**4. Analysis and discussion**

Five flights and ten cloud systems were selected for analysis based on a visual evaluation of the records made with the forward- and side-looking video cameras on the aircraft. The criteria was that no other clouds could be seen within around 10 km on either side of a cloud line, such that far-cloud samples represent "ambient" aerosols, i.e., lacking any recently processed particles by clouds.

## **4.1. Time series to identify clouds**

We studied the data from flights 7, 9, 12, 13 and 17. The flights were conducted in convective clouds by passing through the clouds at different levels (1000, 2500, 4200, and 6000 meters). Moreover, we passed through the cloud base (300 meters) and at surface level (30 meters).

Interaction Between Aerosol Particles and Maritime Convective Clouds:

criterion was to consider the instrument's concentration records ≥ 1 cm-3 obtained within the cloud. In EPIC 2001, we identified 10 cloud systems that met the minimum information necessary for the study. Table 2 shows the location, date and time of each cloud systems.

> Cloud base length (m)

Cloud base T (°C)

Cloud base wind speed (m s-1)

93.7°W HG 910 345 4800 25.60 1.4 79 \*\*\* \*\*\* \*\*\* \*\*\* \*\*\* \*\*\*

95.2°W HG 830 227 25740 25.04 2.5 80 13900 2.44 9.3 91 3370 447

95.9°W MR 380 66 18093 24.18 1.3 85 500 3.63 0.3 65 320 32

95.8°W MR 200 40 12860 23.63 1.5 83 2640 2.95 3.4 79 810 48

93.9°W MR 460 138 13970 25.26 3 83 680 3.7 7.2 62 590 32

94.1°W MR 420 143 4550 24.87 1.2 80 7040 3.74 2.7 80 818 14

94.6°W MR 360 98 11440 24.06 1.6 84 2970 3.97 1.9 88 15574 50

94.9°W MR 390 64 9460 24.15 1.5 84 8690 3.88 2.7 85 1119 98

93.9°W HG 1900 696 36200 26.02 2.3 82 5060 3.92 5.8 81 2810 384

94.1°W HG 1600 510 10560 26.53 0.9 68 2480 3.2 2.4 72 1080 350

Cloud base RH (%)

300m 4200m

Cloud top length (m)

Cloud top T (°C)

Cloud top wind speed (m s-1)

Cloud top RH (%)

CN Conc. (cm-3)

PCAS P Conc (cm-3)

Flights 9, 12, and 13 were made on days with "maritime" (MR) aerosol background and when winds came from the southwest. "Higher" (HG) aerosols concentrations correspond to flights 7 and 17 with average concentrations significantly higher than the other three

A convective cloud in its formative stage has a rapid vertical development. The ambient air surrounding the cloud incorporates into the cloud increasing its volume with the vertical expansion. This process is known as entrainment, so its mixing process is more efficient outboard in the cloud with sub-saturated air from the environment. The droplets evaporate and particles served as CCN are released back into the atmosphere. The mixing with ambient air and the evaporation of cloud droplets produces a cooling air parcel which generates a negative buoyancy force. This could result in shear zones, as the turbulence caused by this effect helps to mix ambient air with the cloud and evaporate more drops. To define the distance corresponding to the cloud border, we did a time series properties analysis of the particles in the clouds, to evaluate the zone of influence. Figure 4 shows the changes in properties of the particles in the vicinity of the cloud. The area of influence for the interaction of particles with the cloud covers a distance of approximately 500 m from the cloud's border. The FSSP100 drops concentration

The data correspond to the average information of all transects made to the system.

PCASP Conc (cm-3)

**Table 2.** Characteristics of cloud system selected for the analysis

**4.2. Cloud boundaries comparison** 

Flight #

Date 2001

Cloud System

7 sep-16 1 16:46-

7 sep-16 2 18:42-

9 sep-20 3 18:16-

9 sep-20 4 18:56-

12 sep-28 5 17:03-

12 sep-28 6 19:14-

13 sep-29 7 18:31-

13 sep-29 8 19:36-

17 06-oct 9 18:34-

17 06-oct 10 20:51-

Time Period (UTC)

17:19

20:12

20:11

20:24

18:12

20:20

19:03

20:22

19:49

21:36

Location Particle Source

12.3°N,

11.9°N,

10.5°N,

8.2°N,

9.3°N,

11.9°N,

11.4°N,

12.4°N,

11.9°N,

11.8°N,

CN Conc (cm-3)

flights. Table 2 summarizes the time, location and type of cloud systems.

