I wrote:
No, that's the whole point. A lower probability of icing in the cloud that is producing the snow/sleet, because the presence of snow is an indicator of glaciation and the probable absence of supercooled water.
to which crab replied:
The weakness in your argument is the use of the word probable here - the fact is that to produce snow in the first place you must have supercooled droplets so that the water can evaporate from the droplets and form ice crystals on the freezing nuclei (the Bergeron-Findeisen process).
So, since both will exist in varying amounts depending on the conditions you cannot say with any certainty that the snow cloud will be a lesser icing hazard than the no-snow cloud.
The question of whether snow is an indicator of reduced supercooled water provoked some research on my part, because I really wasn't sure of the cloud physics of glaciation when I wrote the words above. The point about certainty remains a good one -- there will rarely be a guarantee when it comes to icing. Nevertheless, I thought this was worth sharing. The papers I cite are available as full text online, links at the bottom.
The Bergeron Process is one of many competing processes going on in the cloud. The cloud microphysics models tend to consider water in six states: water vapour, cloud water, cloud ice, hail/graupel, rain and snow. The processes that cause transition between these states are complex -- Lin et al consider between 20 and 30 of them, of which the Bergeron process is just one. If I'm counting correctly, there are 9 responsible for snow formation. In Lin's model example, the Bergeron process turns out to be significant, but not the most significant process in snow production -- simple accretion of cloud ice and cloud water by the snow is the most effective in making more of it.
Reisin et al have a more sophisticated model involving nucleation, though the phases considered are essentially the same. They run the model for a number of different types of cloud e.g. maritime and continental, with different densities (low and high respectively) of cloud condensation nuclei. What is noticeable about their results is that in every case where snow is produced, the cloud water concentration has fallen to a small fraction (say 10% of its maximum) by the time significant snow is present. It's worth noting that the simulations are for cumulus cloud with a relatively high base (about 4000 ft and 4 degC), so the model is not simulating the clouds we see as producing snow on the ground. Nevertheless, the microphysical processes are substantially the same. In every case considered, the cloud is substantially glaciated (water has turned to ice) before snow is produced.
Zawadski and Szyrmer suggest ways of predicting supercooled water content (SWC) from radar reflectivity. That paper is interesting for the assertion (based on another Zawadski paper) it makes in the introduction:
"In a study of the development of microphysics in an
Atlantic storm, Zawadzki et al. (1993a, henceforth to
be referred to as ZOL) showed that during the devel-
opment of a precipitating system, the SCW appears as
a transient phenomenon during the uplift of initially
clear air. Once precipitation develops within the super-
cooled cloud and snow grows at the expense of the
liquid, SCW vanishes rapidly. It is also possible for
SCW to coexist at equilibrium with snow if the vertical
air motion is strong enough so that the rate of the gen-
eration of water vapor excess overcomes the rate at
which snow grows by deposition."
Much of the rest of the paper is about working out the critical vertical velocity that permits SCW to coexist with snow. I'd interpret it as saying that some pretty substantial updrafts are required to make that possible. The more snow, the more difficult it is for SCW to exist.
Then finally, there's the paper that describes the NWS/FAA Current Icing Potential (CIP) model. CIP is a real-world prediction of icing potential, and is quite sophisticated. You can see the output
here. The paper describes how data like numerical model output, satellite, METARs, radar and PIREPs are combined to reach the prediction of icing potential.
"In a similar situation in which only snow is reported
at the surface, ice crystals are clearly present beneath
and within the lowest cloud layer. These crystals scav-
enge SLW through riming and may completely glaciate
the cloud (Geresdi et al. 2005). In such cases, CIP de-
creases the maximum possible icing potential somewhat
by including a snow factor in the equation (see Table 2).
When the snow is associated with widespread radar
echoes of greater than 18 dBZ, there is likely to be an
abundance of large ice crystals aloft, implying more
riming, and the icing potential is further lowered. As
more of the grid box is filled with snow echoes, this
factor becomes stronger, further decreasing the poten-
tial for icing."
All that leads me to the same conclusion: seeing snow falling from a cloud significantly reduces the likelihood that the cloud will offer a significant icing hazard. Whether "significantly reduces" is good enough in the circumstances is a rather different debate!
Bulk Parameterization of the Snow Field in a Cloud Model Journal of Applied Meteorology
Volume 22, Issue 6 (June 1983)
Yuh-Lang Lin, Richard D. Farley, and Harold D. Orville
Diagnostic of Supercooled Clouds from Single-Doppler Observations in Regions of Radar-Detectable Snow Journal of Applied Meteorology
Volume 39, Issue 7 (July 2000)
I. Zawadzki and W. Szyrmer, S. Laroche
Current Icing Potential: Algorithm Description and Comparison with Aircraft Observations Journal of Applied Meteorology
Volume 44, Issue 7 (July 2005)
Ben C. Bernstein, Frank McDonough, Marcia K. Politovich, and Barbara G. Brown, Thomas P. Ratvasky and Dean R. Miller, Cory A. Wolff and Gary Cunning
Rain Production in Convective Clouds As Simulated in an Axisymmetric Model with Detailed Microphysics. Part I: Description of the Model Journal of the Atmospheric Sciences
Volume 53, Issue 3 (February 1996) pp. 497–519
Tamir Reisin, Zev Levin, and Shalva Tzivion
Rain Production in Convective Clouds as Simulated in an Axisymmetric Model with Detailed Microphysics. Part II: Effects of Varying Drops and Ice Initiation Journal of the Atmospheric Sciences
Volume 53, Issue 13 (July 1996) pp. 1815–1837
Tamir Reisin, Zev Levin, and Shalva Tzivion