Further evidence for CCN aerosol concentrations determining the height of warm rain and ice initiation in convective clouds over the Amazon basin

We have investigated how aerosols affect the height above cloud base of rain and ice hydrometeor initiation and the subsequent vertical evolution of cloud droplet size and number concentrations in growing convective cumulus. For this purpose we used in situ data of hydrometeor size distributions measured with instruments mounted on HALO aircraft during the ACRIDICON–CHUVA campaign over the Amazon during September 2014. The results show that the height of rain initiation by collision and coalescence processes (Dr, in units of meters above cloud base) is linearly correlated with the number concentration of droplets (Nd in cm−3) nucleated at cloud base (Dr ≈ 5 ·Nd). Additional cloud processes associated with Dr, such as GCCN, cloud, and mixing with ambient air and other processes, produce deviations of∼ 21 % in the linear relationship, but it does not mask the clear relationship between Dr and Nd, which was also found at different regions around the globe (e.g., Israel and India). When Nd exceeded values of about 1000 cm−3, Dr became greater than 5000 m, and the first observed precipitation particles were ice hydrometeors. Therefore, no liquid water raindrops were observed within growing convective cumulus during polluted conditions. Furthermore, the formation of ice particles also took place at higher altitudes in the clouds in polluted conditions because the resulting smaller cloud droplets froze at colder temperatures compared to the larger drops in the unpolluted cases. The measured vertical profiles of droplet effective radius (re) were close to those estimated by assuming adiabatic conditions (rea), supporting the hypothesis that the entrainment and mixing of air into convective clouds is nearly inhomogeneous. Additional CCN activation on aerosol particles from biomass burning and air pollution reduced re below rea, which further inhibited the formation of raindrops and ice particles and resulted in even higher altitudes for rain and ice initiation. Published by Copernicus Publications on behalf of the European Geosciences Union. 14434 R. C. Braga et al.: CCN concentrations determining the height of warm rain


