Cloud Formation and Fractionation of Stable Isotope of Water within Artificial
Cloud Experimental System (ACES)*Yasushi Fujiyoshi 1, Sou Nakajima 2, Sadamu Yamagata 3, Toshio Harimaya4, Tadashi Yamada5, Ichiro Matsui6,
Nobuo Sugimoto6 and Atsushi Shimizu6(1: ILTS, Hokkaido Univ./FRCGC, 2: Graduate School of Environmental Science, Hokkaido Univ., 3: Graduate
School of Engineering., Hokkaido Univ., 4: Graduate School of Science, Hokkaido Univ., 5: Faculty of Sci. and Tech.,
Chuo Univ., and 6: National Institute for Enviromental Studies)* Inst. Low Temp. Sci., Hokkaido University, Japan, 060-0819, Sapporo,Japan.
e-mail: fujiyo@lowtem.hokudai.ac.jp
Abstract
We invstigated cloud physics and cloud chemistry by using an artificial cloud experimental system (ACES). The system ismade use of the vertical mine shaft with a quasi-real scale of natural clouds. The vertical shaft is 430 m in length and 2.5m
x 5m in cross section. We can change the number density and chemical composition of CCN, and the updraft velocity (0.5 2.0 m/s). Many kinds of insturments were deployed both at the bottom and top of the shaft. Especially, we measured
veritcal profiles of air temperature every 5 m or 10 m interval to detect the supersaturation layer near the cloud base. We
also measured stable isotope of water vapor at the bottom of the shaft and cloud (condensed) water at several levels of the
shaft. Since ACES is the quasi-closed system, we were firstly able to study the validity of the Rayleigh condensation(distillation) model.
Keyword:cloud physics, stable isotope of water, Rayleigh condensatin model

1. Introduction
Study of clouds becomes important especially in recent
years, since they play an essential role in global climate
systems through their interaction with shortwave andlongwave radiation (e.g., Wielicki et al., 1995) as well as
rain/snow formation. Also the acid rain, fog and cloudare quite serious problems of the earth environment (e.g.,
Hobbs, 1993). There are many and complex physical andchemical processes in clouds (e.g., Pruppacher and Klett,1978). We can make laboratory experiment on someelemental processes, and numerically simulate thephenomena in clouds combining these elemental processes.
However, such kinds of numerical simulations would not
succeed in simulating natural phenomena and lead tomisunderstanding of nature, if we do not take account of
the interactions between these elemental processes.
Therefore, we must check the validity or applicability ofpure theoretical models and/or parameterized cloud
schemes.
Many direct and field measurements of physical,
chemical and radiative properties of clouds have been done
both on the ground surface and in the air. The"CLEOPATRA" CLoud OberPfaffenhofen And TRAnsport(Meischner et al., 1993) was one of these field experiments.
However, it is impossible to measure the same clouds
repeatedly under the same conditions, because clouds growand dissipate in a short period of time. Further, it isquestionable whether the measured values are
representative ones of a cloud or not, owing to its
inhomogeneity both in space and time. Therefore, weneed a quasi-real scale artificial cloud which is formed in
the adiabatically ascending air and has reproducible
properties.
On August 1989, we noticed that a quasi-real scale(several hundreds meter) cloud is formed in a long

ventilation shaft of a mine below the ground. Then we
deployed some instruments in the vertical shaft to study
micro-physical and chemical processes in the cloud.
From March, 1992 to August 1993, we had made use of acylindrical shaft (1st shaft) with 5.5 m in diameter and 700
m in length located at Kamisunagawa-cho, Hokkaido,
Japan. After the 1st shaft had to be closed forever on
February 1994, we are making use of a new shaft (2ndshaft) with 2.75 m x 5 m in cross section and 430 m indepth located at Kamaishi, Iwate Prefecture.
The cloud depth, liquid water content and integrated
liquid water content are small in the artificial cloud.
However, the detailed study of thin clouds is very
important, since shortwave cloud albedo increases very
rapidly with increasing integrated liquid water content in
the region below 100 g m-2 (Stephens, 1978). The number
density of cloud droplets strongly depends on that of CCN
when the updraft velocity is less than a few meters.
We reported some results of the experiments in several
papers (Yamada et al. 1995; Yamagata et al., 1998;
Harimay et al., 1998; Yamagata, 2003; Yamagata et al.
2004). In this paper we will discuss the veritcal profilesof air temperature measured every 5 m or 10 m interval todetect the stable layer and supersaturation near the cloudbase.
The stable isotopic ratios of meteoric water (HDO/H2O
and H218O/H216O) has been used as indicators of past
climate and source of water vapor (Friedman et al., 1964;
Dansgaard, 1964; Dansgarrd et al., 1982; Jouzel et al.,1987). Since fractionation occurs during phase change,
condensation of vapor as an air parcel cools progressively
lowers the heavy isotope ratios of the remaining vapor andthe condensate that forms from it (Rayleighdistillation/condensationprocess). So far, however, theRaylegih distillation processs has not proven, yet.

