Ice Particle Initiation and Development at
Temperatures Above -35C
General ice formation processes not specific to cirrus or contrails, i.e. ice
nucleation, multiplication, growth by deposition, riming and aggregation
Andrew Heymsfield, Alexei Korolev, Jean-Francois Gayet,
Paul DeMott, Ottmar Möhler
Pressing Needs
• Weather Forecast and Climate Models representing
precipitation development-IN concentrations are vital
• Global change studies
• Representing ice particle properties (masses, terminal
velocities in models.
• Physics topics:
– Explaining the discrepancies between ice concentrations and ice
nucleus measurements
– Differentiating the different IN modes
– Identifying the reasons why tropical maritime convective clouds
glaciate so quickly
– Characterizing the processes involved in secondary ice production and
have we identified all of them.
From DeMott et al., 2010 BAMS (submitted)
Heterogeneous Ice Nucleation
Red: Difficult to detect with aircraft as their concentrations might be below
the sample volume detection limit of the particle probes and there might be
other sources of these particles, such as blowing snow off the surface, preactivation,
Etc. Surface enhanced nucleation identification requires precision relative humidity
measurements and immediate detection of the ice.
Comments by Markus on Deposition Nucleation
C130
Ht
Above
C130
(km)
Elk Mountain, Wyo. with blowing snow that was lofted to
the C130 level as observed from the onboard cloud radar.
Through simple experiments, Durant and Show (2005) found that the formation of ice
within a liquid water drop by heterogeneous nucleation occurs at higher temperatures
if the IN is in contact with the surface of the drop, than if it is fully immersed within the
bulk of the drop
IN Concentration f(Temperature)
Ambient aerosols are
variable in compositionconsider dust outbreaks
vs pristine maritime air
When IN are related to
the concentration of aerosols
>0.5 microns, this variability
is greatly reduced.
Demott et al. (2010)
IN number concentration (at STP) active at water saturation or above vs. temperature. Projects (see SI Text) are WISP-94 (gray
triangle), Alliance Icing Research Study—2 (X), AMAZE-08 (square), Cloud Layer Experiment-10/ Canadian Cloudsat/CALIPSO
Validation Project (open circle), Ice in Clouds Experiment—Layer Clouds (solid circle), Ice Nuclei SPECTroscopy-1 (–), Ice Nuclei
SPECTroscopy-2 (diamond), Mixed-Phase Arctic Cloud Experiment (black triangle), and Pacific Dust Experiment (open triangle).
Parameterizations described in the text are labeled and are plotted over the experimental measurement range on which they were
based. The dashed gray line is a T-dependent fit to all data.
Hypothesized Activity of IN
•Dust (mainly T<-15C, Ansmann et al, AIDA)
•Carbonaceous Particles, soot (where T<-20C)
•Biologic (dominate where T>-15C) [windblown bacteria, decayed plant
matter, pollen, lichen and fungi, see Pratt et al., 2009 and discussion in
DeMott et al., 2010)]
•Aging is important.
Biologic Nuclei
•
•
•
•
At temperatures warmer than about -25 C, biological particles seem to dominate the icenucleus population, although ice-nucleus number concentrations are only of the order of 1-2
per liter at these temperatures. These ice nuclei will be the first to initiate ice formation in
clouds, and thus despite their low number concentrations, primary biological aerosol
particles will have an important role in precipitation and cloud dynamics (Prenni et al., 2009)
SOA (also carbonaceous) seems to be not an important source of IN
(http://www.agu.org/pubs/crossref/2009/2008GL036957.shtml), consistent with Ottmar's
papers that SOA coatings inhibit freezing at T < -40C). There is indirect evidence that
presence of the operationally defined organic carbon is detrimental to IN efficiency
(http://www.agu.org/pubs/crossref/2009/2008JD011532.shtml (Markus)
Soot are probably not good IN
Conclusion: Carbonaceous IN are mostly biologically derived
Ionizing Cosmic rays as sources?
(Carswell et al., 2002)
Eidhammer
et al (2010)
● The next figure from ASTAR 7 April 2007 taken from the insitu aircraft illustrate the well topped stratiform cloud
layer (T = -23°C) and the ice precipitating down to the sea surface.
● These results suggest efficient ice growth processes mainly due to vapor deposition in the boundary layer which
is likely ice-supersaturated. About 25% of the theoretically available liquid water is converted into ice water with
large precipitating ice crystals.
J.F. Gayet
ASTAR 7 April 2007
Ts = -23°C
MODIS
10:00 UT
Airborne
observations
Calipso /
CloudSat trace
Figure 1
NAMMA
Fractured
Drops
Cannon, 1970
NAMMA, 20 Aug 2006,
17:22:43 UTC, T=-7.7C
Drops, graupel
and needles
Located in LW
region at -7.7C
Schwarzenboeck et al. 2009
Fractured
Branched planar
crystals
D. Other Sources of Ice
1: APIPS
2: Survival of ice in clear air
3. Blowing snow
A. Heterogeneous Processes
Measurement Limitations (see left column)
1. Condensation/freezing nucleation
1, 3, 4, 6, 8, 9
2. Immersion freezing
same as A1
3. Contact nucleation
Same as A1, 7
4. Deposition nucleation
1, 6, 7, 8, 9
B. Secondary Processes
1. Droplet freezing/shattering
1, 2, 5
2. Crystal/Aggregate Fragmentation
1, 2,3, 5
3. Involving the riming process
1, 2, 3, 4, 5, 6, 8, 9, 10
4. Pre-activation
1,7, 8
5. APIPS
10
C. Observations of ice nucleation
1.Laboratory
Representativeness is the big issue
2.In clouds
1, 2, 3, 4, 6, 8, 10
3.Remote sensing
Retrievals are necessary-how good?
D. Ice nucleus composition
1. Biogenic/Biologic
1, 2, 5, 7
2. Dust
2, 3,
3 Cosmic Rays
7, 8
4. Pre-activated ice nuclei
1, 6, 8, 9
Measurement Limitations
1. Probe Sample volume
2. Probe resolution
3. Shattering issue
4. Phase discrimination
5. Ice shape/Morpholgy
6. Differentiating secondary ice
7. Ambient relative humidity
8. Determining ice origin
9. Ice nucleus composition
10. APIPS
A. Dimensional, Area and Mass Growth
1, 2, 3, 4, 5, 6, 7
B. Crystal habit f(time)
1, 2, 3, 4
C. Crystal volume
2, 4, 7
Ideal Instruments: 2DS, a, c axes
Holodec
Measurement Limitations
1. Sample volumes, small particle probes
2. Probe resolution
3. Phase discrimination mixed phase
4. Ice shape/morphology
5. Ambient RH
6. Determining ice origin
7. Mass of individual ice particles
Growth by Accretion, Aggregation
A. Riming Process
1. Collection Efficiencies
2. Fallspeeds
3. Masses/Densities
4. Habits, morphological changes
1, 2
4
4
1, 2
B. Aggregation
1. Collection efficiencies f(temp)
2. Fallspeeds f(time)
3. Masses, Densities single xtals
4. Habits, morphology f(time)
1, 2, 3
4
4
1, 2
Measurement Limitations
1. Probe resolution
2. Resolution of Ice shape/morphology
3. Determining ice origin (position, time)
4. Mass, dimensions individual particles