Aircraft field measurements of cloud condensation nuclei (CCN) and cloud microphysics in maritime air masses showed ubiquitous influence of CCN. Flight averages of CCN concentrations and cloud droplet and drizzle drop concentrations were examined for as many as 17 flights during the Rain in Cumulus over the Ocean (RICO) project. CCN concentrations at only one supersaturation (S) of 1% measured at 100-m altitude were compared with cloud droplet and drizzle drop concentrations at six altitude bands between 600 and 3000 m. High positive correlations (R) between these CCN concentrations and the small size threshold of the cumulative cloud droplet concentrations (i.e., total activated cloud droplets) were found at all altitudes. These high R values also persisted for cloud parcels with a wide span of liquid water contents (LWCs), most of which were far below adiabatic (unmixed) values. For all but the lowest LWC parcels, R was essentially constant. There was an even more consistent negative R between CCN and large cloud droplet and drizzle drop concentrations. There was a sharp transition from positive to negative R over a small size range. The size at which this R transition occurred increased with altitude and LWC as overall droplet sizes increased with altitude or LWC. Entrainment seemed to show an opposite effect on R, but this was only apparent at the highest altitudes where entrainment was greatest and only for the smallest droplet sizes. These results indicate that the effect of CCN concentrations on cloud microphysics was pervasive with altitude, LWC, cloud droplet, and drizzle drop concentrations. This indicates greater impact of the indirect aerosol effect (IAE) in both of its manifestations, first IAE cloud radiation and second IAE precipitation.
 The effect of preexisting or precloud aerosol on cloud microphysics is fundamental to cloud physics. Interest is piqued by the wide range of observed aerosol and cloud droplet concentrations, compositions, and size distributions. The fact that a large but as yet unquantified component of the atmospheric aerosol is of anthropogenic origin, gives rise to an indirect aerosol effect (IAE), which is the largest climate uncertainty [Intergovernmental Panel on Climate Change, 2007].
 IAE consists of at least two components: 1st IAE the effect on cloud radiative properties (i.e., higher cloud condensation nuclei [CCN] and cloud droplet concentrations producing brighter clouds [Twomey, 1977]), and 2nd IAE precipitation inhibition [Albrecht, 1989] due to smaller cloud droplets. Both subjects are addressed here in a study that builds upon the work of Hudson and Mishra  (hereafter HM7). That study was part of the Rain in Cumulus over the Ocean (RICO) project [Rauber et al., 2007], which was done in December–January 2004–2005 in the northeastern Caribbean. Measurements presented by HM7 and here were all made from the NCAR C-130 airplane. The cloud condensation nuclei (CCN) measurements of HM7 and here were flight averages at 1% supersaturation (S) over two 60-km-diameter circles flown at 100-m altitude at the beginning and ends of each flight. Each circle took approximately 30 minutes. There were also similar circles at 300–400-m altitude near cloud base that showed nearly identical CCN concentrations [HM7]. During the usually four hour intervening period the C-130 semirandomly sampled small cumulus clouds at various fixed altitudes for 30–60 minutes [Rauber et al., 2007]. The cloud microphysics measurements (i.e., droplet and drop concentrations) presented by HM7 and here were also averages over each of the flights. HM7 showed both of the expected aerosol effects, namely CCN concentration variations on cloud microphysics; i.e., droplet concentrations (1st IAE) and droplet sizes (2nd IAE).
 However, the analysis of HM7 was limited to only the early stages of cloud development near the bases of the small cumulus clouds that were studied in RICO. Although HM7 did find a strong positive correlation (R) of CCN concentrations with cloud droplet concentrations (1st IAE) and a strong negative correlation with mean PMS Forward Scattering Spectrometer Probe (FSSP; 2–46 μm diameter) cloud droplet sizes (2nd IAE), the analysis was restricted to cloud parcels with liquid water content (LWC) greater than 0.25 gm−3, updrafts (W) exceeding 0.5 m/s and altitudes of 600–900 m. Although that article claimed to demonstrate the greater influence of CCN than giant nuclei (GN) [i.e., Colon-Robles et al., 2006] on precipitation initiation, the limits placed on that analysis did not really demonstrate the effects of CCN on either cloud radiative properties or precipitation. For instance it has been suggested that dynamical processes could wash out initial aerosol effects at cloud base [e.g., Baker et al., 1979, 1980; Telford and Chai, 1980; Telford and Wagner, 1981]. Thus, at higher altitudes where cloud radiative properties are of greater importance and where precipitation is usually initiated, the effect of the subcloud CCN may be muddled. Since there is more entrainment at higher altitudes, which usually reduces cloud LWC well below adiabatic values by partial (homogeneous) or complete (inhomogeneous) evaporation of droplets, it seems certain that entrainment significantly alters many or even most aspects of cloud microphysics including the influence of CCN concentrations. Furthermore, altitude variations of CCN concentrations would result in different CCN concentrations and/or spectra in the entraining air that may also reduce the apparent influences of subcloud CCN. To address these and other considerations the present analysis broadens all cloud microphysical aspects of HM7, LWC, W, droplet/drop sizes, and altitude.