Size distribution of aerosols were measured
continuously both at the bottom and top, and that ofcloud droplets was also measured by using
PMS-probe at the top of the shaft. In 2003, we
deployed a LIDAR (National Inst. forEnvironmental Studies) at the bottom to study thegrowth of aerosol near the cloud base. To change
the number density of CCN, small droplets ofaqueous solution of sodium chloride and ammonium
sulfate were sprayed at the bottom (Yamagata et al.,2004).

(a)Fig. 1 The place and schematic outlook of ACES.
(Yamagata, 2003)

2. Outline of the experimental system
ACES has four unique features: (1) A quasi-real scale
cloud is formed in the adiabatically ascending air. (2)Processes included in this artificial cloud are more
complicated than those of laboratory experiments, but theexperimental conditions can be controlled. (3) Since thissystem is nearly one-dimensional and keeps nearly steadystate, we can compare the experimental results withtheoretical works on the small number of assumptions. (4)In situ measurements are possible in the cloud.
Figure 1 shows the outlook of the experimental systemof the 2nd shaft. Two big fans set at the top of the shaft
suck the air and causes updraft ranging from 0.5 to 2 m s-1
in the shaft.
We measured changes with time oftemperature and relative humidity of air at the bottom of
the 1st shaft from April to August, 1992.
Bothtemperature and relative humidity increased with time from
21.5 to 23.8 ℃ and from 51.4 to 73.8 % (Yamada et al.,1995). Therefore, it is expected that a cloud would bethicker in summer than in winter. As these changes withtime were small, 0.015 ℃ day-1 and 0.15 % day -1, we
can assume that background temperature and relative
humidity were constant during the measurements. Such
surprizingly steady state is one of the unique and importantfeatures of ACES.
We hanged thermometers from the top of the shaft
every 5 or 10 m interval. Under moist adiabatic conditon, 5m interval causes only 0.03 ℃ difference. We sampled
water vapor by using cold trap method at the bottom, andcollected cloud (condensed) water at several levels and at
the top of the shaft. The δO１8 andδD of collected water
were measured by using a mass-spectormeter of ourinstitute.

(b)Fig. 2 Examples of observed vertical profiles of air
temperature in the shaft.

3. Vertical profiles of air temperature
Theoretically, maximum supersaturation near the cloudbase depends on chemical composition and the size
distribution of CCN and ascending velocity. Therefore,
initial size distribution of cloud droplets, optical thickness
and precipitation efficiency of the cloud are strongly
affected by the maximum supersaturation. However, thereliability of in situ measurements of the supersaturation isvery poor as mentioned later. Here, we discuss theaerosol effect on vertical profiles of air temperatures tofind out the maximum supersaturation layer that should be

dD
-140

-120

-100

-80

-60

-40

-20

400.0

Height (m)formed near the cloud base. Preliminary caluculationshows that the temperature lapse rate is dry adiabatic below
the maximum super saturation level and moist adiabatic
above it. Just above the maximum supersaturation level,
condensation of water vapor on CCN rapidly occurrs, that
is, a large amount of latent heat is released. Therefore,
small value of temperature lapse rate should be found near
the level of maximum super saturation.
Figure 2 shows that the observed lapse rate was close
to dry-adiabatic one below 40 m and moist-adiabatic one
above 70 m. In the meantime, the temperature lapse rate
is clearly different in the layer from 40〜70 m, where thetemperature lapse rate was much smaller thanmoist-adiabatic lapse rate. Qualitatively, the range inwhich the moist-adiabatic lapse rate line crosses with dry
adiabatic lapse rate line of the lower layer is asupersaturated layer, and the maximum supersaturation
exists in which the temperature difference is maximum( see an arrow in Fig. 2b ).
Quite high sensitivity of thermometers and the stabilityof air temperature of the environmental atmosphere isindispensable to detect the maximum supersaturation (0.1
〜0.05 C). We cannot expect such stability to in situ
measurements.

