolute
performance
of the instrument.Sincecalibrationof the WVR in
the laboratoryunder "known" conditionsis not feasible,the
absolute performance must be calibrated by colocation
experiments
involvinga variety of techniques,
e.g., similarand
derived from these measurements. However, this method is differentdesignsof radiometers,radiosondes,
and Raman lidar
costlyandtime-consuming,
andthe pathof the ballooncannotbe systems.Variouscomparisons
havebeenmadebetweendifferent
controlled.
It iswellknown
thattheamount
ofwater
vapor
inthe types
ofinstruments
[e.g.,Elgered
etal., 1982;Heggti
etal.,
troposphere
is relatedto the thermalemission
nearthe 1987;Askne
etal.,1987'Westwater
etal.,1989].
Thebrightness
22.235 GHz (1.35 cm) spectralline [e.g. Dicke et al., 1946]. temperatureperformanceof the WVR can be investigated
by
Consequently,
the CDP is investigatingthe use of ground-based comparingdifferenttypes of radiometersand, by assuminga
watervaporemissionline model,by comparingwith radiosonde
data.The integratedwatervapormeasurements
canbe compared
•Now at ComputerSciences
Corporation.
with Ramanlidar measurements.
A comparisonbetweena Raman
Copyright1992by the AmericanGeophysical
Union.
lidar systemand a WVR hasbeenmadeby Askneet al. [1987]
during the Onsala Atmospheric Measurement (ONSAM)
experiment.However,dueto problemswiththisexperiment,the
Paper number91JD02384.
0148-0227/92/91JD-02384
$05.00
899
900
ENGLAND ET AL.: ATMOSPHERIC WATER VAPOR RADIOMETRY
numberand qualityof the humidityprofilesobtained
were IF/mixer,andthenoisediodeareconverted
to temperatures
via
limited,whichreducedtheusefulness
of theexperiment.
The lidar previouslydetermined
calibrationcoefficients.
signals
for theONSAMexperiment
werefairlycleanbetween
50 The watervaporspectral
line at 22.235 Ghz is ratherweak,
and550m, andthelarge-scale
correlation
between
theradiosondewhichimpliesthatradiation
emitted
bywatervapormolecules
at
profilesandthelidarprofileswasgoodwiththedifferences
being highaltitudeswill be only slightlyattenuated
whenit arrivesat
attributed
to a slowhumidity
detector
in theradiosonde
or to the thesurface
of theEarth,forall realistic
densities
of atmospheric
factthatthetwo instruments
measure
differentvolumes.
water vapor. A complication
is that liquidwater also emits
An opportunity
to compare.
the integrated
water vapor radiation
of comparable
or greaterintensities
thanthevaporat
measurements
fromtheCDPWVRJ03withthose
fromtheGSFC these
frequencies
(22GHz).However,
thetworadiation
processes
Raman lidar systemwas availableduring the Atmosphericexhibitdistinctlydifferentspectralfeatures[e.g. Beckerand
Moisture
Intercomparison
Study(ATMIS)heldatWallops
Island, Autler,1946;VanVleck,1947;Goldstein,
1951],andtheliquid
Virginia,fromApril 11, 1989,to April 18, 1989.Thelidarand contribution
canbe separated
fromthe vaporcontribution
by
WVR use completelyindependent'
techniques,
and thus an measuring
theemission
attwodifferentfrequencies.
Although
the
intercomparison
between
thetwowatervapormeasurements
could instrument
takesmeasurements
at threefrequencies
(20.7, 22.2,
give valuableinsightinto the performanceof the WVR, and31.4 GHz), onlymeasurements
at twofrequencies
(20.7 and
particularly
in estimating
themagnitude
of systematic
errorsinthe 31.4 GHz) areactuallyusedin thecalculation
of theintegrated
WVR system.
preeipitable
watervaporwiththehigherfrequency
contributing
mostto theestimate
of theliquidwatercomponent.
The choiceof
2. WATER
VAPOR
RADIOMETER
MEASUREMENTS
WVRSystem
frequencies
has beendiscussed
by numerous
authors[e.g.,
Westwater,
1967,1978;Resch,1983;Garyetal., 1985].Garyet
al. [1985]foundthattheadditionof measurements
fromthethird
frequency
channelat 22.2 GHz mayproducea slight(<7%)
Theradiometer
used
inthisexperiment
isa three
channel
improvement
intherms
performance
over
thetwo-frequency
microwave
instrument
operating
atfrequencies
around
thewaterapproach.
Thelower
frequency
used
inthecalculation
ofthe
vapor
spectral
linecentered
at22.235
GHz
(3,= 1.35
cm).
Theprecipitable
water
vapor
(20.7
GHz)
ispositioned
close
tothe
basic
design
ofthe
instrument
isdescribed
byJanssen
[1985].
Thecenter
ofthe
water
vapor
emission
line,
while
the
other
frequency
addition
ofa "hot"
load
tothesystem
has
greatly
improved
the(31.4GHz)is placed
wellawayfromthelinecenter.
system
calibration
andallows
better
gain
stability
during
periods
Measurements
atthisfrequency
(20.7GHz)
arebetter
correlated
when
themeteorological
conditions
arenotsuitable
forcalibration
withtheintegrated
water
vapor
than
aremeasurements
attheline
(discussed
below).
Theinstrument
is fullysteerable
in both center
[Westwater,
1967].
azimuthandelevation,allowingfull skycoverageto be obtained.
A blockdiagramof the microwave
package
andthecontrollingCalibration
hardwarefor the WVR systemas configuredfor the ATMIS
experiment
is shownin Figuresl a and lb. The incoming The basiccalibration
method
for the radiometer
is the "tip
radiationpasses
througha frequency
diplexerwhichsplitsthe curve"or elevation
scanmethod
witheachchannel
beingtreated
signalinto channels
1 and2 (20.7 and22.7 GHz) andchannel3 independently
[Resch,
1983;Hogget al., 1983].Tip curves
are
(31.4 GHz). The hotloadanda reference
loadarecoupled
into obtainedby measuring
the sky brightness
as a functionof
eachof the microwave
pathsby ferriteswitches,
allowingthe elevationangle(air mass).Sevensky measurements
between
waveguide
termination
to be switched
between
the skyandthe elevations
of 20* and 160' spacedin equalair massintervals
referenceand hot loads. The signal is mixed down tO an constitute
thedatafor a tip curve.A second,
orthogonal,
scan
intermediatefrequencywith a passband
of 40 - 200 MHz, follows
thefirstscan.Thedatafromthese
orthogonal
tipcurves
amplifiedanddetected
by a square-law
detector.Channels1 and were usedto solvefor the systemgain(G•,)
T andzenithopacity
2 sharethe samemicrowave
circuit,differingonlyin the Gunn (r•) foreachchannel
byperforming
a leastsquares
solution
to the
oscillator
usedin themixingstage.
Thesquare-law
detector
output equation
is amplifiedand converted
(usinga V/F counter)to a digital
Nan
t - N,•+ O• [T•.-T,,/+(T•-T•.)e
-'•]
(1)
signal,whichis passedto the dataacquisition
electronics
to be
logged
as "counts"
in thefielddatalog.An estimate
of the where
N• andNr•
/ areantenna
andreference
loadcounts;
T•,,,is
uncertainty
onthecountmeasurements
is alsologgedin thefield theeffective
radiating
temperature
oftheatmosphere,
T•/isthe
datalog.Eachlogged
measurement
utilizesfiverepetitions
of the reference
loadtemperature,
andT½
theextraterrestrial
background
switching
sequence.
Eachswitching
sequence
cyclesthrough
all temperature;
m is theair mass;and•',_is thezenithopacity.A
the requiredcombinactions
of the switches
with blankingtimes spherically
symmetric
model
witha 3-kmscaleheight
isassumed
inserted
where appropriate
to avoidswitching
transients
(details asthemeasurement
modelforthewettroposphere.
Thiscondition
aredescribed
byJanssen
[1985].Alsoincluded
witheachlogged is approximately
satisfied
duringperiodsof good,cloudless
measurement
is the outputfrom an analogto digital (A/D) weather.