Introduction
Understanding cloud and precipitation forming processes and their impacts on the global energy budget and water cycle is crucial for meteorological modeling.Therefore, many studies have focused on improving cloud parameterization in numerical weather and climate models (e.g., Frey et al., 2011;Khain et al., 2005Khain et al., , 2000;;Klein et al., 2009;Lee et al., 2007;Machado et al., 2014).
Cloud droplets form when humid air rises and becomes supersaturated with respect to water.Then water vapor condenses onto surfaces provided by preexisting cloud condensation nuclei (CCN; a list of abbreviations and symbols is given in Table 1) aerosols.For ice formation, the ambient temperatures must reach values lower than 0 • C. At temperatures between 0 and −36 • C, ice in convective clouds mostly forms inhomogeneously on ice nuclei (IN) aerosols, often when they interact with supercooled liquid water droplets (Pruppacher et al., 1998).Ice multiplication is an important mechanism that masks the primary ice nucleation activity when cloud droplets are sufficiently large to also promote warm rain by coalescence at temperatures of −3 to −8 • C (Hallet and Mossop, 1974).At much colder temperatures (less than −37 • C), cloud particles freeze due to homogeneous ice nucleation (Rosenfeld and Woodley, 2000).
A cloud predominantly consists of droplets with diameters larger than about 3 µm, except for transient smaller sizes right at cloud base.The number concentration of cloud droplets (N d in cm −3 ) at cloud base mainly depends on the conditions below cloud base, i.e., the updraft wind speed (W ) and the supersaturation (S) activation spectra of cloud condensation nuclei [CCN(S)] (Twomey, 1959).In very clean conditions, values of N d near cloud base are in the range of ∼ 50-100 cm −3 , while in polluted conditions N d may reach values between 1000 and 2000 cm −3 (Andreae, 2009;Rosenfeld et al., 2008Rosenfeld et al., , 2014a)).
Below the freezing level, raindrops are formed due to cloud droplet coagulation (collision-coalescence) processes (warm rain process).Mixed-phase precipitation results from interactions between ice particles and liquid water droplets (Pruppacher et al., 1998).Several studies based on aircraft, radar, and satellite measurements support the idea that warm rain formation requires that the cloud consist of droplets with values of the effective radius (r e ) larger than 13-14 µm (Freud and Rosenfeld, 2012;Konwar et al., 2012;Prabha et al., 2011;Chen et al., 2008;VanZanten et al., 2005;Pinsky and Khain, 2002;Gerber, 1996;Rosenfeld and Gutman, 1994).
The effects of aerosol particles on clouds and precipitation have been studied in different parts of the globe (e.g., Fan et al., 2014;Li et al., 2011;Ramanathan et al., 2001;Rosenfeld and Woodley, 2000;Rosenfeld et al., 2014a;Tao et al., 2012;Voigt et al., 2017;Wendisch et al., 2016).A particularly interesting region is the Amazon basin, which presents contrasting environments of aerosol particle concentration be-tween dry and wet seasons and steep aerosol concentration gradients within regions with near-constant thermodynamic conditions (Andreae et al., 2004;Artaxo et al., 2013).The background number concentrations of aerosol particles and CCN over the pristine parts of the Amazon region are about a factor of 10 lower than those of polluted continental regions, including polluted conditions over the Amazon (Martin et al., 2016).During the dry-to-wet transition season in the Amazon region, total aerosol number concentrations reach values up to 10 000 cm −3 , mostly due to forest fires (Andreae, 2009;Andreae et al., 2012;Artaxo et al., 2002).On the other hand, in the rainy season aerosol number concentrations are about 500-1000 cm −3 with CCN concentrations on the order of 200-300 cm −3 for 1 % supersaturation, mainly consisting of forest biogenic aerosol particles (Artaxo, 2002;Martin et al., 2016;Pöhlker et al., 2016;Pöschl et al., 2010).Additionally, the city of Manaus, which is located at the central Amazon basin, releases significant concentrations of urban pollution aerosol particles (e.g., due to traffic, combustion-derived particles, or different types of industrial activities).This increases CCN concentrations by up to 1 order of magnitude (for 0.6 % supersaturation) from the wet (Green Ocean) to the dry season (Kuhn et al., 2010).Rosenfeld et al. (2012b) showed that by estimating the adiabatic number of droplets nucleated at cloud base (N a ), the height above cloud base at which the first raindrops evolve can be parameterized.This approach is based on the assumption that the entrainment and mixing of air into convective clouds is almost completely inhomogeneous (Beals et al., 2015;Burnet and Brenguier, 2007;Freud et al., 2011;Paluch, 1979).The inhomogeneous mixing occurs when the evaporation rate of cloud droplets significantly exceeds the mixing rate of the cloud with ambient air.This causes the droplets that are at the boundary of the entrained air filament to evaporate completely and moisten that air until it is saturated.Further mixing of the saturated entrained air would not cause additional evaporation, but only decreases N d and LWC while maintaining r e of the remaining droplets as unaffected.This implies that the vertical profile of the actual cloud droplet effective radius behaves nearly as in an idealized adiabatic cloud.This uniquely connects the adiabatic drop number concentration, which is approximated by N a at cloud base, with the adiabatic droplet effective radius (r ea ) based on an adiabatic parcel model for which droplet growth is dominated by condensation (Freud and Rosenfeld, 2012;Pinsky and Khain, 2002).This parameterization can be applied to estimate the height above cloud base at which raindrops start to form, when r ea reaches 13 µm (D 13 ) (Freud and Rosenfeld, 2012;Konwar et al., 2012;Rosenfeld et al., 2012b;Prabha et al., 2011;VanZanten et al., 2005).However, uncertainties associated with the calculated N a decrease the agreement between r ea and r e .Most of these uncertainties arise when additional CCN activation of droplets happens above cloud base because the adiabatic model does not predict that N d will increase with height, but will decrease due to Atmos.Chem. Phys., 17, 14433-14456, 2017 www.atmos-chem-phys.net/17/14433/2017/The effective radius of the cloud droplet spectra µm r ea The adiabatic effective radius of the cloud droplet spectra µm r v The mean volume radius of the cloud droplets µm RWC Rainwater content Maximum vertical velocity during the cloud profiling flight m s −1 evaporation and deviations from inhomogeneous cloud mixing (Pinsky and Khain, 2012).Braga et al. (2017) applied the methodology described by Freud et al. (2011) to calculate N a at the base of growing convective cumulus clouds for the Amazon region during the ACRIDICON-CHUVA campaign (Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems -Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM [Global Precipitation Measure-ments]; Wendisch et al., 2016).The N a is calculated from N a = CWC a /M va , where CWC a is the adiabatic cloud water content (CWC a ) as calculated from cloud base pressure and temperature, and M va is the adiabatic mean volume droplet mass as approximated from the actually measured mean volume droplet mass (M v ) by the cloud probe DSDs obtained during the cloud profiling measurements.Measurements of M v with height are considered only for cloud passes for which CWC is greater than 25 % of the adiabatic CWC and r e is lower than 11 µm (i.e., for cloud droplets that have grown mostly via condensation).The calculated N a values based on the measured vertical profile of r e agreed well (within 20-30 %) with the actual measurements of cloud droplet number concentrations at cloud base.This approach provides the opportunity to test the agreement between estimated r ea and the height above cloud base of warm rain initiation (D r ) within clouds for the Amazon region.In addition, measurements of the height above cloud base of ice initiation (D i ) in convective clouds are also available from flights that include cloud penetrations at ambient temperatures as low as −60 • C with the HALO aircraft (Wendisch et al., 2016).
This study analyzes the vertical development of cloud and precipitation particles (water drops and ice crystals) in growing convective cumulus over the Amazon based on measurements of cloud microphysical properties from instruments mounted on HALO during ACRIDICON-CHUVA (Wendisch et al., 2016).The vertical profile of r ea is used to estimate the depth above cloud base at which warm rain initiation occurs.The dominance of inhomogeneous mixing causes the r e profile to behave almost as in adiabatic clouds, constrained by N d at cloud base (Burnet and Brenguier, 2007;Freud et al., 2011).This means that the height above cloud base for reaching r e of 13-14 µm, which is required for rain initiation, is also determined by cloud base N d (Freud and Rosenfeld, 2012).Rain initiation depends strongly on r e because the rain production rate by collision and coalescence is proportional to ∼ r 5 e (Freud and Rosenfeld, 2012).Here we test and quantify these relationships for the measurements conducted with HALO aircraft during ACRIDICON-CHUVA.
The HALO flights during the ACRIDICON-CHUVA campaign were performed over the Amazon region under various conditions of aerosol concentrations and land cover (Wendisch et al., 2016).Figure 1a shows the flight tracks during which cloud profile sampling in growing convective cumulus was performed.Figure 1b shows a schematic sketch of the flight pattern while sampling cloud clusters (the locations in three dimensions of each flight are available at Fig. S1 in the Supplement).The aircraft obtained a composite vertical profile by penetrating young and rising convective elements, typically some 100-300 m below their tops.
The cloud droplet size distributions (DSDs) between 3 and 50 µm in diameter were measured at a temporal resolution of 1 s by the CAS-DPOL and CCP-CDP probes (Baumgardner et al., 2001;Lance et al., 2010;Brenguier et al., 2013).Each DSD spectrum represents 1 s of flight path (covering ∼ 150 m of horizontal distance for a typical aircraft speed).The value of r e was calculated for each 1 s DSD.The two probes (CAS-DPOL and CCP-CDP) were mounted on opposite wings of HALO (horizontal distance of ∼ 15 m).Similar values of N d and derived r e were measured by CAS-DPOL and CCP-CDP (they agree within 30 %), even though they were mounted on different wings.A previous study (Braga et al., 2017) showed that both probes were in agreement within the measurement uncertainties with respect to the measured cloud droplet number concentrations at cloud base and in accordance with the expected values for different conditions of CCN concentration and updraft wind speed below cloud base.In addition, the CWC calculated from the measured DSDs shows similar values to those measured with a hot-wire device for different heights above cloud base (the probes' measurements agree within their uncertainty range of 16 % for probe DSDs and 30 % for the hot-wire device; Braga et al., 2017).
The determination of the height of rain initiation is based on the drizzle water content (DWC) calculation from the CCP-CIP probe (Brenguier et al., 2013).The DWC is defined as the mass of the drops integrated over the diameter range of 75-250 µm (Freud and Rosenfeld, 2012).This size range is selected because it includes only drops with a terminal fall speed of 1 m s −1 or less, which maximizes the chance that the drizzle was formed in situ and did not fall a large distance from above.Rainwater content (RWC) is defined as the CCP-CIP integrated liquid water mass of droplets with diameters between 250 and 960 µm.The CCP-CIP images were used to distinguish raindrops and ice particles during cloud passes.The hydrometeor type is identified visually by shape.The phase of the smaller CCP-CIP particles cannot be distinguished.Therefore, the precipitation is considered as mixed phase when ice particles are identified, and the combined DWC and RWC are redefined as mixed-phase water content (MPWC).Table 2 summarizes the calculated cloud microphysical properties with respect to the instrumentation used and its size ranges.