300.0

dD
d18O

200.0

100.0

0.000
-24

-22

-20

-18

-16

-14

-12

-10

-8

d18O

Fig. 4 Vertical profiles of δ18O and δD of water vapor
and cloud water(1) Extinciton coefficient is small
from the bottom to 20 m level,
indicating the dry state of aerosol.
(2) Extinction coefficient increases
rapidly in the layer between 20 m
and 60 m from the bottom,
indicatingthecondensational
growth of aerosol.
(3) Extinction coeficient is quite
large above 60 m from the bottom,
indicating the formation of cloud
droplets.
The pictures taken by a CCD
camera (right panel of Fig. 3)
support the explanation of LIDAR
data. The results shown above arealso consistent with those of verticalprofiles of air temperature.

5.
δ18O and δD of water
vapor and cloud water
Fig. 3 Time series of vertical profiles of the extinction
coefficient (λ=532 nm) and pictures of visibility in theshaft taken by a camera.

4. Detection of sub-cloud layer by LIDAR
LIDAR can measure the fine structure of sub-cloudlayer, where CCN change from dry to wet aerosols. As
shown in Fig. 3, the vertical profile of the extinction
coefficent changed a little depending on updraft velocity,chemical composition and number density of CCN.
However, these 5 cases show common featrues.

Stable isotope of water is very
useful tool to study the water cycle. Fractionation duringphase change is the basic process. The accuracy ofRalyeigh condensation model has been tried to demonstrateby a few researchers (Gedzelman and Lawrence 1982;
Gedzelman et al. 1989). However, their studies were madefor snow sotrms, that is, non-closed system. We measured
stable isotope of water vapor at the bottom and cloud(condensed) water sampled at several levels of the shaft.
Since ACES is the quasi-closed system, we were firstly
able to study the validity of the Rayleigh condensation(distillation) model.

-66.00-67.00dD=18.68+8.08 d18O
dD

-68.00-69.00-70.00-71.00
-11.1

-11

-10.9

-10.8

-10.7

-10.6

-10.5

18

d O
Fig. 5 Relationship between δ18O and δD of cloudwater.
Figure 4 shows the vertical profiles of δ18O and δD ofwater vapor at the bottom and cloud water sampled at 50m,
100m, 150m, 250m, 350m and 430m (top). As is
expected, δ18O and δD of cloud water are much larger thanthose of water vapor at the bottom, and decrease withaltitude. Since cloud droplets can grow only when therelative humidity is higher than 100 %, nonequilibrium
condensation may affect the isotopic ratio of cloud water.
The relation beween δ18O and δD can be used to assess therole of nonequilibrium procesees. As shown in Fig. 5,
δD/δ18O slope is almost the same with that of the meteoric
water line (δD=7.97δ18O + 8.6), and that of equilibrium
condensation.
We are trying to simulate the vertical profiles of δ18O
and δD of water vapor and cloud water. We will try tomeasure these values just below, within and just above themaximum supersaturation layer, where non-equilibrium
effect is the largest.

5. Concluding remarks
All the data observed are both micro-physically andchemically are consistent with each other, and clearly show
the aerosol effect on vertical profiles of air temperature andsupersaturation. All these data indicate that ACES is a good
simulator of natural clouds and has the capability of
studying the complex processes in natural clouds.
Acknowledgements: The authors are grateful to Dr.
Takeshi Nakatsuka, ILTS Hokkaido Univ., for analysis ofstable isotope of water. We also express our sincere thanks
to Kamaishi Kozan Co. Ltd. for providing their facilities
used for this experiment. Finally we wish to acknowledge
the assistance provided by many students of Hokkaido
University and Chuo Univeristy.

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