Where is current activity ??
1. 12th AMS conf. on cloud physics/atmospheric radiation
July, 2006
14 sessions: 2 - aerosol + 2 - indirect effects (aerosol)
2 - stratiform+ 2 RICO + 1 Cumulus
2 deep convection + 2 precipitation
2 cirrus
2. Recent field experiments:
RICO, TWP-ICE, ACE-2, Crystal-Face
3. 2007 Radiation & Climate Gordon conf. theme:
“Integrating multiscale measurements and models for
key climate questions”
Presentations on:
• Quantifying (measurements) aerosol, cloud nuclei & properties
(smoke, pollution)
• cloud dynamic/microphysics interfaces
(cloud/dry air; drizzle dynamics; mixing; aerosol/precipitation)
• subvisual cirrus
• improvements on measuring the Earth’s RB from space
(inc. clouds)
RT presentations de-emphasize new RT techniques, more
emphasis on improved calibrations, fine-tuning coefficients
and algorithms => greater accuracy, same concepts
Work shifting towards data-integration, model/data synthesis,
more complex scenarios
(e.g. amazonian burning or mineral dust/cloud &radiation impact)
MICROSTRUCTURE OF BOUNDARY LAYER CLOUD
“Parcel theory suggests that the microstructure of cumulus
clouds is mainly a function of height”
What does that mean ??
• during moist processes (i.e. allows for phase changes),
the total water mixing ratio remains conserved:
1. Total water mixing ratio rt = rwater vapor + rliquid + rice
r = water vapor/dryair ;  = density
As air is lifted, rwater vapor is determined by the saturation mixing
ratio, which depends on the temperature. As the temperature
drops, water is released from the parcel.
Because everything depends on the release of water from
a parcel with height, the cloud properties also are primarily
a function of height.
d(rl)/dz
- d(rv)/dz
since
r = water vapor/dryair and  = density varies linearly as p/T
d(rl)/dz = is roughly constant
~ 2.0-2.2 in Chilean
stratus
Then LWC = fadz where 0 < fad < 1
Given fad and it is possible to derive:
LWP,
cloud radius as f(z), cloud-top effective radius
cloud vol. ext. coeff. ext(z), optical depth.
=> Adiabaticity is a powerful concept
• instrumental constraint
• application to satellite remote sensing
• departure from adiabaticity indicates physical processes
• microphysical processes theoretically understood (e.g. Kohler)
Remarkable that it works…
Comparison of Observations and
Adiabatic Model Predictions is poor
OBSERVED
N= 481 cm-3
<d>, s= 17.7, 7.3 mm
MODELED
N= 467 cm-3
<d>, s= 17.9, 0.24 mm
Modeled distributions are too narrow.
Comparison of Observations and
Adiabatic Model Predictions is poor
Observed drop size distribution
BROADENS w/ height; modeled
Distributions NARROW
RY, fig. 5.7
Arctic example
• lidar-determined liquid
cloud base parcel
• interpolated sounding
temperature structure
• constrained w/ microwave
radiometer-derived liquid
water path
excellent correspondence
between adiabatic calc. and
King probe LWC
May 4
adiabatic LWC
1.0
King LWC
CB
0.6
FSSP
Z
(km)
0
0.5
Liquid water content g/m^3
An aside on the FSSP
(Forward-Scattering Spectrometer Probe)
An optical sensor that sizes and counts drops, from which
LWC is derived. The optics rely on Mie scattering:
X=2pi*r/wavelength. The bigger x is, the more light is
Forward-scattered.
South-eastern Pacific stratus
(also Californian stratus, but not so much in north Atlantic)
Fair-weather Cumulus: how often/much they are adiabatic
has been debated
Kollias et al. 2001
Miami Cu had narrow (400m) adiabatic updraft region flanked
by downdrafts
CORE
(Hess, 1959: Holt, Rinehart, and Winston, NY)
Pruppacher and Klett, 1978: Reidel ( Pub.)
Large resources have been devoted towards addressing
how clouds mix/entrain, with adiabaticity serving to constrain
or measure how much mixing is occurring
2 field experiments (at least) devoted to this question:
• Small Cumulus Microphysics Study (SCMS), FL, summer 1995
• Rain in Cumulus over Ocean (RICO), Antigua, Jan 2005
New tech. from SCMS: a fast FSSP
1hz (100m) vs 1000hz (10 cm) LWC
SCMS; 28 July; 1434
(5. Gerber, 2000: 13th ICCP)
PVM
(XGLWC)
605 SCMS Cloud Passes
18
CONCLUSIONS
1.
2.
3.
4.
5.
6.