Table 1 shows that the present analysis considers three more RICO flights than HM7, Research Flight (RF) 4, 11 and 17, December (D)10, January (J)7, and 19. RF17 is, however, hampered by the failure of the 260× drizzle drop probe (∼40–600 μm diameter). Nonetheless, this brings the total number of flights under consideration up to 17 of the 19 total RICO research flights. RF19 (J24) could not be considered because of failure of the FSSP and RF16 (J18) did not have sufficient CCN measurements.
Table 1. Flight Number; Date; and Duration (Number of Seconds) of Data in Each Cloud Threshold Category, Hudson and Mishra , FSSP LWC, and Concentrationa
Duration (s) LWC > 0.25 (gm−3) w > 0.5 m/s HM7
Duration (s) LWC > 0.1 (gm−3)
Duration (s) LWC > 0.01 (gm−3)
Duration (s) LWC > 0.001 (gm−3)
Duration (s) Concentration > 1 (cm−3)
Everything in this table pertains to 600–900 m altitude. w is updraft velocity.
 In an effort to better understand and define the influence of CCN on cloud radiation and precipitation we relaxed the criteria for cloud parcels considered in the work of HM7 (Figure 2a). It has often been assumed that CCN concentrations should be more closely related or correlated with cloud droplet concentrations that are closer to adiabatic (unmixed). The LWC and W, restrictions imposed by Colon-Robles et al.  and HM7 attempted to do this. However, here in Figure 1 the only restriction on cloud parcels is LWC >0.1gm−3 rather than 0.25 gm−3 and there is no restriction on W. This increases the number of cloud parcels considered for each flight by more than a factor of three and expands the total number of 1s cloud parcels under consideration for Figure 1 by a factor of five (Table 1). This data increase is especially pertinent for the inordinately small number of parcels considered by HM7 for RF2 (1s) and RF7 (2s). These two data points in Figure 1 are now more robust with 30 and 73s of measurements (Table 1). These relaxed cloud criteria also result in two additional data points in Figure 1 because two more flights, RF4 and 11, now have cloud parcel measurements that meet the eased cloud criteria. The CCN-total cloud droplet concentration (Nc) correlation coefficient (R) is higher with this data expansion, 0.85 for Figure 1 versus 0.80 in the work of HM7 (Figure 2a). The slope of the linear regression is diminished from 1.08 to 0.93 because of the many lower concentration cloud parcels that are included with the lower LWC threshold. The low-magnitude regression intercept is only slightly changed by this data expansion. If this regression analysis is restricted to the same 14 flights reported by HM7, R increases to 0.88 (Figure 1). When the cloud threshold criterion is further reduced to FSSP LWC >0.01 gm−3, which provides three times more data than the 0.1 gm−3 threshold (Table 1), R increases to 0.88. This relaxed LWC threshold also allows the addition of RF17 albeit with only one 1s measurement. However, the addition of this flight raises R to 0.89. A further reduction of the cloud threshold either to 0.001 gm−3 FSSP LWC or to FSSP droplet concentrations greater than 1 cm−3 expands the number of cloud parcels by another 40% (Table 1) and raises R to 0.90 for 16 flights or 0.92 for all 17 flights. Note that even an R of 0.78 has a significance level (SL) of 99.95% even for only 14 flights. An R of 0.80 means a coefficient of determination (R2) of 0.64, which means that CCN are responsible for 64% of the variations in Nc. An R of 0.90 means that CCN are responsible for 81% of the Nc variations. These results indicate that CCN influence is not restricted to adiabatic cloud parcels.