Measurements in ITCZ During the EPIC 2001 Project 233

**Figure 3.** Cloud processing signatures

Furthermore, during the flights were conducted surveys of the atmosphere's vertical profile. This information is useful because surveys have different locations, but they are associated to the clouds recorded data.

We observed changes in the properties of atmospheric particles and the processes responsible. Also we recorded environmental and weather conditions in zones which the property changes occur more frequently, comparing both sides of the clouds.

The droplets concentration in a cloud is function of the particles number in the atmosphere, so any variation in the amount of particles will affect the cloud microphysics evolution. In marine areas the concentration of particles is about 100 per cm3, if there is a greater amount of particles is likely to pollution particles are present. The EPIC 2001 research area is located approximately 800 - 1000 km away from Mexico and Central America, allowing the transport of pollutants from the continent to the area when the prevailing winds are favourable. The opposite situation is also possible in maritime areas away from the coast. Wind patterns during flights 12 and 13 shows weather characteristics of maritime areas.

The cloud boundaries are identified by means of videotapes taken from the plane C-130 and the analysis of time series using reference measurements obtained by the FSSP100. The criterion was to consider the instrument's concentration records ≥ 1 cm-3 obtained within the cloud. In EPIC 2001, we identified 10 cloud systems that met the minimum information necessary for the study. Table 2 shows the location, date and time of each cloud systems. The data correspond to the average information of all transects made to the system.


**Table 2.** Characteristics of cloud system selected for the analysis

Flights 9, 12, and 13 were made on days with "maritime" (MR) aerosol background and when winds came from the southwest. "Higher" (HG) aerosols concentrations correspond to flights 7 and 17 with average concentrations significantly higher than the other three flights. Table 2 summarizes the time, location and type of cloud systems.

## **4.2. Cloud boundaries comparison**

232 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

**Figure 3.** Cloud processing signatures

to the clouds recorded data.

Furthermore, during the flights were conducted surveys of the atmosphere's vertical profile. This information is useful because surveys have different locations, but they are associated

We observed changes in the properties of atmospheric particles and the processes responsible. Also we recorded environmental and weather conditions in zones which the

The droplets concentration in a cloud is function of the particles number in the atmosphere, so any variation in the amount of particles will affect the cloud microphysics evolution. In marine areas the concentration of particles is about 100 per cm3, if there is a greater amount of particles is likely to pollution particles are present. The EPIC 2001 research area is located approximately 800 - 1000 km away from Mexico and Central America, allowing the transport of pollutants from the continent to the area when the prevailing winds are favourable. The opposite situation is also possible in maritime areas away from the coast. Wind patterns during flights 12 and 13 shows weather characteristics of maritime areas.

The cloud boundaries are identified by means of videotapes taken from the plane C-130 and the analysis of time series using reference measurements obtained by the FSSP100. The

property changes occur more frequently, comparing both sides of the clouds.

A convective cloud in its formative stage has a rapid vertical development. The ambient air surrounding the cloud incorporates into the cloud increasing its volume with the vertical expansion. This process is known as entrainment, so its mixing process is more efficient outboard in the cloud with sub-saturated air from the environment. The droplets evaporate and particles served as CCN are released back into the atmosphere. The mixing with ambient air and the evaporation of cloud droplets produces a cooling air parcel which generates a negative buoyancy force. This could result in shear zones, as the turbulence caused by this effect helps to mix ambient air with the cloud and evaporate more drops. To define the distance corresponding to the cloud border, we did a time series properties analysis of the particles in the clouds, to evaluate the zone of influence. Figure 4 shows the changes in properties of the particles in the vicinity of the cloud. The area of influence for the interaction of particles with the cloud covers a distance of approximately 500 m from the cloud's border. The FSSP100 drops concentration

measurements correspond to the solid line, which marks the cloud's boundary. Each tick mark represents 110 m at the aircraft's average velocity of 110 m s-1. The dotted lines represent the behavior of the average diameter of particles measured by the FSSP300 (dash) and FSSP100 (dash and dot). These values denote the limits of the transition region between ambient and cloud air. Diameter measurements show a significant increase of particles up to ~500 m from the cloud's boundary. That determines the representative area to evaluate the mechanisms that modify the properties of particles due to the interaction with the cloud.

Interaction Between Aerosol Particles and Maritime Convective Clouds:

**P**

0 100 200 300

**U**

**D**

0 20 40 60 80

**<sup>D</sup> CS-06**

0 50 100 150 200

**D CS-08**

0 20 40 60 80 100

0 200 400 600 800 1000 PCASP conc (cm-3)

**D**

**U**

**D**

**CS-10**

**U**

**P**

**U**

**P**

**P**

**P**

**D**

**D P**

**U**

**<sup>D</sup> CS-04**

**U P**

**U**

**D**

**U**

**D**

**U**

**P**

**P**

**U**

**P**

**<sup>P</sup> CS-02**

**P P**

**P P**

**Figure 5.** Vertical profiles of particle concentrations measures for the 10 cloud cases. The far-cloud profiles (short dashed) and near-cloud profiles on each side of the cloud (solid and long dashed lines).