The scientific motivation
The aircraft-based in situ measurements of cloud properties were collected within convective clouds formed over the Amazon from cloud base up to cloud top above the glaciated level.These measurements provided a unique opportunity to evaluate previous theoretical knowledge about aerosol impacts on convective clouds characteristics over the Amazon.
In this study the impact of N a (adiabatic cloud drop concentrations) in determining the initiation of rain and ice within convective clouds is evaluated.This is performed through the analysis of the calculated N a , D r , and D i for several different environmental conditions over the Amazon (cloud base updrafts, aerosol concentration, surface cover).The relationship of N a and D r was previously analyzed for Israel and India; a linear relationship was found (D r ≈ 4 • N a ; Freud and Rosenfeld, 2012).For the Amazon region a similar analysis is performed here also taking into account the impact of N a on D i .This is the first study that analyzes the impact of N a on D r and D i on the Amazon region using in situ measurements of convective cloud properties.The results obtained from comparisons of N a estimates and the measured effective number of droplets nucleated at cloud base (N * d ), shown at Braga et al. (2017) for the same flights in the Amazon region, support the methodology of deriving N a based on the rate of r e growth with cloud depth under the assumption that the entrainment and mixing of air into convective clouds is extremely inhomogeneous.This is important because the characteristics of convective clouds based on N a values can be extended in space and time by their application to satellite-calculated N a (which is obtained with the same parameterization that has been recently developed from the satellite-retrieved vertical evolution of r e in convective clouds; Rosenfeld et al., 2014b).

Cloud particle measurements
The instrumentation used to measure cloud particles and rain or ice formation consists of three cloud probes: CAS-DPOL, CCP-CDP, and CCP-CIP (Brenguier et al., 2013).In this study, cloud particle counts are accumulated for bin diameters larger than 3 µm from the CCP-CDP and CAS-DPOL; the lower size bins from these probes overlap with haze particles.Nucleated cloud drops in convective clouds grow quickly beyond 3 µm.Details about the cloud probe measurement characteristics are described in the following subsections and in Braga et al. (2017).

CCP-CDP and CCP-CIP measurements
The Cloud Combination Probe (CCP) combines two detectors, the Cloud Droplet Probe (CDP) and the grayscale Cloud Imaging Probe (CIPgs).The CDP detects the forwardscattered laser light of cloud particles when penetrating the CDP detection area (Lance et al., 2010).The CIP records 2-D shadow-cast images of cloud elements.In this study, we deduced the existence of ice from the occurrence of visually nonspherical shapes of the shadows.The particle detection size range is 2 to 960 µm when measuring with the CCP at a 1 Hz frequency (Wendisch et al., 2016).The combination of CCP-CDP and CCP-CIP information provides the ability to measure cloud droplets and raindrops within clouds for nearly the same air sample volume.The maximum number of particles measured by CCP-CDP and CCP-CIP are about 2000 and 500 cm −3 for a 1 Hz cloud pass, respectively.For the data processing of the CIP measurements, ice is assumed as the predominant particle phase in the mixed-state cloud conditions throughout the ACRIDICON-CHUVA campaign.
The assumption of ice density instead of water density implies a slight overestimation (∼ 10 %) of the calculated rainwater content for particles greater than 75 µm.An additional data processing assuming water density as the predominant particle phase was performed for flights during which warm rain was initiated below the 0 • C isotherm.

CAS-DPOL measurements
The CAS-DPOL measures particle size distributions between 0.5 and 50 µm at a 1 Hz time resolution (Baumgardner et al., 2011;Voigt et al., 2010Voigt et al., , 2011)).Number concentrations are derived using the probe air speed measured at the instrument.Particle inter-arrival time analysis did not show influences of coincidence (Lance, 2012).The data analysis and uncertainties are described in detail in Braga et al. (2017).Braga et al. (2017) have shown sufficient agreement between the CAS-DPOL and CCP-CDP measurements of cloud droplet number concentration to distinguish convective clouds that develop above clean vs. polluted regions during the ACRIDICON-CHUVA campaign.In addition, the CWC estimated by integration of the DSDs measured with both probes showed good agreement with hot-wire CWC measurements (Braga et al., 2017).

Meteorological data
The HALO aircraft was equipped with a meteorological sensor system (BAsic HALO Measurement And Sensor System -BAHAMAS) located at the nose of the aircraft (Wendisch et al., 2016).The uncertainties for measurements of temperature, relative humidity, and vertical wind speed are 0.5 K, 5 %, and 0.3 m s −1 , respectively (Mallaun et al., 2015).

Aerosol measurements
Aerosol particle measurements were performed using the Passive Cavity Aerosol Spectrometer Probe 100X (PCASP-100X), which is an airborne optical spectrometer that measures aerosol particles in the 0.1 to 3 µm diameter range (Liu et al., 1992).The maximum number of particles measured by PCASP is about 3000 cm −3 for a 1 Hz cloud pass.During the ACRIDICON-CHUVA campaign, PCASP was not operated with a heated inlet, and thus the measured aerosol particles below cloud base (about 200 m) can be larger than the original dry size due to swelling.

Methods
The analyses are performed along the following general steps.c.The height of rain initiation based on the modeled adiabatic growth of r e with height is estimated for different aerosol conditions as a function of estimated N a .The value of D 13 is estimated as the cloud depth for which the adiabatic r e reaches 13 µm (as described also in Sect.4.2).
d.The extent of agreement between the directly measured D r within convective clouds and the estimated D 13 based on the assumption of adiabatic r e growth and on the measured r e is discussed in Sects.5 and 6.

