GEOPHYSICALRESEARCHLETTERS,VOL. 25, NO. 9, PAGES1363-1366,MAY 1, 1998
Ice nucleationprocesses
in uppertropospheric
wave-cloudsobservedduring SUCCESS
E. J. Jensen
•, O. B. TooI12,
A. Tabazadeh
•, G. W. Sachse
s, B. E. Anderson
•
K. R. Chan•, C. W. Twohy
4, B. Gandrud
4, S. M. Aulenbach
4, A.
Heymsfield
4, J. Hallett5, andB. Gary6
Abstract. We have compared in situ measurements
near the leading-edgesof wave-cloudsobservedduring the SUCCESS experimentwith numericalsimulations. Observationsof high supersaturationswith re-
with sporadicand localizednucleation[e.g.,Sassenet
al., 1989]. It is often impossible
to tell what stageof
evolutiona sampledcloudelementwasin. Wave-clouds
that form at the cold crests of mountain waves are ideal
systems
to studycloudphysical
processes
because
the
spect
toice/•"
50%)
near
the
leading
edge
ofavery
cold
wavecloud < -60øC) are approximatelyconsistent wind field is laminar and well defined, and the cloud
with recenttheoreticaland laboratory studiessuggest- is stationary.Ice crystalsnucleateat the leading(uping that large supersaturations
are requiredto homoge- wind) edgeof the cloud,and growasthey are advected
neouslyfreezesulfateaerosols.Also,the peakicecrystal downwind.Heymsfield
andMiloshevich
[1993,1995]exnumberdensities
observed
in thiscloud(about4 cm-s) ploitedobservations
in wave-clouds
to exploreice nucleaxe consistent with the number densities calculated in ation mechanisms
at temperaturesrangingfrom -31 øC
our model.In the warmerwave-cloud
(T _ -37øC) rel- to-56øC. Although updraft velocitiesin wave-clouds
ativelylargeice numberdensitieswereobserved(20-40 may be larger than in typical cirrus, the wave-clouds
cm-S). Ourmodelcalculations
suggest
that theselarge are still usefulto study cloudprocesses.
In this study we have combinedobservationsfrom the
number densitiesare probably causedby activation of
sulfate aerosolsinto liquid dropletsfollowedby subse- SUCCESSmissionwith numericalmodelingto evaluate
quent homogeneousfreezing. If moderate numbersof ice nucleationprocesses
in two wavecloudsat very dif-
effective
heterogeneous
freezing
nuclei(0.5-1cm-s) had ferenttemperatures(-64øC and-37øC). We will show
been presentin either of theseclouds,then the number that the observed critical humidities for ice nucleation
densitiesof ice crystalsand the peak relative humidities and ice crystal number densitiesare consistentwith calshould have been lower than the observed values.
culationsassuming
that homogeneous
freezingof sulfate
aerosols is the dominant nucleation mechanism.
The
first sectionof the paper briefly summarizesthe SUCCESSwave-cloud
observations
usedin thisstudy.Next,
Introduction
Over the past few decades,severalstudieshaveshown we describes the wave-cloud formation simulations. Fithat cirrus cloudsplay an important role in the earth's nally, we comparethe model resultswith observations
radiationbudgetand climate[e.g.,Liou, 1986].Hence, and evaluatethe implicationsfor ice nucleationpro-
it is important to understandthe processesresponsi- cesses.
ble for their formation. In particular, the temperatures
and humidities required for ice nucleationmay control SUCCESS
Wave-cloud
Measurements
cirrus frequency. Theoretical analyseshave been used
For comparisonwith nucleation simulations,we reto predict the ice supersaturationrequired for homoquire
measurementsof peak relative humidities and
geneous
freezingof sulfateaerosols[Sassen
and Dodd,
ice
crystal
number densities at the wave-cloudlead1989;Heymsfieldand Sabin,1989;Jensenet al., 1994],
ing
edges.
Relative
humiditiesare calculatedfrom the
and it has been suggestedthat this is probablythe dom-
laserhygrometerwatervapormeasurements
[Collinset
al.,
1995],
and
the
meteorological
measurement
system
ever, these predictions have not been extensivelyconon boardthe NASA
firmed with atmosphericobservations. Nor is it clear (MMS) temperaturemeasurements
inant ice nucleation
mechanism
in cirrus clouds. How-
DC-8. Given the uncertaintiesin these measurements,
what role heterogeneousice nucleationplays.
