43
Weather and a r n a t e (1981) 1 : 43-52
HOW CUMULUS CLOUDS WORK
J. T. Steiner*
Presidential Address t o t h e Conference o f
the Meteorological Society o f N e w Zealand, October 1 9 8 0
ABSTRACT
Observational techniques f o r cumulus cloud dynamic studies are surveyed. Can the observed characteristics be modelled? The techniques o f
numerical cloud modelling are discussed. I t is shown that somewhat paradoxically there has been greater success i n the simulation o f severe convective storms than o f small cumulus clouds. The principle deficiencies in
models o f small cumuli are i n the representation o f their initiatio:ri and
the neglect o f radiative processes.
INTRODUCTION
This paper is a discussion o f some o f the
problems that have been solved and some of
the problems that remain to be solved in the
field o f cumuliform cloud dynamics. I will
concentrate o n t h e numerical modelling
studies though I acknowledge that much has
also b e e n accomplished t h r o u g h c a r e f u l
observational studies and indeed I strongly
support the view that while numerical models
have the advantage that it is possible to isolate
the effects o f changes i n individual parameters they are o f little value unless the
numerically simulated clouds resemble what
can be observed.
What are cumuliform (convective) clouds?
Cumulus is defined by the W M O (1956) as
"detached clouds, generally dense with sharp
outlines, developing vertically in the form of
rising mounds, bulging
parts often resemble a caulid
o m eupper
s
flower. The sunlit parts o f these clouds are
o
r brilliant white; their base is relatively
mostly
t o awn de n er a r l y horizontal. Sometimes
dark
scumulus is ragged."
o Cumulonimbus
f
clouds a r e " h e a v y a n d
dense hclouds,
w
i w i t h a considerable vertical
c
h
t* D r Steiner
h is Assistant Director (Research) o f the
e New Zealand Meteorological Service.
extent, i n the form o f a mountain o r huge
towers. A t least part o f its upper portion is
usually smooth o r fibrous o r striated, and
nearly always flattened; this part often spreads
out i n the shape of an anvil o r vast plume.
Under the base of this cloud, which is often
very dark, there are frequent l o w ragged
clouds, either merged with it or not, and precipitation sometimes in the form of virga."
These definitions are the results of careful
observational studies dating f r o m the nineteenth century. They represent the principal
ideas of cumuliform structure as can be seen
from the ground.
OBSERVING M E T H O D S
What additional ways are there o f observing such clouds? Firstly, w e can consider
photography. M o v i e o r t i m e lapse photographic studies, particularly those employing
stereo-paired views, e.g. Warner (1972) and
Shaw (1969) enable one to observe the rate
of cloud development. Such studies have also
provided information o n t h e lifetime o f
cumuli o r the frequency o f tower development from the main cloud masses and on the
relationship of the cloud outline t o the precipitation containing volume as determined
from radar.
44
H
o
With aircraft i t is possible t o get another
view o f t h e clouds. One o f the intriguing
things about the cumuli observed from aircraft i s their varying distribution - - sometimes apparently random and sometimes well
organized. Plank (1966), was among the first
to systematically study cumulus from aircraft
and was able t o relate their organization t o
the wind shear through the cloud layer.
Satellites provide a wider view. They cannot always resolve the individual cloud elements. However, satellites have revealed certain characteristic patterns o f cloud clustering. Observation a n d explanation o f t h e
cloud patterns i s an important part o f the
GATE ( G A R P A t l a n t i c Tropical Experiment) programme study.
Balloon soundings are essential i n cloud
studies t o reveal t h e ambient conditions.