Estimation of r e , rain, and ice initiation
Rain is initiated during the warm phase of growing convective cumulus by the intensification of the collision and coalescence (coagulation) processes with height.The efficiency of the process of droplet coalescence is determined by the collection kernel (K) of the droplets and their concentrations (Pruppacher et al., 1998).Freud and Rosenfeld (2012) have shown through model simulations and aircraft measurements that K ∝ r 4.8 v , where r v is the mean volume radius obtained from the cloud probe DSDs in the absence of ice; r v is defined as follows: where ρ is the water density (1 g cm −3 ), CWC is in g m −3 , and N d is in cm −3 .The values are obtained from the 1 Hz data of droplet size distributions from the cloud probes.The calculation of CWC is performed separately with the CAS-DPOL and CCP-CDP probe droplet concentrations as follows: where N is the droplet concentration and r the droplet radius.The calculations of DWC, RWC, and MPWC are done in a similar fashion to CWC but with different cloud probes and particle size ranges (see Table 2).The definition of r e is r e = N (r)r 3 dr N (r)r 2 dr .
(3) Freud and Rosenfeld (2012) showed that r v ≈ 1.08 • r e , depending on the droplet size distribution.Using this relationship, they derived r e from r v and showed that warm rain initiates within clouds when r e is about 13-14 µm (Klein et al., 2009;Rosenfeld and Gutman, 1994;Rosenfeld and Lensky, 1998;Rosenfeld et al., 2012aRosenfeld et al., , 2014c)).Only measurements with CWC larger than 25 % of the adiabatic water content are considered in order to exclude convectively diluted or dissipating clouds.It is assumed that rain (or ice) formation starts when calculated DWC exceeds Table 3. Classification of each flight as a function of N a at cloud base.The values of cloud base height (Cbh) and temperature (T ), D 13 , D r and D i in meters, and temperatures in • C are also shown for the convective cloud measurements of each flight.Additionally, information about the height of D r−1 , D i−1 , T r , T i , T i−1 , NLP, and W max is also shown for each flight.The uncertainties of N a and D 13 estimates are described in Appendix A.  (Freud and Rosenfeld, 2012).For rain initiation in liquid phase, the DWC threshold is ∼ 10 % greater due to the overestimation of DWC during CIP measurements in warm clouds (as stated in Sect.3.2.1).The small terminal fall speed of the drizzle drops (≤ 1 m s −1 ) allows for a focus on in situ rain (or ice) initiation while minimizing the amount of DSDs affected by raindrops falling from above into the region of measurements.In addition, cloud passes with rain were eliminated when cloud tops were visibly much higher than the penetration level (> ∼ 1000 m) based on the videos recorded by the HALO cockpit forward-looking camera.However, cloud tops higher than a few hundred meters above the penetration level occurred only rarely.
Table 3 shows the cloud depth above cloud base at which warm rain initiation (D r ) occurs (i.e., DWC > 0.01 g m −3 ) for all flights as a function of estimated N a .The D r is taken as the cloud depth for ice initiation (D i ) if ice particles are evident in the CCP-CIP images.Here, the D i is visually ascribed for sizes greater than ∼ 0.25 mm and it does not mean that frozen smaller particles cannot be present.The assumption of water or ice density as the predominant particle phase in DWC calculation based on the CCP-CIP probe did not impact the D r and D i measured because the DWC threshold (i.e., DWC > 0.01 g m −3 ) for warm rain or ice initiation was achieved at the same cloud depth for both particles densities.Additional details about the cloud profiling characteristics for each flight, such as the number of altitude levels sampled (NLS) and the highest cloud depth without raindrop (D r−1 ) or ice particles (D i−1 ), are also available in Table 3.Furthermore, Appendix A discusses the uncertainty calculations of the estimated parameters of cloud properties.

Estimating N a and adiabatic r e
The N a for the convective clusters is estimated based on the slope between the calculated adiabatic CWC (CWC a ) and the mean volume mass of the droplets (M v ), which is the mass of a water sphere having the radius r v .M v is calculated for 1 s DSD measurements of CAS-DPOL and CCP-CDP for nonprecipitating cloud passes (Braga et al., 2017).The underlying assumption is that the measured r v is approximating the adiabatic r v (r va ) due to the nearly inhomogeneous mixing behavior of the clouds with the ambient air (Beals et al., 2015).Therefore, the measured M v approximates the adiabatic M v (M va , where M va = CWC a /N a ).This methodology does not account for cloud mixing losses from droplet evaporation or additional drop activation.Both incur an overestimation of N a .It was found that the calculated N a values based on the vertical profile of r e commonly overestimate the measured N a near cloud base by 30 % (Freud et al., 2011).Therefore, in calculating N a a factor of 0.7 is applied to N a estimates.Braga et al. (2017) have shown that this estimated N a was in reasonably good agreement with the directly measured cloud base droplet number concentration, N d , as obtained from the CCP-CDP and CAS-DPOL during ACRIDICON-CHUVA.Once N a is estimated, the adiabatic r e (r ea ) can be calculated based on a simple adiabatic parcel model in which droplet growth is dominated by condensation (Pinsky and Khain, 2002), where r ea = 1.08 • r va .The value of D 13 is defined as the cloud depth for which r ea reaches 13 µm.The uncertainty calculations of cloud properties estimated from cloud probes were described in Braga et al. (2017).The uncertainties of r e , r v , r ea , r va are about 10 %, while for CWC and M v the uncertainties are about 30 %.The N a calculation does not take into account the possibility of new nucleation above cloud base (Freud et al., 2011).Braga et al. (2017) have shown that the assumption of the adiabatic growth of droplets via condensation from cloud base to higher levels within cloud can lead to an overestimation by ∼ 20-30 % of the number of droplets at cloud base when calculating N a in cases with additional droplet nucleation above cloud base.
The N a calculated for cloud base was used to classify clouds as having developed in clean, polluted, or very polluted regions.A clean cloud case was defined as N a < 500 cm 3 , polluted as 500 cm −3 < N a < 900 cm −3 , and very polluted as N a > 900 cm −3 .During ACRIDICON-CHUVA, a flight in clean clouds (AC19) was performed over the Atlantic Ocean.Clouds observed during flights over the northern Amazon were classified as polluted, mainly due to diluted smoke from biomass burning advected by long-range transport.This region represents the Amazon background condition for aerosol concentration during the dry season.Very polluted conditions were met over the central Amazon, which was strongly affected by biomass burning over the Amazonian deforestation arc (southern Amazon).