**U**

**D**

0 200 400 600 800 PCASP conc (cm-3)

**P**

**P**

**U**

**D**

**P**

**<sup>P</sup> CS-09**

**U**

**P**

0 100 200 300 400 500

**<sup>P</sup> CS-03**

0 40 80 120 160 200

**<sup>D</sup> CS-05**

0 50 100 150 200 250

0 50 100 150

**D**

**D**

**U U**

**<sup>D</sup> CS-07**

**D**

**U U**

**D**

**PCS-01**

**U**

**U**

**U**

**D**

**P**

**P**

**P**

**P**

**D D**

**D**

**P**

**P**

**P**

**P**

**U**

Altitude (m)

Altitude (m)

Altitude (m)

Altitude (m)

particles increased their volume within the cloud.

**P**

**U**

**D**

**U**

Altitude (m)

Figure 6 shows concentrations measured with FSSP100 (> 2 μm) in the vicinity of the cloud (solid and dotted lines) and away from the cloud (dotted line). In the region where there are drops of cloud measurements, we used them to detect giant particles (> 1 micron) coming from the ocean. In most cases, the concentration values for particles greater than 1 micron near the cloud have a maximum at 1000 m high. It happens perhaps because smaller size

Sometimes it is possible to observe when the particle concentrations decrease with height that there is an increase in the concentrations of larger diameters. The combination of patterns is indicative of changes in particles by mixing and dilution on the total concentration dominated by small particles. Also, a simultaneous increase in the

concentrations of particles suggests that it there is a change in particles size.

Measurements in ITCZ During the EPIC 2001 Project 235

**P**

**Figure 4.** Medium volume diameters measured by FSSP300 (dashed line) and FSSP100 (dot-dash line) indicating a cloud boundary.

The particles properties on both sides of the cloud border must be different. The particles characteristics in the neighboring area of the cloud have a determining effect on the modification of some of their properties. Changes in humidity, altitude and environmental conditions, where the samples are collected, affect the particles concentration and size. So, in order to compare both sides of the cloud we analyze data from the clouds vicinity (500 m from the border of the cloud) to obtain average values. Figure 5 shows the average concentrations of vertical profiles measured by the PSCASP (> 0.1 microns) on the cloud borders (cases identified by U, D or P). A third profile, corresponding to a far area from the cloud (average 500 to 1500 m from the border (dotted line), is used to compare the profiles against those close to the cloud.

In conditions with and without pollution, particle profiles measured in the vertical gradient has two patterns. One shows a constant value or a decrease with height. The second shows an increase in concentration up to 2500 m and then decreases to lower values than those measured at the base. It is possible to observe cases where the particle concentration profiles are similar to the concentration profile far away from the cloud. This is due to the presence of dilution processes, where particle concentrations in the vicinity of the cloud are lower than in remote areas. When the concentration of particles near the cloud is greater than the environment it is possible that there is an increase of particle size < 0.1 μm to ranges that is not possible to detect. In summary, measures of concentration of particles increased with height indicating that the smaller particles (< 0.1 μm) at the base of the cloud grow to detectable size ranges for the instrument during transport through the cloud. On the other hand, when the concentrations decrease with height means a dilution effect.

Interaction Between Aerosol Particles and Maritime Convective Clouds: Measurements in ITCZ During the EPIC 2001 Project 235

234 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

with the cloud.

indicating a cloud boundary.

against those close to the cloud.

measurements correspond to the solid line, which marks the cloud's boundary. Each tick mark represents 110 m at the aircraft's average velocity of 110 m s-1. The dotted lines represent the behavior of the average diameter of particles measured by the FSSP300 (dash) and FSSP100 (dash and dot). These values denote the limits of the transition region between ambient and cloud air. Diameter measurements show a significant increase of particles up to ~500 m from the cloud's boundary. That determines the representative area to evaluate the mechanisms that modify the properties of particles due to the interaction