If clouds
arepresent,
or if theatmosphere
is unsettled,
converter,
whichis dedicated
to measuring
thermistor
voltages
for or it is raining,thenthisapproximation
fails.The tip curve
temperature
monitoring,
powersupply
voltages,
andtheoutput method
issensitive
toanyinhomogeneities
intheatmosphere,
but
froma tilt sensor
usedfor automatically
referringtheelevationprovidedthattip curvesare carriedout at differentazimuthal
angleto localzenith[Janssen,
1985].Theuncertainty
on the angles
(generally
twoorthogonalazimuths),
these
inhomogeneities
count
measurements
isestimated
bydiscarding
thefirstrawdata canbedetected.
If theatmosphere
is veryinhomogeneous
(for
package
(toensure
all transients
andpointing
movements
have example,
whensignificant
quantities
of liquidwaterarepresent
ceased),averaging
the remaining
four measurements,
and incloudy
weather),
these
dataaredownweighted
inthecalibration
calculating
thestandard
deviationfor the fourmeasurements.
The procedure.
thermistor
voltages
monitoring
thehotandreference
loads,
the Thegaincalibration
is maintained
between
goodquality
tip
ENGLAND ET AL.' ATMOSPHERIC WATER VAPOR RADIOMETRY
31.4-
901
GHz
GUNN
OSCILLATOR
40-200MHz
/ FILTER
!
I•D•
QUARE
I I
LAW •--•
TO V/F
DC
AMPLIFIER
MI>:ER
•
TECTORI
[
IF
CHANNEL
B
AMPLIFIER
Ka-BANDAMB'IENT
I
TEMP I
FREQUENCY
DIPLEXER
AMBIENT
TEMP
LOAD1
K-BAND
I
__
DC
AMPLIFIER
ER•
40-200MHz
IF
-3(
TO V/F
CHANNEL
A
AMPLIFIER
,
INO LO^J
DIC
STEPPING
CONTROL
--
OSCILLATOR
t5
HYE
TEMPERATURES
IAZ IEL
MOTOR
o.
GUNN
MO'
22.2
GHz
GUNN
OSCILLATOR
RADIOMETER
VO LTAG ES
TILT
SENSOR
I
A/D
MOTOR
SYSTEM
COUNTER
RS252
COUNTER
M CROPROCESSOR
RS232
PERSONAL
COMPUTER
Fig.1. (a)Microwave
circuit
and(b)block
diagram
oftheJ-series
microwave
water
vapor
radiometer
103.
curves
andduringperiods
of inclement
weather
bycalculating
an The instrument
gainis calculated
usingthe hot andreference
instrument
gain
loadsaswaveguide
terminators.
Thehotloadis maintained
at a
temperatureof 376+0.02 K. The referenceload is inside the
G•-'[N•ø•-Nre't] (2)radiometer
enclosure,
which
istemperature
regulated
atabout
[T•-T,,el]
andforminga gainratio
310
+2K.Thereference
load
tracks
thediurnal
temperature
variation
butwithgreatlyreduced
amplitude.
r
R- G•
G•
The calibration scheme must accurately reproduce the tip
(3)calibration
during
times
when
the
tipcalibration
isvalid
and
must
bestable
enough
tomaintain
calibration
through
several
hours
of
by usingthesystem
gaincalculated
fromhighqualitytip curves. inclement
weather.A running
average
gainratio( <R >) aswell
902
ENGLAND
ET AL.' ATMOSPHERIC
WATER VAPOR RADIOMETRY
The calculation of these opacities from the brightness
asa runningaverageinstrument
gain( < G• > ) is maintained
to
reducethe randomuncertainty.The averageinstrumentgain is temperatures
usesan "effectivetemperature"
(T•) for the
atmospheric
emission
[Resch
et al., 1985].The siteandseasonal
updated
usinga weighting
factor,f, as follows:
(4)
where G• is the instantaneous
instrumentgainvalue and < G• >
variation
in Te/rof 4.5 K [Resch,1983;Reschet al., 1985]
contributes
about0.5 mm to the systematic
errorin theintegrated
watervapormeasurement,
a.lthough
thisbiaserrorwill change
from nightto night.
istheun-updated
average
instrument
gain.A shortcoming
ofthis Thepathdelay
duetowater
vapor
(PD,•t),
when
expressed
as
averaging
is thattheaverage
valuetends
to lagbehind
the a departure
fromthelong-term
siteaverage
andwhenthe
instantaneous
value.Asf increases,
thediscrepancy
between
the observables
arealsoexpressed
asdepartures
fromtheirlong-term
instantaneous
and averaged
values,A, decreases,
but the siteaverages,
isempirically
related
tothese
various
observables
uncertainty
intheinstrument
gainincreases.
by[Garyetal., 1985]
The averagegain ratio is updatedusinga differentweighting
factor,
g'
4
PD•,
a- (PDwet)
- • C•(Oi- (0•)),
-
g/e.
(9)
(5)
where< PD•> is thesitespecific
average
pathdelayandC•are
Sincethe gainratiois muchmorestablethanthe instrumentsitespecific
retrievalcoefficients.
Theobservables
Ol andO2 are
gain, the averagingconstant(g) can be muchless than the theopacitiesat20.7and31.4
GHz, respectively,
O3isthesurface
constantfor the instrumentgain •.
temperature
in Kelvin,and04 isthesurface
pressure
inmillibars.
The averagedquantitiesare the corresponding
site specific
To maintainthe calibrationrequirementof
Either of two setsof averages
(6) averagesfor theseobservables.
•
< 0.001,
( < Oi>) andretrievalcoefficients
(Ci) maybe usedto determine
thepathdelaydepending
upontheweatherconditions.
Onesetis
the weightingfactors(f andg) are chosensuchthatthe difference
(A) betweenthe instantaneous
andaveragedvaluesis lessthanthe
noise [Gipsonand Lundqvist,1986]. Using weightingfactorsof
f=0.1 andg=0.01 contributes0.3% to the systematic
error. This
amountsto 0.4 mm of precipitablewater vapor.
The line-of-sightbrightnesstemperaturesare givenby
valid for "clear" conditionsand the other is valid for "cloudy"
conditions.
GaryandKeihm[1986,privatecommunication,
1989]
suggest
usinga liquidburdencriterionfor determining
thesetof
coefficients
to be used.If the liquidburdenis lessthan 100/am
of precipitable
water,"clear"coefficients
shouldbe used.
The integratedprecipitablewater vapor content(PW in
centimeters
of precipitable
water)of the particularcolumnof
atmosphere
beingobserved
is empirically
relatedto thewetpath
delay by [Resch,1983]
whereNs• are the countsmeasured
by the radiometer
when
PDwee
PW (10)
lookingat thesky,N•f arethecounts
whenthereference
loadis
[5.6
0.022
(T- 308)]
thewaveguide
terminator,
Try!is thephysical
temperature
of the
reference
loadwaveguide
terminator,
and < O•w>is thesystem wherePD• is expressed
in centimeters
of pathdelayandT the
gain definedas
surfacetemperaturein Kelvin.
<%2-
x
(8)
Thesebrightness
temperatures
are convertedinto line-of-sight Data and Error Analysis
opacitiesfor usein the retrievalalgorithmto obtainthe "wet" Theobservation
sequence
for theWVR measurements
consisted
componentof the extra signaldelay due to the troposphere
and of two orthogonal
tip curvesinterspersed
with zenithline-of-sight
the integrated
precipitable
watervaporcontentof thatcolumnof (LOS)measurements.