Threshold of r e for warm rain initiation
The values of r e derived from integrating the cloud probe DSDs were used to identify rain initiation.Some caution is required to eliminate possible bias resulting from peculiar shapes of the drop size spectrum.An r e value of 13-14 µm represents the rain initiation threshold for growing convective cumulus observed at different locations in the world as long as there is no significant influence from giant CCN (GCCN; dry soluble diameter > 1 µm; Freud and Rosenfeld, 2012).The presence of GCCN during cloud droplet formation at cloud base can lead to a faster formation of raindrops due to both the rain embryo effect and the competition effect that reduces cloud base maximum supersaturation and consequently reduces N d (Rosenfeld, 2000;Segal et al., 2007).Such cases are very common over the ocean due to sea spray aerosols; there, the values of r e at which raindrops start to form are commonly smaller than the usual threshold of 13-14 µm (Freud and Rosenfeld, 2012).In our study the DSDs from flight AC19 performed over the Atlantic Ocean did not show a large drop tail near cloud base (see Fig. S2).The cumulative sample volume from the CCP-CDP probe at cloud base was about 5.8 L −1 for 176 s of measurements.The figure shows the scarcity of large cloud droplets (with diameters > 20 µm) near cloud base where the mean concentration of such droplets is smaller than 0.1 drop cm −3 .Such a small concentration of large droplets at cloud base is insufficient to have any significant effect on supersaturation.
Figure 2a-b show the precipitation initiation probability as a function of r e calculated from the CCP-CDP and CAS-DPOL probes for all flights analyzed over the Amazon.The probability of precipitation is the fraction of 1 Hz in-cloud measurements that exceed certain DWC thresholds (i.e., for DWC > 0.01 g m −3 ).This was calculated as a function of the r e value.These figures show that for the CCP-CDP probe rain initiation is expected to occur at r e > 13 µm, whilst for CAS-DPOL the rain initiation threshold is r e > 12 µm.The differences of the two instruments in the r e range below ∼ 7 µm and above ∼ 11 µm have been discussed in Braga et al. (2017).For r e < 7 µm, they are related to a higher sensitivity of the CAS-DPOL for small cloud and aerosol particles, whereas for r e > 11 µm CAS-DPOL has lower sensitivity to large particles than CCP-CDP; however, the differences are not significant within the uncertainties of the measurements.Because the CCP-CDP was mounted very close to the CCP-CIP, the results from this probe are shown in subsequent sections; similar results were found from data collected with the CAS-DPOL probe.

Comparing estimated r ea with measured r e
The comparison between the values of r ea (calculated from the estimated N a at cloud base described in Sect.4.2) with the measured r e is the basis for analyzing the evolution of cloud particle size until rain or glaciation initiation occurs within the cloud.Rosenfeld et al. (2012b) showed that a tight relationship between the N a calculated for cloud base and the evolution of r ea with height (r ea − D c ) provides a useful proxy for the depth in convective clouds at which raindrops start to form.

Case study: flight AC07 over the Amazon deforestation arc
Flight AC07 was performed over the deforestation arc (see Fig. 1a).Figure 3 shows the number of droplets measured at different heights in the convective clouds.Droplet concentrations reaching ∼ 2000 cm −3 were measured at cloud base, which is characteristic of very polluted clouds.The cloud base was located at about 1900 m a.s.l.(above sea level), with ambient air temperature at about 15 • C. Figure 4a shows the mean DSD for a cloud penetration at cloud base.It emphasizes the higher number concentration of small droplets (< 10 µm) that are observed in convective clouds forming in polluted environments.Figure 4b shows the evolution of r e measurements and estimated r ea as a function of temperature.The figure also shows that the values of r e do not exceed the 13 µm threshold at warm temperatures.These results suggest that cloud droplets formed at cloud base grow mainly via condensation and no raindrops were formed during the warm phase of convective cloud development.However, to rule out coalescence processes as a possible reason for droplet growth, further analysis using CCP-CIP images was done.Figure 5a-c show the evolution of DSD and CWC (mean values) as a function of height above cloud base and the cloud particle images from the CCP-CIP.Figure 5a   when ice particles were observed on the CCP-CIP images.Also, for a cumulative sample volume of 1.24 m −3 from 89 s of CCP-CIP measurements, no raindrops were observed between the heights above cloud base of 2900 m (0 • C) and 7100 m (−26.25 • C).This means that the raindrop concentration, if any, was smaller than 1 drop m −3 .This is a negligible rain rate and supports the notion of a practical shutoff of coalescence.Furthermore, the CCP-CIP did not detect any raindrops at lower levels (warm temperatures) for a cumulative sample volume of 5.9 m −3 from 426 s of measurements.These results indicate a strong inhibition of raindrop formation within growing convective cumulus for this flight over the deforestation arc of the Amazon.Even though some of the indicated effective radii values are larger than 13 µm for colder temperatures, these values do not indicate rain formation when only ice particles are observed.This does not exclude the possibility that small raindrops froze soon after their formation in such low temperatures.
The mean DSD and CIP images shown in Fig. 5c result from a passage through a convective cloud with lightning activity.Figure 6 shows a photo of the cloud taken from the HALO cockpit just before the cloud penetration.The CCP-CIP has imaged graupel in this case.The presence of these types of ice particles within convective clouds is very common in thunderstorms, and previous studies highlight the large frequency of lightning occurrence during the dry-to-wet season over the deforestation arc region of the Amazon (Albrecht et al., 2011;Williams et al., 2002).These results also highlight the role of aerosols from biomass burning in warm rain inhibition and in the aerosol invigoration effect due to the generation of large ice particles and lightning (Rosenfeld et al., 2008).
Regarding the values of r e as a function of D c , Fig. 7a shows the estimated r ea (calculated from the adiabatic CWC  region was classified as clean because N a is about 300 cm −3 (see Table 3).The cloud base was located at 600 m a.s.l. at a temperature of 22 • C. Given the clean conditions over the ocean, the high relative humidity at surface level and the low concentration of CCN lead to the formation of large droplets close to cloud base.Figure 8b shows the estimated r ea and the measured r e as a function of D c .Several cloud passes showed large droplets with r e ∼ 13 µm at only 1660 m above cloud base.Figure 9a-b show the DSDs and CCP-CIP images for the cloud passes at the height at which rain starts to form and at the greatest height measured above cloud base, respectively.Figure 9a shows that rain is already initiated (DWC > 0.01 g m −3 ) when the droplets become larger than about r e > 12 µm.This is probably due to the presence of GCCN over this maritime region.
Figure 10 shows the mean aerosol particle size distribution (PSD) as measured by the PCASP just below cloud base for clean, polluted, and very polluted regions.The mean total number concentration of aerosol particles with sizes larger than 0.1 µm is about 1000 cm −3 over the Atlantic Ocean, whilst for the polluted (very polluted) case this value is about 3 (10) times larger.In addition, the mean total number concentration of particles measured by the CCP-CDP shows a concentration 10 times greater for particles larger than 10 µm over the ocean in comparison with the inland Amazon region.This figure indicates the presence of large aerosol particles with sizes greater than 1 µm (possibly GCCN) over the ocean.When it nucleates droplets, this type of aerosol accelerates the growth of droplets during the warm phase, leading to a faster formation of raindrops than predicted by the adiabatic parcel model.About 3500 m above cloud base, large raindrops are observed in the CCP-CIP images (see Fig. 9b).The low CWC indicates that most of it was already converted into raindrops.These results highlight the fact that under clean conditions, raindrops were formed mainly by the warm-phase processes of cloud development.Even if the convective clouds reach colder temperatures, the low remaining amount of cloud water reduced a key ingredient for cloud electrification.
Before raindrops start to form (D c ∼ 1660 m) updrafts were observed with most values < 4 m s −1 , and when rain starts downdrafts start to be evident (see Fig. S3g).The values of vertical velocities measured for flight AC19 (clean region) were smaller than measured for flight AC07 (very polluted region).However, for both cases updrafts are more evident during droplet growth via condensation and downdrafts are stronger when precipitation particles are observed in the cloud.Strong updrafts (∼ 10 m s −1 ) are observed in polluted cases after ice starts to form (see Fig. S3a), probably due to the latent heat release during freezing processes.An alternative explanation for updraft enhancement due to environmental conditions in these cases cannot be excluded.