**Figure 4.** Medium volume diameters measured by FSSP300 (dashed line) and FSSP100 (dot-dash line)

The particles properties on both sides of the cloud border must be different. The particles characteristics in the neighboring area of the cloud have a determining effect on the modification of some of their properties. Changes in humidity, altitude and environmental conditions, where the samples are collected, affect the particles concentration and size. So, in order to compare both sides of the cloud we analyze data from the clouds vicinity (500 m from the border of the cloud) to obtain average values. Figure 5 shows the average concentrations of vertical profiles measured by the PSCASP (> 0.1 microns) on the cloud borders (cases identified by U, D or P). A third profile, corresponding to a far area from the cloud (average 500 to 1500 m from the border (dotted line), is used to compare the profiles

In conditions with and without pollution, particle profiles measured in the vertical gradient has two patterns. One shows a constant value or a decrease with height. The second shows an increase in concentration up to 2500 m and then decreases to lower values than those measured at the base. It is possible to observe cases where the particle concentration profiles are similar to the concentration profile far away from the cloud. This is due to the presence of dilution processes, where particle concentrations in the vicinity of the cloud are lower than in remote areas. When the concentration of particles near the cloud is greater than the environment it is possible that there is an increase of particle size < 0.1 μm to ranges that is not possible to detect. In summary, measures of concentration of particles increased with height indicating that the smaller particles (< 0.1 μm) at the base of the cloud grow to detectable size ranges for the instrument during transport through the cloud. On the other

hand, when the concentrations decrease with height means a dilution effect.

**Figure 5.** Vertical profiles of particle concentrations measures for the 10 cloud cases. The far-cloud profiles (short dashed) and near-cloud profiles on each side of the cloud (solid and long dashed lines).

Figure 6 shows concentrations measured with FSSP100 (> 2 μm) in the vicinity of the cloud (solid and dotted lines) and away from the cloud (dotted line). In the region where there are drops of cloud measurements, we used them to detect giant particles (> 1 micron) coming from the ocean. In most cases, the concentration values for particles greater than 1 micron near the cloud have a maximum at 1000 m high. It happens perhaps because smaller size particles increased their volume within the cloud.

Sometimes it is possible to observe when the particle concentrations decrease with height that there is an increase in the concentrations of larger diameters. The combination of patterns is indicative of changes in particles by mixing and dilution on the total concentration dominated by small particles. Also, a simultaneous increase in the concentrations of particles suggests that it there is a change in particles size.

Interaction Between Aerosol Particles and Maritime Convective Clouds:

**Figure 7.** Percentages of cloud processing signatures, derived from vertical profiles of particle properties and evaluation of particle size distributions, for the MR cases (bottom panel), HG cases

4200 m particles were evenly distributed between patterns A and D.

There were no consistent trends with altitude between MR and HG days. Particles at 1000 m and 2500 m altitude were predominantly like pattern A, in both the MR and HG cases. In MR cases, there were slightly more type B than type A particles at 4200 m. In HG cases, the

The refractive index was used to estimate the particles composition at the ends of the clouds. We calculated and average refractive indices at 500 m from the borders of the cloud. Figure 8 shows the results. The refractive index profile for the area between 1000 and 1500 m away from the border of the cloud is also shown. This area is considered free from the influence of

We consider three refractive indexes as benchmarks. The refraction indexes of water (1.33), ammonium sulfate (1.48), and sodium chloride (1.54). Another factor we take into account is the size distribution and composition of particles as a function of their height in normal conditions without the influence of pollution. The type and composition of particles depend on local sources. Thus, in sea areas the main sources are the production of salt particles from the surface of the oceans that are caused by wind friction and breaking waves. These particles are mainly in the lower parts of the troposphere near its source. In the upper troposphere, main sources of particle are the conversion of gas to particle and deposition by

(middle), and combined cases.

**4.4. Particle composition estimation** 

particle processing by clouds.

Measurements in ITCZ During the EPIC 2001 Project 237

**Figure 6.** The vertical profiles of concentrations measured with the FSSP-100.

### **4.3. Processes classification and evaluation**

There are different processes at each side of the cloud and in each level of each clouds system. We used as reference the processes signal description and their property. This subjective classification is based on an examination of vertical profiles, shown in Figs. 4, 5, and 6 and on the shapes of PSDs associated with the near-cloud region at each level. The 300 m passes were only evaluated for evidence of removal by precipitation (pattern D). Figure 7 summarizes the frequency of each category. There were 49 classifications made on MR days and 35 during HG days. A classification could not be made in 10% of the MR cases and 5% of the HG ones. The largest fraction of the observations was classified as pattern A (40% and 60% of MR and HG cases, respectively). Pattern C matched only 4% of the MR observations and none during HG days. Patterns B and D were equally represented during both MR and HG days.