The processesresponsiblefor cirrus cloud formation the uncertainty in the derived relative humidity with
(i.e., ice nucleationand growth)are typicallyvery dif- respectto ice (RHI) is about 10%. During the flight
ficult to study with in situ observations. Midlatitude on May 2, the leadingedgeof a wave-cloudsystemover
continental cirrus cloudsare usually highly structured Colorado was crossedseveraltimes. In this study, we
will focuson the leading-edgecrossings
at 20:18:28UT
and 20:29 UT, when the dynamicsseemedto approxiNASA AmesResearch
Center,MoffettField, CA
mately match the idealizedwave-cloudmodel. At these
times, the DC-8 flew approximatelydownwindinto the
2Universityof Colorado,Boulder,CO
SNASALangleyResearch
Center,Hampton,VA
leading-edge
ofthewave-cloud
(20:18:28
UT cross.
in•)
(20:29UT crossing).
4NationalCenterforAtmospheric
Research,
Boulder,CO andupwindout of the leading-edge
5DesertResearchInstitute,Reno,NV
6JetPropulsionLaboratory,Pasadena,CA
Copyright
1998bytheAmerican
Geophysical
Union.
Papernumber98GL00299.
0094-8534/98/98GL-00299505.00
The measuredtemperature, relative humidity, and ice
crystal number density are plotted versustime for the
first crossingin Figure 1. The peak number densities
of ice crystalslarger than about 3/•m radius measured
by both the counterflowvirtual impactor (CVI) and
the video ice particle sampler(VIPS) were about 27 cm-s, and the peak RHI wasabout 150-160%.Ice
1363
1364
JENSEN ET AL.' ICE NUCLEATION IN WAVE CLOUDS
Wove-cloud
simulation: results at ! 1.9 km
DC-8
20.48
0
data:
2
4
-
20.491
[•ce •n) I0
12
14
Toro!N•
!o.ooo ....
N• (r>3 •)
:.•0
140
.r..,
1,o00
100
~ .., ..,
4,
i 140
O.lOO
12o
Figure 1. DC-8 measurements
for the leading-edge
crossing
at 20:18:28UT, May 2 are plottedversustime.
At this time, the DC-8 flew downwindinto the leadingedgeof the wave-cloud
at 11.9km. The measuredtem-
o.o,o
I
0,001 L, ........
o
• .........
t., .•, .....
• .......
1
2
3
ß • ........
4
•, -. ......
n 100
5
6
-7O
Ti.• (.•.)
½ ..-c-oC• N•, (era•)
: : : : SlmuloUo,
perature(MMS), relativehumidity(laserhygrometer),
and ice crystalnumberdensity(CVI and VIPS) are Figure 2. The model RHI, ice crystalnumberdensity,
plotted versustime. The magentaasterisksand trian- and temperature are plotted versus time at 11.9 km
glesarethe VIPS datafromthe lowresolution
andhigh for the May 2 case. The total number density of ice
resolution cameras, respectively.
crystals(solidblackcurve)and the numberdensityof
ice crystalswith radii largerthan about 3/•m (dashed
curve) that would be detectedby the CVI are shown.
The DC-8 RHI and CVI data from the passat 20:29 UT
number
densities
largerthanabout10cm-3 werenever havealsobeenplotted versustime (convertedto parcel
observed in this wave-cloud.
time advectedby the wind) for comparison.
Duringthe wave-cloud
sampling
flighton April 30,
we werenot ableto fly legsdirectlyupwindof the cloud
due to restrictedair-space.However,severallegswere
flownalongthe leadingedgedippingin andout of the sizedistributionwith N - 100 cm-•, rocloud. The peak RHIs measured
just upwindof this and er = 2.3.
0.02/•m,
Tabazadehet al. [1997]usedrecentlaboratorydata
cloud were on the order of 120-130%, and the peak ice
for the physicalquantities
numberdensitiesindicatedby the CVI rangedfrom 20 to developnew expressions
fleezingof sulfateaerosols.
to 40 cm-3. The actual maximum RHI may not have that control homogeneous
We have used the expressions
recommendedby Tababeen detecteddue to the cross-windflight path.