Polluted regions
The flights AC09 and AC18 were classified as polluted (see Table 3).These flights were performed over the northern Amazon region (see Fig. 1a).Figure 11a shows the measured N d from flight AC09.The cloud base was located about 1200 m a.s.l. at a temperature of 19.5 • C. Figure 11b shows the estimated r ea and the measured r e as a function of D c .Values of r e > 13 µm were observed for temperatures around 0 • C, indicating the possibility of rain starting at this height.Figure 12a-b show the DSDs and CCP-CIP images from flight AC09 at the height at which rain starts to form (D r ∼ 3000 m) and at the greatest height with measurements above cloud base.The CIP image in Fig. 12b shows the first pass in which ice hydrometeors are observed mixed with supercooled raindrops.For lower levels only raindrops were observed.For flight AC18 cloud base was located about   S4a-b. Figure S5a shows that the first raindrops in AC18 are observed at the −5.7 • C isotherm and that they still remain liquid or at least spherical at the −11.4 • C isotherm (see Fig. S5b).Larger raindrops and a high amount of DWC were observed on AC09 for warmer temperatures than on flight AC18 (not shown).These results show that differences in cloud particle formation are associated with the D c at which convective clouds start to form raindrops or ice, defined earlier as D r and D i .Flight AC18 has a droplet concentration, N d , of up to 100 cm −3 greater than the measurements during AC09 (see Fig. S4a).With higher N d at cloud base, droplet growth via condensation in convective clouds is a less pronounced function of height due to the water vapor competition between droplets.Under these conditions, the collision and coalescence process and the freezing of droplets are initiated at higher D c (Freud and Rosenfeld, 2012;Rosenfeld et al., 2008).For this reason, the formation of raindrops and ice particles on flight AC09 starts at lower D c than on flight AC18 (assuming nonsignificant additional CCN activation above cloud base).

Very polluted regions
Five flights were classified as very polluted (see Table 3): AC07, AC08, AC12, AC13, and AC20.The microphysical analysis of the measurements collected in growing convective cumulus during flight AC07 was already presented in Sect.5.2.1.Figure 13a shows the measured N d from flight AC13, which was made in the same region as flight AC07.
The figure shows that the values of N d near cloud base on flight AC13 reach 2000 cm −3 , similar to AC07.However, the rate of decrease in N d with height above cloud base is much smaller in AC13 compared to AC07.During flight AC13 the measurements of large updrafts (which increase supersaturation and induce new droplet activation) and large aerosol concentrations above cloud base suggest the occurrence of additional CCN activation, leading to the observed relative increase in N d with height.This is supported by the fact that the observed r e values are smaller than the calculated r ea , as shown in Fig. 13b.Only values below 13 µm are observed (maximum of 12 µm), indicating the suppression of raindrop formation.Indeed, no raindrops were observed in the CCP-CIP images from growing convective cumulus passes on this flight, and only cloud droplets and ice particles were detected.Figure 14 shows the DSD and CCP-CIP images at the start of glaciation (D i ∼ 4800 m).These results highlight the role of aerosols in the inhibition of raindrop formation due to inducing a larger N d and respective lower r e , which leads to the suppression of collision and coalescence processes in very polluted regions.
The measured N d during flights AC08, AC12, and AC20 was greater above cloud base than at cloud base on several cloud passes (especially in flights AC08 and AC20; see Figs.S6 and S7 for these flights).In these flights the estimated r ea values were larger than the measured r e as a function of D c and strong updrafts (up to 15 m s −1 ) were observed above cloud base (see Fig. S3b, d, and h).The acceler- no raindrops are formed in growing convective clouds under these conditions.Instead, large precipitation particles are formed at cold temperatures in the form of ice.The D c at which these ice particles are formed depends on the size of the cloud droplets (r e ) at colder temperatures (larger droplets freeze earlier or at lower D c ; Pruppacher et al., 1998).This was previously documented by satellite retrievals (Rosenfeld et al., 2011) in which the glaciation temperatures of convective clouds were strongly dependent on r e at the −5 • C isotherm, and smaller r e values were correlated with lower glaciation temperatures.