However, in relating the sounding to the cloud
conditions it is important to know where the
balloon was i n relation to the cloud and a t
what time. This is because ambient conditions
are not themselves either uniform or static in
a convective situation. Sometimes balloons
can be persuaded t o penetrate the interesting parts o f the cloud. From such a penetration Barnes (1967) was able t o determine
that a horizontal pressure fluctuation of 3 mb
can occur in a large convective cloud. Such
pressure variations have important consequences. Newton (1960) demonstrated that
such pressure anomalies c a n e ff e c t t h e
dynamics o f clouds. H e postulated that the
pressure anomalies caused separation of flow
around the cloud walls. A more recent aircraft observational study by Ramond (1978)
tends to verify this theory. Moreover the possibility o f t h e presence o f large pressure
anomalies in convective clouds leads to difficulties i n t h e formulation o f approximate
equations for numerical models.
Aircraft penetrations enable one t o assess
the internal properties of clouds. Instruments
are available that enable one to obtain data
on the drop size distribution and total water
content o f the cloud, o n the velocity field
within the cloud and on fluctuations of temperature a n d h u m i d i t y. T h e pioneering
studies o f this sort were done from Woods
Hole in the 1940's (Bunker et al, 1949). I n strumentation has developed in resolution and
w
Cumulus Clouds W o r k
accuracy since then. Such Penetrations are
difficult to interpret. One needs to know just
where the aircraft was relative to the apparent most active parts of the cloud, the stage
of cloud development and the height relative
to the cloud base and too. Moreover, clouds
are time dependent, so that even i f one can
make several penetrations, e.g. a t different
levels at different times, it is not easy to relate
them. Few research groups can afford to use
several aircraft at once — and there are some
dangers involved! There is an accumulation
of observations o f cloud f r o m aircraft and
certain cloud types such as small cumuli over
the sea, off Australia, have been penetrated
sufficiently so t h a t Warner i n a series o f
papers (1969, 1970) has been able to derive a
climatology of cloud characteristics.
The most powerful tool has been radar.
The classic study in which radar Played the
major part was that o f Byers and Braham
(1949), w h o identified t h e thunderstorm
cloud as a cluster of randomly oriented cells.
The study was seen as definitive f o r some
years b u t t h e observations o f Browning
(1962), Chisholm (1973) and Marwitz (1972)
showed that, under appropriate patterns o f
wind shear, thunderstorms can occur w i t h
markedly different structure.
Two developments of weather radar are of
considerable significance. F i r s t l y, Doppler
radar enables one t o get a measure o f the
precipitation's velocity pattern. This can help
to identify the flow structure inside storms.
However, the Doppler radar data can be developed t o do more. Studies, e.g. Hane and
Scott (1978), have revealed methods o f incorporating the radar derived wind data t o
compute the pressure and temperature fields.
Absolute values cannot be derived but i t is
possible t o get departures from averages i n
each horizontal plane.
The other important development is dual
polarized radar. By frequently shifting from a
vertical to a horizontally polarized beam it is
possible to take advantage of the oblate shape
of raindrops t o assess the characteristics o f
the drop size distribution and hence the rainfall rate m o r e accurately. T h i s technique
(Hall et al, 1980), also makes i t possible to
more readily distinguish different types o f
precipitation, e.g. wet or dry, hail, snow, rain.
How Cumulus Clouds W o r k
REASONS F O R STUDIES O F CONVECTIVE
CLOUD D Y N A M I C S
Apart from natural curiosity there are some
good practical reasons f o r studying t h e
dynamics of convective clouds. These include:
(i) cumulonimbus are the source of violent
weather phenomena — tornadoes, hail,
lightning. T h e r e i s interest i n t h e
prediction a n d abatement o f these
phenomena;
(ii) cumuliform clouds play a major role in
the atmospheric circulation. I n the subtropics t h e y a r e responsible f o r t h e
mixing into a deeper layer of moisture
picked u p f r o m t h e sea. I n t h e
equatorial zone, a relatively small number of cumulonimbi raise energy to high
levels t o " d r i v e " the tropical circulation cells (Riehl and Malkus, 1958).