Interaction Between Aerosol Particles and Maritime Convective Clouds: Measurements in ITCZ During the EPIC 2001 Project 237

**Figure 7.** Percentages of cloud processing signatures, derived from vertical profiles of particle properties and evaluation of particle size distributions, for the MR cases (bottom panel), HG cases (middle), and combined cases.

There were no consistent trends with altitude between MR and HG days. Particles at 1000 m and 2500 m altitude were predominantly like pattern A, in both the MR and HG cases. In MR cases, there were slightly more type B than type A particles at 4200 m. In HG cases, the 4200 m particles were evenly distributed between patterns A and D.

## **4.4. Particle composition estimation**

236 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

**Figure 6.** The vertical profiles of concentrations measured with the FSSP-100.

There are different processes at each side of the cloud and in each level of each clouds system. We used as reference the processes signal description and their property. This subjective classification is based on an examination of vertical profiles, shown in Figs. 4, 5, and 6 and on the shapes of PSDs associated with the near-cloud region at each level. The 300 m passes were only evaluated for evidence of removal by precipitation (pattern D). Figure 7 summarizes the frequency of each category. There were 49 classifications made on MR days and 35 during HG days. A classification could not be made in 10% of the MR cases and 5% of the HG ones. The largest fraction of the observations was classified as pattern A (40% and 60% of MR and HG cases, respectively). Pattern C matched only 4% of the MR observations and none during HG days. Patterns B and D were equally represented during both MR and

**4.3. Processes classification and evaluation** 

HG days.

The refractive index was used to estimate the particles composition at the ends of the clouds. We calculated and average refractive indices at 500 m from the borders of the cloud. Figure 8 shows the results. The refractive index profile for the area between 1000 and 1500 m away from the border of the cloud is also shown. This area is considered free from the influence of particle processing by clouds.

We consider three refractive indexes as benchmarks. The refraction indexes of water (1.33), ammonium sulfate (1.48), and sodium chloride (1.54). Another factor we take into account is the size distribution and composition of particles as a function of their height in normal conditions without the influence of pollution. The type and composition of particles depend on local sources. Thus, in sea areas the main sources are the production of salt particles from the surface of the oceans that are caused by wind friction and breaking waves. These particles are mainly in the lower parts of the troposphere near its source. In the upper troposphere, main sources of particle are the conversion of gas to particle and deposition by

clouds (Hobbs, 1993) which produce small particles (< 0.1 μm). In marine areas the particles are composed of sulfate, because they are formed by the condensation of SO2. Particles ranged between 0.1 to 1 microns are composed of sulfate (Hobbs, 1993). Based on the sources we expected to find high ammonium sulfate in the lower troposphere.

Interaction Between Aerosol Particles and Maritime Convective Clouds:

**Figure 9.** Scattering coefficients compared against those measured with the nephelometer for three refractive indexes: 1.33, 1.48, and 1.54, for MR days (a) and high aerosol concentrations (HG) days (b).

Atmospheric particles play an important role in the planet radiative budget. Their effects on radiative forcing by absorbing solar radiation backscattered or as facilitating clouds

The uncertainty of particle-radiation interactions is still very large. For example, some particles with sulfate or organic carbon cool the atmosphere. On the other hand, black carbon particles warm it, because they absorb visible light and convert it into thermal energy (IPCC, 2000). This strange balance increases the uncertainty of the magnitude of their

The cloud process and modify particles size and composition. Larger particles scatter more sunlight and increase the extinction of light. This impact on the radiative balance can be

���� � � ����� ���� �

Where τ is the optical thickness and σe is the particle's extinction coefficient. In our case, we assume that the particle's composition is mainly sodium chloride (sea salt) and sulfates. The particle does not absorb visible light, so its extinction and dispersion coefficients are equal.

� � ∑ ������� ����

To calculate the optical depth, we use the size distribution spectra for the following heights: 30, 300, 1000, 2500 and 4200 m on both sides of the cloud, as well as the average between

� (3)

���� (4)

estimated with the optical depth, since the extinction of particles is expressed:

**5. Effects of atmospheric particles** 

formation are important objects of study.

**5.1. Direct effects of particles processed by clouds** 

effects on the atmosphere.

Thus, the above equation becomes:

1000 and 1500 m away from the cloud.

Measurements in ITCZ During the EPIC 2001 Project 239

**Figure 8.** Derived refractive indexes for far- and near-cloud vertical profiles for the maritime (MR) day cases.

In estimating the composition of particles from optical counters measurements, the environmental conditions can strongly influence the outcome. Figure 9 shows the comparison between the dispersion coefficients obtained with a nephelometer and the dispersion coefficient calculated from the particles size distribution. Data were collected on transects at 2500 m without pollution (Figure 9 right) and with pollution from the continent (Figure 9 left). The reference line 1:1 is used to compare dispersion coefficients calculated and from nephelometer, assuming three different compositions.