Indentification of LWCa requires a fast and accurate LWC sensor
LWCa exists in SCMS Cu
“Classical Adiabatic Cores” in SCMS Cu: none
Entrainment/mixing already starts near cloudbase (one turn-over distance)
Large LWCa parcels found only near cloud base
Above cloud base mean LWC approaches 20% of LWCa
Parcel theory, with cloud formation described by Kohler etc.
Can be usefully applied to all boundary layer clouds
QUESTIONS
1.
2.
3.
4.
5.
How does entrainment/mixing affect the evolution of LWC in Cu?
What is the proper description of adiabatic cores?
What size of LWCa parcel must be considered for modeling drop spectra evolution?
Does the size and vigor of Cu affect the presence of LWCa?
Does LWCa in RICO Cu differ from other small Cu, e.g., CCOPE or SCMS?
ENTRAINMENT and MICROPHYSICS in RICO Cu
Hermann Gerber
NASA/GISS Workshop
Sept. 2006
CONDITIONAL SAMPLING FOR ACTIVE TURRETS
VERTICAL VELOCITY IS POSITIVE (~80%) IN AREA WITH LWC
TOP OF CLOUD IS VISIBLE IN FORWARD-LOOKING VIDEO
CLOUD IS TRAVERSED NEAR CLOUD TOP
A SINGLE TURRET IS TRAVERSED
(Raga, G.B., et al, 1990: J. Atmos. Sci., 47, 338-355.)
PVM
FSSP
Fast FSSP
10-cm RESOLUTION (1000 Hz) LWC DATA
PVM
TURRET SPECTRA
Moving on to other observations…..
Aircraft data across a Florida Cumulus Cloud
• Higher LWC correlated w/ stronger updrafts
• Downdrafts occurring at the edge
• drop conc. doesn’t vary much
Moving on to other observations…..
Cloud interior humidity almost always between 98% and 102%
Supersaturation values typically ~ 0.1%, rarely > 0.2%
Soluble
aerosol
deliquesce
• The supersaturation relative to a droplet(S’) is
increased by two factors:
– The size of a droplet (Kelvin’s Law):
• For a given “bulk” supersaturation, a droplet (having a curved
surface) has a lower relative supersaturation
– A solution droplet (Raoult’s Law):
• For a given “bulk” supersaturation, the larger amount of solute
dissolved in the droplet, the higher the supersaturation relative to the
droplet
Activation of CCN
• Consider a rising air parcel in which the RH just increased
above 100%
• As the parcel continues to rise, the RH (or S) continues to
increase, and solution droplets containing the largest
nuclei would grow larger than r* and activate, growing into
cloud droplets
• The supersaturation S continues to increase and more and
more of the smaller droplets are activated
• As the droplets are growing, they are decreasing the
amount of water vapor in the parcel, offsetting the increase
in S from the rising (cooling) air parcel
• At some point the cloud droplets are taking up so much
vapor that S starts to decrease in the air parcel-- the max S
has occurred
According to parcel theory, the conditions at cloud base
determine much of the microstructure of the cloud above
Experimentalists search for relationships between
the cloud base or sub-cloud layer and the cloud itself
(or the lack thereof)
Droplet concentration near cloud base in updrafts in
marine cumuli is controlled primarily by two
processes:
1. Concentration of cloud condensation nuclei
(CCN) entering cloud base
2. Peak supersaturation occurring in updrafts
[Twomey, 1959]
CCN Concentrations
• Cleaner, more maritime air masses contain
fewer aerosol particles and CCN than more
polluted, continental air masses
• Fewer CCN result in fewer, but larger cloud
droplets, accelerating rain production
Areas Targeted
Criteria was met in
clouds sampled on
12 of the 15 flights
Updrafts and Downdrafts;
Intensity = length of arrow
Criteria chosen to obtain droplet
concentration 10Hz:
 600-900m above the ocean surface
FSSP
(nominal cloud base = 600m)
 LWC > 0.25gm-3
 Updraft velocity > 0.5ms–1
 No droplets > 65 μm 260X (avoids drop shattering)
 At least three consecutive data points
Vertical velocities & Droplet concentration
Vertical velocities
> 0.5ms-1 between
600-900m above the
ocean surface show a
relationship (R =
0.66) with average
droplet concentration
Vertical Velocity – a proxy for peak supersaturation
Vertical velocities
> 0.5 ms-1 between
600-900 m above the
ocean surface show a
relationship (R =
0.79) with 100-m
wind speeds
Results – Droplet Concentration
Droplet concentrations between
600-900 m above ocean surface
increase (R = 0.71) with 100-m
wind speeds (5-14 ms-1).
CCN or peak supersaturations?
 The total concentration of smaller CCN (PCASP and
CN measurements) did not show a clear dependence
on wind. This suggests that variability in the cloud
base updraft was the most important control on the
growth of drops.