Afterthesecond
tip curveandzenithLOS
the atmosphere.
measurement,
azimuthscansweredoneat elevations
of 30ø and,
occasionally,45 ø. Becausethe lidar exclusivelysamplesat the
PrecipitableWater
zenith, only the WVR zenithmeasurements
were considered
in
By usingvariousapproximations,
severalalgorithmscan be thisstudy,andconsequently,
theWVR datasetis notasdenseas
developedto
estimate
the "wet"delayandthewatervaporcontent the lidar data set. The observingsequencewas repeatedat
of theparticularcolumnof atmosphere
beingobserved
fromthe intervalsof about33 min. Because
eachtip curveproduces
an
WVR brightness
temperatures
[e.g., Resch,1983; Gary et al., estimateof the zenithopacity(and hencethe zenithbrightness
1985; Johanssonet al., 1987; Robinson,1988]. The modelthat temperature)for each frequency,the data consistof clumpsof
yieldsthepathdelayfromthe WVR measurements
is calledthe fourdatapoints(twotip andtwoLOS pointsspreadovera time
retrievalalgorithm.The retrievalalgorithmusedin thisstudywas rangeof about3.5 min)separated
by approximately
33 min. The
developed
by Gary et al. [1985] and Gary and Keihrn[1986, WVR datawereprocessed
to produce
clumps
of four(twotip and
privatecommunication,
1989]. The retrievalalgorithmusesan twoLOS)measurements
of theintegrated
precipitable
watervapor
archiveof atmospheric
(radiosonde)
profilesto calculatepath andtheirassociated
uncertainties.
Eachsetof fourmeasurements
delaysand all observables
for a site. Theseare then usedto was averagedto producea vapor measurement
approximately
calculate
the "average"
properties
andthedepartures
fromaverage every33 min. WVR datatakensimultaneously
withthelidarexist
for eachradiosonde.
The retrievalcoefficients
are computed
by for threenightsduringtheexperiment
period(April 11-12,April
a leastsquares
minimization
technique
involving
the covariance16-17,andApril 17-18,1989).Thechoice
of"clear"or "cloudy"
matricesof the observable
andpathdelaydepartures
fromtheir retrievalcoefficients
andaverages
wasdetermined
by examining
averages(see Westwater[1972] for detailsof the statisticalthelidarresultsfor cloudbaseheightandby visualexamination
procedure).
Theretrievalalgorithm
usesopacities
(tO calculatedof the prevailingmeteorological
conditions.
If the lidar results
fromthebrightness
temperatures
measured
.bytheWVR.
showed
significant
cloudcoverinthezenithdirection
(asindicated
ENGLAND ET AL.' ATMOSPHERIC WATER VAPOR RADIOMETRY
by no usablelidar dataabovea few kilometers),then "cloudy"
conditions
were deemedto exist(April 17-18) andthe coefficients
and averageswere chosenaccordingly.Gary and Keihm[1986,
private communication,
1989] suggestusing a liquid burden
criterionfor determining
the setof coefficients
to be used.If the
liquidburdenis lessthan 100ttmof precipitable
water, "clear"
903
The randomgain uncertainties
contributeapproximately
0.06 K
to theuncertainties
on thebrightness
temperatures.
Duringperiods
of goodweatherthebrightness
temperature
randomuncertainties
aretypicallylessthan0.5 K (seeFigure2 for an examplefrom
April 17, 1989).
The emissionmodeluncertainty
is an estimateof the uncertainty
coefficientsshouldbe used.However, becausethe radiosondedata introduced
by the retrievalalgorithmusedin gettingintegrated
usedin the derivationof the retrievalcoefficientsdo not provide
any direct indication of the presenceof liquid water, the
regressionanalysisfor the liquid water retrieval relies upon a
model for the distributionof liquid (clouds) derived from the
radiosonde
relativehumiditymeasurements.
Due to problemswith
the liquid water retrieval coefficients,the liquid burdencriterion
for choosingcoefficientswas not used. As a checkon the error
introducedby usingincorrectcoefficients,data from the period
determinedto be "cloudy" from the lidar results (April 17-18)
were processed, using both "clear" and "cloudy" sets of
watervapor(via variousemission
models)from the brightness
coefficients. The mean difference between the two determinations
"known"
temperaturemeasurements
at the two frequenciesused in this
study. Even though this is poorly understood, it is the best
estimateavailablefor the uncertaintyon the vapor measurements.
This uncertaintyis calculatedfollowingthe preceptsof Gary and
Keihm [1986, unpublishedmanuscript, 1989], who recommend
thatthe total uncertaintyconsistof a performanceexpectationand
an emissionmodel uncertainty.The performanceexpectationof
the algorithm takes into accountthe random uncertaintyin the
brightnesstemperature measurementand is equivalent to the
uncertainties
defined
above.
The
emission
model
of the precipitablewater vaporcontent("cloudy"minus"clear") uncertainty attempts to correct for the uncertaintiesin the
emissionmodelsof Rosenkranz[1988] (for oxygen)andLiebe and
was 0.2 mm of precipitablewater vapor.
Layton
[1987] (for vapor). In calculating the performance
The finaluncertaintyin theradiometricwatervaporestimates
is
composedof errors from a variety of sources' the "known" expectationthe Gary and Keih•n [1986, private communication,
uncertainties
in the measurements
of the WVR
antenna
1989] retrieval algorithm usesa brightnesstemperaturerandom
temperatures(brightnesstemperatures)and the emissionmodel uncertaintyof 0.5 K. Becausethe brightnesstemperaturerandom
uncertainty. The brightness temperature uncertaintieswere uncertaintiesfor this experimentare slightlylessthan 0.5 K, the
quotedby B. L. Gary and S. J. Keihm
calculatedby propagatingthe "known"uncertaintiesthroughthe performanceexpectations
reduction procedure and then including (in quadrature) the (private communication,1989) were used in the error analysis,
emission model uncertainty in the final result. The known giving a slight overestimateof the actualintegratedwater vapor
uncertainties are the uncertainties in the count measurements for
random uncertainty.
Gary and Keihm [1986] suggest a total emission model
sky, referenceload, and hot loadmeasurements
that are recorded
in the field data log. These can be compared with their uncertainty of about 8 % of the retrieved parameter. This
characteristicvalues as a quality control check. Characteristic contributesfrom 0.4 mm (April 11-12) to 1.7 mm (April 17-18)
standard
errorsfor theseparameters
werecalculatedfromthe long to the systematicuncertaintyin the integratedwater vapor results.
term behaviorof the parameters.Thesecharacteristic
uncertainties However, recent estimates for the actual uncertainties in the
(a) are tabulated in Table 1 for both count parametersand emission models have been made by Davis et al. [1985] and
physicaltemperatureparameters.Also listed in Table 1 are the Elgered et al. [1991]. Elgered et al. [19911 estimatethat the
contributionsto the uncertainties
on the brightnesstemperatures uncertainty for the water vapor emission model is about 6%
(using equation (7)). The logged uncertaintiesfor the count (0.3 mm of precipitablewatervapor for April 11-12, 0.6 mm for
April 16-17, and 1.2 mm for April 17-18). The uncertaintyfor
measurementsare typically about 4 - 10 counts (0.1 - 0.3 K
uncertaintyin the brightnesstemperature),which comparewell the oxygenemissionmodelis estimatedto be lessthan0.4 mm of
precipitablevapor. Elgered et al. [1991] also notethat if the size
with
the characteristic
values in Table
1. Characteristic
uncertaintiesfor the physical temperaturemeasurementsare of the liquid dropsbecomescomparableto the wavelengthof the
radiation, the algorithm over estimatesthe vapor. However,
+_ 0.02 K for the hot load and _+ 0.18 K for the reference load
experiencehas shown that in these cases (rain) the WVR is
measurements.
Propagatingtheseuncertaintiesthroughthe analysisgives the ineffectivefor calculatingthe water vapor. In fact, any moisture
randomuncertainties
on the gainsandthe brightnesstemperatures. (such as dew or rain) on the mirror flat or the Teflon window
coveringthe microwavehorn completelyinvalidatesthe WVR
TABLE
Hot load
1. Characteristics:
WVR
J03
data.
The total uncertaintiesfor the individual WVR precipitable
water vapor measurements
(Table 2) range from 0.9 mm for
cloud-free conditions (April 11-12) to 1.9 mm for cloudy
conditions
(April 17-18). Theseuncertainties
canbe separated
into
Channel
o
bo(T•, K
1,2
0.019 K
0.08
3
0.011 K
0.05
1,2
0.18 K
0.18
from systematicerrors in the effective temperatureand gain
0.17K
0.17
calibrations
contributions
are tabulatedin Table 2. The corresponding
random
errorsrange from 0.4 mm to 1.3 mm.
random and bias errors.