Figure 9 (left) shows that polluted cases at the same height had calculated coefficients higher than those measured with instrumentation. This may be due to anthropogenic particles that absorb and scatter light. So, the measured values will be lower than calculated, since it is not taken into account the particles absorption. Moreover, no polluted cases have a better correlation because marine particles do not absorb light. This feature allows us to use this technique to more easily estimate the composition of particles in cases without contamination.

Interaction Between Aerosol Particles and Maritime Convective Clouds: Measurements in ITCZ During the EPIC 2001 Project 239

**Figure 9.** Scattering coefficients compared against those measured with the nephelometer for three refractive indexes: 1.33, 1.48, and 1.54, for MR days (a) and high aerosol concentrations (HG) days (b).

## **5. Effects of atmospheric particles**

238 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

clouds (Hobbs, 1993) which produce small particles (< 0.1 μm). In marine areas the particles are composed of sulfate, because they are formed by the condensation of SO2. Particles ranged between 0.1 to 1 microns are composed of sulfate (Hobbs, 1993). Based on the

**Figure 8.** Derived refractive indexes for far- and near-cloud vertical profiles for the maritime (MR) day

In estimating the composition of particles from optical counters measurements, the environmental conditions can strongly influence the outcome. Figure 9 shows the comparison between the dispersion coefficients obtained with a nephelometer and the dispersion coefficient calculated from the particles size distribution. Data were collected on transects at 2500 m without pollution (Figure 9 right) and with pollution from the continent (Figure 9 left). The reference line 1:1 is used to compare dispersion coefficients calculated

Figure 9 (left) shows that polluted cases at the same height had calculated coefficients higher than those measured with instrumentation. This may be due to anthropogenic particles that absorb and scatter light. So, the measured values will be lower than calculated, since it is not taken into account the particles absorption. Moreover, no polluted cases have a better correlation because marine particles do not absorb light. This feature allows us to use this technique to more easily estimate the composition of particles in cases without contamination.

and from nephelometer, assuming three different compositions.

cases.

sources we expected to find high ammonium sulfate in the lower troposphere.

Atmospheric particles play an important role in the planet radiative budget. Their effects on radiative forcing by absorbing solar radiation backscattered or as facilitating clouds formation are important objects of study.

The uncertainty of particle-radiation interactions is still very large. For example, some particles with sulfate or organic carbon cool the atmosphere. On the other hand, black carbon particles warm it, because they absorb visible light and convert it into thermal energy (IPCC, 2000). This strange balance increases the uncertainty of the magnitude of their effects on the atmosphere.

### **5.1. Direct effects of particles processed by clouds**

The cloud process and modify particles size and composition. Larger particles scatter more sunlight and increase the extinction of light. This impact on the radiative balance can be estimated with the optical depth, since the extinction of particles is expressed:

$$
\pi(\lambda) = \int\_0^\infty \sigma\_e(\lambda, \mathbf{z}) d\mathbf{z} \tag{3}
$$

Where τ is the optical thickness and σe is the particle's extinction coefficient. In our case, we assume that the particle's composition is mainly sodium chloride (sea salt) and sulfates. The particle does not absorb visible light, so its extinction and dispersion coefficients are equal. Thus, the above equation becomes:

$$\mathbf{\dot{\pi}} = \sum\_{\mathbf{n}=30}^{4200} \mathbf{\sigma}\_{\mathbf{s}(\mathbf{n})} \Delta \mathbf{z} \tag{4}$$

To calculate the optical depth, we use the size distribution spectra for the following heights: 30, 300, 1000, 2500 and 4200 m on both sides of the cloud, as well as the average between 1000 and 1500 m away from the cloud.

Table 3 shows the optical depth on both sides of the cloud (upwind and downwind) and data away from the cloud that are used as reference atmosphere without the influence of processed particles. The values are higher near than far away from the cloud. Figure 10 shows the optical depth near and far from the cloud. The particle optical depth near the cloud is 10 times higher than distant to the cloud. System 7 has a ratio about 1:1 indicating that the physical and optical properties of particles near and far from the cloud do not exhibit noticeable differences. The data suggest that particles near to the cloud in system 7 have not been yet processed or it could be a very young cloud with no mixing with ambient air.

Interaction Between Aerosol Particles and Maritime Convective Clouds:

**5.2. Indirect effects of particles processed by clouds** 

flights. Table 2 summarizes the time, location and type of cloud systems.