The temperatureat the cloudleadingedgefor the zadeh et al. to calculate aerosolfleezing rates in this
May2 casewasabout-64øC.FortheApril30 casethe work. In someof the simulations,we alsoincludedhet-
fleezingnuclei(seeJensenandToon[1997]
temperature
wasabout-37øC.The slopeof the poten- erogeneous
fleezingcalculations).
tial temperaturesurfaces
(measured
by the microwavefor detailsof the heterogeneous
We initialized the model atmospheric temperature
temperature
profiler(MTP)) onthe upwindsideof the
(MTP and
wave crestindicated a vertical wind speedof about 1.2 profilesbasedon SUCCESSmeasurements
MMS).
We
used
an
initial
RHI
vertical
profile
with a
m-s-1 for the May 2 case.This estimateapproximately
agrees
withthe verticalwindspeedindicated
by MMS. Gaussianshapepeakedwherethe wave-cloudwas obThe verticalwind speedsindicatedby MMS in the April served(11.9 kin). The peak RHI was initially set at
30 wave-cloudweremuchstronger(updraftsup to 5 m- just below100%.The updraftvelocityin the modeloscillatedsinusoidallywith time; however,overthe short
s-l). Theseverticalwind speedmeasurements
have
largeuncertainties;
the sensitivity
of the modelresults
to verticalwind speedis discussed
below.The temperatures,humidities,ice numberdensities,
and plausible
Wove-cloud simulation: results at 8.75 km
1•0
-3
15,o
-
rangesfor verticalwindspeeds
for the twowave-cloud
casesare given in Table 1.
Wave-Cloud
Ice Nucleation
lO.OOo
Simulations
1.000
To simulate ice nucleation at the wave-cloudleading
edges,weuseda one-dimensional
versionof the detailed
0.100
ice cloudmodeldescribedby Jensenet al. [1994].Previously,we haveusedthis modelto evaluatethe sensitivity of cirruscloudsto sulfateaerosolnumberdensity,
temperature,
andcoolingrate [Jensen
andToon,1994];
and heterogeneous
ice nuclei[Jensenand Toon, 1997].
0.001
-1100
Threeparticletypesare included:puresulfatesolution
1.50
1.60
1.70
1.80
1.90
2.0,0
2. I0
2.20
aerosols(H2SO4/H20), activatedwater droplets,and
Time(min)
ice crystals.For eachparticletype, 60 radiusbinsare
includedspanningthe ranges0.005- 100/•m for sulfate Figure 3. SameasFigure2, but forthe April 30 wave-
1
aerosols
anddroplets,
and0.01- 232/•mfor icecrys- cloudcase.We alsoshowthe liquiddropletnumber
tals. For the sulfateaerosols,we assumea log-normal densityversustime in this case.
JENSEN ET AL.' ICE NUCLEATION
Table 1. Summary of SUCCESS Wave-CloudMeasurements
Date
May 2, 1996
April 30
Time (UT)
Temp
20:29:12
-64øC
21:12:00
-36.7øC
Updraft
0.8-1.6m-s-•
3-5 m-s-
Peak RI-II
Peak Ice Conc.
150-160%
2-7 cm-3
_•130%
20-40 cm
IN WAVE CLOUDS
1365
Table 1, if we use our old aerosolfreezingparameterization, then not only is the peak RHI decreasedto about
126%,the peakice crystalnumberdensityis 17 cm-•
(muchhigherthan the observedvalues).