Referenceload
3
Hot counts
1,2
6 cts
0.09
3
6 cts
0.09
1,2
5 cts
0.20
3
5 cts
0.20
Sky counts
4-10 cts
0.2-0.4
to the bias errors come
and from the emission model uncertainties.
3. RAMAN LIDAR
Referencecounts
Contributions
These
MOISTURE MEASUREMENTS
Lidar System
The lidar systemusedin the investigation
hasbeendescribedby
Melfi and Whiteman[19851andMel.fiet al. [19891. Whitemanet
904
ENGLAND ET AL.' ATMOSPHERIC WATER VAPOR RADIOMETR¾
18.0
I
I
I
I
I
+
2_0.7
17.
165
GHz
I !
I
16.0
15.5
15.0
I
-? 145
14.0
31.4
000
GHz
2'00
4'00
6'00
@'00
17 Apr,
[UT]
Fig.2. Zenith
skybrightness
temperatures
at20.7and31.4GHzmeasured
bytheWVRatWallops
Island,
Virginia,
forApril
17, 1989.The errorbarsrepresent
therandomuncertainties
onthemeasurements.
al. [1991] give a morecompletedescription
of the systemand wavelength of 355 nm. A 0.75-m diameter Dall-Kirkham
measurementproceduresthat were used during the ATMIS
experiment.
telescopecollectsthe scatteredlaser light (as the laser pulse
propagatesthroughthe atmosphere),which beam splittersdivide
A blockdiagramof the lidar instrument
is givenin Figure3. into three channels'one sensitiveto Raman scatteringby water
The lidar consists
of a Nd:YAG laseroperatingat the tripled vapor moleculesat 408 nm, a second sensitiveto Raman
scatteringby nitrogen at 387 nm, and the third sensitiveto
scatteringby moleculesand aerosolsat the laser wavelength
TABLE2. WVR Integrated
WaterVaporMeasurements
in Millimeters (355 nm). Interference filters select these Raman wavelengths.
Photomultiplier
tubes(PMTs) detectthe backscattered
radiation
Uncertainties
in each of the three channelsand provide outputsignalsto both
Date
April11-12April16-17April17-18 A/D convertersand photoncounters(PCs). The A/D data are
,
Totalprecipitable
vapor(WVR)
Randomerror
5
10
21
0.4
0.4
1.3
Emissionmodel(WV)'
0.3
0.6
1.2
Emissionmodel(O0'
0.4
0.4
0.4
Gain calibration
0.4
0.4
0.4
T• calibration
0.5
0.5
0.5
Total systematic
0.8
0.9
1.4
Total error (WVR)
0.9
1.0
1.9
Systemaicerror
FromElgered et al. [1991]
smoothed
from
their
maximum
altitude
resolution
of
30 m
(200 ns) to a resolutionof approximately100 m usinga "nearly
equal ripple" low-passfilter [Kaiser and Reed, 1977]. The Pcs
providean altituderesolutionof 150 m. From nearthe surfaceto
an altitudeof approximately2 km, A/D dataare generallyused,
with PC data being usedabovethis altitude.The PC datatend to
be of higherqualitybut cannotbe usedbelow2 km becausethe
highatmospheric
backscatter
intensityfrom shortrangesleadsto
PC saturation.Signalsfrom approximately1000 laser shotsare
collected,after which the accumulatedsignalsacquiredby the
A/Ds and PCs are storedon magneticdisk. The sum of the
squaresof the A/D dataare alsostoredin orderto computethe
standard error of the A/D data. The standard errors for the PC
data are estimatedassumingPoissonstatistics(i.e., the noise
equalsthe squareroot of the total numberof events).
ENGLANDET AL.: ATMOSPHERICWATER VAPORRADIOMETRY
'
905
CAMAC
Crate i
.75 M DalI-Kilkham
.dtiRecorders
!-.I,II
Telescope
--[
Nd:
YAG
Laser
Iw:•J••
III
II1
i,l•11
ISN
i Z[•"li'ng
II!1
I-1 Cir(:t,il,y
I) 111
,
W = H20 PMT
N = N2 PMT
i
A = Aerosol
Disk• • Computer Real
Time
••I • Vector
!
19-Track
Gr•!•l•ics
Display
I Tape
•lCøprøcessør
PMT
FS = Field Stop
CL- Collimating Lens
BS = Beamsplitter
FL--- Field Lel•s
SN = Snubber
Fig. 3. Block diagramof the water vaporRamanlidar system."Discs"refersto the discriminators.
Theory
three separateradiosondesensorpackages,were launchedeach
As shownby Melfi [1972], the ratio of Ramanscatteringby
watervaporin the atmosphere
to thatby nitrogenis proportional
to the value of the atmosphericwater vapor mixing ratio. The
watervapor mixingratio is the massof watervapordividedby
the massof dry air in a givenvolume.A smallcorrectionto the
nightin orderto comparethe temperatureand humidity-sensing
calculated ratio is made which takes into account differential
atmosphericattenuationat the two Raman wavelengths.Under
clearatmospheric
conditions
thiscorrectionis lessthan5% at an
altitude of 7 km and is smaller at lower altitudes. The actual
amount of this attenuation correction is estimated from data
elementsof eachpackage.The PC data were calibratedwith the
radiosondepackages,sincethe PC data generallyhave a higher
signal/noiseratio than the A/D data. Sincethe A/D and PC data
both include the altitudesbetween2 and 6 km, the A/D data were
then calibratedusingthe PC calibrationas well as the radiosonde
comparisons.Each balloontook about20 min to ascendto 6 km;
thereforethe lidar PC datawere averagedover this20-minperiod
to reduce the random error in the lidar data. (Since there was
little changein the meteorological
conditionsduringthe course,
acquiredfromthelidaraerosolchannel,whichrecordsthesignal the uncertaintyintroduced by this 20-min averaging was
backscattered
at the laser wavelength(355 nm).
insignificant.)Radiosonde
mixingratioscorresponding
to relative
Scatteringdue to atmospheric
aerosolscan be analyzedin an humidities less than 20% were not used in the lidar calibration,
analogousmannerto that for water vapor. The lidar aerosol because
two of the threeradiosonde
packages
havepreviouslynot
channeldata are sensitiveto scatteringby moleculesand Mie providedreliablemoisturemeasurements
belowthis value [Melfi
scattering
by aerosols.SinceMie scatteringincreases
abruptly et al., 1989; Wade and Wolfe, 1989]. A proceduredesignedto
when the laserbeamencounters
a cloud, the cloudbaseheightis compensate
for any smallchangesin channelsensitivitywasused
easily determinedfrom the aerosolscatteringratio profile. to maintain a constantsystem calibration during the ATMIS
However,becauseof thisgreatlyenhancedMie scattering,clouds experiment[Whitemanet al., 1991].
rapidlyattenuate
thelaserlight, sothatthe watervaporretrieval During the sevennightsthe lidar was operatingtherewere 43
is confined to altitudes below cloud base.
individualcomparisons
betweenthe lidar and radiosondemixing
ratios; these comparisonswere obtained from 15 radiosonde
Calibration
launches(on two of the launchesone of the sensorpackages
The water vapor mixingratio is proportionalto the ratio of failed). Over the first five nights,whichincluded10 balloonswith
Ramanscattering
by watervaporto Ramanscattering
by nitrogen. 29 radiosondecomparisons,the standarddeviationof the meanof
The calibrationconstantrelatingthe measuredlidar ratio to the the lidar calibrationconstantwas slightlygreaterthan 1%. Thus
watervapormixingratiois determined
by computing
a weighted the lidar was able to maintaina single calibrationvalue with
least squaresregressionof the lidar ratiosto the water vapor excellentstability.After the fifth nightsomeminor changesto the
recalibratingthe
mixingratiosobtainedfromcoincident
radiosonde
measurements. transmitteropticsand electronicsnecessitated
This regression
yieldsa singlecalibrationconstantrelatingthe lidar data. During the lasttwo nightsthe standarddeviationof the
lidar ratiosto the watervapormixingratios.The lidar ratioswere meanof the lidar calibrationconstantwasapproximately3 % from
calibrated
usingtheradiosondes
launched
at WallopsIslandduring 5 balloonswith 14 radiosondeintercomparisons.