The r o l e o f convective clouds must
therefore be considered i n general circulation studies such as the modelling
of possible climatic change. T h e drop
size distribution o f t h e clouds i s dependent on the dynamics, and the radiative properties are i n turn dependent
on the drop size distribution. Twomey
(1974) has pointed o u t the effect o f
drop s i z e distribution o n radiation
which also leads t o implications f o r
climatic change;
(ii) there are attempts to modify the clouds
to change the rainfall;
(iv) convective clouds can be used as tracers
in weather map analysis, providing that
a relationship between cloud motion
and the ambient winds is known;
(v) i n numerical forecasting models, t h e
effects o f cumulus clouds a r e parameterized. There is a need to test the
parameterization against more precise
models.
4
5
without mixing or heat exchange with its surroundings. The parcel will rise to a cloud top
level determined by the environmental temperature and humidity profile. This level can
be determined graphically. The parcel method
often over-predicts t h e c l o u d t o o height.
Bjerknes (1938) modified the method to allow
for compensating downward motion o f the
environment, a n d Stommel ( 1 9 7 4 ) a n d
Austin (1948) allowed for mixing of environmental a i r a t some prescribed rate. These
developments help explain some deficiencies
of the parcel method but do n o t normally
provide accurate estimates of the cloud top.
Other approaches have been t o calculate
indices o f the static stability and statistically
compare these with cloud height t o provide
an e m p i r i c a l p r e d i c t i o n m e t h o d , e . g .
Showalter (1953).
Another theoretical approach has been that
of Kuo (1961) who, using linear theory, was
able to demonstrate the controlling effect o f
turbulent mixing o n determining t h e preferred size of cumuli. Kuo (1963) also showed
that ( d r y ) convection w i l l occur i n rolls
whose axes are normal t o the wind shear.
This has important applications to numerical
cloud model design.
The theory o f convective bubbles a n d
plumes has been applied to cloud dynamics.
These theories provide a mixing law on the
assumption that the convective elements are
shape preserving and that there i s a fixed
ratio o f lateral to vertical dimension.
Further theoretical study reouires a numerical solution o f t h e equations o f motion
suitably scaled to simulate the processes important i n convection. I n designing a numerical cloud model the theoretical dynamicist
must decide on a number of key issues. These
are discussed i n the following sections.
W H AT E Q U AT I O N W I L L B E SOLVED?
E L E M E N TA R Y T H E O R Y
The m o s t simple t h e o r y o f convective
cloud growth is that of an air Parcel warmer
than its surroundings (perhaps through contact with a heated surface), converting its
potential energy to kinetic energy as i t rises
If t h e Navier-Stokes eouations o f f l u i d
dynamics are scaled for the modelling of deep
convective clouds we derive a simpler set —
the anelastic system o f eauations. This set
excludes sound wave solutions (the solution
by numerical methods o f the eouations that
include sound waves requires a very small
46
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o
time step in the integration) but includes internal gravity wave solutions. This is desirable since some studies, e.g. Takeda (1971)
show that pre-existing gravity waves help to
determine t h e location o f new convective
updrafts.
When these equations a r e written w i t h
height as the vertical co-ordinate, a complication arises in that a highly implicit relationship arises between the buoyancy, the temperature, the analysis o f saturation and the
pressure. O g u r a a n d Wilhelmson ( 1 9 7 2 )
experimented with the link between pressure
departures from a basic state and the other
quantities above and concluded the pressure
variations could be neglected i n the thermodynamic analysis. However, the geometry o f
the model with which they experimented has
deficiencies which may invalidate their results.
There are two ways o f avoiding this problem. Miller (1974) demonstrated that i f the
equations were scaled t o eliminate sound
waves using pressure as the vertical co-ordinate no implicit relationship occurs. His technique has not been widely adopted, possibly
because observations have generally been
collected in terms of height.