For the rapid cooling rate and low temperature of
this wave-cloud, the peak crystal number density is
probably controlled exclusivelyby homogeneousfreezing. However, heterogeneousnuclei could modify the
crystal number density in wave-cloudsif a substantial
fraction
of the sulfate aerosols contained
effective het-
erogeneousfreezingnuclei. Simulationsincludingheterogeneous
ice nucleiindicate that the number density
of ice crystalsgeneratedcould be reducedcomparedto
freezingof pure
time-period
duringwhichnucleation
occurred,
thever- the numbergeneratedby homogeneous
sulfateaerosols(seeTable 2). Also,if substantialnumtical windspeeddid not varysubstantially.
bers of effectiveheterogeneousice nuclei are included,
then the peak RHI at the cloud leading edge is much
Results
lower than the observedvalues. The consistencybeMay 2, 1996 Case
tw.een the observedpeak ice number densitiesand RHIs
We are assuming
herethat our 1-D modelrepresents and the results from modeling with only homogeneous
a columnof air passingthroughthe wave-cloud.For freezingsuggeststhat relatively large numbersof effec-
icenuclei(•_ 0.5-1 cm-s) werenot
comparison
with aircraftdata,we extractethe model tive heterogeneous
resultsversustime at the DC-8 flight level. Figure 2
present. However,this doesnot rule out the possibility
ice nucleiwere present.
showsthe modelRHI, ice crystalnumberdensity,and that fewer heterogeneous
effective radius versus time at 11.9 km for the May 2
case.Icecrystalsdonotbeginnucleating
in thissimula- April 30, 1996 Case
total numberof ice crystals,we alsoshowthe number The results of the simulation for the April 30 wavedensityof crystalswith radii largerthan about3 pm cloud case are shownin Figure 3. In this simulation,
that wouldbe detectedby the CVI. The crystalstake the temperatureis just high enoughsuchthat sulfate
about28 seconds
to growto 3 pm, sothe numberof aerosolsare activated into water dropletsbeforethe suldetectablecrystalsdoesnot rapidlyincreaseuntil just fate aerosolscan freeze directly. Large numbersof liqtion until the RHI reaches145-150%. In additionto the
after the RHI reachesits maximum. Usingthe aircraft uid droplets are activated sincethere is no nucleation
speedandambientwindspeed,wehaveconverted
the barrier to overcome. The liquid droplets grow, dilute,
time-seriesdata from the passat 20:29 UT to a data and freeze within 5-10 seconds.The droplets never get
seriesversustime as an air parcelwouldhavebeenen- larger than about 1-2 •umradius. The peak ice crypteringtheleadingedgeandoverlaid
thedataonFigure tal numberdensityin the simulation(about 30 cm-•)
for this case. The
2. ThepeakRHI andicenumberdensityfromthesim- agreeswell with the measurements
ulationagreereasonably
wellwiththe observed
values.
Theobserved
peakRHI wasabout10%largerthanpredictedby ourmodel,andicecrystals
weredetected
by Table 2. Wave-CloudSensitivityTests(May 2 case)
the CVI furtherupwindthat predictedby the model.
The sensitivityof the modelresultsto key environ-
Test
Vz
Nc,
Nh•t
•
Ni•
RHI.
mental conditions assumedin the model is summarized
in Table2. As discussed
previouslyby JensenandToon I
baseline
1.2
100
0
2.3
6.9
150.4
[1994],
changes
in theupdraftvelocity
cansubstantially2
low vz
0.8
100
0
2.3
4.0
149.0
distributionhaveonlymoderateimpacton the number 5
highvz
highN•,
low No,
1.6 100 0
1.2 300 0
2.3
2.3
9.7
8.2
151.3
148.9
1.2 100 0
2.8
6.1
149.1
highScrit 1.2 100 0
2.3
2.3
5.7
9.8
160.0
151.1
changethe peakice crystalnumberdensity;whereas 3
changes
in the sulfateaerosol
numberdensityandsize 4
of icecrystalsnucleated.A reduction
of the updraft 6 higha•,
speed
to 0.8m-s-• reduces
thepeakicecrystalnumber 7 low ac,
densityto lessthan 4 cm-3 andimproves
the agree- 8a low Scrit
ment with the observations.Ice crystalgrowthratesare
9a
1.2
1.2
1.2
30
100
100
0
0
0
anotherimportantsource
of uncertainty
in the model. 10b slowgrow 1.2 100 0
For our baselinesimulation,we assumed
that the depo- 11
sitioncoefficient
(or massaccommodation
coefficient)12
wasunity. Decreasing
thisparameter
to 0.5 resultsin 13
anincrease
in thepeakicenumber
density
to 9.8cm-3. 14
The peak ice saturationin thesesimulations
is al- 15
bet.
her.
bet.
her.
bet.