 Comparisons among flight-averaged cloud microphysical properties within various altitude bands such as the 600–900 m band shown in Figure 1 are justified by the fact that cloud base altitudes (∼600 m; ∼945 mb) and temperatures (∼20.3C) were rather consistent throughout RICO. Rather than the gross measure of the overall droplet spectra expressed by the mean diameter of the FSSP distribution [HM7] we now examine CCN concentration correlations with cumulative droplet concentrations that exceed various threshold sizes; i.e., cumulative concentrations of larger cloud droplets. Figure 2 shows how the CCN-cumulative droplet concentration regression (R) reverses sign (is negative) when only larger droplets are considered. Figure 3 shows R as a function of altitude bands for various droplet size thresholds. Figure 3a considers all of the flights that had data within the various altitude bands, but this means different numbers of flights and different flights at the different altitudes. Since this could bias the results, Figure 3b considers only the same 8 flights for all altitudes though this restriction eliminates the 2400–3000 m band. The smallest droplet size thresholds (2.4, 5, and 10 μm) have rather similar large positive R values at all levels, whereas the largest cloud droplet thresholds (35 and 40 μm) have negative R at all levels. The magnitude of the negative R for these largest cloud droplets is similar for all but the lowest-altitude band (600–900 m). Intermediate droplet size thresholds (15, 20, 25 and 30 μm) shift from low positive or high negative values at low altitudes to high positive values at higher altitudes as a result of greater droplet growth at higher altitudes due to more condensation on the same concentration of droplets. This growth results in greater concentrations of larger droplets at the higher altitudes. This results in a shift with altitude of the intermediate droplet size thresholds from only the tail of the distribution at low altitudes toward the entire droplet spectrum at higher altitudes. The magnitudes of R for both the smallest and largest droplets are much greater in Figure 3b than 3a. The lower R for the small droplets in the 1500–1800-m-altitude band in Figure 3a is due to the RF9 data. RF9 small cumulative droplet concentrations are a significant outlier in this altitude band as they are more than 100 cm−3, whereas they are less than 50 cm−3 at the other altitudes. This was probably consistent with the fact that a longer-duration high-concentration CCN “spike” was measured during one of the 100-m-altitude circles during RF9. As noted by HM7, these usually short-lived high-concentration CCN spikes due probably to ship exhaust remnants [Colon-Robles et al., 2006], were removed from consideration of the CCN concentration averages. Apparently that high CCN concentration air parcel measured during RF9 produced a few cloud parcels with correspondingly high droplet concentrations and those parcels happened to be observed only in the 1500–1800-m-altitude band. This anomalously low R at 1500–1800 m is not displayed in Figure 3b because RF9 was not one of the eight flights displayed here because RF9 did not have data at all five altitude bands. An R of 0.79 for eight flights has an SL of 99%.
Figure 4 shows R for CCN and drizzle drop concentrations from the 260× probe as a function of altitude for several different threshold sizes. Figure 4 displays all of the data, which means that like Figure 3a the different numbers of flights and different flights considered at the different altitudes may bias these interaltitude comparisons. A figure similar to Figure 4 (not displayed) is analogous to Figure 3b in that data are only from the same eight flights. This undisplayed figure is quite similar to Figure 4. Therefore the different numbers of flights and the different flights at the different altitudes did not seriously bias the data. Figure 4 also shows that drizzle drop concentrations near cloud base are not correlated with CCN concentrations, but the next four or five altitude bands (900–3000 m) display increasingly negative R for all drizzle drop sizes. R is lower in magnitude for larger drizzle diameters especially at higher altitudes.
 The same R values shown in Figures 3a and 4 are displayed in Figure 5, where R is plotted against threshold diameter for the various altitude bands. Figure 5 shows that, as expected, the highest R for Nc and the smallest threshold sizes is near cloud base where subcloud CCN concentrations should have the most direct influence. R for these smallest sizes decreases somewhat at higher altitudes as also shown in Figure 3. However, Figure 5 also shows very high positive R for somewhat larger droplet thresholds (i.e., 15–30 μm) at the higher altitudes. This indicates that the positive influence of the input CCN on cloud droplet concentrations is not restricted to the lowest altitudes; i.e., droplet number concentrations apparently persist to higher altitudes as the droplets change only in size (larger). The most obvious feature of Figure 5 is the abrupt transitions from positive to negative R in the 10–45 μm range. This transition tends to occur at larger sizes for higher altitudes because overall droplet sizes increase with altitude as more water condenses on the same concentrations of droplets. This R transition and the negative R for larger droplets shows that droplet concentrations due to input CCN concentrations also have a strong negative effect on larger droplet concentrations; i.e., higher CCN/cloud droplet concentrations restrict droplet sizes due to the fact that the same amount of condensing water has to be split among more droplets when the concentrations are higher. Clouds formed with lower CCN concentrations can achieve larger droplet sizes, which results in relatively higher concentrations of large droplets. The size at which R plummets from large positive to large negative values generally increases with altitude because of the overall larger droplet sizes at higher altitudes. The 1500–1800-m-altitude band is somewhat of an exception in this regard; its R plummet is more gradual with diameter. One reason for this is the low R at small sizes due to the anomaly of RF9 mentioned earlier but other factors must also be at work to reduce R at this altitude. For the 600–900-m-altitude band the magnitude of the negative R decreases for diameters larger than the diameter at maximum negative R (20 μm; R = −0.62) to no correlation for sizes greater than 40 μm (absolute value of R < 0.2). This lack of correlation for larger droplets is probably due to the limited sizes of the droplets at this low altitude because of the small amount of condensed water. For higher altitudes R generally progressively reaches greater negative values at slightly larger threshold droplet sizes. For the higher altitudes R generally remains at large negative values out to considerably larger sizes before finally decaying to very small R values at large drop sizes. Nonetheless, for all altitudes except the lowest (600–900 m) R is always negative for all droplet or drop sizes beyond the size where R plummets to negative values. R is generally a greater magnitude negative number at higher altitudes. The 2400–3000-m-altitude band is an exception for drops larger than 90 μm. This may be a result of the small number of flights with data in this altitude band. Nonetheless, this altitude band does have the greatest negative R of 0.88 at 45 μm. Other reasons consistent with this one for the decrease in magnitude of R for larger drizzle drops include the lower statistics of the smaller concentrations of the largest droplets. The extreme of low statistics, zero concentrations of large droplets for some flights, puts a limit on the concentration variations among flights, which thus tends to reduces R. In general we would expect the influence of the total CCN concentrations to be progressively less explicit for larger drop sizes because CCN concentrations only directly influence the total concentrations of droplets (Nc).
