AMBIENT
CLOUD SAMPLING STRATEGY
The strategy to sample ambient (unseeded) cloud systems
draws on the "closure study" paradigm that was shown to be very
successful during ACE-2 and CRYSTAL-FACE. It consists of four
sampling strategies conducted in succession. The first leg is
flown below cloud to fully characterize the aerosol feeding the
clouds at their bases. Self-consistency among aerosol size, chemistry,
hygroscopic growth, and CCN behavior will be tested in an "aerosol-CCN"
closure. The second leg samples the lowest 100 meters or so of
the cloud base to measure cloud microphysics and cloud turbulence
in the region where activation takes place. These data will be
used to test cloud parcel models that predict cloud drop number
concentration based on sub-cloud aerosol properties and updraft
velocity. The third leg is a spiral up through the cloud to characterize
the vertical profile of cloud microphysics and precipitation.
The following questions will be addressed using the microphysical
profile: Is it possible to link the vertical and horizontal variation
of cloud drop dispersion to turbulent processes? to mixing with
detrained air? to the chemistry of the aerosol on which the cloud
forms? to giant nuclei? Does entrainment mixing appear to be homogeneous
or inhomogeneous or a conditional combination of the two? Is it
possible to predict which clouds are precipitating based on the
updraft strength, cloud thickness, and sub-cloud aerosol characteristics?
The last leg is an extended run above the cloud system to see
how well the radiometric retrievals of cloud properties compare
to the observed microphysical profile, and to characterize the
properties of the free troposphere aerosol that mixes with the
cloud from above. These radiometric runs provide evidence for
indirect effects (if they are apparent) as well as validation
of satellite remote sensing techniques for these cloud systems.
CLOUD SEEDING EXERCISES
Two cloud seeding sources will be used: ship tracks (if and when
they can be identified using satellite remote sensing) and the
cloud seeding flares. When a ship track is found, sampling will
proceed as described above, but in a race-track pattern transverse
to the track, so that at each altitude leg, both in- and out-of-track
samples will be characterized to maximize the contrast. Use of
the cloud seeding flares is more exploratory. The first step will
be to characterize the particle emission by the flares. Cloud
activation models will be used in the field to determine the predicted
effect these flares will have on the cloud as a function of measured
updraft velocity distribution and sub-cloud ambient aerosol characteristics.
It has been shown that different cloud systems have different
susceptibilities based on the local meteorology and ambient aerosol
characteristics. The activation model will predict the susceptibility
of these different cloud systems to various types of cloud forcing:
Twomey effects; precipitation suppression (Albrecht effect); and
precipitation enhancement (precipitation seeding effects). It
is anticipated that in some meteorological conditions the perturbation
may induce drizzle (i.e. the cases where there are few giant nuclei
in the upper reaches of the cloud), and in other cases it may
suppress drizzle (cases in which the mean droplet radius is suppress
to below 14 microns Ð the nominal threshold for the onset of collision-coalescence
drizzle formation). Coupled with a Gaussian dispersion model,
the effects will be predicted as a function of time and space
as the perturbation slowly disperses.
IMPORTANCE OF FORECASTING
The Naval Postgraduate School yields access to a wealth of satellite
images and forecast modeling data that can be used to identify
ship tracks and those meteorological variables (cloud cover, inversion
strength, sea surface temperature) that are most important for
predicting cloud susceptibility. These observations and predictions
will thus guide the choice of where to fly, which types of experiments
to conduct, and even whether or not to have a "no-fly" day.
PRE-EXPERIMENT MODELING
Key to the strategy will be modeling the experiment well before
reaching the field. A 3-D cloud resolving model (RAMS) that was
successfully used to model sub-tropical trade cumulus in HALO
and tropical cumulus congestus in CRYSTAL-FACE is presently being
modified to describe marine stratocumulus systems. The planned
sampling strategies can be tested against the predicted cloud
fields by asking: What is the evolution of the cloud over the
time it takes to make a single sampling run? What is the timescale
for the dispersion of the cloud seeding flare? Can Lagrangian
parcels be coupled to the cloud activation model to describe the
penetration of a perturbation to upper cloud regions where remote
sensing strategies can detect it? Under what background conditions
a strong signal be most likely? Do dynamical responses to aerosol
forcing have a signature that can be identified by either the
in situ measurements or the highly resolved remote sensing measurements?
By answering these questions before going to the field, it is
possible to design sampling strategies that provide the best opportunity
for success.
In summary, the following elements of the above strategy give
this proposed experiment a high probability for success. (1) Use
of a full hierarchy of models both before and during the field
campaign to anticipate the meteorological conditions and to shape
the sampling strategies; (2) use of closure study strategies using
state-of-the-art instrumentation that proved very successful in
the CRYSTAL-FACE campaign last July; and (3) use of local contrasts
in aerosol conditions under identical meteorological conditions
by cloud seeding and pursuit of ship tracks to isolate the aerosol
indirect effect. The data from these experiments should validate
an array of process models that are central to the development
of fundamentally based algorithms for the prediction of aerosol
indirect effects in local, mesoscale, and global models.
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Last Update: April 9, 2003