Response of the Nevzorov hot wire probe in clouds …...2004 (Arctic Study of Tropospheric Aerosols, Clouds and Radiation) performed over the island of Svalbard in the Arctic a constant-temperature

Atmos. Meas. Tech., 2, 779–788, 2009www.atmos-meas-tech.net/2/779/2009/© Author(s) 2009. This work is distributed underthe Creative Commons Attribution 3.0 License.

AtmosphericMeasurement

Techniques

Response of the Nevzorov hot wire probe in clouds dominated bydroplet conditions in the drizzle size range

A. Schwarzenboeck1,2, G. Mioche1,2, A. Armetta1,2, A. Herber3, and J.-F. Gayet1,2

1Clermont Universite, Universite Blaise Pascal, LAMP, 63177 Aubiere, France2CNRS, UMR 6016, LAMP, 63173 Aubiere, France3Alfred Wegener Institute for Polar and Marine Research (AWI), Columbusstrasse, 27568 Bremerhaven, Germany

Received: 27 April 2009 – Published in Atmos. Meas. Tech. Discuss.: 15 May 2009Revised: 20 October 2009 – Accepted: 30 October 2009 – Published: 4 December 2009

Abstract. During the airborne research mission ASTAR2004 (Arctic Study of Tropospheric Aerosols, Clouds andRadiation) performed over the island of Svalbard in theArctic a constant-temperature hot-wire Nevzorov Probe de-signed for aircraft measurements, has been used onboard theaircraft POLAR 2. The Nevzorov probe measured liquid wa-ter (LWC) and total condensed water content (TWC) in su-percooled liquid and partly mixed phase clouds, respectively.As for other hotwire probes the calculation of LWC and/orTWC (and thus the ice water content IWC) has to take intoaccount the collection efficiencies of the two separate sensorsfor LWC and TWC which both react differently with respectto cloud phase and what is even more difficult to quantifywith respect to the size of ice and liquid cloud particles. Thestudy demonstrates that during pure liquid cloud sequencesthe ASTAR data set of the Nevzorov probe allowed to im-prove the quantification of the collection efficiency, particu-larly of the LWC probe part with respect to water. The im-proved quantification of liquid water content should lead toimproved retrievals of IWC content. Simultaneous retrievalsof LWC and IWC are correlated with the asymmetry factorderived from the Polar Nephelometer instrument.

1 Introduction

Condensed water content (CWC: liquid and/or ice water con-tent) in clouds is a fundamental parameter in cloud physicsresearch. To experimentally measure liquid water content(LWC) on research aircraft, hot-wire probes are state of theart instruments (Ruskin, 1976; Nicholls et al., 1990). Untiltoday the most commonly used hot-wire devices have beenthe Johnson-Williams probe, the DMT LWC-100, and the

Correspondence to:A. Schwarzenboeck([email protected])

King probe (King et al., 1978). These hot-wire probes aredifficult to calibrate concerning their exact collection effi-ciencies. This is due to uncertainties on the one hand topredict the trajectories of hydrometeors having diameters be-low 5–10µm (Korolev et al., 1998), and on the other handdue to incomplete evaporation and break-up during and afterimpaction of hydrometeors having diameters beyond 40µm(Biter et al., 1987; Strapp et al., 2003). Another type of in-strument to measure cloud liquid water content is the ParticleVolume Monitor (PVM) based on the principle of light diffu-sion by an ensemble of droplets (Gerber, 1993; Wendisch etal., 2002). A principal problem of the PVM, as for other opti-cal instruments, is the exact knowledge of the sample volumeand an eventual drift of the baseline.

Besides these direct measurements of LWC, estimates ofthe condensed water contents (LWC and IWC) can be de-rived by integrating the size spectra given from 1-D or 2-D cloud probes. Examples for 1-D probes are the classicalForward Scattering Spectrometer Probe FSSP (Baumgard-ner, 1985) and its newer version called Cloud Droplet ProbeCDP from DMT. Concerning 2-D probe imagery, classicalinstruments are the 2-D-P and 2-D-C (Knollenberg, 1981)probes, the newer Cloud and Precipitation Imaging ProbesCIP and PIP, respectively, and also the Cloud Particle ImagerCPI (Lawson, 1998). Another method is to entirely samplethe condensed water content as done with the CVI (Coun-terflow Virtual Impactor) sampling technique (Ogren et al.,1985), evaporating all hydrometeors in an environment of dryair to finally derive the condensed water content for exam-ple with the technique of Lyman-a hygrometry (Strom et al.,1994). The CVI technology has been recently integrated intoan oversize PMS canister, including hygrometer, by DropletMeasurement Technologies (DMT). Real-time informationon cloud ice water content (IWC), however, stays a majorchallenge, particularly in mixed-phase clouds.

Published by Copernicus Publications on behalf of the European Geosciences Union.