Figures 3–5 use FSSP LWC >0.1 gm−3 as the threshold to define cloud parcels. Figures similar to these have been drawn using the various cloud threshold criteria displayed in Tables 1 and 2. Although these criteria produced vastly different numbers of cloud parcel data points that made up the flight-averaged droplet and drop concentrations, the R values from these figures had nearly the same patterns and even quite similar values to those displayed in Figures 3–5. This ensued in spite of lower average droplet concentrations for the less restrictive cloud thresholds that resulted in the consideration of more measurements to produce the droplet concentration averages.
Table 2. Number of 1-s Parcels Within Various Altitude Bands and for Various Cloud Thresholds for All of the Data Considered Here
Data Points for All Altitudes
FSSP LWC > 0.1 (gm−3)
FSSP LWC > 0.01 (gm−3)
FSSP LWC > 0.001 (gm−3)
FSSP Concentration > 1 (cm−3)
260× Concentration > 1 (l−1)
Table 3 summarizes the average LWC and altitudes for the cloud parcels with FSSP LWC >0.01 gm−3 within the six altitude bands. These are averages for the same flights depicted in Figures 6–13 and text concerning correlations for various LWC bins. These averages are almost identical to the averages of all of the flights with and for cloud parcels that have LWC >0.01 gm−3. Table 3 (sixth column) shows the adiabatic LWC for the altitudes in column 2. Table 3 (last column) is the fifth column divided by the sixth column, which is the average adiabaticity in each band.
Table 3. Altitude Bands, Means, and Standard Deviations of Measured Mean Flight-Averaged Altitudes for LWC > 0.01 gm−3 for Flights Considered for Correlations Within the Various LWC Bins in Figures 6–13 and the Text, Mean LWC for These Flights, Adiabatic LWC at the Mean Altitudes, and Ratio of Mean Total LWC to Adiabatic LWC
Altitude Band (m)
Mean Altitude (m)
Mean LWC FSSP (gm−3)
Mean LWC 260× (gm−3)
Mean Total LWC (gm−3)
Adiabatic LWC (gm−3)
2660 ± 150
0.34 ± 0.18
0.22 ± 0.10
2010 ± 70
0.33 ± 0.16
0.09 ± 0.05
1612 ± 87
0.29 ± 0.10
0.04 ± 0.03
1358 ± 74
0.25 ± 0.08
0.02 ± 0.02
1049 ± 77
0.18 ± 0.05
0.01 ± 0.01
798 ± 33
0.10 ± 0.02
0.01 ± 0.01
Figure 6 is like Figure 5 except that it shows R as a function of cloud droplet threshold diameter for various FSSP LWC bins within one altitude band, 600–900 m. Similar high positive R is seen for all LWC up to 10 μm except for the lowest two LWC bins (<0.10 gm−3) at 10 μm. Between 10 and 20 μm R plunges to extreme negative values of 0.7–0.8 at 20 μm and then gradually decreases in magnitude for larger droplets. The only positive R (0.17, which indicates no correlation) for thresholds above 20 μm is for the 40 μm droplets in the highest LWC bin (0.35–0.40 gm−3). Figure 7 displays the same data as Figure 6 but as a function of LWC bins for each cumulative droplet diameter. The consistency of R with LWC is most significant. The only exception is the one data point just mentioned and the 15 μm threshold. This is the transition size threshold, which changes from only the large-size tail of the droplet distributions in the low LWC bins (negative R) to a greater share of the cloud droplets in higher LWC bins (positive R) where droplet concentrations above this size more closely approximate Nc. For the eleven flights considered here, R of 0.73 has an SL of 99.5% and R of 0.84 has SL of 99.95%.
