Conventional wisdom is that stratus cloud supersaturations [S] are < 0.3% (100.3% RH) (Hegg et al. 2009) and that higher CCN concentrations (N_{CCN}) restrict cloud S (i.e., Twomey 1959). The Physics of Stratocumulus Tops (POST) field experiment in JulyAugust, 2008 off the central California coast provided a wide enough range of N_{CCN} and droplet concentrations (N_{c}) to test these concepts. Condensation nuclei (CN) were measured with a TSI 3010, CCN were measured by a Desert Research Institute CCN spectrometer (Hudson 1989), cloud droplets were measured with a Cloud Aerosol Spectrometer (CAS) probe (diameter 0.5851 µm), W was measured with a GPS corrected CMIGITS III all aboard the CIRPAS Twin Otter. N_{c} are averages of droplets larger than 0.58 µm diameter for those one second periods where CAS liquid water content (LWC) exceeded 0.1 gm^{3}. N_{CCN} are measured below the clouds.
Row 1, Table 1 shows the high correlations (R) between N_{1%} (N_{CCN} at 1% S) and N_{c}. Although belowcloud CCN provide the greatest influence on cloud microphysics the oftenobserved high N_{CCN} immediately above California coastal stratus (e.g., Hudson and Frisbie 1991) might also play a role in cloud microphysics by entrainment. In an attempt to ascertain this influence, the 69 vertical cloud penetrations are divided according to vertical aerosol profiles of CN concentrations (N_{CN}). These are used because the faster response of CN makes for easier discrimination from withincloud measurements. Columns 3 and 4 of row 1, Table 1 indicate high and similar R of N_{c}N_{1%} for the 40 cases with higher N_{CN} immediately above the stratus than below cloud N_{CN} (designated HA) and the 29 cases with just above cloud N_{CN} lower or similar to below cloud N_{CN} (designated LSA). These facts indicate that there was minimal influence of the above cloud CCN on N_{c}. This is also indicated by a division of each cloud penetration into altitude quartiles, which revealed the highest N_{c}N_{1%} R for the highest cloud altitude quartile.
Table 2 uses the entire CCN spectra between 1.5 and 0.04% S to estimate effective cloud S (S_{eff}) by determining the S of the various N_{CCN} that match mean N_{c} of each of the corresponding 69 vertical cloud penetrations (i.e., Hudson 1983). The last column of Table 1 is an attempt to minimize the effects of entrainment and droplet coalescence that reduce N_{c} and thus obscure N_{c}N_{CCN} relationships that usually establish N_{c} at cloud base. Such reductions of N_{c} could be independent of N_{CCN} , which would perturb the N_{c}N_{CCN} relationship and thus also the relevance of S_{eff}, which is the most pertinent when it reflects the influence of N_{CCN} on N_{c} at cloud base. Therefore, penetrations with linear LWC altitude profiles that are characteristic of adiabatic unmixed clouds should show higher N_{c}N_{CCN} R. Since they do not this indicates that entrainment does not seem to disrupt the N_{c}N_{CCN }relationship_{. }
Table 2 shows mean S_{eff} within various N_{1%} intervals. This is consistent with row 5, Table 1 in showing that S_{eff} is lower for higher N_{CCN}. R for S_{eff}N_{c} is also negative (with one small exception), but with smaller absolute values (Row 6, Table 1) than R for S_{eff}N_{1%}. R for S_{eff}N_{c} are less negative than R for S_{eff}N_{1%} because both S_{eff} and N_{c} are functions of N_{CCN}.
W also determines N_{c}; i.e., higher W produces higher S and N_{c}. R for N_{c}W is positive in row 3, Table 1 (except last column) but is much lower than R for N_{c}N_{1%} (row 2). Variations of W thus contribute to the scatter of N_{c}N_{1%} because W variations ought to be independent of N_{1%}. But N_{1%} and W are positively correlated (row 4; except last column). But since the effects of N_{CCN} and W on S_{eff} are opposite (higher N_{CCN} reduces S_{eff} whereas higher W increases S_{eff}) this positive albeit small coupling of N_{CCN} with W is probably the reason that S_{eff} does not display the expected positive correlation with W (last row, Table 1). Apparently this coupling allowed the greater effect of N_{CCN} variations on S_{eff} to overwhelm the effect of the W variations on S_{eff}. This means that the decrease of S_{eff} with N_{1%} shown in Table 2 could have been even greater had W been constant or independent of N_{CCN}.
Consistent with this is the fact that for the 17 adiabatic clouds W and N_{1%} were not correlated (R = 0.28; last column of row 4) and this probably contributed to the greater negative R of S_{eff}N_{1%} for the adiabatic clouds compared to all 69 vertical clouds (0.84 versus 0.74) in spite of the more limited N_{1%} range of the adiabatic clouds, which thus prevented observations of the greatest reductions of S_{eff} caused by the highest N_{1%}.
Table 2 shows the decrease of cloud S with N_{CCN} and higher stratus cloud S than conventional wisdom especially since these are underestimates of cloud S. This means that much smaller particles can nucleate stratus clouds (e.g., 30 nm rather than 60 nm ammonium sulfate particles). This has important implications for the largest climate uncertaintythe indirect aerosol effect (Alley et al., 2007) and for geoengineering schemes to brighten marine stratus clouds. Smaller particles are easier to produce either deliberately or inadvertently.
Alley, R.B., and Coauthors, 2007: Cambridge University Press, 118.
Hegg, D.A., D.S. Covert, H.H. Jonsson, and R. Woods, 2009: Tellus, 61B, 669676.
Hudson, J.G., 1983: J. Atmos. Sci., 40, 480486.
Hudson, J.G., 1989: J. Atmos. & Ocean. Techn., 6, 10551065.
Hudson, J.G. and P.R. Frisbie, 1991: J. of Geophys. Res., 96, D11, 20,79520,808.
Twomey, S., 1959: Pure. Appl., 43, 243249.
Table 1. Correlation coefficients (R) between various parameters. First rownumber of clouds.
all 
HA 
LSA 
adiabatic 

number 
69 
40 
29 
17 
N_{c}N_{1%} 
0.85 
0.89 
0.84 
0.79 
N_{c}W 
0.45 
0.39 
0.51 
0.23 
N_{1%}W 
0.39 
0.30 
0.53 
0.28 
S_{eff}N_{1%} 
0.74 
0.86 
0.35 
0.84 
S_{eff}N_{c} 
0.35 
0.62 
0.13 
0.41 
S_{eff}W 
0.12 
0.06 
0.18 
0.57 
Table 2. Mean S_{eff} within various average N_{1%} ranges.
N_{1%} (cm^{3}) 
< 100 
100200 
200300 
300400 
> 400 
mean S_{eff} 
0.87 
0.51 
0.46 
0.43 
0.11 