A comparisonbetweenthe lidar mixing ratiosderivedwith the
the ATMIS experiment.Three or four balloons,each carrying
906
ENGLAND ET AL.' ATMOSPHERIC WATER VAPOR RADIOMETRY
7000
-
6000
LIDAR
+ VAISALA
* AIFI
5000
x VIZ
o 20
•
%
RH
4000.
.__
__
<
3000.
2000.
1000.
1.0
2,0
3,0
4,0
5.0
Mixing Ratio (g/kg)
Fig.4. Watervapormixingratioprofiles
measured
using
thelidarsystem
andtheVAISALA,AIR, andVIZ radiosonde
packages
ona balloon
launched
onApril 17, 1989,at 0455UT at Wallops
Island,Virginia.Forcomparison,
mixingratioscorresponding
to a constant
20% relativehumidityarealsoshown.The symbols
onlyidentifythedifferentradiosonde
profilesanddo not
represent
theactualmeasurements.
Representative
errorbarsare shownfor thelidarprofile.
constant
system
calibration
andthemixingratiosmeasured
by the PrecipitableWater
variousradiosonde
sensors
is shownin Figure4. The datain the
theintegrated
watervaporcontent,the A/D
figurewereacquiredduringthe earlyhoursof April 17, 1989. Beforecomputing
mixingratioprofilesweremergedto givea
The balloon was launchedat 0455 UT, and the lidar data were andPC calibrated
from about100 m to approximately
acquiredover a 20-minperiodaIter the balloonlaunch.The data singleproffieextending
in Figure4 indicate
thatfromthesurface
to about2 km andagain 6.75 km or cloud base (if the cloud base was lower than
from 4 km to 7 km all four moisturemeasurements
agreeto 6.75 km). For a 2-minaveragethistopaltitudewaschosen,since
to about 10% randomerror in the lidar data. The
approximately + 5%. Note the error bars on the lidar data it corresponds
where'"'t'h8
A/D andPCdataprofiles
weremerged
is
indicatea standard
error of about+ 5% below2 km andabout altitude
chosen
at
the
lowest
altitude
where
the
PC
data
are
not
saturated;
+ 0.1 g/kg above4 km. Mixing ratios corresponding
to a
this generallyoccursbetween1.5 and2.0 km. Thusthe A/D data
constant
20% relativehumidityarealsoshown.Thedisagreement
amongthe sensorsfor altitudesbetween2 and 4 km is due to the
were usedfrom about100 m to this transitionaltitude,while the
differentradiosonde
sensors
and calibration
procedures.
In this PC dataw•ereused.abovethetransitionaltitude.
water,PW(in millimeters),
iscomputed
using
the
altituderegiontheVIZ andAIR sensors
bothindicate
a mixing Preeipitable
followingequation[Haitiher and Martin, 1957]:
ratioof abouti g/kg, whichis slightlylessthana mixingratio
eorrespondingto
20% relativehumidity.Bothof thesesondes
use
carbonhygristors
with similarcalibration
procedures
whichlimit
g 1000
+w(P
•)
sensitivityfor relativehumiditiesless than 20% [Brousaides,
1975]. The VAISALA sensorusesa capacitive
devicewith a whereg is the acceleration
dueto gravity,p is the pressure(in
different calibrationprocedurewhich apparentlymaintains millibars),andw(P)is thewatervapormixingratio(in gramsper
sensitivity
evenfor very dry atmospheric
conditions,
as shownin kilogram). Sincethe mixing ratios derivedfrom the lidar data
Figure 4. The lidar, on the otherhand,indicatesan intermediate werecomputed
as a functionof altituderatherthanpressure,the
level of moisturein thisaltituderegion.
radiosonde
pressures
werelogarithmically
interpolated
to thelidar
,,,w-.-o.•
• w(•,')
,/•,; (•)
ENGLAND
ET AL.'
ATMOSPHERIC
WATER
VAPOR
RADIOMETRY
907
I
II
'5
n ,4.0 (a)
I
2'00
I
4'00
I
I
B'00
8'00
I
I
I
B.OO
8.QQ
•2 Apn, •989
(UT)
d2.5
I
12105
11
•_ 11.0-
I
iiI
10.5
oo 10.0
9.5
--
g.o
.__
.__
Q)
8.5-
8.0
(b]
7•:00
17 Apr, 1BSB
I
2.oo
4'OO
(UT)
Fig. 5. Integratedprecipitablewater vapor(in millimeters)from lidar (circles)andWVR (stars)measurements
at WallopsIsland,
Virginia, for (a) April 11-12, 1989, (b) April 16-17, 1989, and(c) April 17-18, 1989. The WVR measurements
are connected
by the line. The error bars representthe randomuncertaintyon the measurements.
altitudesbeforeusing this equation.The altitudeincrementused estimates
were computedfrom 30-minaveragelidar mixingratio
for the lidar datais 150 m which corresponds
to the spacingof profilesas well asthe 2-min averageprofilesin order to directly
the PC data. Sincethe altitudeof the lowestlidar-derivedmixing comparewith the precipitablewater values obtainedfrom the
ratio value is about 100 m, the surface mixing ratio was microwave radiometer(WVR)measurements. The lidar-derived
interpolated
in time fromthe radiosonde
data.Precipitable
water precipitablewatervalueswere computed
by usingequation(11)
908
ENGLAND
ET AL.'
ATMOSPHERIC
I
WATER
I
VAPOR
RADIOMETRY
I
I
•_22
210-
•7•6-
I
4'00
I
2.oo
•8 Apn, •g8B
Fig. 5.
I
8'00
I
8'00
CUT)
(continued)
between the surface and 6.75 km. Since a small amount of water
Errors
vapor existsabove this altitude,the lidar measurements
of
Therearevarioussources
of errorwhichaffecttheprecision
of
precipitablewaterwill be biasedslightlysmallerthanthe true the lidar-derived
watervapormixingratio measurements.
The
amounts. This error will be discussed in the next section.
8.0
I
first source of error is due to the random error associated with the
I
I
I
No Clouds
q-I-
5.5
--
I
5.0
-
o3.õ
3.0
2.5
I
2.00
I
4'00
I
8'00
I
8'00
18 ApP, 1•8B
(UT)
Fig. 6. Cloudbaseheightat WallopsIsland,Virginia, for thenightof April 17-18, 1989, inferredfrom the lidar measurements.
Cloud free periodsare indicatedby gapsin the line.
ENGLAND
2Ei.O
ET AL.:
ATMOSPHERIC
I
WATER
VAPOR
RADIOMETRY
I
I
909
I
• 2.5.0¸
24,0-
> 23.0
.
._
,,
I I
._a.28.0-
n
18
I
2:88
'18 Apr', •989
I
I
4:[]8
8:00
I
8:00
(UT]
Fig. 7. Integratedprecipitablewater vapormeasurements
(in millimeters)at WallopsIsland,Virginia, for April 17-18, 1989. The
lidar measurements
(circles)havebeenaugmented
by measurements
from VAISALA radiosondes
launchedeverythreehours.The
WVR measurements
(stars)are connected
by the line. Error barsrepresentthe randomuncertaintyon the measurements.
lidar data; both Raman water vapor and nitrogen channels errors in the calibration of the sensors on the lidar measurements
contributeto this error. Sincethe signal-to-noise-ratio
of the lidar is thus reducedby averagingover the data set. For the ATMIS
data decreaseswith altitude, this error increaseswith altitude. For proceduredescribedabove, the averageof the lidar calibration
varied by 1-3TOover the courseof the experiment.
a 2-min averageprofile the randomerror is slightlylessthan 10% constants
^ third sourceof uncertaintyis associatedwith the differential
at an altitudeof 6.75 km. Averagingthe data reducesthe random
error, so that for a 30-min averagethis random error becomes transmissioncorrectionwhich is appliedto the lidar ratios. Since
about 1-2 %.
the differentialtransmissiondue to Rayleigh scatteringcan be
A seconderror source is the uncertaintyin the calibration computedwith high accuracy,differentialscatteringdue to Mie
constantrelatingthe lidar Ramanwater vapor to nitrogenratio to scatteringfrom aerosols accountsfor this uncertainty. This
the water vapor mixing ratio. Since this calibrationconstantis differential aerosol transmission is estimated from the aerosol
derived from the radiosondecomparisons,this constantwill scatteringratio obtainedfrom the lidar data. During the ATMIS
experimentthe aerosolloadingwas generallysmall, so that the
dependon the accuracyof the balloon measurements.