Five flights and ten cloud systems were selected for analysis based on a visual evaluation of the records made with the forward- and side-looking video cameras on the aircraft. The criteria was that no other clouds could be seen in 10 km on either side of a cloud line, such that far-cloud samples represent "ambient" aerosols, i.e., lacking any recently processed particles by clouds. Flights were also classified by aerosol type. Figure 11 shows frequency distributions of CN and PCASP measured concentrations at ≤ 300 m for those five days. Flights 9, 12, and 13 were made on days with "maritime" (MR) aerosol background and when winds came from the southwest. "Higher" (HG) aerosols concentrations correspond to flights 7 and 17 with average concentrations significantly higher than the other three

**Figure 11.** The frequency of occurrence of 300 m concentrations measured by the PCASP (top panel)

The cloud albedo depends on the concentration of droplets (Twomey, 1974). One way to estimate, with good approximation, the changes in albedo (A) is using the Meador and

� � ������

Where g is the asymmetry factor, which is the average cosine of scattering angle. For the scattering clouds by sunlight g = 0.85 (Hobbs, 1993), we can simplify the equation 5.3 to:

� � �

�������� (5)

����� (6)

and CN (bottom) are shown here for the five days used in the case studies.

Weaver (1980) equation:

Measurements in ITCZ During the EPIC 2001 Project 241


**Table 3.** Optical depth on both sides of the cloud

**Figure 10.** Optical depths calculated for particle size distributions at 30, 300, 1000, 2500, and 4200 m, near-cloud and far-cloud cases. These optical depths are compared for the ten cases (labeled by their number).

The decrease in the amount of radiation reaching Earth's surface can increase the optical depth, suggesting that cloud particles processed promote a local cooling. Indeed, satellite images of cloud cannot detect the optical depth because it is very large.

## **5.2. Indirect effects of particles processed by clouds**

240 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

be a very young cloud with no mixing with ambient air.

**Table 3.** Optical depth on both sides of the cloud

number).

Table 3 shows the optical depth on both sides of the cloud (upwind and downwind) and data away from the cloud that are used as reference atmosphere without the influence of processed particles. The values are higher near than far away from the cloud. Figure 10 shows the optical depth near and far from the cloud. The particle optical depth near the cloud is 10 times higher than distant to the cloud. System 7 has a ratio about 1:1 indicating that the physical and optical properties of particles near and far from the cloud do not exhibit noticeable differences. The data suggest that particles near to the cloud in system 7 have not been yet processed or it could

> cloud (U) (D) (far) 1 0.125 0.021 0.027 2 0.158 0.373 0.018 3 0.116 0.124 0.013 4 0.152 0.196 0.017 5 0.192 0.118 0.010 6 0.247 0.316 0.084 7 0.171 0.231 0.211 8 0.272 0.306 0.005 9 0.322 0.355 0.036 10 0.196 0.613 0.041

**Figure 10.** Optical depths calculated for particle size distributions at 30, 300, 1000, 2500, and 4200 m, near-cloud and far-cloud cases. These optical depths are compared for the ten cases (labeled by their

The decrease in the amount of radiation reaching Earth's surface can increase the optical depth, suggesting that cloud particles processed promote a local cooling. Indeed, satellite

images of cloud cannot detect the optical depth because it is very large.

Five flights and ten cloud systems were selected for analysis based on a visual evaluation of the records made with the forward- and side-looking video cameras on the aircraft. The criteria was that no other clouds could be seen in 10 km on either side of a cloud line, such that far-cloud samples represent "ambient" aerosols, i.e., lacking any recently processed particles by clouds. Flights were also classified by aerosol type. Figure 11 shows frequency distributions of CN and PCASP measured concentrations at ≤ 300 m for those five days. Flights 9, 12, and 13 were made on days with "maritime" (MR) aerosol background and when winds came from the southwest. "Higher" (HG) aerosols concentrations correspond to flights 7 and 17 with average concentrations significantly higher than the other three flights. Table 2 summarizes the time, location and type of cloud systems.

**Figure 11.** The frequency of occurrence of 300 m concentrations measured by the PCASP (top panel) and CN (bottom) are shown here for the five days used in the case studies.