The other solution (Hill, 1974) i s to solve
the elastic equations that include sound wave
solutions b u t t o avoid numerical instability
problems, leading t o unreasonable solutions,
by using a small time step. Klemp and Wilhelmson (1978) refined t h e method. T h e y
identified which terms in the equations gave
rise to sound wave solutions and used a short
time step o n l y f r o m those parts o f t h e
eouations and a longer step f o r the other
integrations. T h i s technique makes i t u n necessary to solve an elliptic equation f o r the
pressure.
M O D E L DIMENSIONS
Early cloud models used o n l y a o n e dimensional framework. Radial symmetry o f
clouds is assumed and the mixing is by way
of the plume theory o f Morton, Taylor and
Turner (1956) o r the bubble theory of Scorer
(1957). Models of this sort by Weinstein and
Davis (1968), a n d Simpson a n d Wiggert
(1969) have been used as the key tools i n
w
Cumulus Clouds Work
programmes o f cloud seeding f o r weather
modification. T h e i r use w a s criticised b y
Warner (1970), who showed that while such
models can be "tuned" t o produce realistic
cloud tops they simultaneously produce excessive liquid water contents. Being simple i n
terms o f dynamics such models have t h e
virtue o f being suitable f o r including complex c l o u d micro-physical representations
without excessive computing.
A modification of this type of model again
assumes axial symmetry. The cloud comprises
an inner cylinder surrounded by an outer ring
of clear a i r ( A s a i a n d Kasahara, 1967).
Ryan and Lalousis (1979) developed a technique which allows the cloud radius to vary
and which accounts f o r pressure difference
between t h e cloud and cloud-free a i r. B y
"tuning" this model they could reproduce
both the height and liquid water control o f
the clouds studied by Warner (1969). However, they were forced to start their experiments with an enormous impulse o r protocloud of a sort not found in nature.
To better represent cloud dynamics, multidimensional models a r e m o r e appropriate.
The computing requirements a r e clearly
greater since t h e amount o f information
stored in the computer needs t o be squared
(for a two-dimensional model) o r cubed ( i n
three-dimensions) a s compared with a onedimensional model.
Without going to the complication of threedimensional modelling, a representation i n
two-dimensions — one horizontal and one
vertical — seems attractive. Uniformity i n
the third-dimension i s assumed. Although
such "slab-symmetrical" models a r e c o n ceptually simple they have deficiencies; they
cannot represent both the linear and areal
ratios o f the upward and downward motion
areas in a real cloud and if wind shear is present they allow only r o l l circulations w i t h
axes normal to the plane o f the model (and
the wind shear) whereas, the Kuo study, referred to earlier, and a subsequent study by
Asai (1970), demonstrated t h a t transverse
rolls (axes parallel t o the shear) are more
likely. Nevertheless, some insight has been
developed f r o m these models notably b y
Takeda (1971), who demonstrated the critical
effect o f shear on cloud evolution and H i l l
(1973), who was able to reproduce the spac-
How Cumulus Clouds Work
4
ing of real clouds using such a model with a
heat flux from the surface.
vective terms. I f the advection is represented
more carefully then i t becomes possible t o
more p r e c i s e l y r e p r e s e n t a t m o s p h e r i c
turbulence.
Axial symmetry overcomes the disadvantage of the slab symmetric models. The equations are developed i n cylindrical polar coordinates a n d a l l terms involving angular
variations are set to zero. A three-dimensional
environment i s thus represented b y a twodimensional data frame but, o f course, such
models cannot cope with the non-symmetric
cloud evolution associated with wind shear.
If shear is important a three-dimensional
model is necessary. Such models were introduced b y Steiner (1973) a n d Pastushkov
(1973).
RESOLUTION
Cloud features have various scales. To adequately represent small cumuli a space scale
of 100 m or less is probably necessary. A resolution o f a kilometre o r more may be adequate f o r studying the gross properties o f
cumulonimbus. T h e need f o r three-dimensionality and high resolution indicates a vast
array of grid points (at which calculations are
made) — each g r i d p o i n t represents t h e
atmospheric " b o x " surrounding it. Some reduction can b e achieved b y reducing t h e
resolution i n the area o f least interest (e.g.