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780 A. Schwarzenboeck et al.: Response of the Nevzorov hot wire probe

In 1998, Korolev et al. (1998) presented an extended char-acterisation of the Nevzorov instrument to overcome the lackof simultaneous and separate measurements of liquid and icewater contents. The Nevzorov probe which is a constant-temperature, hot-wire probe has been explicitly designed forrapid and simultaneous measurements of the ice and liquidwater contents (phase discrimination) and thus, was exten-sively used on research aircraft for microphysical character-isation of mixed-phase clouds (Korolev, 2003) and in effec-tive diameter studies (Korolev, 1999). It consists of two sep-arate sensors for measurements of cloud liquid and total (iceplus liquid) water content, giving two linear equations for thevariables LWC and IWC to be solved.

In principal, Korolev (1998) gave some insight in dry airbaseline drift with airspeed, temperature, and pressure vari-ations to explain possible offset variations for instance dur-ing vertical flight patterns. Moreover, collection efficienciesof the two separate sensors with respect to water and iceare discussed up to cloud particle (droplets, crystals) diame-ters of 25µm. The probe performance is then discussed bymeans of measurement examples comparing the NevzorovLWC and TWC data to the King and FSSP probe (Baumgard-ner, 1985) and also 2-D-C probe (Knollenberg, 1981) deriveddata. The correlation seems to be acceptable knowing thelimited performance of the FSSP in view of larger ice crystals(Gardiner and Hallet, 1985) and the underestimation of watercontent by the 2-D-C due to the fact that below 150µm thisprobe is underestimating the crystal concentration (Gayet,1993). The Nevzorov LWC and TWC sensors correlate quitewell in small-droplet clouds. In mixed phase clouds, theTWC sensor measurement exceeds the LWC measurementdue to its much higher efficiency in detecting ice particles, asexpected due to the aerodynamic design of the capture vol-ume. In large-droplet conditions of pure liquid clouds, theTWC measurement exceeds the LWC measurement, becausethe TWC sensor has much lower re-entrainment losses, anddue to the fact that the existing collection efficiency assump-tions for these probes in such conditions have not been wellcharacterized to date.

Another study (Strapp, 2003) conducted in the NASAIcing Research Tunnel (IRT) presents results on NevzorovLWC and TWC sensor retrievals of pure liquid droplet popu-lations, as a function of the median volume diameter (MVD– also noted as DV50) which is the diameter in the LWC ver-sus diameter distribution at which half of the liquid water isbelow, and the other half is above that diameter.

Whereas the Nevzorov TWC sensor matches the windtunnel LWC (within WT LWC measurement accuracy), theNevzorov LWC sensor significantly underestimates the WTLWC, particularly for larger median volume droplet diame-ters. The Nevzorov probe was also studied in the NRC Alti-tude Icing Wind Tunnel (AIWT) to assess differences in theresponse of LWC and TWC sensors of the probe with respectto ice (Korolev, 2002). These tests at the NRC high-speed ic-ing tunnel have provided verification of the TWC recovery

for small frozen droplets to an accuracy of approximately10%–20% (Korolev, 2002). However, a series of tests at theCox and Co. wind tunnel, using ice shaved from blocks tosimulate ice particles, revealed that a fraction of these ice par-ticles bounce out of the sample volumes of various hot wiredevices, including the Nevzorov TWC probe, resulting in anunderestimate of the IWC measurement (Emery et al., 2004;Strapp et al., 2005). Recently, a new design of the NevzorovTWC sensor cone has been studied in the Cox wind tunnel(Korolev, 2008), where collection efficiencies with respect toice particles of a new deep cone (60◦) have been comparedto those of the classical shallow cone (120◦). It turns out thatthe classical shallow cone is considerably underestimatingIWC due to ice particles bouncing off the TWC cone surfaceback into the air stream and being swept away.

The results presented here in this study, however, aremainly dedicated to improve our knowledge of the Nev-zorov probe performance in large-droplet conditions of liq-uid/supercooled clouds, when drizzle size droplets are domi-nating LWC.

2 Field project

The geographic anomalies (high surface albedo, low solar el-evation) in Polar regions were the principal motivation to ini-tiate the international program Arctic Study of TroposphericAerosols, Clouds, and Radiation (ASTAR) to experimentallyinvestigate the direct and indirect aerosol effects in the Arc-tic. The ASTAR project is particularly dedicated to investi-gate origin, transport pathways, vertical structure, physico-chemical properties and radiatif impact of the troposphericArctic aerosol as well as related aerosol-cloud and cloud-radiation interactions (particularly ice phase).

Within these objectives, aircraft in situ and remote sensingmeasurements on the two research aircraft Polar2 and Polar4from Alfred-Wegener Institute (AWI), Germany, were con-ducted from the island of Spitsbergen (Norway) to study themicrophysical and optical properties of Arctic aerosol andsupercooled to mixed-phase clouds.