Discussion
The results from cloud probe measurements under clean, polluted, and very polluted conditions highlight the role of aerosol particles in rain and ice formation for growing convective cumulus.Figure 15 summarizes the estimated depths above cloud base at which the initiation of rain and ice formation is observed (D r and D i ) and the estimated D c for rain initiation as indicated from r ea by D 13 .This figure shows a close relationship between N a and D r of D r = (5±1.06)•Na , demonstrating the capability to predict the minimum height at which raindrops are expected to form based on cloud base drop concentrations.For flights in which rain was observed (AC19, AC18, and AC09), D r occurs at heights slightly greater than D 13 .For cases in which neither rain nor ice was observed (AC08, AC12, and AC20), the estimated D 13 was not reached during the HALO cloud profiling flights.In addition, D 13 and D i show similar values for flight AC07, whereas for flight AC13 the values are less comparable (probably due to an overestimation of N a and thus D 13 caused by additional CCN activation above cloud base).
The linear relationship between N a and D 13 indicates a regression slope of about 5 m (cm −3 ) −1 between D 13 and the calculated N a for the Amazon during the dry-to-wet season.This value is slightly larger than the values observed by Freud and Rosenfeld (2012) for other locations around the globe (e.g., India and Israel).These clear linear relationships found between N a and D r (∼ D 13 ) for different regions highlight the efficiency of the adiabatic parcel model to estimate the height of rain initiation within convective clouds in this study.Additional associated cloud processes, such as GCCN, cloud, and mixing with ambient air and other processes, which are not accounted for in this study, would produce deviations that are likely to be the cause of the observed scatter in the results.
For the flight in the cleanest conditions (AC19), the presence of larger aerosol particles (possibly GCCN from sea spray) below cloud base leads to a faster growth of cloud droplets via condensation with height, and consequently r e is smaller than 13 µm (see Fig. 9a) for warm rain initiation.A similar decrease in r e for rain initiation over ocean was observed by Konwar et al. (2012).While D r is explained by N d and well correlated with it, there is no correlation between N d and D i .
Figure 16 illustrates the vertical development of precipitation water content by symbols representing the amount of DWC and MPWC as a function of D c and CDP-measured r e .Also shown are the lines of r ea as a function of D c .The figure shows that raindrops began to form at r e of 13 µm for AC09 and AC18.The r e for rain initiation is slightly smaller (12 µm) on AC19, probably due to the sea spray giant CCN, which accelerates the coalescence for a given r e .Mixedphase precipitation was initiated on flights AC07 and AC13, well below the height of D 13 at an r e of 11.5 and 10.2 µm, respectively.Ice starts to form at lower temperatures when the cloud droplets are smaller, as manifested by D i of −9 and −14 • C for flights AC07 and AC13, respectively.The remaining flights did not reach the height for rain initiation (AC08, AC12, and AC20).It is evident that raindrops form faster via collision and coalescence process in a cleaner atmosphere.For the polluted cases, raindrops form at colder temperatures (∼ 0 • C and colder) via collision and coalescence than for clean conditions.Rain can initiate at supercooled temperatures, e.g., −5 • C on AC18.The raindrops were documented to start freezing at −9 • C in AC09.In very polluted conditions, only cloud droplets and no raindrops were observed at D c < 4000 m.In these cases, precipitation was initiated as ice particles at D c > 4000 m.These flights with completely suppressed warm rain were performed over the smoky deforestation arc.Measurements of large updrafts that increase supersaturation within cloud and the higher N d above cloud base indicate new activation of cloud droplets for flight AC13 (not observed at AC07) in the course of the development of convective cumulus.This additional CCN activation leads to smaller r e .For flights during which additional CCN activation was significant, the differences between the estimated r ea and the r e measurements at the same height are larger because the adiabatic estimation does not consider the additional CCN activation of droplets above cloud base and thus overestimates the observed size.
Figure 17 summarizes the findings from the vertical profiling flights.It illustrates the vertical microstructure of growing cumulus above the Amazon and the adjacent ocean in varying aerosol conditions.The figure highlights the differences in aerosol concentrations and cloud particle distribution within convective clouds over the Amazon basin (including the Atlantic Ocean, forested, and deforested regions).The aerosol concentration is smaller over the Atlantic Ocean and increases significantly at the continental Amazon, especially over the deforestation arc due to biomass burning emissions from forest fires.The more polluted the atmosphere, the larger the number of droplets nucleated at cloud base and the less efficient the growth of cloud droplets via condensation with D c .The new activation of CCN above cloud base has also been shown to decrease the efficiency of cloud droplet growth due to the higher competition for water vapor available.The increase in aerosol concentration over the Amazon basin according to our findings has been shown to suppress the warm rain formation because larger cloud depths were necessary for raindrops to start to form (when cloud droplets have r e ∼ 13-14 µm).The additional aerosol concentrations observed at polluted regions from forest fires suppress rain such that most hydrometeors are ice when they are at a size that allows us to distinguish their phase (∼ 0.25 mm).In addition, the formation of ice particles was also delayed (or occurred at higher D c ) in more polluted atmospheres because smaller cloud droplets freeze at lower temperatures.

Conclusions
This study focused on the effects of aerosol particle number concentration on the initiation of raindrops and ice hydrometeors in growing convective cumulus over the Amazon.Data from aerosol and cloud probes onboard the HALO aircraft were used in the analysis.The values of the estimated N a at cloud base were applied to classify the atmospheric conditions under which convective clouds developed as a function of aerosol particle number concentration (i.e., clean, polluted, and very polluted regions).From the estimated N a , the evolution of r ea and the theoretical r e , assuming adiabatic growth of droplets with cloud depth above cloud base (D c ), were compared with the observed r e at the various heights.A DWC value of 0.01 g m −3 was used as a threshold for rain initiation or glaciation within clouds.Images from the CCP-CIP probe were used to detect the presence of raindrops and/or ice hydrometeors.The results shown in previous sections support the following conclusions.
1.The use of r e ∼ 13-14 µm as a threshold for rain initiation is suitable for convective clouds formed at the Amazon basin during the dry season.It is in agreement with r e of rain initiation elsewhere.
2. The evolution of the directly observed r e generally follows that of the calculated r ea due to the nearly inhomogeneous mixing behavior of the convective clouds with the ambient air.Convective clouds are usually nonadiabatic systems because of strong wind and turbulence effects, heating, and other factors, but the similarities of r e and r ea provided the capability to estimate D r over the Amazon and other regions around the globe (e.g., India and Israel).
3. Rain initiation occurred higher in more polluted clouds, as manifested by higher D c .Rain was initiated at supercooled levels in moderately polluted clouds.In very polluted conditions, warm rain was suppressed completely.This was exacerbated by the occurrence of additional CCN activation above cloud base, which further reduced r e compared to r ea .
4. The initiation of ice hydrometeors is also delayed to greater D c in more polluted clouds because smaller drops freeze at colder temperatures due to suppressed ice multiplication processes (Hallett and Mossop, 1974).Ice was initiated mostly by freezing raindrops in cases when warm rain formation was not completely suppressed.
5. Both the D 13 and D r increased linearly with N a , which is in agreement with the theoretical considerations of Freud and Rosenfeld (2012).Despite the suspected occasional additional CCN activation, r e was sufficiently close to r ea to allow a linear relationship in the form of D r = (5 ± 1.06) • N a .The deviation from an exact linear relationship can be associated with additional cloud processes, such as GCCN, cloud, and mixing with ambient air.The magnitude of these additional processes is insufficient to mask the linear relationship.The observations also suggest that, in the absence of new droplet activation above cloud base, D 13 is very similar to D i under very polluted conditions in which raindrops are not formed at warmer temperatures.
These results show that even moderate amounts of smoke, which fills most of the Amazon basin during the drier season, are sufficient to suppress warm rain and elevate its initiation to above the 0 • C isotherm level.This results in a suppression of rain from small clouds and an invigoration in the deep clouds, as hypothesized by Rosenfeld et al. (2008).While the net effect on rainfall amount is unknown, the redistribution of rain intensities and the resulting vertical latent heating profiles are likely to affect the regional hydrological cycle in ways that need to be studied further.