Figures 8 and 9 show the same data as Figures 6 and 7 for the next higher-altitude band (900–1200 m). Since there is more condensed water at higher altitudes there are more LWC bins to be displayed (11 instead of 8). The positive correlations for Nc (2 μm) are even greater in magnitude (∼>0.9) than at 600–900-m altitude for all but the two extreme LWC bins (0.01–0.05 and 0.50–0.55 gm−3). Because of the greater overall droplet sizes at this higher altitude because a greater LWC has condensed on the same concentrations of droplets, R continues to be uniformly high positive out to larger threshold diameters than for the 600–900-m-altitude band; i.e., 15 μm instead of 10 μm. The plunge to negative R then occurs at larger sizes; i.e., 15–25 μm because the droplets are larger at this higher altitude. Within this figure the size where the plunge occurs is generally at larger sizes for the higher LWC bins where droplets are larger because concentrations are not a function of LWC. The maximum magnitude of the negative R here is at 25 μm rather than 20 μm in the 600–900-m-altitude band, and it is greater in magnitude (0.8–0.9 compared to 0.7–0.8). The gradual decrease in magnitude of R for sizes larger than 25 μm is much less than it is for the 600–900 m band because the higher concentrations of larger droplets provide better statistics than was the case for the 600–900 m band. R for sizes above the transition (plummet) is never anywhere near positive. The least negative R beyond 25 μm (−0.37) is for the lowest LWC bin (0.01–0.05). In spite of the low positive R values for the two extreme LWC bins (0.50–0.55 and 0.01–0.05) for Nc and small droplet thresholds (<15 μm), the negative R for diameter 25 μm even for these two extreme LWC bins is approximately the same value as the minimal R values for the other LWC bins. The highest LWC bin (0.50–0.55) shows the most negative R above 30 μm while the lowest LWC bin (0.01–0.05) shows the least negative R probably because of a shortage of large droplets (low statistics). The lower R values for the lowest LWC bin (0.01–0.05) at small droplet sizes (<15 μm) is probably due to entrainment, which will be discussed later. The more extreme R values of this higher-altitude band are most apparent by comparing Figures 7 and 9. Here the transition size is 20 μm rather than 15 μm at 600–900 m. This transition size goes from negative R at low LWC where this threshold size is only the tail of the distribution (few droplets exceed this size) to positive R for high LWC where most droplets exceed this size. Thus the concentrations above this threshold size at high LWC more closely approximate Nc, which is positively correlated with the CCN concentration. This negative to positive R transition is due to similar Nc at most LWC, which then results in larger droplet sizes at higher LWC.
 The next two altitude bands 1200–1500 m and 1500–1800 m have very similar R patterns. The 1200–1500-m-altitude band had twelve flights with data within all of the same eleven LWC bands displayed for the 900–1200-m-altitude band, up to 0.50–0.55 gm−3. The 1500–1800-m-altitude band has three more LWC bins to consider, 14 bins up to 0.70–0.75 gm−3. However, the 1500–1800-m-altitude band has fewer flights, seven, with these 14 LWC bins. Most of the LWC bins for these two altitude bands follow the same pattern as the two lowest-altitude bands. One exception is the lowest 2 or 3 LWC bins (<0.15 gm−3), which like the two lowest LWC bins for 900–1200 m show low or no correlations at the smallest sizes. This is also probably because of entrainment, which is discussed later. There is still consistency of the R values for each LWC bin at the various small size thresholds up to 20 μm for 1200–1500 m and up to 25 μm for 1500–1800 m. This maximum threshold size with positive R values similar to those of smaller size thresholds is larger at higher altitudes because of the greater condensation on the same droplet concentrations at the higher altitudes. However, below these maximum size thresholds with positive R there is a lot of inconsistency in R among the LWC bins. The plunges from positive to negative R are quite consistent among the LWC bins especially for 1500–1800 m. The plummets continue the trend of occurring at progressively larger droplet sizes for the higher altitudes; 20–30 μm for 1200–1500 m and 25–30 μm for 1500–1800 m simply because of the overall larger droplet sizes at higher altitudes. The negative R for 30–40 μm is very consistent for all LWC in both of these altitude bands. The magnitude of all R values is lower for the 1200–1500 m band than the 1500–1800 m band. The magnitude of the positive R for small sizes is lower for most of the 1500–1800 m bands as explained earlier due to RF9. However, the magnitude of the negative R values for the large droplets is similar to the 900–1200 m band. The SL for this smaller number of flights is still 99% for R = 0.83 and 99.5% for R = 0.87.