Cloud in situ measurements were performed onboard Po-lar2 using a Nevzorov probe (Korolev, 1998), the PolarNephelometer (Gayet, 1997), a Cloud Particle Imager (Law-son, 1998 and 2001), and classical FSSP and 2-D-C PMSprobes. In total 14 cloud flights have been performed on Po-lar2 during the entire ASTAR 2004 flight campaign for de-tailed (cf. Table 1) microphysical and optical cloud in situstudies. In particular, the campaign yielded observations oficed nimbostratus, altostratus, and stratus clouds which areoften found in the Arctic boundary layer. Despite just slightlynegative temperatures between 0 and−20◦C encounteredduring Polar-2 flight missions, the ice phase (mixed phase)was observed quite frequently. Simultaneous research flightswere performed on the Polar4 aircraft to characterise theaerosol particles. During the entire period aerosol particle

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A. Schwarzenboeck et al.: Response of the Nevzorov hot wire probe 781

Table 1. Summary of cloud in situ instrumentation mounted onPolar-2 research aircraft during ASTAR 2004.

Instrument Measurement parameter Range

Polar Scattering phase functionNephelometer (asymmetry parameter, 3–800µm

extinction coefficient,...)

CPI Cloud particle microphysical andmorphological properties D>10µm

Nevzorov Ice and liquid water content 0.–1. g/m3

PMS FSSP Cloud particle size distribution 3–95µm

PMS 2-D-C Cloud particle size distribution 25–800µm

concentrations, measured with a CPC 3010 (measuring par-ticles larger 11 nm), have been very low (<300 aerosol par-ticles per cm3). These clean conditions should have beenat the origin of frequently observed supercooled drizzle sizedroplets (cf. Fig. 1), up to some hundreds ofµm in diam-eter even in very shallow stratus type Arctic cloud layers(∼500 m between cloud base and cloud top). In addition,lowest IN concentrations (coming along with low aerosolconcentrations) may slow down considerably the ice relatedprocesses including nucleation, multiplication, and precipi-tation. Consequently, only little precipitation was observedduring ASTAR 2004. Moreover, onboard nadir looking li-dar observations which revealed specific cloud features, i.e.stratiform layers and ice crystals precipitating from beyond(Stachlewska et al., 2006; Gayet et al., 2007) determinedflight levels for subsequent cloud in situ measurements. Thecloud in situ measurements thus could confirm the presenceof the “feeder-seeder” mechanism, initiating the ice phase inlow level stratocumulus cloud layers at slightly negative tem-peratures.

3 Instrumentation: Nevzorov probe and other cloud insitu instruments

The instrumental payload used for the cloud in situ studieson Polar-2 (Dornier-228) comprised an extensive, state-of-the art set of cloud microphysical/optical instruments includ-ing particularly: (i) a Polar Nephelometer for the measure-ment of the scattering phase function of ice particles, (ii) aCloud Particle Imager (CPI) recording digitised cloud par-ticle images at high pixel resolution (2.3µm), and (iii) theNevzorov probe for the measurement of the liquid and icewater content in supercooled and mixed-phase clouds. Themain focus in this study will be given to the performance ofthe Nevzorov probe. The Nevzorov sensors have been aremounted the probe pylon on the right side of the fuselageabout three meters behind the nose of Polar2 and at a dis-tance of roughly 25 cm from the aircraft skin. The particle

200 µm

Fig. 1. Presence of drizzle size droplets (100–500µm) in stratustype Arctic clouds during ASTAR 2004.

trajectories are not perturbed by other installations upstreamthe probe. Even though we cannot completely rule out de-pletion or enrichment effects at the position of the Nevzorovprobe (aircraft flight trajectory related wind vector), at leastboth sensors (TWC and LWC) have been exposed to identicaldroplet sizes.

The two TWC and LWC sensors of the Nevzorov hot-wireprobe (kept at constant temperature) are composed each ofa reference and a collector/sample zone, whereby the refer-ence zone will not undergo cloud particle impaction. Dueto cloud particle impaction (and thus evaporation) the sam-ple zone experiences heat loss, which has to be compensated,thus, making the hotwire probe a constant temperature probe.The necessary power to apply to the sensors is related toLWC and TWC, both functions of electrical powersPLWCandPTWC, sensor surfacesSLWC andSTWC, the velocity U,and the four collection efficiencies of LWC and TWC sensorswith respect to water droplets and ice crystals. In addition,the known sensor resistancesRLWC andRTWC appear in theelectrical powers

PLWC =VLWC 2

RLWC(1)

and

PTWC =VTWC 2

RTWC(2)

supplied to the sensors via the voltagesVLWC and VTWC.CombiningPLWC andPTWC supplied to both sensors givesone single solution for LWC and IWC (Korolev, 1998):

LWC =

PLWC −PTWC×εLWC,crystals×SLWC

εTWC,crystals×STWC

LV × SLWC ×U ×

(εLWC,droplets−

εLWC,crystals×εTWC,dropletsεTWC,crystals

) , (3)

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and

IWC =

PTWC−PLWC×εTWC,droplets×STWC

εLWC,droplets×SLWC

(Lf +LV)× STWC×U ×

(εTWC,crystals−

εLWC,crystals×εTWC,dropletsεLWC,droplets

) . (4)

The most crucial question then is the exact knowledge ofTWC and LWC sensor efficiencies, depending on particlephase (droplets, crystals) and size. Lv and Lf denote latentheat of vaporization and fusion, respectively. Since duringASTAR 2004 we encountered pure supercooled and mixedphase conditions, but no pure ice phase clouds, we will fo-cus the discussion of the Nevzorov probe response to flights(flight sequences) of pure liquid cloud phase in the Arctic en-vironment. In this way we can skip the two sensor efficien-cies related to ice (εLWC,crystalsandεTWC,crystals), in order tosolely study those two efficiencies related solely to droplets:εLWC,dropletsandεTWC,droplets.