IN
IN
IN
IN
IN
1.2
1.2
1.2
1.2
1.2
100
100
100
100
100
0.1
0.5
0.7
I
2
2.3
1.8
2.3
2.3
2.3
2.3
2.3
2.3
5.2
7.8
17.0
6.3
2.4
0.71
0.90
1.8
151.1
151.9
126.6
149.9
147.1
140.7
136.8
131.7
mostentirelycontrolled
by the assumed
freezingproperties of the sulfate aerosols.Changesin coolingrate
The sensitivitiesof the peak ice crystal number densi-
-60øC the sulfate aerosolsshouldfreezewhen the RHI
erogeneous
freezing
icenuclei,Nh•t (cm-S),andthe width
(cm-S),andpeakRHI (%) to updraftvelocity,
vz
or crystalgrowthratedonot affectthe peakRHI. We ties,Nice
1
3
havepreviously
suggested
that at temperatures
below (m-s-), sulfateaerosolnumberdensity,No, (cm-), het-
exceeds
onlyabout125%(ratherthanabout150%in- of the aerosolsize distribution,a•,, are given.
aThe aerosolfreezingrate was increased(decreased)
redicated
by ourcurrentfreezing
parameterization).
The
May 2 wave-cloud
measurements
suggest
that the ice suitingin a decrease(increase)in the peakRItI.
coefficient
wasdecreased
to 0.5,resulting
supersaturation
required
forhomogeneous
freezing
may bThedeposition
be ashighas 160%.As indicated
by the lastentryin in a 30% reductionin crystalgrowthrates.
1366
JENSEN ET AL.: ICE NUCLEATION
ß
ß
ß
i
-
ß
ß
i
ß
ß
ß
i
ß
-
ß
i
-
ß
IN WAVE CLOUDS
possiblyresultingin a decreasein the icecrystalnumber
density. If a very large fractionof the sulfateaerosols
contained effective freezing nuclei, then the observed
high ice number densitiescould have been generated
without intermediate liquid droplet activation. However, given the high crystal number densitiesin this
case, it seemslikely that homogeneousfreezing domi-
ß
r'e,lce
nated the ice nucleation process.
lO
1
Summary
Our model simulationsincludingonly homogeneous
freezingnucleationpredict peak humiditiesand icenumber densitiesthat agreewith the SUCCESS wave-cloud
-42
-40
-38
-36
-34
-32
observations(within the rangesof measurementand
model uncertainties). The observationssupportthe
Figure 4. The pe•k liquiddrople••nd ice crystal recent predictions that large supersaturationsare renumberdensity•re plo•ed versusminimum•emper•- quired to initiate homogeneous
freezingof sulfateaero•ure for simulationswi•h • r•nge of ini•i•1 •emper•ures. sols. Sensitivity tests suggestthat no more than about
The effec•iYer•dius of ice crystalsin •he simulations•e
0.5-1 cm-3 effective
heterogeneous
icenucleicouldhave
•1soshown. The maximum number densityof ice crys- been presentgiven the observedhigh supersaturations
tals forms• •emper•ures jus• low enoughfor liquid and ice number densities.We cannot rule out the possiwaterdropletsto form (near-37.5ø0).
bility that smaller numbersof heterogeneous
ice nuclei
were present. In other types of cirrus cloudswith lower
coolingrates, smallnumbersof effectiveice nucleicould
peak RHI in the simulation(147%) is somewhatlarger dominate the ice nucleation process.
than the observedpeak valuesof about 135%;however,
Acknowledgments.
This researchwas supported by
the locations where the peak RHIs occurred may not
NASA's SubsonicAssessment
Program, directedby Howard
have been sampledon this flight.
Wesoky.
The peak number of ice crystals is very sensitiveto
the formation of activated liquid droplets prior to ice References
nucleationin our simulations.Figure 4 showsthe peak
ice crystal and liquid droplet number densitiesversus Collins, J. E., et al., A novel external path water vapor
sensor,presentedat the AtmosphericEffects of Aviation
the minimum temperature. If the temperatureis just
Program5th annualmeeting,April 23-28, 1995.
low enoughsuchthat the sulfatehazeaerosols
freezebefore liquid dropsform, then the peak ice numberdensity Heymsfield,A. J., and R. M. Sabin,Cirruscrystalnucleation
,
,
,
i
i
i
i
i
ß
shouldbe lessthan 10 cm-3; whereasthe observations by homogeneousfreezingof solutiondroplets, J. Airnos.