Unfortunately,thereare very limiteddatawith which to assessthe correspondingerror in this differential transmissionis much
accuracy of the radiosonde humidity measurements. smaller than the random and calibration errors discussed above.
the precipitablewater, since in clear
Manufacturer'sspecifications
list _+4To for the carbonhygristor The lidar underestimates
humidity sensorsused by the VIZ and AIR packages [viz conditionsthe lidar mixing ratio measurementsare integrated
specifications,1987] and -I- 2% for the VAISALA capacitive from the surface to 6.75 km. This bias in the lidar measurements
by computing
theprecipitable
water, using"hybrid"
sensor [VAISALA specifications, 1986]. Laboratory wasestimated
by usingthe lidar mixing ratio
measurementshave obtainedslightly higher values. Brousaides profileswhich were constructed
[1975] foundmeanerrorsfor the carbonhygristorto vary from
0% to q- 8% depending
upontemperature.A NationalBureauof
Standardstest (1981) found a systematicerror of 4-5% in the
values
from
the surface to 6.75 km and the radiosonde
values
from 6.75 km to an altitudeof nearly 16 km (100 mbar). These
computations
were performedusingeachof the three radiosonde
VAISALA measurementsof relative humidity. However, since sensorpackages.For the nightsof April 11-12 and April 16-17
thesetestsare severalyears old and sincethe errors have shown when the skies were cloud free, the precipitable water
which usedonly the lidar datawere approximately
some dependenceon the particular manufacturedlot, it is not measurements
clear whether or not these resultswould apply to the sensors 3-4 TOlowerthanthosewhichusedthe "hybrid"profiles.This bias
flown duringATMIS.
appearsregardless
of radiosonde
sensortypeusedto constructthe
The lidar calibration constant was obtained from the entire
"hybrid" profiles. When clouds were present such that the
ATMIS radiosondedata set, which is composedof humidity maximum altitude for the lidar data is lower than 6.75 km, this
measurements
obtainedfrom bothtypesof humiditysensors,two biasnaturallyincreases.During the nightof April 17-18 the lidar
carbonhygristorsensorsandonecapacitivesensor.The impactof acquireddatawhile scatteredcloudsdrifted over the ATMIS site.
910
ENGLAND
ET AL.: ATMOSPHERIC
WATER VAPOR RADIOMETRY
12000,
11000.
+ April 12
10000
x April 17
o April 18
8000
8000
7O00
5000
4000
3000
2000
a)
1000
I
10.
,
I
20.
I
30.
40.
50,
60.
._
80.
70.
I
90.
100,
Relative Humidity (%)
12000
11000
-
•.•.•
+ April
12
••..,
'••,..
10000.8000.8000.-
-
x April
17
oApril
18
-
7000.8000.50O0
-
4000
-
3000
-
2000
(
1000
-80.
••.
-50.
-40.
-30.
-20.
-10.
O,
10.
20.
Temperature
Fig. 8. (a) Relativehumidityand (b) temperature
profilesmeasured
with the VAISALA radiosonde
packageat WallopsIsland,
Virginia.The radiosondes
werelaunched
at 0500UT onApril 12, 1989(pluses),
0455UT onApril 17, 1989(crosses),
and0457
UT on April 18, 1989 (circles).
4. RESULTS
The lidar data indicatedthat the cloud base was approximately
4 km. The precipitablewater, computedto cloudbasefrom the
from the
lidar dataonly, wasapproximately25 % lower thanthatcomputed The integratedprecipitablewater vapormeasurements
using the "hybrid" lidar plus radiosondeprofiles. However, lidar and the WVR for the three nights of the experimentare
during those intermittenttimes when cloudswere not overhead shown in Figures 5a-5c. Although the lidar and the WVR
such that the lidar data could be used to 6.75 km, this error operatedfaultlesslyfor 7 nights,due to problemswith the post
dataacquisitionarchivingprocedures
for the WVR, datafrom a
decreasedto the clear conditionvalue of approximately3 %.
ENGLAND
8.5
ET AL.'
ATMOSPHERIC
I
WATER
VAPOR
RADIOMETRY
911
I
I
I
I
4.00
I
is.00
I
8.00
EB0o
>5.
© 5.0-
© 4.5-
[a)
I
2'00
4.0
12 Apr, 1989
11.0[
I
I
I
• 1015
10.0
(UT]
I
I
I
_
õ.0
8.5
Cb]
80
I
2.00
I
4.00
I
B'00
I
8'00
17 Apr, 1989
(UT]
Fig. 9. Integratedprecipitablewater vapor measurements
(in millimeters)at WallopsIsland, Virginia, from the lidar (circles)
averagedaroundthe timesof the WVR measurements
(stars)for (a) April 11-12, 1989, (b) April 16-17, 1989, and (c) April
17-18, 1989. The WVR measurements
are connectedby the line. Integratedprecipitablewater vapor inferred from the VAISALA
radiosondesalso are shown(crosses).Error bars representthe randomuncertaintieson the measurements.
significantportionof the experimentwere lost (nightsof April but unfortunatelynot all data were archived). The WVR
12-16andthe latterportionof the nightof April 18, 1989).The measurements
arethe fourpointaverages
(spanning
a timerange
reliability of the WVR instrumentduring the experiment•vas of 3.5 min) calculatedfrom the two tip curveresultsandthe two
excellent
(dataweretakenforthewholeof theexperiment
period, line-of-sight
results.Thelidarmeasurements
are2-minaverages.
912
ENGLAND
ET AL.'
23.5
ATMOSPHERIC
WATER
VAPOR RADIOMETRY
I
I
I
I
I
4'00
I
8'00
•230
22.5
22.0
•
21.5
•
21.0
--
•
20.5
'•
20.0
.__
1õ.5
2.oo
18 Apr, 1989
8
(UT)
Fig. 9.
(continued)
The agreement
betweenthe WVR andlidar resultsis very good previous24 hours,and the sky was clear, still, and dry. The
for the first period, April 11-12, 1989, Figure 5a. The water agreementfor the secondperiod, April 16-17, 1989, Figure 5b,
vapor contentfor this time period is low (5 mm of preeipitable is not quiteas goodas for the first period.The moisturecontent
water). A weatherfront had passedthroughthe area within the on this nightis around10 mm of precipitablewater. However, a
1.0
I
I
I
I
.8
.B
.4
.2
0.0•
-.2
-.4
-.8
Ca)
-.8
-1.0
I
2'00
12 Apr, 1989
I
4:00
I
6'00
.I
8'00
(UT)
Fig. 10. Differences
(in millimeters)
between
theWVR watervapormeasurements
andthelidar30-minaverage•at Wallop•
Island,Virginia, for (a) April 11-12, 1989, (b) April 16-17, 1989, and(c) April 17-18, 1989.