Thus, when ice is absent the TWC and LWC sensors indi-vidually give the liquid water content:

LWC(LWCsensor) =PLWC

εLWC,droplets×LV × SLWC ×U(5)

from the LWC sensor and

LWC(TWCsensor) =PTWC

εTWC,droplets×LV ×STWC×U(6)

from the TWC sensor.Both equations should give identical amounts of LWC in

pure liquid cloud, where liquid water content depends on air-craft velocity U, the electrical powers PLWC or PTWC sup-plied, and the collection efficiency of LWC and TWC sensorswith respect to water droplets:

LWC = f (PLWC,U,εLWC,droplets) = f (PTWC,U,εTWC,droplets). (7)

4 Description of the dataset and data processing

4.1 Cloud presence criterion

Ideally the Nevzorov probe signals should have very smallto zero offsets, achievable at constant flight levels. Beforeentering a cloud the collector signal has to be adjusted to thereference signal to operate the sensors at zero offsets. Thesignal ideally returns to zero after leaving the cloud at thesame level, which indicates a zero offset for the entire leg atthat flight level. To avoid truncated slightly negative signals itmay be even worthwhile to operate the Nevzorov probe witha very small positive offset. In addition, during the ASTARexperiment the flight pattern consisted sometimes of climbsand descents in clouds, which made it difficult to achievethe objective of zero offset. Since for the Nevzorov data itis necessary to subtract the offset in both raw signals, beforecalculating the condensed water contents LWC and IWC, ouridea was to benefit from simultaneous measurement signalsof other fast and highly sensitive cloud probes, like the Po-lar Nephelometer, to define precisely cloud presence (Fig. 2),

0

20

40

60

9 9,5 10 10,5 11 11,5 12 12,5

ex

tin

cti

on

NP

[k

m-1

]

hour

Fig. 2. Definition of cloud presence via the extinction coefficientcalculated from the Polar Nephelometer (22 May 2004).

such that experimentally we can calculate the offsets of Nev-zorov probe raw signals for clear sky passages and interpo-late the offset within cloud sequences.

4.2 Offset correction

The Nevzorov offset has to be deduced from the measuredsignal to get the raw cloud related signal. Figure 3 showsan example (corresponding to Nephelometer cloud detectionin Fig. 2) of an unusually high offset caught during a flight.Due to the fact that the electrical powerP supplied to thetwo sensors is proportional to the square of the correspondingvoltagesV , the pure cloud related signalVcloud is calculatedfrom the total raw signalVraw and the offset signalVoffset inthe following way:

Vcloud=√

Vraw 2 −Voffset 2. (8)

5 Results for the Nevzorov probe response toarctic clouds

5.1 Discussion of the sensor efficiencies in liquid clouds

In order to get an idea of the variation of droplet spectra ob-served during the ASTAR campaign, Fig. 4 presents aver-aged number size distributions for some of the flights. Inparticular, the large-droplet condition is often dominatingthe number size distributions. The collection efficiency ofthe Nevzorov TWC sensor for drizzle-size droplets is closeto unity, as was demonstrated in wind tunnel testing at theNASA Icing Research Tunnel (Strapp et al., 2002). Fur-thermore, Strapp et al. (2003) presented a detailed studyof Nevzorov LWC and TWC sensor response with respectto large-droplet conditions (Fig. 5). The study was con-ducted in the NASA Glenn Icing Research Tunnel (IRT) in1998. The Nevzorov LWC sensor with cylindrical sensorwire of 1.8 mm in diameter was found to measure solely50% of the LWC at a median volume diameter of approxi-mately 200µm. Similar results were first shown by Biter etal. (1987) for the King probe, another cylindrical hot wirelike the Nevzorov LWC, and for various other cylindrical hotwires by Strapp et al. (2003). The Nevzorov TWC sensor



0

1

2

3

4

5

6

-3

-2

-1

0

1

2

3

9 9,5 10 10,5 11 11,5 12 12,5

corr

ecte

d L

WC

sig

nal

[V

]

LW

C r

aw s

ign

al [

V]

hour

Fig. 3. Offset subtraction for a high offset example of the LWCsensor (22 May 2004).