The cloud albedo depends on the concentration of droplets (Twomey, 1974). One way to estimate, with good approximation, the changes in albedo (A) is using the Meador and Weaver (1980) equation:

$$\mathbf{A} = \frac{(\mathbf{1} - \mathbf{g})\mathbf{r}}{\mathbf{1} + (\mathbf{1} - \mathbf{g})\mathbf{r}} \tag{5}$$

Where g is the asymmetry factor, which is the average cosine of scattering angle. For the scattering clouds by sunlight g = 0.85 (Hobbs, 1993), we can simplify the equation 5.3 to:

$$\mathbf{A} = \frac{\pi}{\mathbf{r} + \mathbf{6.7}} \tag{6}$$

The cloud optical depth (τ) of h that contains a concentration of droplets n (r), with radius r is given by:

$$
\pi = \pi \hbar \int\_0^\infty \mathcal{Q}\_\mathbf{e} \mathbf{r}^2 \mathbf{n}(\mathbf{r}) d\mathbf{r} \tag{7}
$$

Interaction Between Aerosol Particles and Maritime Convective Clouds:

The physical and optical properties analysis of atmospheric particles is focused on the observation of several processes involved in convective clouds and their environment. We have studied cloud systems on Mexico's Pacific ITCZ. The research flights were conducted during September and October 2001. The data obtained point to some relevant cases marked by the weather and cloud characteristics. The analysis and evaluation of information allows

We identify the most important interaction processes between particles and clouds, which can cause changes in the size and composition of atmospheric particles: a) diluting the concentration of particles with minimal changes in size, b) increasing atmospheric concentration of submicron particles (≤ 1 μm), c) increasing the concentration of atmospheric supermicron particles (> 1 μm) d) removal of supermicron particles. The analysis of particles and clouds interaction shows that the most common contact mechanisms were: a) vertical transportation with mixing and dilution, which occurred in 44% of the MR days and 55% on HG episodes b) oxidation of aqueous phase particles are present in 20% and 24% days MR and HG events, respectively, c) coalescence of droplets occurred in 18% and 15% days MR

The particles change their optical properties and the way they interact with solar radiation and clouds. Particles that are processed in the vicinity of the cloud increase the optical depth. The growth comes in quantities up to 10 times larger than the value recorded in distant particles. Therefore, variations in the optical properties of particles affect directly the

The cloud observations were classified into two categories: typical values of maritime areas with prevailing westerly winds and low concentrations of cloud condensation nuclei (conc. < 500 particles per cm3) and values influenced by anthropogenic pollution (conc. < 1800

Increasing the concentration of particles in a place influenced by a pollution source also enlarged the number of CCN. Data analysis shows a good correlation between the concentration of CCN at cloud base and the concentration of droplets inside the cloud (r2 = 0.92), which explains the clouds albedo augmentation on days with influenced by

Future work considers the application of detailed microphysics models to evaluate the different processes of interaction of particles and clouds. Thus, also intends to use these models to analyze the effect of these particles processed in the dynamics of the cloud as well

*ESIME U. Ticomán, Instituto Politécnico Nacional, Gustavo A. Madero, Mexico City, Mexico* 

**6. Conclusions** 

and HG, respectively.

particles/cm3).

anthropogenic pollution.

**Author details** 

J.C. Jiménez-Escalona

as the influence on processes like rain.

us to reach the following conclusions.

radiative balance and influence in local climate.

Measurements in ITCZ During the EPIC 2001 Project 243

Where Qe is the extinction efficiency factor for the wavelengths of visible radiation (λ = 400 – 700 nm).

We calculated the single scattering albedo employing equations 5.4 and 5.5 for each concentration of drops at 6000 m, using a layer of cloud thickness h = 100 m, based on the distance of a datum to another along the horizontal axis (data per second). The 6000 m level is considered the top of the ice-free clouds. Previous figure shows the histograms of the single scattering albedo calculated inside the cloud for different environmental conditions. The albedo on HG episodes ranged between 0.8 – 0.9, while in MR days ranged between 0.6 – 0.8. The results agree with those obtained theoretically by Lohmann et al (2000) stating that anthropogenic pollution causes a diminution in the effective radius of cloud droplets and an increase in the albedo of the cloud.

There is a relationship between the maximum concentrations registered by both FSSP100 and PCASP, indicating a higher concentration of cloud droplets in the episodes with anthropogenic influence and resulting in a diminution in droplet size, because a bigger amount of CCN compete for moisture in the air. Last figure shows the different droplets average diameters in pollution-free days (~14 microns) and polluted days (~10 microns).

Analysis shows the indirect effect of the particles in the formation of convective clouds. During episodes of anthropogenic contamination, the concentration of droplets in the cloud increases and their size decrease, thus causing low rainfall. These phenomena will increase the albedo of the cloud, because it depends on the concentration of drops (Twomy, 1974).

Table 4 shows the values of optical depth (τ) and albedo (A) of the clouds studied. The highest values of albedo were presented in systems 1 and 9, corresponding to days with pollution.


**Table 4.** Optical depth (τ) and albedo (A) of clouds studied