Gordon, 1978) b u t the number is still high
and requires a large computer. ( T h e threedimensional cloud simulations of Cotton and
Tripoli, 1978, were among t h e first tasks
carried out b y the US National Center f o r
Atmospheric Research's giant C R AY computer). To model a 10 km cube with a resolution of 100 m would require a million grid
points! Although spectral methods have been
used i n d r y convection models (Daley and
Merllees, 1971) a n d finite elements o n a
model of the boundary layer (Manton, 1978),
all cloud models have used a finite difference
representation.
7
The conventional approach has been to use
a first order closure scheme i n which turbulent stress is dependent on the component of
deformation (combination o f velocity gradients) and the coefficient in this dependence
— the exchange coefficient — is related t o
the square root of the sum of the terms of the
deformation. The method is strictly valid only
in the inertial sub-range of turbulence, which
is less than the total range the formulations
are required to represent. A study by Klemp
and Wilhelmson ( 1 9 7 8 ) i n t r o d u c e d a n
additional equation f o r the total turbulent
energy and related the magnitude of the exchange coefficient t o this quantity. Higher
order representations o f the turbulence requiring additional calculations to be made at
each point were introduced by Lipps (1977).
CLOUD PHYSICS
TURBULENCE
The pioneering work in accounting for the
cloud physical processes that transform cloud
droplets to falling rain was the parameterization o f Kessler (1969). I t is assumed that
cloud water turns to rain at an arbitrary rate
once a certain minimum cloud water i s
attained. This treatment has been used f o r
many of the cloud models with the more complex dynamics. I n its simplest form only two
cloud physical variables a r e considered.
Equations for the quantity of rain increasing
by capture o f cloud droplets, f o r rainfall
speed and f o r evaporation o f r a i n are a l l
derived from the integration of equations for
single drops across the observed Marshall and
Palmer (1948) distribution of raindrop sizes.
Similar techniques can be added to account
for frozen particles (e.g. Takahashi, 1976).
There are difficulties i n this extension since
the origin o f t h e i c e phase i n cloud i s
stochastic and becouse ice particle structure is
dependent on temperature.
All scales less than those exolicity resolved
by the grid must be considered as turbulence.
Early models i n which t h e equations were
solved using crude finite difference methods
included a numerical diffusion which originated from a poor representation o f the ad-
The alternative to this bulk properties approach requires an equation f o r the number
of drops i n each o f many drop size ranges.
Drops transfer f r o m range t o range b y
growth, through condensation, or capture o f
smaller droplets, or by break up. This requires
48
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a very large number o f equations a n d i s
practicable o n l y i n models w i t h simplified
dynamics. C l a r k (1973), a n d Danielson,
Bleck a n d M o r r i s (1972) pioneered t h i s
work.
B O U N D A RY CONDITIONS
The specification o f the lateral boundary
conditions f o r cloud models is dependent on
the nature of the cloud being studied. I f it is
part o f a field o f clouds some symmetry
may be assumed. There must be provision
for studying inter-cloud reactions shown to be
important by Wilkins et al (1976). For isolated clouds, it is necessary to properly simulate
the cloud a n d t h a t p a r t o f i t s clear a i r
environment where the cloud's circulation is
significant while, at the same time, allowing
for proper interactions between the cloud's
circulation and larger scale processes. This is
not always easy to do under the constraints of
computer limitations.
CLOUD I N I T I AT I O N
A detailed m o d e l o f t h e atmospheric
boundary layer and of deep cumulus clouds is
not yet possible because o f the huge computing requirement. Models therefore must
introduce some simplfying representation o f
the initial organisation o f a cumulus cloud.