was found to agree within +/−20% of tunnel reference LWCacross the entire tested range of MVD within 11–236µm.According to Strapp (2003) the accuracy of IRT tunnel LWCis estimated to be 5% for populations of small droplets and20% for populations of large drops. The findings that LWCretrievals from Nevzorov TWC sensor throughout all dropletMVD are higher than IRT wind tunnel LWC measurementsshould indicate that the Nevzorov TWC sensor may not missa significant amount of LWC even within droplet populationsshowing large values for MVD (∼200µm). The NevzorovTWC sensor is therefore considered the most accurate hot-wire estimate of LWC in large-droplet conditions of purewater clouds, whereas LWC sensor efficiencies remain un-clear in these conditions. Thus, we will focus here primarilyon the Nevzorov sensor efficiencies with respect to water,knowing that the ASTAR 2004 cloud flights sampled eithersupercooled or mixed phase clouds. The phase recognitionof clouds was performed using the simultaneously operatedCloud Particle Imager CPI. For subsequent data analysis ofpure liquid clouds or liquid cloud sequences, the Nevzorovdata were analyzed when the CPI detected pure liquid phase.

The Nevzorov LWC and TWC sensors correlate quitewell in small-droplet liquid clouds whereεLWC,droplets andεTWC,droplets efficiencies are close to one. Taking theabove Eqs. (5) and (6) of calculated liquid water contentsfrom LWC sensor and TWC sensor, and imposing thatLWC(LWCsensor)=LWC(TWCsensor) for whatever population ofdroplet sizes, leads to the ratio of sensor efficiencies relatedto the raw signals:

εLWC,droplets

εTWC,droplets=

PLWC ×STWC

PTWC× SLWC=

VLWC 2 ×RTWC×STWC

V 2TWC× SLWC ×RLWC

= 1.595×VLWC 2

VTWC 2. (9)

0

0,01

0,02

0,03

0,04

0,05

0,06

10 50 90 130 170 210 250 290 330 370

co

nce

ntr

ation

(# µ

m-1

cm

-3)

diameter (µm)

21.05.2004

29.05.2004

15.05.2004

04.06.2004

07.06.2004

05.06.2004

03.06.2004

22.05.2004

Fig. 4. Variation of droplet size spectra during ASTAR 2004.

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

0 50 100 150 200 250

Nev

zo

rov

L

WC

/

WT

L

WC

MVD (µm)

Nevzorov LWC sensor

Nevzorov TWC sensor

Fig. 5. Findings of Strapp et al. (2003) for the Nevzorov TWC andLWC sensor behaviour with respect to the wind tunnel referenceLWC in pure liquid clouds.

The factor 1.595 has been calculated from known instrumen-tal parameters of sensor surfaces and electrical resistancesof the respective Nevzorov probe used during ASTAR 2004.Plotting 1.595×V 2

LWC againstV 2TWC for all measured AS-

TAR data in pure liquid clouds, reveals thatV 2TWC is in gen-

eral dominating 1.595×V 2LWC, thus, demonstrating that the

liquid water recovery from TWC sensor is higher than therecovery from LWC sensor (Fig. 6). Merely at lower val-ues of raw signals it nevertheless happens that the LWC sig-nal slightly dominates the TWC sensor signal (data pointsabove the theoretical line of equal LWC and TWC sensorefficiencies with respect to water). To better understand dif-ferences in efficiency of water recovery of both sensors, wehave to relate the LWC recovery to the respective ensem-ble of sampled cloud droplets. For a more detailed anal-ysis of the above results, the ratios of the two efficienciesεLWC,dropletsandεTWC,dropletsof LWC and TWC sensors arestudied as a function of the droplet size distribution, that wetry to best parameterize using an adequate cloud particle di-ameter. Strapp et al. (2003) have chosen in their efficiency



study of the Nevzorov probe the median volume diameterMVD as the spectrum reference diameter, to parameterizethe IRT wind tunnel droplet populations, where MVD is de-fined as the diameter out of the droplet spectrum at which50% of the water is below, and 50% is above that diameterMVD:

MVD∫0

D3N(D)dD =

Dmax∫MVD

D3N(D)dD. (10)

MVD is particularly used to describe artificially produceddroplet populations, thus, representing an adequate diame-ter parameterization for the droplet populations sprayed intothe IRT tunnel. Whereas droplet distributions generated ina wind tunnel are often characterized by long tails in the“bell” shaped mono-modal distributions, these artificial dis-tributions lack the typical distinct mode in the small-dropletpart seen usually in atmospheric distributions. To best pa-rameterize natural droplet populations (mono-modal and par-ticularly bi-modal) encountered during ASTAR (this study),we have chosen the volume-weighted mean diameter VMDdefined as

VMD =

Dmax∫0

D4N(D)dD

Dmax∫0

D3N(D)dD

. (11)