 The effect of more intense updrafts would be to
increase the peak supersaturation, leading to
activation of more cloud droplets and smaller cloud
droplets near cloud base.
These conclusions were based on data from the most cleanly
Adiabatic cloud portions.
parcel (‘adiabatic’) theory appears able to explain some
aspects of cumulus behavior, but note again that observed
LWCs are often well below adiabatic values
Parcel theory also can’t explain why precipitation onset occurs
so quickly. Thus observations search for clues into other
mechanisms;
• Factors that may be important:
– Details of aerosol and CCN number
concentrations, composition, sizes, including
giant/ultragiant aerosol particles
– Entrainment and mixing
– Turbulence
– Successive thermals
– Preconditioning of cloud environment
– “Time zero?”
Giant/Ultragiant Aerosol Particles
• Giant: aerosol particles with diameters between 2
and 20 micrometers
• Ultragiant: aerosol particles with diameters > 20
micrometers
• Soluble, giant aerosol particles (like sea salt!) do not
have to grow long by vapor diffusion to be large
enough to collect smaller droplets
• Ultragiant particles, if > ~45 micrometers, don’t even
have to be soluble!
Work based on RICO data appears to discount this mechanism
(but I don’t understand the argument)
Turbulence
Turbulent energy dissipation rate
RY fig 5.5
Turbulence observed to increase with height, so that strongest
Up/downdrafts are in top third of cloud
This will increase the collision/collection rate of the drops &
Can help explain a broader spectrum
Successive Thermals
•
Some investigators have suggested that the drops
from previous thermals within the same cloud may
not completely evaporate, leaving some drops behind
that may then be ingested by new thermals, giving
them a “head start”
Preconditioning of Cloud Environment
• Numerical models of precipitation formation
often start from pristine conditions in an
undisturbed environment, but it is likely that
earlier clouds change the local environment
for the later clouds
High degree of structure
in cloud field is compelling
evidence (I think) of
preconditioning, clouds
coming and going as part of
a larger convective
lifecycle
Good correlation between
vertical and horizontal
velocities also seems
consistent.
600 m
Entrainment and Mixing
• The mixing in of dry air from outside the cloud via the
cloud’s own motions is called entrainment
• It is widely acknowledged that entrainment can lead
to the production of smaller particles in the droplet
size distribution
• It has been hypothesized that entrainment can
actually lead to the production of larger drops, by
significantly reducing the number of droplets in
regions of the cloud that then experience less
“competition” for the vapor
Mixing w/ air from aloft
Total water
Equivalent potential temperature
Shows evidence of air from 380 mb mixing down
Most compelling in env. with dry air aloft (e.g., CO, NM)
Homogeneous Mixing:
All drops evaporate evenly
LWC decreases; drop conc. stays the same;
effective radius decreases
Mixing time scale << evaporation time scale
Inhomogeneous Mixing:
Some drops evaporate completely, resaturating air parcel
& allowing some drops to stay the same size
LWC decreases; effective radius stays the same;
Drop conc. decreases
Parcels mix& evaporate, then more mixing
HOMOGENOUS MIXING
INHOMOGENEOUS MIXING
ADIABATIC PEAK
SUPER
ADIABATIC
(Lasher-Trapp, S., W. Cooper, and A. Blyth, 2005: QJRMS, 195-220)
Homogeneous mixing: all droplet size evaporate evenly.
LWC decreases but N unchanged. Can’t increase drop size
Inhomogeneous mixing: some drops evaporate first, resaturating
Mixed-in air & allowing other drops to grow (LWC decreases)
COMPOSITE OF 35 Cu
IN
CLOUD EDGE
1000 Hz
-60
-50
-40
-30
-20
-10
0
(Brenguier, J.-L, 1993: J. Appl. Meteor., 32, 783-793)
10
20
COMPOSITE OF ENTRAINED PARCEL LENGTH
(Brenguier, J-L, and W.W. Grabowski, 1993: J. Atmos. Sci., 50, 120-136)
(Kreuger, S.K., et al, 1997: J. Atmos. Sci., 54, 2697-2712)
COMPOSITE OF ENTRAINED PARCEL PENETRATION
ENTRAINMENT CONCEPT
ENTRAINMENT
SHEATH
DILUTION
DOMINATES
SMALL
PARCELS
NEW CCN
ACTIVATION
RH HALO?
NO HOLES
VORTEX
RINGS?
X
SUPER-ADIABATIC
DROPS?
REFERENCES
Much of what I’ve shown today is observations that
don’t fit into an easy theory.
We need the theory however, as it conceptualizes for
us what we are capable of modeling
In the long run the observations can tell us how to
improve the models and thereby improve weather
forecasts and climate predictions
Important to become comfortable with both