The simplest approach i s t o assume t h e
existence o f a "blob" — or more elegantly
proto-cloud o f warmer or more humid air
at the start of the computer run. This form of
initialization is simple but regrettably, at least
for simulations o f small cumulus, the evaluation of the subsequent cloud is dependent on
the shape and strength of the initial feature.
The author (unpublished) has attempted t o
simulate the cumuli off the Australian coast,
studied empirically by Warner (1969), with
an axis-symmetric model and has found that
variations i n initiation are critical t o t h e
experiments. I n some published cloud simulations the initial "blob" has been so vigorous
that the developing cloud has resembled an
atomic explosion i n shape rather t h a n a
cumulus!
In simulation o f some large clouds t h e
initiating "blob" is less critical. Under some
circumstances cloud evolution i s enhanced
w
Cumulus Clouds Work
markedly b y characteristics o f the ambient
wind patterns. I n modelling, under these
conditions, the initial "blob" acts merely as
a "trigger" t o get a circulation started and
not as a major source o f the energy of the
cloud.
Attempts have been made to simulate both
the clouds and the sub-cloud layer and avoid
the use o f the " b l o b " initialization. Orville
(1965) simulated cloud growth over mountains b y t h e u s e o f a diurnal heating
function on the slopes. Sommeria (1976) has
modelled cloud evolution in three-dimensions
using a carefull simulation o f the sub-cloud
layer b u t has o n l y been able t o simulate
stratocumulus o r very shallow cumulus. H i l l
(1976), w i t h a two-dimensional model and
with random surface heating, simulated the
spacing o f clouds quite well, but the limitations of the dynamics of his model, discussed
earlier, suggest h i s results m a y have been
fortuitous. However, Michaud (1980) using a
similar method in three-dimensions, simulated
cloud spacing in the GARP Atlantic Tropical
Experiment quite well.
TESTING C L O U D M O D E L S
If a numerical model is to be considered
as a simulation o f a real phenomenon, so
that deductions made from the model about
parameters that are not readily observed can
be believed, i t is necessary to be satisfied that
the model w e l l represents t h e observable
features. I n this regard it is essential to compare model output w i t h as many observed
features as possible. I t is also desirable that
models be compared not with a few observations o f o n e cloud, b u t rather w i t h t h e
statistics o f an ensemble o f observations o f
several clouds in the same regime.
A C H I E V E M E N T A N D PROBLEMS O F C L O U D
MODELLING
One o f t h e principal results o f cloud
modelling experiments has been the knowledge gained o f the effect o f wind shear on
cloud development. F o r non-precipitating
cloud o r t h e initial phase o f precipitating
cloud, wind shear inhibits convection. T h e
slanting updraft in the presence of shear that
reaches a particular height is longer than the
How Cumulus Clouds Work
4
vertical current i n a n unsheared case and
therefore more eroded b y turbulent mixing
with its environment. This occurs despite the
fact t h a t i n t h e sheared case there i s a n
alternative source of convective energy — the
energy of the ambient flow.
computed b y t h e i r model. Steiner (1979)
questioned their success because their simulation used a very large initial proto-cloud.
In the resulting discussion they (Cotton and
Tropoli, 1979) referred t o t h e w o r k o f
Heymsfield e t a l (1978) w h o indeed found
near-adiabatic w a t e r contents i n cumulus
over Colorado. This raises the question as to
why liquid water contents should be different
in similar sized clouds i n the two locations.
The answer may well be in the initial conditions. There is evidence that the Australian
coastal cumuli d o n o t grow from thermals
originating at the surface (e.g. Warner and
Telford, 1965). I t may well be that on the
high plains o f Colorado, clouds may indeed
have "roots" convective columns extending f r o m near the ground. T h e above discussion suggests that t o successfully model
small cumulus clouds i t will be necessary to
accurately model the convective processes of
the sub-cloud layer.