Figure 10 displays R as a function of droplet size for the next altitude band, 1800–2400 m. This altitude band does not continue the trend to a larger number of displayed LWC bins. The decrease to only 12 LWC bins is probably because of the greater amount of entrainment and smaller number of flights with data in this altitude band. The trend of greater entrainment at higher altitudes is shown in Table 3 (last column). Adiabatic LWC at this altitude band goes from 1.5–2.35 gm−3; the lower of which is still even 2.5 times greater than any of the measurements in Figure 10, which includes 73% of all of the measurements in this altitude band. As mentioned earlier and discussed below, entrainment is probably the reason for the rather low positive and even negative R values for small droplet size thresholds for all LWC bins. However, high positive R values are achieved at 20 μm and/or 25 μm diameter for all but the lowest LWC bin (0.01–0.05). Large negative R values are consistently seen for all LWC bins in the 30–40 μm range. This is also apparent in Figure 11 where the larger and more consistent negative R values for large droplets contrast with the lower and more inconsistent R values for most of the other droplet sizes. The exception is the 20 μm diameter range, which displays consistently high positive R except for the extreme LWC. This indicates that at this altitude, only droplets smaller than 20 μm are subject to R reductions due to entrainment. Compared to lower altitude bands this altitude band has a greater small droplet size range (up to 20 μm) with R values that are considerably lower than the maximum R values at the intermediate sizes (20–25 μm here). This is probably because there are very few small droplets within the adiabatic parcels due to the overall considerably larger droplet sizes at such high altitudes. Therefore the only droplets that are within these smallest size ranges (<20 μm) are probably those that have been partially evaporated from larger droplet size ranges by entrainment. Higher CCN concentrations reduce adiabatic droplet sizes so that when these droplets are evaporated by entrainment they are more likely to be reduced below the various thresholds. This leads to fewer small droplets when CCN concentrations are high and more small droplets when CCN concentrations are low; i.e., larger droplets before entrainment means larger droplets after the same amount of entrainment. This effect reduces or even reverses R. Even for this small number of flights R of 0.81 has an SL of 97.5% and R of 0.92 has an SL of 99.5%.
 The highest-altitude band, 2400–3000 m, has the largest number of LWC bins, 16 up to 0.75–0.80 gm−3 in Figure 12, which therefore requires two panels. Figure 12 shows consistently negative R for the smallest threshold size ranges (2 and 5 μm). The R values in Figures 12 and 13 are different from those in Figure 3 where R for the small sizes is somewhat positive. This difference is mainly because of the vastly different LWC ranges in Figures 12 and 13 compared to Figure 3 for some flights, especially RF1. There is also the smaller number of flights in Figures 12 and 13. Nevertheless, even for only four flights, R of 0.90 has an SL of 95% and even R of 0.50 has SL of 75%. The consistently negative R for small droplet thresholds here again suggests the influence of entrainment, which Table 3 (last column) shows to be the greatest for this highest-altitude band. Negative R may be a result of the fact that the smaller droplets of clouds formed with higher CCN concentrations evaporate more readily than the larger droplets formed on lower CCN concentration flights. This tendency has been predicted by Xue and Feingold , Xue et al. , and Zuidema et al. . This tendency would result in lower concentrations of small droplets when CCN concentrations are higher, which makes negative R. This reversal of R by entrainment is also seen to a lesser extent at lower altitudes because there is less entrainment at lower altitudes. Thus, at lower altitudes the effect of entrainment is confined to small droplets at low LWC and usually only reduces positive R as seen in Figures 8, 9, 10, and 11.
 At the highest-altitude band the R pattern for droplets larger than 10 μm is similar to that of the lower altitudes, high positive R for intermediate sizes (10–25 μm) and large magnitude negative R for the largest sizes (35 and 40 μm). Because of the greater variability of R at this highest altitude, it is also necessary to provide two panels for the R versus LWC plot in Figure 13. The greater R variability is probably due to the smaller number of flights and the greater amount of entrainment, which is therefore almost certainly more variable. Nevertheless, Figure 13 shows consistent high positive R for all LWC bins at 25 μm and for nearly all LWC bins at 15 and 20 μm; there is also consistent large negative R for 35 and 40 μm.
Figure 14 displays the percentage of cloud observations when LWC exceeded specific values for the flights used in Figures 6, 7, 8, 9, 10, 11, 12, and 13 and the two intermediate altitude bands described but not displayed, 1200–1500 m and 1500–1800 m. For the 900–1200-m-altitude observations the minimum adiabatic LWC (0.4 gm−3, at 900 m) was exceeded by less than 15% of the measurements. Figure 8 indicates that in this altitude band fewer than 11 flights had LWC in excess of 0.55 gm−3, a value that was exceeded only 7.1% of the time for these 11 flights. However, Figure 14 indicates that less than 3% of the 900–1200 m observations exceeded the maximum LWC of 0.7 gm−3 (at 1200 m). Less than 5% of the 1200–1500 m observations exceeded the minimum adiabatic LWC of 0.7 gm−3 at 1200 m. For 1200–1500 m no more than twelve flights had any LWC observations in excess of 0.55 gm−3, a value that was exceeded by only 10% of the 1200–1500 m observations. The maximum adiabatic LWC for the 1200–1500 m band, 1.1 gm−3, was exceeded by less than 0.2% of the observations in this altitude band. Less than 0.3% of the 1500–1800 m observations exceeded the 1.1 gm−3 minimum adiabatic LWC. For this altitude band less than seven flights had any observation of LWC >0.75 gm−3, a value that was exceeded by only 9% of the observations at this altitude band. The highest LWC in this altitude band was 1.40 gm−3, which was achieved by less than 0.1% of the observations, whereas the maximum adiabatic LWC was 1.5 gm−3 in this altitude band. The minimum adiabatic LWC of 1.5 gm−3 for the 1800–2400-m-altitude band was exceeded by only 0.3% of the observations in this altitude band. Figure 10 indicates that no more than six flights had LWC in excess of 0.60 gm−3, a value that was exceeded by 27% of the observations in the 1800–2400-m-altitude band. The highest LWC observation in this altitude band, 1.75 gm−3, was well below the maximum LWC for this band of 2.35 gm−3 (at 2400 m). In the highest-altitude band 2400–3000 m the minimum adiabatic LWC of 2.35 gm−3 was never exceeded because the maximum observed LWC was only 1.75 gm−3, which is well short of the maximum adiabatic LWC of 3.2 gm−3. Figure 12 indicates that only three flights had LWC in excess of 0.80 gm−3, which was exceeded by 15% of the observations in this altitude band. Table 3 (column 4) indicates that drizzle LWC was trivial at low altitudes. Though drizzle LWC was not trivial at higher altitudes the effect on relative adiabaticity was still small.
