than is drop size. Nevertheless, the magnitude, distri-
ASOS (Automated Surface Observing System) observa-
bution, and organization of supercooled liquid water in
tions at over 600 locations nationally (Ramsay 1997),
3-D space is still only generally understood, especially
which observe freezing rain, could improve understand-
with regard to the conditions that aircraft typically
ing of the location, spatial patterns, frequency, and mag-
encounter. A large component of the problem within
nitude of SLDs.
supercooled clouds is glaciation. Though attempts have
Proponents of in-flight remote-sensing systems have
been made to model and measure glaciation to develop
argued that outside air-temperature measurements made
a better understanding of the process, it is still not possi-
at the fuselage are adequate for temperature character-
ble to predict accurately whether a given cloud is glaci-
ization ahead of the aircraft. Though this may be gener-
ated, when it will glaciate, and how much of the total water
ally true in cruise at constant-altitude flight, it is not
content is ice. Some remote sensors are sensitive primari-
true where icing is most likely to occur: within storms
ly to liquid water, such as microwave radiometers, and
and in the climb-out and descent phases of flight. Air
for users of these systems, mixed-phase clouds are of
temperature changes most rapidly in the vertical and
little concern. However, mixed-phase conditions may
within storm systems. Storms and lower altitudes are
enhance the ability of radar to detect liquid water, so
also where supercooled water is more frequent, so the
the glaciation process needs to be better understood.
reliability of outside air-temperature measurements for
Although less important than liquid-water content for
predicting temperature ahead of the aircraft is least
determining the amount of ice to form on an aircraft,
where the need is greatest. Thermal lag also occurs as
drop size, and especially supercooled large drops
snow falls into warm air and melts, and as rain falls
(SLDs), determine the location and shape of ice forma-
into colder air and supercools, making drop tempera-
tions. Thus, drop size may have a larger impact on iced
ture unknown even if air temperature is known. In addi-
aircraft aerodynamics than liquid-water content does.
tion, evidence from a few studies suggests that temper-
Drop size is also a more difficult parameter to measure
ature does fluctuate considerably within cloud masses
than liquid water, and characterization is therefore less
and from cloud to cloud and from clear to cloud. Air-
temperature fluctuation, especially near 0C, must be
complete than for liquid water. Cloud droplet size varies
with cloud type, cloud dynamics, location within clouds,
better characterized within clouds and near frontal sur-
from cloud to cloud, with the season, air-mass origin,
faces. Radiosonde observations and in-flight measure-
and other factors. Drop sizes are often characterized by
ments from existing flight programs can provide most
the median volume diameter (MVD), which assumes a
of this information.
unimodal drop-size distribution. This may not always
The spatial structure and the size of icing areas have
be the situation, especially when SLDs are present.
not been characterized. Spatial patterns of icing must be
The shape of the drop-size distribution must be care-
characterized at all scales, from global to submesoscale,
fully sensed and characterized. This is especially impor-
but spatial patterns are perhaps best understood at the
tant for SLDs. Instruments that count drops, such as
synoptic scale. The horizontal extents of icing speci-
optical array probes, have the best probability of suc-
fied in FAR 25, Appendix C, do not imply the overall
cessfully characterizing drop size. Characterizations of
dimensions of icing cloud systems. Overall, little work
drop size conducted concurrently with liquid-water
has been conducted in this area, with the best character-
measurements will provide relationships between the
izations being by Cooper at al. (1982) and by the Cana-
two and to atmospheric dynamics. Drops are usually
dian CFDE program (Cober et al. 1996b).
smaller within stratiform than within cumuliform clouds,
Cloud microphysics are a focus of several large fed-
but more emphasis should be placed on explicit drop-
erally funded research programs, and icing remote-
size measurements and, at least, characterization of the
sensing researchers should partner with these teams to
drop-size spectra.
accomplish objectives more efficiently. For example,
The need to characterize SLDs is even more critical
the DoE Atmospheric Radiation Measurement (ARM)
than characterizing smaller drops because of the danger
Program monitors cloud microphysics to determine the
SLDs present to aircraft and because far less is currently
effects of cloud cover, type, height, and phase on glo-
known about them than about smaller drops. Flight pro-
bal radiation budgets. The ARM program maintains
grams to measure SLD characteristics, such as the Cana-
field sites in Oklahoma and on the North Slope of
dian CFDE project and the NASA Glenn Research Cen-
Alaska. Remote sensing of clouds is one of their tools,
ter SLD program, should be continued and expanded.
and NOAA ETL has been a participant in this capacity.
Ground-based programs may also be useful for charac-
The Global Energy and Water Cycle Experiment
terizing conditions aloft. For example, sleet, freezing
(GEWEX), part of the World Climate Research Pro-
drizzle, and freezing rain at the surface are often accom-
gram, also has a cloud microphysics component that
panied by freezing precipitation aloft. Utilization of
may be of value to aircraft-icing remote-sensing research.
12
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