ENGLAND
1.0
ET AL.' ATMOSPHERIC
WATER
VAPOR RADIOMETRY
913
I
I
I
I
I
2,00
I
4.00
I
B'00
1
8 '00
17 Apr', 1989
(UT]
1.0
-2.0
I
_1
2'00
18 Apn, 1989
I
I
I
4'OO
B'00
I
8
(UT]
Fig. 10. (continued)
systematic
difference
between
theWVR andthelidarisapparent.more moist(about21 mm of precipitablewater), Figure 5c. The
Thedifference
between
thetwoi•strurnents
decreases
through
the WVR measurements
have a meanof about21 mm of precipitable
night. Neither the WVR r•easurementsnor the lidar water, whereasthe lidar measurements
are predominantly
at about
measurementsare anomalous,and the observed trend in the
the 18 mm of precipitablewater level. The cloudbaseheight, as
differences
is unexplained.
Theclifferences
aregenerally
small, inferred from the lidar results,is shown in Figure 6. During
withthemaximum
beingabout!.6 rnmof precipitable
water. periodswhen cloudsare not present,as indicatedin Figure 6, the
Thenightof April17-18,1989,wascloudy
andsignificantly
lidar and the WVR measurementsare in good agreement.The
914
ENGLAND ET AL.: ATMOSPHERIC WATER VAPOR RADIOMETRY
lidar is underestimating
the watervaporin the presence
of clouds
becausethe lidar signalcannotpenetratethe clouds.This indicates
TABLE3. Integrated
WaterVaporMeasurements
in Millimeters
Summary
that a significantamountof watervaporis presentaboveabout
4 km (the approximatecloud base height). To emphasizethe Date
April 11-12 April 16-17 April 17-18
limitationof the lidar in the presenceof clouds,when the lidar
Number
of pairs
results are augmentedwith the VAISALA radiosonderesults
vapor(WVR)
abovethe cloudbase,the ag•'eement
with the WVR measurements Totalprecipitable
improves(Figure7). Relativehumidityand temperature
profiles Meandifference
I
measuredwith the VAISALA radiosondepackage from the
deviation
I
balloon launchesat approximatelythe midpointof each of the Standard
nightsare shownin Figures 8a and 8b. The VAISALA sensor Biaserror(WVR)
results are shown as the sensorprovides readingsfor relative
Random
error(WVR)
humiditiesbelow 20%. The effect of these cloudscan be seenin
12
10
6
5
10
21
-0.2
-0.8
-0.4
0.2
0.5
0.3
0.8
0.9
1.4
0.4
0.4
1.3
the relativehumidityprofile for April 18.
Totalerror(WVR)
0.9
1.0
1.9
A more quantitativemeasureof the comparisonbetweenthe
WVR and the lidar was obtainedby computing30-min averages Regression
results
withWVRandlidar:PW•,•= m(PWea,•)
+ c; slope
for the lidar results centered around the times of the WVR
data.
This comparisonis shownin Figures9a - 9c, andthe differences
(WVR minus lidar) in Figures 10a - 10c. The integrated
precipitable water vapor results inferred from VAISALA
radiosondemeasurements
for the three periodsalso are shown
with the WVR and lidar measurementsin Figures 9a - 9c. The
VAISALA radiosonderesultsare plottedas this sensorprovides
relative humidityreadingsbelow 20% relativehumidity,whereas
the AIR and VIZ
the WVR
sensors do not. The mean differences between
and the lidar
and standard
deviations
for the three
periodsare-0.2 + 0.2 mm (April 11-12),-0.8 _+0.5 mm (April
(m), 0.992mm/mm;intercept
(c), -0.37 mm;correlation
coefficient,
0.998; numberof pairs,28.
Difference is (WVR minuslidar).
for all threetimeperiodsis shownin Figure11. A linearleast
squares
regression
solution
resulted
in a relationbetween
the
WVR and lidar precipitablewater vapor of PW• =
0.992(PW•-0.37 for the 28 datapairs.A highcorrelation
(r = 0.998) betweenthe WVR and lidar measurements
was
obtained for the whole data set.
16-17)and-0.4+ 0.3mm(April17-18)(seeTable3). The Theonlycommon
element
inthecomparison
between
theWVR
differences
arescattered
about
these
mean
values
forthenights
of andlidarmeasurements
isthatultimately
thecalibration
forboth
April11-12andApril17-18butnotforthenightofApril16-17, methods
relies
uponradiosonde
data,albeitin different
fashions.
whichshows
a systematic
trendwithtime.Thissystematic
trend Thelidarusesradiosonde
datato provide
theabsolute
mixing
is veryevident
in Figure10b.
ratioscalefor theprofiles.
TheWVR usesradiosonde
datato
Thecomparison
between
theWVRandthelidarmeasurements
determine
setsof retrievalcoefficients
for the moisture
25
I
I
I
IO
o__
o__
©
5
I
5.
I
10.
I
15.
I
20.
25.
Precipitable water (mm) LIDAR
Fig. 11. Scatterplot
of thelidarandWVR integrated
precipitable
watervapormeasurements.
Theleastsquares
regression
line,
PW,,•,.= m(PWea,,)+c
, is shown(dashedline)aswellasthePW•,,,,.
= PWa,
• line(solidline).
ENGLAND
ET AL.:
ATMOSPHERIC
WATER
VAPOR
RADIOMETRY
915
measurements.In its normal operatingmodethe WVR useslong
term averagesof radiosondedata to provide general retrieval
coefficients.The radiosondedata cover a specifictime period
(e.g., 1979-1982 for the coefficientsusedhere), but the retrieval
coefficientsderivedfrom thesedataare appliedto all other times.
Elgered,G., B.O. Ronnang,J.I.H. Askne,Measurements
of atmospheric
watervaporwith microwaveradiomerry,
Radio Sci., ] 7, 1258, 1982.
Elgered,G., J.L. Davis, T.A. Herring, and I.I. Shapiro,Geodesyby
radio interferometry:Water vaporradiomerryfor estimationof the wet
delay,J. Geophys.Res., 96, 6541, 1991.
On the other hand, the radiosonde data used to calibrate the lidar
water vapor radiometersoperatingat sitesof the Crustal Dynamics
Gary, B.L., and S.J. Keihm, Path delay retrievalcoefficientsfor use with
Project,Interim Report,Jet Propul. Lab., Pasadena,Calif, 1986.
systemare takensimultaneously
with the lidar measurements
(e.g.
Gary, B.L., S.J. Keihm, and M.A. Janssen,Optimum strategiesand
the lidar systemhere was calibratedwith data from radiosondes performancefor the remotesensingof path delay usingground-based
launchedevery 3 hoursduringthe experiment).The main focus
microwave radiometers,IEEE Trans. Geosci. Re,note Sens.,
GE-23, 479, 1985.
of this studywas to determinethe performanceof the WVR under
normal, routine Crustal Dynamics Project operating conditions. Gipson,J.M., andG.L. Lundqvist,The effectof randomand systematic
errors on the sensitivityand precisionof water vapor radiometers,
Theseproceduresusetime-averagedretrieval coefficientsfor the
NASA CrustalDynamicsInternalReport,GoddardSpaceFlightCenter,
moisturemeasurements,and becausea follow-on experiment is
Greenbelt, Md, 1986.
plannedfor late 1991 and becauseof the shorttime spanof data. Goldstein,H., Attenuation
by condensed
matter,in Propagation of
ShortRadio Waves,editedby D.E. Kerr,p. 671,McGraw-Hill,New
availablefor this intercomparison,
the question of the difference
York, 1951.
in using time-averagedretrieval coefficientsand site specific,
Haltiner,
G.J., and F.L. Martin, Dynamical and physical
simultaneouslydetermined retrieval coefficients has not been
meteorology,McGraw-HillBookCompany,
Inc., NewYork, 1957.
directly addressedin this study, althoughthe importanceof the Heggli, M., R.M. Rauber, and J.B. Snider, Field evaluation of a dualretrievalcoefficientsis recognized.The follow-onexperimentwill
channelmicrowaveradiometerdesigned
for measurements
of integrated
water vapor and cloud liquid water in the atmosphere,J. Atmos.
concentrateon validation of the resultsof this study and on the
issue of the suitability of time-averagedor "instantaneous" Oceanic Technol., 4, 204, 1987.
retrieval
coefficients
and the uncertainties
associated with each.