Compared to MVD used in the IRT study, VMD should beless sensitive to the presence of observed small droplets co-existing with large drops in the drizzle size range, most im-portant for this study. Furthermore, when comparing thisstudy to the findings presented by Strapp et al. (2003), wehave to take into account that VMD should slightly exceedMVD calculations (by 0–10% for the droplet size distri-butions measured during ASTAR). In addition, we have tostate that VMD (also MVD) estimation can be difficult withcommon probes. The difficulty to derive an absolute esti-mate of the uncertainty in calculating cloud particle VMD(or MVD) for measurements of (i) a specific cloud probe,(ii) a particular combination of several probes, and (iii) whenusing/comparing different cloud probes arises from individ-ual probe performances/characteristics, from data process-ing software, and from other probe and/or operator specificparameters. This could be causing some of the differencesbetween the results presented by Strapp et al. (2003) andthe results presented here (Fig. 7). Putting together all 14scientific research flights within the ASTAR project, Fig. 7shows plotted ratios of the two efficienciesεLWC,dropletsandεTWC,droplets of LWC and TWC sensors during pure liquidcloud sequences as a function of VMD. As a result we ob-serve that for very small droplet diameters up to roughly 20–40µm the LWC sensor seems to be more efficient than theTWC sensor, which is due to the fact that the large TWC conerepresents an important obstacle for the cloud particles which

0

20

0

5

10

15

20

0 5 10 15 20

1.5

95

x V

LW

C²

VTWC²

Fig. 6. “Correlation” of LWC and TWC sensor voltages inpure liquid clouds, a theoretical line of equal sensor efficienciesεLWC,droplets=εTWC,droplets, is added.

begin quite early to curve around the sensor and thus don’timpact as efficient as on the smaller LWC sensor obstacle.Droplet sizes beyond several tens of micrometers, however,should impact more efficiently on the TWC sensor but lessefficiently on the LWC sensor with increasing droplet diame-ters. It is important to recall that for the two previous figureswe have chosen only liquid cloud sequences automaticallyderived from CPI data of the entire ASTAR 2004 campaign.All data were averaged over 10 s intervals to avoid larger sta-tistical fluctuations. The signal averaging of FSSP, CPI, 2-D-C and Nevzorov data was chosen since the instrumentswere not mounted side by side. In addition, the evaporationof droplets on the surface of hot wire probes is not instanta-neous, leading to a slightly delayed and smoothed signal asa function of droplet diameters. They-axis error bars reflectthe standard deviation of the 10 s average calculations of theratio of the sensor efficiencies. Possibly an additional errormay be due to small gain differences between the LWC andTWC probe, since we cannot measure the calibration con-stants perfectly, so there might be some possibly small lineareffect.

To interpret the above results we recall that Korolev (1998)presented theoretical calculations of the collection efficien-cies with respect to liquid droplets of (i) the cylindrical LWCsensorεLWC,dropletsbased on Voloshchuk (1971) and (ii) ofthe conical TWC sensor efficiencyεTWC,dropletsbased on ex-perimental studies (Nevzorov, 1983). Moreover Strapp etal. (2003) presented collision efficiency estimates for a rep-resentation of the Nevzorov TWC sensor, using the NASALEWICE model, whereεTWC,dropletsdeviates little from re-sults shown in Korolev (1998). In Korolev’s work the twoefficienciesεLWC,dropletsandεTWC,dropletswere presented asa function of effective diameter Deff limited to diameters upto 25µm and calculated according to:

εSENSOR,droplets=Deff 2

Deff 2 +D02

(12)



0,0

0,3

0,5

0,8

1,0

1,3

1,5

0

0,25

0,5

0,75

1

1,25

1,5

0 50 100 150 200 250 300

LW

CN

evzo

rov

/ T

WC

Ne

vzo

rov (

Str

ap

p )

LW

C,d

rop

lets

TW

C,d

rop

lets

MVD [µm] for IRT studyVMD [µm] for ASTAR study

ASTAR 2004 study

IRT wind tunnel study (Strapp (2003))

Fig. 7. Efficiency ratio of LWC to TWC Nevzorov sensors with respect to pure water droplets. In addition, ratio of Nevzorov LWC overTWC from Strapp (2003).

with D0=7.5 for TWC sensor andD0=1.7 for the LWCsensor, respectively, for an aircraft velocity in the order of100 m/s. For droplet diameters beyond 25µm, εTWC,dropletsshould approach the ideal value of 1, whereasεLWC,dropletsmay decrease to values significantly smaller than 1, at leastfor diameters of several hundreds ofµm (Korolev, 1998). Anexact behaviour ofεLWC,dropletscurve has not been discussedyet and will be determined subsequently in this study. Notknowing the exact size distributions that led to (i) deducedMVD in the wind tunnel study of Strapp et al. (2003) and (ii)the effective diameters in theεTWC,dropletsefficiency calibra-tion study of Nevzorov (1983), we make the assumption thatthese experimental spectra were “bell” shaped distributions.The assumption that

D84

D50=

D50

D16= σ (13)