3. Discussion and Conclusions
 The pattern of positive R for CCN and total cloud droplet concentrations (Nc) and negative R for CCN and large cloud droplet and drizzle drop concentrations is consistent with classical predictions of adiabatic (unmixed) cloud microphysics. However, the preceding paragraph and Table 3 showed that the vast majority of RICO cloud measurements had LWC far below adiabatic values [e.g., Rauber et al., 2007]. Since adiabatic cloud parcel measurements have been rare, anything else would be inconsistent with most previous cloud measurements. Moreover, consistent with most previous studies, subadiabaticity in RICO increased with altitude (Table 3, last column). A surprising aspect of this study was that the R values continued to be just as large for clouds that exhibited LWC far below adiabatic values. R was essentially independent of LWC; it was difficult to find cloud parcels that did not follow the R pattern described. The only exceptions to this R pattern were Nc or small droplet size thresholds at very low or a few very high LWC bins. Large negative R between CCN and large droplet concentrations was universal in this study. The R pattern was consistent in spite of the fact that data from the various flights had to be averaged over substantial, 300 or 600 m, altitude bands and that cloud base may have varied among the flights. This would make it more difficult to quantify the subadiabaticity, but the results indicate that except for the most extreme LWC, adiabaticity was irrelevant to the effects of CCN on cloud droplet concentrations at all size ranges. Although the subadiabatic parcels had lower droplet concentrations, the droplet concentrations were still proportional to the CCN concentrations. Better correlations may have been possible with more careful attention to distances from cloud base and cloud base temperatures. However, those compromises were needed in order to obtain enough data for comparisons among flights. Since the good correlations ensued anyway, it was not necessary to do more detailed analysis. The results show that the influence of CCN permeates to just about all parts of the clouds and all aspects of the microphysics. For instance the correlations are consistent regardless of how the cloud threshold is defined, be it 0.001 to 0.1 gm−3, which results in a factor of 4 to a 40% difference in the number of observations (Table 2). A cloud threshold of 1 droplet cm−3 or for drizzle concentrations of 1 drop per liter measured by the 260× probe still produced similar R patterns and values.
 The negative R that was consistently found for small droplets at the higher-altitude bands indicated that entrainment might reduce the apparent usual effect of CCN. However, this counter effect was limited to the smallest droplets, which had lower concentrations than the larger droplets, which are more important for radiation and precipitation. Moreover, this counter effect of entrainment appears to be directly opposite of the usual CCN effect rather than random. If this is so then the influence of CCN on cloud microphysics is even more pervasive; i.e., even the influence of entrainment on cloud microphysics is modulated by the relative CCN concentrations, albeit that the CCN effect is opposite to the usual effect of CCN on cloud microphysics.
 The positive correlations of CCN concentrations with Nc have been shown in many previous studies, but not in the detail presented here. Previous studies required larger concentration contrasts typical of clean and polluted air masses [e.g., Hudson and Yum, 2001, 2002; Yum and Hudson, 2002] and relied on near or quasi adiabatic parcels [Yum et al., 1998] and/or more than one field study [e.g., Yum and Hudson, 2004] to show decent CCN-droplet concentration correlations. All of the observations here were made in what has traditionally been deemed clean maritime air masses (concentrations < ∼200 cm−3), and the vast majority of the cloud parcels considered here were very subadiabatic. The substantial variability of the maritime CCN and cloud droplet concentrations among the RICO flights was as unforeseen as the good correlations between them. The fact that the CCN influence permeated to nearly all parts of the clouds in terms of altitude and LWC, except perhaps extremely low LWC, suggests that 1st IAE can be pervasive. Contrasts in drizzle drop concentrations between continental and maritime air masses have been shown [Squires, 1956; Hudson and Yum, 2001] as have negative correlations between droplet concentrations and sizes [Hudson and Svensson, 1995; HM7]. Negative correlations have also been found between aerosol concentrations and effective radius [Twohy et al., 2005] and between CCN concentrations and cloud droplet mean sizes [HM7]. However, negative correlations of CCN with large cloud droplet and drizzle drop concentrations have not been shown and certainly not in the detail of this study. In fact the negative correlations with large cloud droplets and drizzle were even more persistent than the more expected positive correlations with Nc. This was especially significant for the very subadiabatic cloud parcels of this study. This has important implications for precipitation initiation and thus for 2nd IAE. Although the RICO particle or droplet concentrations were not nearly high enough to be considered polluted or even continental, anthropogenic influences cannot be ruled out. The fact that differences in cloud microphysics were so obvious with such small differences in CCN concentrations means that larger differences from more obviously polluted air masses should have more profound effects on cloud microphysics. This supports the findings of Freud et al. , who found geographically widespread influences of air mass differences on precipitation.