Sci., J6, 2252, 1989.
onApril 30 showed
icenumberdensities
of 20-40cm-3.
The largestnumberof ice crystalsis generatedif the
temperature is just cold enoughsuchthat liquid drops
are activated. Above this temperature, the ice number density decreaseswith increasingtemperature becausethe liquid dropletsget larger beforethey freeze.
Hence,when the first few dropletsfreeze,the resulting
large ice crystals deplete the vapor rapidly, resulting
in rapid evaporationof the remaining dropletsbefore
they can freeze. If the temperature drops just below
-37.5øC suchthat the sulfate aerosolsfreezebefore liquid droplets are activated, then the peak ice crystal
number density drops dramatically. This lower number
density resultsfrom the fact that the aerosolfreezing
rate is strongly dependent on their size and composition, and the freezing temperature varies substantially
acrossthe aerosolsize range. Hence, the largest few
aerosolsfreeze first, and the resulting crystalsdeplete
the vapor before more aerosolscan freeze.
The transition temperature of about -37.5øC predicted by our calculationsis consistentwith previous
Heymsfield,A. J., and L. M. Miloshevich,Homogeneous
ice nucleationand supercooledliquid water in orographic
wave clouds,J. Atmos. Sci., 50, 2335, 1993.
Heymsfield,A. J., and L. M. Miloshevich,Relativehumidity
and temperature influenceson cirrus formation and evolution: Observationsfrom wave clouds and FIRE II, J.
Atmos. S½i., 5œ,4302, 1995.
Jensen,E. J., et al., Microphysicalmodelingof cirruspart I:
Comparisonwith 1986 FIRE IFO measurements,J. Geophys. Res.,, 99, 10421, 1994.
Jensen, E. J., and O. B. Toon, Ice nucleation in the upper troposphere: Sensitivity to aerosolnumber density,
temperature, and coolingrate, Geophys.Res. Lett., , 21,
2019, 1994.
Jensen,E. J., and O. B. Toon, The potential impact of soot
particlesfrom aircraft exhauston cirrusclouds,Geophys.
Res. Lett.,, ϥ, 249, 1997.
Liou, K.-N., S.C. Ou, and C. Koenig,An investigationon
the climatic effect of contrail cirrus, Lecture Notes in En-
grg., Vol. 60, Springer,Berlin, 138-153,1990.
Sassen, K., et al., Mesoscaleand microscale structure of
cirrus clouds: Three case studies, J. Atmos. Sci., •6,
wave-cloud
measurements
[Heyrnsfield
andMiloshevich, 371, 1989.
1995]. Their measurements
indicateddropletswith Sassen,K., and G. C. Dodd, Haze particle nucleationsimulations in cirrus clouds, and applicationsfor numerical
radii up to a few •m in a cloud leading-edgewith a
and lidar studies,J. Atmos. S½i.,•6, 3005-3014,1989.
temperature of-35øC. In a leading edge with a temperature of-37øC, dropletswere marginally detectable Tabazadeh,A., E. Jensen,and O. B. Toon,A modeldescriptionforcirruscloudnucleation
fromhomogeneous
freezing
with radii of only 1-2 urn. In a penetration at -44øC,
of sulfateaerosols,submittedto J. Geophys.Res., 1997.
no dropletsformed. Also, the earlier wave-cloudmeasurementsshowedlowerice numberdensities(about 10 Eric. J. Jensen,NASA Ames ResearchCenter, MS 245-4,
cm-3) in the penetration
at -44øCthanin the warmer Moffett
cases(about20 cm-3).
Field, CA 94035.
Heterogeneous
freezingnucleicouldpotentially cause (ReceivedJune25, 1997; revisedNovember20, 1997;
aerosolfreezingbeforeactivationinto dropletsoccurred, acceptedNovember25, 1997.)