Figure 1 .
Figure 1.(a) HALO flight tracks during the ACRIDICON-CHUVA experiment.The flight number is indicated at the bottom by colors; (b) flight patterns below and in convective clouds during the ACRIDICON-CHUVA campaign.
R. C. Braga et al.: CCN concentrations determining the height of warm rain a.The relationship between r e and the probability of drizzle is found.The value of r e is calculated from the size distributions measured by the CAS-DPOL and the CCP-CDP (two different values).DWC, RWC, and MPWC are obtained from the CCP-CIP data.The calculations of these cloud properties are detailed in Sect.4.1.b.The N a at cloud base is estimated through the vertical profile of r e .The calculation of N a is detailed in Sect.4.2.

Figure 2 .
Figure 2. (a) Precipitation probability as a function of r e for the CCP-CDP probe for different DWC thresholds (black DWC > 0.01 g m −3 ; blue DWC > 0.02 g m −3 ; green DWC > 0.03 g m −3 ; gold DWC > 0.05 g m −3 ; red DWC > 0.1 g m −3 ).The dashed line indicates the number of cases (in seconds for each 1 s cloud pass) for each r e size interval (right axis); (b) similar for the CAS-DPOL probe.

Figure 3 .
Figure 3. Cloud droplet concentration measured with CCP-CDP as a function of temperature for flight AC07.Each dot indicates a 1 Hz average concentration.The sample number (N) and the approximate start time of the cloud profile are shown at the top of the panel.
Figure 4. (a) Mean cloud droplet size distribution calculated from the CCP-CDP data for a cloud pass at cloud base during flight AC07.The flight number, initial time of cloud pass, and duration in seconds are shown at the top of graph.The mean total number of droplets (N dmean ), the maximum total number of droplets (N dmax ) in 1 s for this cloud pass, and the approximate height (H ) and temperature (T ) are shown at the upper right corner of the graph; (b) cloud droplet effective radius (r e ) calculated from CCP-CDP as a function of temperature is indicated with dots.The black line indicates the estimated adiabatic effective radius (r ea ) as a function of temperature.

Figure 6 .
Figure 6.Image taken from the HALO cockpit just before the aircraft penetration of a convective cloud with lightning activity during flight AC07.In this case, the cloud pass height was 9022 m (temperature ∼ −25 • C) and the maximum CWC measured was 0.55 g m −3 .

Figure 7 .
Figure 7. (a) Cloud droplet effective radius (r e ) as a function of cloud depth (D c ) for flight AC07.The line indicates the r e estimated for adiabatic growth (r ea ) from cloud base (dashed lines indicate the r ea values considering the uncertainty of the estimate).The height of 0 • C is indicated by a black horizontal bar across the r ea line.The estimated adiabatic number of droplets (N a ) at cloud base is shown at the top of the figure.(b) Similar to panel (a) for cloud water content (adiabatic values are shown by lines).

Figure 8 .
Figure 8.(a) Cloud droplet concentrations measured with the CCP-CDP as a function of temperature for flight AC19.Each dot indicates 1 Hz average concentration.The sample number in seconds (N) and the start time of the cloud profile are shown at the top of the panel; (b) similar to Fig. 7 for flight AC19. 14445

Figure 10 .
Figure 10.Cumulative aerosol size distribution below cloud base calculated from the PCASP probe for typical clean, polluted, and very polluted regions (solid line) for flights AC12 (very polluted), AC18 (polluted), and AC19 (clean).Similar for cumulative cloud droplet size distribution calculated with CCP-CDP (dashed line).The flight numbers are indicated by colors at the top of the panel.

Figure 11 .
Figure 11.(a) Cloud droplet concentrations measured with the CCP-CDP as a function of temperature for flight AC09.Each dot indicates 1 Hz average concentration.The sample number in seconds (N ) and the start time of the cloud profile are shown at the top of the panel; (b) similar to Fig. 9 for flight AC09.

Figure 15 .
Figure 15.Cloud depth (D c ) as a function of the estimated adiabatic number of droplets (N a ) at cloud base.The D c values for adiabatic cloud droplet effective radius (r ea ) equal 13 µm (or D 13 ) and are indicated by triangles.Similar for cloud depth of rain initiation (D r ) (indicated by circles) and cloud depth for ice initiation (D i ) (indicated by an asterisk).The flight numbers are indicated by colors on the right side of the panel.The values of D 13 , D r , and D i are shown in Table 1.The uncertainties of N a estimates are shown by horizontal error bars.The vertical error bars indicate the cloud depth between D r and D r−1 or D i and D i−1 .The black line indicates the linear equation for D 13 as a function of N a for all flights, where D r = (5 ± 1.06)N a .

Figure 16 .
Figure 16.CDP-measured cloud droplet effective radius (r e ) (colored dots) and estimated cloud droplet adiabatic effective radius (r ea ) (colored lines) as a function of cloud depth (D c ) for all flights (indicated by colors).The height of 0 • C is indicated by a horizontal bar across the r ea line.The circles indicate the approximate values of drizzle water content (DWC) calculated from the CCP-CIP data; the range of DWC values is indicated in the table in panel (b).The star symbols indicate the approximate mixed-phase drizzle water content (MPWC) values calculated from the CCP-CIP data (indicated in the table in panel c).The temperature in • C of rain or ice initiation (D r and D i , respectively) is indicated by colored numbers close to the circle or star symbols.

Figure 17 .
Figure 17.General characteristics of growing convective cumulus formed over the Amazon basin during the dry season.The heights of cloud base are higher over the continental Amazon due to the smaller relative humidity in comparison with the maritime region.Convective clouds formed over the Atlantic Ocean near the Brazilian coast have smaller cloud droplet concentrations (N d ) at cloud base due to the smaller concentration of aerosol and updraft speeds below cloud base.The initiation of warm rain (D r ) is observed at lower cloud depths (∼ 2 km or ∼ 10 • C) from collision and coalescence processes.When convective clouds are more continental, larger aerosol concentration and updrafts are observed below cloud base, leading to larger N d nucleated at cloud base (as observed above forested and deforested regions).Over the forest D r is observed near 0 • C, whilst for the deforestation arc region the collision and coalescence processes are totally suppressed and the formation of ice particles took place at higher altitudes in the clouds in very polluted conditions because the resulting smaller cloud droplets froze at colder temperatures compared to the larger drops in the less polluted cases.

Table 1 .
List of abbreviations and symbols.Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems-CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM [Global Precipitation Measurements])

Table 2 .
Description of cloud probes, size range intervals, and hydrometeor shapes observed on CCP-CIP images used to calculate CWC, DWC, RWC, and MPWC.