 To some extent these good correlations may have been due to the effects of the clouds on the aerosol; e.g., clouds with lower Nc and larger droplets would have enhanced coalescence that would reduce CCN concentrations. However, the RICO flights were chosen when the clouds were in early stages of development because the goal of RICO was to understand precipitation onset. Thus the RICO clouds were small and short-lived and thus not especially capable of aerosol scavenging. Flight days with considerable cloudiness and precipitation that would be capable of considerable aerosol scavenging were successfully avoided during RICO. This is not to say that cloud scavenging did not play a role in producing the variability of CCN concentrations among flights. It is likely that cloud scavenging was the reason for the variations in CCN concentrations among flights. However, the consistency of the concentrations during and between the two 100-m-altitude half-hour circles from which the flight-averaged CCN concentrations were derived [HM7] before and after the cloud observations, argues against the immediate effects of the observed small clouds on the observed CCN concentrations. The effect of cloud scavenging on the low-altitude CCN concentrations was probably a longer-term process that may have involved larger clouds during previous days acting on the air masses that were observed during the RICO flights.
 There was, nevertheless, variability of cloud extent during the RICO flights. Cloud extent was roughly estimated from the percentage of time that the aircraft spent within clouds compared to the total time spent at the same altitude bands. Although this was an overestimation of cloudiness, because the pilots were trying to semirandomly fly through clouds, it provides some estimate of the relative cloudiness among the flights. These cloudiness estimates ranged from 1–40% among the flights depending on the cloud threshold criteria and altitude band. These low percentages also argue for minimal immediate effects of the clouds on CCN. Moreover, all of the correlations of cloudiness with flight-averaged CCN concentrations were positive except for the 1200–1500-m-altitude band, but those were only weak negative correlations. Negative correlations between CCN concentrations and cloudiness might have suggested that the greater cloud scavenging of larger cloud amounts would have enhanced the positive correlations of CCN with cloud droplet concentrations. However, the contrary positive correlations that were predominantly found between cloudiness and CCN concentrations, though mostly somewhat weak, are on the other hand suggestive of 2nd IAE where higher CCN concentrations inhibit precipitation enough to produce greater cloudiness through cloud persistence.
 Since variability in updraft velocities (W) should produce variations in droplet concentrations that would depend on the shape of the CCN spectra it is astounding that CCN concentrations at just one S value produced such high correlations. HM7 reported flight-averaged W ranging from 1.64–2.50 for 14 RICO flights. Furthermore, it is a wonder that vertical variability of CCN concentrations, especially with the prevalence of entrainment, did not perturb the correlations with below cloud CCN concentrations. It was amazing that it was not necessary to delve into these complex issues in order to find the pervasive influence of CCN. The results show that CCN influence is indeed not washed out by entrainment. This seems to suggest that scenarios such as inhomogeneous and entity mixing did not materially reduce the influence of CCN on cloud microphysics. Beyond the results presented here this analysis has shown the unexpectedly high value of the RICO microphysics data set. Therefore research is continuing and subsequent articles will deal with issues such as the entire CCN spectrum, the vertical variability of the CCN concentrations and with updraft velocity.
 The results further substantiate those of HM7 and Göke et al.  that CCN are the aerosol that has the most influence on precipitation initiation. This is also consistent with the study of Lasher-Trapp et al.  that CCN concentrations rather than giant nuclei (GN) have the greatest effect on supercooled large drizzle drop concentrations. Nevertheless, it is difficult to separate the effects of these two aerosol components since their concentration variations often go together [HM7; Lasher-Trapp et al., 2008] but their effects on precipitation are oppositely related to their concentrations. Therefore some influence of GN cannot be ruled out, but results so far indicate that the CCN effect is the dominant aerosol effect on cloud microphysics and precipitation. The results also indicate the value of near surface CCN measurements for predicting and even ascertaining cloud microphysics.
 Support was from the US National Science Foundation grant ATM-0342618. Measurements other than CCN were provided by the Research Aviation Facility of NCAR, which provided the platform for all measurements, the C-130 airplane.