(for considered lognormal distributions), then translates(within error bars calculated for 1.5<σ<2.0) the effec-tive droplet diameters from Nevzorov (1983) into MVDand VMD (Martin et al., 1994; Hinds, 1999). Knowingthe droplet size distribution, median volume and volume-weighted mean diameters can be calculated and convertedinto each other. In addition, an extrapolation ofεTWC,dropletsof the conical TWC sensor to values approaching 1 for clouddroplet effective diameters far above 25µm has been sug-gested by Korolev (1998). This suggestion has been sup-ported by Strapp (2003) due to measurements in the IRTwind tunnel, where the Nevzorov TWC sensor measure-ments are slightly, but systematically, exceeding the tun-nel reference LWC measurements (as well for small-dropletas for large-droplet conditions) within the estimated accu-

racy of wind tunnel reference LWC measurements. Withinthe assumptions of the above mentioned extrapolation, thisallows to give an estimate of the least known efficiencyεLWC,droplets. The procedure is presented in Fig. 8 wherethe efficiency ratio from Fig. 7 has been multiplied by theextrapolatedεTWC,droplets to deduceεLWC,droplets. A maxi-mum in εLWC,droplets is reached roughly around 20–30µm,indicating that droplets smaller than 20–30µm partly tendto curve around the LWC sensor, whereas larger ones im-pact with decreasing efficiencies related to a loss in dropletmass.εLWC,dropletsrapidly starts to decrease (with increasingdroplet size) beginning at droplet sizes beyond 30–40µm.

This study therefore suggests for VMD diameters beyond25µm the following parametrization forεLWC,dropletsof theNevzorov probe:

εLWC,droplets(VMD) =a0[

1+

{V MD−a1

a2

}2×

{2

1a3 −1

}]a3(14)

with a0 = 0.98,a1 = 20,a2 = 90,a3 = 0.26;

5.2 Application of above calculatedεLWC,dropletsefficien-cies to calculate IWC and LWC in observed mixedphase clouds during ASTAR 2004

Accurate determination of the liquid VMD from particleprobes in mixed-phase conditions is exceedingly difficult.The only reliable means is based on the CPI distributions,and therein the separation of the ice particles from the wa-ter droplets. The CPI images were preprocessed usingthe software (Lefevre, 2007) developed at the Laboratoirede Meteorologie Physique (LaMP). More specifically, weadded, to the original automated habit classification, three



0

0,2

0,4

0,6

0,8

1

1,2

0 50 100 150 200 250 300

LW

C,d

rop

lets

WC

,d

rop

lets

VMD [µm]

LWC,droplets (Korolev) TWC,droplets (Korolev & extrapolation)

LWC,droplets (ASTAR measurement data)

LWC,droplets (proposed extrapolation)

LWC,droplets (Korolev) TWC,droplets (Korolev & extrapolation)

LWC,droplets (ASTAR measurement data)

LWC,droplets (proposed extrapolation)

Fig. 8. Derived LWC sensor efficiencyεLWC,dropletsassuming the TWC sensor efficiencyεTWC,droplets from Korolev (1998) includingextrapolation ofεTWC,dropletsfor large-droplet conditions.

habit types and used our algorithm to evaluate the effectivesampling volume of the CPI (Lefevre, 2007). To be ableto calculate IWC and LWC in mixed phase clouds for theNevzorov probe, thus, using size and phase dependent Nev-zorov probe efficiencies, we have to determine and calculatephase and MVD, respectively, from size distributions for liq-uid and solid cloud particles. The most critical point is thecorrect phase discrimination (surface roughness) for spheri-cal particles, which is more difficult to determine for smallestspherical particles. However, we are convinced that beyonda diameter of 50µm we can be quite sure from CPI imagesabout the phase (liquid or ice) of spherical particles capturedon CPI images.

For further analysis of the Nevzorov data within realmixed phase Arctic clouds sampled during ASTAR 2004,efficienciesεTWC,dropletsandεLWC,dropletsare applied as ex-trapolated and calculated above, respectively. Furthermore,the efficiencyεLWC,crystals is estimated to be approximately0.11 (Korolev, 1998), explaining a slight reaction of the LWCsensor with respect to impacting ice crystals, which thenbounce off. Unfortunately, the value of 0.11 is only a roughestimate sinceεLWC,crystals will certainly depend on crystalsize and probably shape, however, we have no other estima-tion than was given by the manufacturer. Finally, the effi-ciency εTWC,crystals is considered to equalεTWC,droplets foridentical median mass aerodynamic diameters (thus, includ-ing the particle density), to take into account ice particleswith estimated density of 0.9. An eventual discussion of sen-sor efficiency variations with ice crystal shape seems to becomplicated and is beyond the scope of this study. In ad-dition, Korolev (2008) presented evidence that ice particlesmay significantly bounce off from the surface of the Nev-