Once precipitation occurs shear may have
a variety of effects. The precipitation leads to
the creation o f a downdraft and when this
downdraft approaches t h e surface a horizontal divergent flow is established. Under
appropriate shear conditions this flow can
push moist environmental a i r u p i n t o t h e
initial updraft helping to sustain a long-lasting
cloud, e.g. M i l l e r (1978). Under other circumstances, (Klemp and Wilhelmson, 1978),
the model updraft is destroyed once the downdraft is formed.
Although, i n general, we are dealing with
a three-dimensional problem, the initial i n sight into this issue, derived from Takeda's
two-dimensional model (1971), provides a
simple guide t o t h e mechanism involved.
Under conditions of wind changing direction
with height, a downdraft will be formed on
either the up-shear or down-shear side of the
updraft, according to the level at which the
wind change occurs. T h e downdraft carries
with it air from high levels which will have a
horizontal component o f velocity different
from that of the ambient surface air. According to the level o f the wind change this may
induce either convergence a n d hence e n hancement, beneath the existing updraft, o r
divergence leading to a clearing of the cloud.
This is illustrated in Fig. I . The significance
of downdrafts in cloud evolution has recently
been highlighted by Simpson (1980)
Severe convective storms can be modelled.
Squall lines in both middle and tropical latitudes c a n b e simulated reasonably w e l l
(Gordon, 1978, Miller and Moncrieff, 1976).
Paradoxically there are some problems i n
modelling small cumuli. T o reproduce observed cloud heights and liquid water contents (below those to be expected by adiabatic
ascent from cloud base) i s difficult. Cotton
and Tripoli (1978) showed that i f the wind
shear was included i n a simulation o f the
clouds observed i n detail o ff the Australian
coast by Warner (1969, 1970), realistic cloud
heights and liquid water contents could be
9
One issue in cumulus studies that requires
greater attention i s t h e interaction o f t h e
dynamics w i t h the radiative processes. T h e
top o f a cloud is cooled b y infra-red heat
losses by several degree per hour. This heat
loss m a y extend over a depth o f several
metres (Yamato 1970). The effect needs to be
considered i n cumulus cloud models. I t has
been studied only for very shallow clouds by
Veyre e t a l (1980). Their results show an
interesting feedback. The cooling of the cloud
top leads t o a greater degree o f turbulent
mixing. T h u s dynamics a n d radiation a r e
implicitly related.
The effects o f solar radiation on cumulus
evolution also needs t o b e considered. I n
addition to effects on the clouds themselves,
the differential heating rates, generated b y
cloud shadow effects, may be significant i n
determining where new clouds form.
CONCLUSIONS: A N E W Z E A L A N D
VIEWPOINT
The previous section has indicated the current achievements a n d problems i n cloud
modelling studies on the world scene. Much
of the pioneering work can only be done at
major research centres having accesss to large
computers and with sufficient specialized staff
to develop new ideas and approaches. What
50
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A
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Cumulus Clouds Work
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e
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r
r
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Fig. 1 : Three types o f cumulus redevelopment (after Takeda, 1972). The broad arrows indicate the updraft and
downdraft o f the initial cloud. Regions I and I I are areas where t h e c o l d o u t f l o w tends t o f a v o u r a n e w
updraft. I n Ty p e A ( n o w i n d shear) a n d Ty p e B ( w i n d shear o f constant sign) t h i s tendency does n o t
reinforce the initial updraft, b u t i n Ty p e C (wind shear changing sign, i.e. winds increasing t o the left w i t h
height a n d then t o t h e r i g h t a t higher levels) Region I I corresponds with the initial updraft which is therefore reinforced.
How Cumulus Clouds W o r k
5
then is the particular relevance of this work
to New Zealand?
Chisholm, A . J . , 1973: A l b e r t a hailstorms. R a d a r
Case Studies and A i r f l o w Models. Meteorological Monographs, N o . 36, P a r t 1.