Hogg, D.C.,
Westwater,
F.O. Guiraud, J.B. Snider, M.T. Decker, and E.R.
steerable dual-channel microwave radiometer for
A
Coupled to this follow-on experiment is an analysis of the
measurement
of watervaporand liquidin the troposphere,
J. Appl.
uncertaintiesin the radiosondemeasurementsof temperature, Meteorol., 22, 789, 1983.
pressure, and relative humidity (see M. N. England et al., Janssen,M.A., A new instrumentfor the determinationof radio path
delayvariationsdueto atmospheric
watervapor,IEEE Trans. Geosci.
Atmospheric Moisture Measurements: Are All Radiosondes Remote Sens., GE-23, 485, 1985.
Equal? A Microwave Radiometer-RadiosondeComparison, Johansson,J.M., G. Elgered, J.L. Davis, Geodesy by radio
submitted to IEEE Trans. Geosci. Remote Sens., 1991).
interferometry:Optimizationof wet path delay algorithmsusing
Becausethe agreementbetween the two moisture-measuring microwaveradiometerdata,Res. Rep. No. 152, ChalmersUniv. of
techniquesis goodthrougha varietyof meteorologicalconditions, Technol., Goteborg, Sweden, 1987.
Kaiser, J.F., and W.A. Reed, Data smoothingusinglow-passdigital
the conclusion
is that the WVR
measurements
are accurate
filters, Rev. Sci. Instrum., 48, 1447, 1977.
estimatesof the integratedwater vaporcontentof the atmospheric Liebe, H.J., and D.H. Layton, Millimeter-wave propertiesof the
columnbeing observed.The excellentagreementbetweenthese
atmosphere:
Laboratorystudiesand propagation
modeling,Rep. 87224, Natl. Telecommun.andInf. Admin., Boulder,Colo., 1987.
independentmeasurementtechniquesgives confidencethat the
of the atmosphereusing Raman
WVR is capable of accurately measuringthe sky brightness Melfi, S.H., Remote measurements
scattering,
Appl. Opt., 11, 1605,1972.
temperaturesand from thesederivingthe extra "wet" signalpath Melfi, S.H., and D. Whiteman, Observationof lower-atmospheric
delay and the moisturecontentof the troposphere.
moisturestructureand its evolutionusinga Ramanlidar, Bull. Am.
Meteorol. Soc., 66, 1288, 1985.
Aclo•owledgments.
A wordof thanksis owedto the Science
Review Melfi, S.H., D. Whiteman,
andR.A. Ferrare,Observation
of atmospheric
Boardat Interferometrics
Inc. for theirusefidreviews,especially
Clara frontsusingRamanlidar moisturemeasurements,
J. Clim. Appl.
Kuehn, whose commentsand suggestions
greatly improvedboth the
Meteorol., 28, 789, 1989.
presentation
and the contentof this paper, and to the reviewerswho Resch, G.M., Water vapor - The wet blanket of microwave
contributed useful comments.
We also would like to thank Frank
interferometry,
in AtmosphericWater Vapor, editedby A. Deepak,
Schmidlinfor the radiosondedata, the staff at Wallops Island, Virginia,
T.D. Wilkerson, and L.H. Ruhnke, p. 265, Academic, San Diego,
for the balloon launches, AI Wu, Dave Sims, and Mark Hitch of Bendix
Calif., 1980.
Field EngineeringCorp., Columbia, Maryland, for their supportof the Resch,G.M., Inversionalgorithmsfor water vaporradiometersoperating
J03 instrument, and the staff at the NASA/GSFC Crustal Dynamics
at 20.7 and 31.4 GHz, TDA Prog. Rep. 42-76, Jet Propul.Lab.,
Project.
Pasadena,Calif, 1983.
REFERENCES
Resch, G.M., M.C. Chavez, N.I. Yamane, K.M. Barbier, R.C. Chandlee,
Water vapor radiometryresearchand developmentphase:Final report,
Pub. 85-14, JetPropul.Lab., Pasadena,
Calif., 1985.
Askne, J., G. Elgered, H. Nordius, G. Skoog,E. Winberg, A. Hagard,
E. Andersson,N. Gustafsson,J. Svensson,and I. Carlsson,The Robinson,S.E., The profile algorithmfor microwavedelay estimation
data,Radio Sci., 23, 401, 1988.
ONSAM experiment:Remotesensingtechniquesfor vertical sounding fromwatervaporradiometer
Rosenkranz,P.W., Interfacecoefficientsfor overlappingoxygenlines in
of the atmosphere,
J. Almos. Ocean Technol., 4, 180, 1987.
air, J. Quant. Spectrosc.Radiat. Transfer, 39, 287, 1988.
Becker, G.E., and S. H. Autler, Water vapor absorption of
electromagnetic
radiationin the centimeter
wavelength
range,Phys. Shapiro, I.I., Estimation of astrometricand geodetic parameters, in
Rev., 70, 300, 1946.
Methodsof ExperimentalPhysics,Vol. 12C,editedbyM.L. Meeks,
p. 264, Academic,San Diego, Calif., 1976.
Brousaides,F.J., The radiosondehygristorand low relative humidity
Van Vleck, J.H., The absorptionof microwavesby uncondensedwater
measurements,
Bull. Am. Meteorol. Soc., 56, 229, 1975.
vapor,Phys. Rev., 71, 425, 1947.
Clark, T.A., et al., Precisiongeodesyusing the Mark-III very-longbaselineinterferometer
system,1EEE Trans. Geosci. Remote Sens., Wade, C.G., and D.E. Wolfe, Performanceof the VIZ carbonhygristor
GE-23, 438, 1985.
in a dry environment,paper presentedat 12th Conferenceon Weather
Analysis and Forecasting,Amer. Meteorol. Soc., Monterey, Calif.,
Davis, J.L., T.A. Herring, I.I. Shapiro,A.E.E. Rogers,and G. Elgered,
1989.
Geodesyby radiointerferometry:
Effectsof atmospheric
modelingerrors
Westwater, E.R., An analysisof the correctionof range errors due to
on estimates
of baselinelength,Radio Sci., 20, 1593, 1985.
reft'action
by microwaveradiometrictechniques,
Tech.
Dicke, R.H., R. Beringer, R.L. Kyhl, and A.B. Vane, Atmospheric atmospheric
absorption
measurements
with a microwaveradiometer,Phys. Rev.,
Rep. IER 30-ITSA30, Environ.Sci. Serv. Admin., Boulder,Colo.,
70, 340, 1946.
1967.
916
ENGLAND ET AL.: ATMOSPHERIC WATER VAPOR RADIOMETRY
Westwater, E.R., Ground-baseddeterminationof low-altitude temperature
D. N. Whiteman, Laboratory for Terrestrial Physics, Code 924.0,
NASA/Goddard SpaceFlight Center20771.
Westwater, E.R., The accuracy of water vapor and cloud liquid
T. A. Clark, Laboratory for Terrestrial Physics, Code 926.9,
determinationby dual-frequency
ground-based
microwaveradiomerry, NASA/Goddard SpaceFlight Center20771.
Radio Sci., 13, 677, 1978.
Martin N. England,IUE Observatory,ComputerSciencesCorporation,
Westwater, E.R., M.J. Falls, and I.A. Popa Fotina, Ground-based
Code 684.9, NASA/GoddardSpaceFlight Center, Greenbelt,MD 20771.
microwave radiometric observationsof precipitablewater vapor: A
R. A. Ferrare and S. H. Melfi, Laboratory for Atmospheres,Code
comparison
with groundtruth from two radiosonde
observingsystems, 917.0, NASA/GoddardSpaceFlightCenter,Greenbelt,MD 20771.
J. At•nos. Oceanic Technol., 6, 724, 1989.
Whiteman, D.N., S.H. Melfi, and R.A. Ferrare, Raman lidar systemfor
(ReceivedJanuary8, 1991;
revised June 4, 1991;
the measurement
of watervaporandaerosolsin theEarth'satmosphere,
acceptedJuly 17, 1991.)
Appl. Opt., in press,1991.
profilesby microwaves,
Mon. WeatherRev., 100, 15, 1972.