zorov TWC sensor cone (and other hot-wire sensor geome-tries). They demonstrated thatεTWC,crystals of the commer-cial shallow (120◦) TWC cone of the Nevzorov Probe couldbe up to 3 times smaller thanεTWC,crystalsfor a modified deepcone (60◦) of the same sensor. Due to the lack of ice crystalcalibration standards a detailed investigation of the poor IWCrecovery by the TWC shallow cone is still under discussion.Future work will have to detail dependencies ofεTWC,crystals,that may exist with respect to cloud phase (mixed phase,pure ice phase) and as a function of crystal diameter (VMD,MVD). We decided here not to apply a simple scaling factorof 3 for εTWC,crystals for several reasons: first of all we havebeen measuring in mixed phase clouds, compared to pure iceclouds in wind tunnel and in natural cloud studies (Korolev etal., 2008). Second, we should learn more about correlationsbetween the crystal habit/size and ice water recovery of theTWC Nevzorov probe. Moreover, retrieved IWC (and TWC)from the Nevzorov shallow cone during ASTAR has been ex-ceeding IWC values presented in the Korolev et al. study bya factor of at least two, such that we would have to extrapo-late the Korolev et al. findings to larger IWC contents, whichmight be tricky. Thus, the above assumed sensor efficien-cies with respect to water (high reliability) and ice (signifi-cant lack of knowledge) as a function of diameter, allow atleast under the described efficiency assumptions to estimatesimultaneously IWC and LWC of Arctic mixed phase cloudsas described in Sect. 3.

Figure 9 presents the results of calculated IWC and LWCin terms of the fraction of ice water content IWC out of totalcondensed water TWC (TWC=LWC+IWC) plottet againstthe asymmetry parameter. The asymmetry parameterg isdeduced from the scattering phase function of the Polar



0,74

0,76

0,78

0,8

0,82

0,84

0,86

0 0,2 0,4 0,6 0,8 1

asym

met

ry g

ice fraction IWC / TWC

22.05.2004

01.06.2004

02.06.2004

07.06.2004

25.05.2004

21.05.2006

Fig. 9. Cloud ice fraction related to asymmetry parameter deducedfrom scattering phase functions of the Polar Nephelometer.

Nephelometer (Gayet, 1997) and gives an indication of themean cosine of light scattered in a two-dimensional planefrom cloud particles. The scattering characteristics (asym-metry factor etc.) vary with respect to cloud phase, cloudparticle size, ice crystal shape, surface roughness and others.Theoretically the asymmetry factor is comprised between 0for isotropic scattering and 1 in case that the light is not atall deviated with respect to the incident direction of light.Garrett et al. (2001) showed a quite good correlation be-tween IWC number fraction and asymmetry parameter. Sim-ilar to Garret’s results we obtain approximately 0.85 for theasymmetry factor of smallest ice mass fractions (10–20%) inmixed phase clouds and 0.74 for highest observed ice frac-tions (80%) during the ASTAR 2004 campaign. There isclear correlation betweeng and the ice fraction for all pre-sented flights, however, the correlation coefficient is quitelow due to certainly complicated relations between asym-metry factor and crystal size, shape, surface roughness, etc.The parameterised efficiencies for the two sensors, in partic-ularεLWC,droplets, seem to produce a consistent ratio betweenice and total condensed water calculated from the Nevzorovprobe that correlates quite well with the asymmetry factor.

6 Conclusions

Within the frame of 14 scientific cloud flights during theASTAR 2004 measurement campaign, this study representsan extended analysis of the Nevzorov probe response inArctic supercooled and mixed phase clouds. Knowing thatthe efficiencies of the LWC and TWC sensors of the Nev-zorov probe have not yet been adequately characterized be-yond cloud particle diameters of 25µm, this study con-tributes to confine current uncertainties in Nevzorov Probeefficiencies. The efficiencies are dependent on cloud parti-cle size and phase. In this study a reasonable response of

the critical efficiencyεLWC,droplets (LWC sensor efficiencywith respect to water) was fixed from experimental data inArctic clouds, where droplet sizes far beyond 25µm havebeen observed quite frequently. The efficiencyεLWC,dropletswas estimated from the calculated size-dependent ratio ofεLWC,dropletsoverεTWC,droplets, assuming an extrapolation forεTWC,droplets. The assumed extrapolation ofεTWC,dropletsandthe assessment ofεLWC,dropletsas a function of cloud dropletdiameters should lead to an improved adequacy of calculatedcondensed water contents (IWC, LWC). The proposed im-provement inεLWC,dropletsis applied to calculate ice fractionssampled from the Nevzorov probe as a function of the asym-metry parameter deduced from the scattering phase functionof the Polar Nephelometer.

Acknowledgements.This work was funded by the “Centre Nationald’Etudes Spatiales” (CNES), the “Institut Polaire Francais PaulEmile Victor” (IPEV) and by a grant from the CNRS/INSU. Wethank the members of Optimare and AWI (Alfred Wegener Institut)managing and organising the experiment and aircraft operations.We acknowledge C. Gourbeyre (LaMP) and J.-F. Fournol (LaMP)for their technical assistance and active accomplishment of theASTAR measurement campaign.

Edited by: M. Wendisch

The publication of this article is financed by CNRS-INSU.

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Response of the Nevzorov hot wire probe in clouds …...2004 (Arctic Study of Tropospheric Aerosols, Clouds and Radiation) performed over the island of Svalbard in the Arctic a constant-temperature