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dynamics a n d microphysics o f w a r m cumulus
convection. J o u r n a l Atmospheric Sciences, 3 0 ,
857-878.
Cotton, W. R . and Tripoli, G., 1978: Cumulus convection i n s h e a r f l o w — three-dimensional
numerical n
J o u r n a l Atmospheric
Sciences, 35, 1503-1521.
Cotton, W . R . a n d Tripoli, G . T. , 1979: R e p l y t o
comments. J o u r n a l Atmospheric Sciences, 3 6 ,
1610-1611.
Danielsen, E. F. , Bleck, R. and Morris, D . A., 1972:
Hail growth by stochastic processes in a cumulus
model. J o u r n a l Atmospheric Sciences, 2 9 , 135155.
Daley, R . and M e r l lees, P., 1971: A spectral model
of b u b b l e convection. J o u r n a l A t m o s p h e r i c
Sciences, 28, 933-943.
Gordon, N . D . , 1978: N u m e r i c a l simulation o f a
long-lasting mesoscale squall line. Sc.D. thesis,
Massachusetts Institute o f Technology.
Hall, M . P. M . , Cherry, S. M . , Goddard, J. W. F.
and Kennedy, G . R., 1980: Raindrop sizes and
rainfall r a t e measured b y d u a l polarization
radar. Nature, 285, 195-198.
Hane, C . E . a n d Scott, B . C . , 1978: Temperature
and pressure perturbations w i t h i n convective
clouds derived f r o m detailed a i r m o t i o n i n formation: Preliminary testing. Monthly Weather Review, 106, 654-661.
Heymsfield, A . J., Johnson, P. N . a n d Dye, J . E ,
1978: Observations o f moist adiabatic ascent i n
northeast C o l o r a d o c u m u l u s clouds. J o u r n a l
Atmospheric Sciences, 35, 1689-1702.
Hill, G . E . , 1974: Factors controllinr
cumulus
, t h
e
s clouds
i z ea s revealed
o
fb y numerical e x periments. J o u r n a l Atmospheric Sciences, 3 1 ,
646-673.
Klemp, J . B . a n d Wilhelmson. R . B . , 1978: T h e
simulation o f three dimensional convective storm
dynamics. J o u r n a l Atmospheric Sciences, 3 5 .
1070-1096.
Kessler, E . , 1969: O n t h e distribution a n d c o n tinuity o f water substances i n atmospheric circulations. Meteorological Monograph, 1 0 , N o .
32.
Kuo, H . L . , 1961: Convection i n conditionally u n stable atmosphere. Telhis, 1 3 , 442-459.
Kuo, H . L . , 1963: Perturbation o f plane Couette
flow i n stratified f l u i d a n d o r i g i n o f c l o u d
streets. Physics o f Fluids, 6 , 195-211.
Lipps, F . B . , 1977: A s t u d y o f turbulence parameterization i n a m o d e l c l o u d . J o u r n a l A t mospheric Sciences, 34, 1751-1772.
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moist atmospheric boundary layer. Tel/us, 3 0 ,
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distribution o f raindrops w i t h size. J o u r n a l
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If, in convective situations, short term district weather forecasts are to be more specific
than "scattered showers" i t will be necessary
to develop techniaues to identify the motion
and life cycle of individual convective clouds.
Initially such techniques may be based o n
empirical methods: extrapolation o f recent
radar weather patterns would be a starting
point. For more precision i t will be necessary
to routinely predict the cloud dynamics and
resulting rainfall using a numerical method
that incorporates details o f the local topography and surface heating b u t derives its
general w i n d f l o w a n d temperature a n d
humidity profiles from a model of flow on a
larger scale. I would like to see considerable
progress along these lines i n the next ten
years.
The empirical parameterizations o f cloud
physical processes that are included i n such
models will need to be checked against data
for New Zealand clouds as they become available. I t may be necessary to compare cloud
evolution in the highly parameterized models
with some more detailed models.
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