The aerosol indirect effect on cloud microphysical and radiative properties
is one of the largest uncertainties in climate simulations. In order to
investigate the aerosol–cloud interactions, a total of 16 low-level stratus
cloud cases under daytime coupled boundary-layer conditions are selected
over the southern Great Plains (SGP) region of the United States. The
physicochemical properties of aerosols and their impacts on cloud
microphysical properties are examined using data collected from the
Department of Energy Atmospheric Radiation Measurement (ARM) facility at the SGP site. The aerosol–cloud interaction index (
Clouds play a critical role in the Earth's climate by acting as the dominant modulator of radiative transfer in the atmosphere and have substantial impacts on the global climate. The radiative effect of clouds contributes to one of the largest uncertainties in climate modeling (IPCC, 2013) and has been well known to be influenced by aerosol loading. An increase in aerosol concentration can lead to the enhancement of cloud-droplet number concentration (
The magnitude and sensitivity of ACIs in low-level clouds have been investigated by numerous studies, using various observational datasets such as ground-based measurements (Garrett et al., 2004; Feingold et al., 2006; Kim et al., 2008; McComiskey et al., 2009; Wang et al., 2013a, 2018a), satellite retrieved products (Sekiguchi et al., 2003; Su et al., 2010), and airborne in situ measurements (Twohy et al., 2013; Painemal and Zuidema, 2013; Zhao et al., 2018). However, large variations exist among various assessments because of intrinsic instrument uncertainty, differing analysis methods, and, more physically, the inherent variation in aerosol properties. The physical mechanism underlying the aerosol effect on clouds is that aerosols activate as cloud condensation nuclei (CCN) and then influence the cloud microphysical features. The efficacy of the activation of aerosol has been widely known to be influenced by aerosol size distribution and chemical composition, which are the primary sources of uncertainty in assessing ACI (Dusek et al., 2006; McFiggans et al., 2006; Liu and Li, 2014; Che et al., 2016).
Previous studies have suggested that the composition of aerosols can be inferred by their optical properties such as aerosol optical depth, single-scattering albedo, and the Ångström exponent (Clarke et al., 2004, 2007; Bergstrom et al., 2007; Russell et al., 2010; Cazorla et al., 2013; Cappa et al., 2016). For instance, fine-mode carbonaceous particles (e.g., black and organic carbon) have strong light-absorbing abilities in the ultraviolet and visible spectra (Logan et al., 2013). Urban pollution aerosols associated with sulfate and nitrate particles are considered to be weakly absorbing aerosols (Eck et al., 1999, 2005; Bergstrom et al., 2007; Mian Chin et al., 2009). Although studies have been done to classify aerosol types using the absorption Ångström exponent, which is associated with the absorptive spectral dependence of particles, the measurements of this parameter typically carry large uncertainty and can provide limited information when there are mixtures of different aerosol species that share similar spectral dependences (Bergstrom et al., 2007; Lack and Cappa, 2010). Alternatively, the single-scattering albedo (SSA) and co-albedo (1-SSA) can be used to better separate the aerosol types because they focus on the relative absorbing ability of aerosols at specific wavelengths (Logan et al., 2013; Tian et al., 2017). Given the wide availability of aerosol optical property measurements, the feasibility of inferring aerosol species from their optical properties is useful particularly in areas with no direct measurements of aerosol chemical composition (Logan et al., 2013; Schmeisser et al., 2017).
The Atmospheric Radiation Measurement (ARM) program initiated by the US Department of Energy (DOE) aims to improve the parameterization of clouds in global climate models (Stokes and Schwartz, 1994). Thus far, the ARM program has established over 20 years of long-term ground-based measurements of cloud properties and surface-measured aerosol properties at the southern Great Plains (SGP) site, which represents typical continental conditions (Ackerman and Stokes, 2003; Dong et al., 2005). The size and composition of aerosols have been found to have a considerable seasonal and regional dependence, and their impacts on clouds also vary with different aerosol regimes (Sorooshian et al., 2010; Logan et al., 2018). The prevailing fine-mode aerosols at the ARM SGP site typically contain organic and black carbon associated with biomass burning and inorganic aerosols composed of sulfate and nitrate species (Parworth et al., 2015; Logan et al., 2018). The differences in intrinsic hygroscopicity among those aerosol species play various roles in aerosol activation processes and consequently lead to various interactions with clouds. Thus, it is necessary to investigate the aerosol and cloud properties as well as the magnitude of the ACI index at the ARM SGP site in order to (a) enhance the understanding of the ACI and (b) reduce the uncertainty in quantifying the ACI and associated radiative effects when modeling aerosol influences on low-level continental clouds.
In this study, the aerosol and cloud properties at the ARM SGP site from 16 selected non-precipitating low-level stratiform cloud cases during the 2007–2012 period are examined. Details of the observational measurement platforms and methods are introduced in Sect. 2. The development and analysis of the ACI for the 16 selected cases, the aerosol activation and cloud microphysical responses, and consequent cloud radiative effects under different aerosol absorptive regimes are investigated in Sect. 3. Lastly, a summary of our findings and future work is presented in Sect. 4.
The cloud boundaries at the ARM SGP site were primarily determined by the
ARM Active Remotely-Sensed Cloud Locations (ARSCL) product, which is a
combination of data detected by multiple active remote-sensing instruments,
in particular, the millimeter-wavelength cloud radar (MMCR). The MMCR
operates at a frequency of 35 GHz (and wavelength of 8.7 mm) with a zenith-pointing beamwidth of 0.2
The cloud radar is sensitive to the sixth moment of droplet size distribution and can be contaminated by insects below the cloud base (Dong et al., 2006). The laser ceilometer measurement, which is sensitive to the second moment, is used to provide an accurate cloud base estimation. The uncertainty of cloud base height is around 10 m (Morris, 2016). Hence, the lidar–radar pair provides the most precise determination of cloud boundaries from a point-based perspective, with combined uncertainties of cloud thickness for MMCR and KAZR periods being 55 and 40 m, respectively. Note that this will not cause a significant difference in determining the cloud boundaries between these two radar periods. In this study, the cloud base and top heights were averaged into 5 min bins, where the low-level stratus cloud is defined as a cloud-top height lower than 3 km with no overlying cloud layer (Xi et al., 2010).
The cloud liquid water path (LWP), defined as the column-integrated cloud
liquid water, was retrieved based on the measured brightness temperatures
from the microwave radiometer (MWR) at 23.8 and 31.4 GHz, using the
statistical method described in Liljegren et al. (2001). The uncertainty of
LWP retrieval is 20 g m
For microphysical properties of low-level stratus, following the methods
developed by Dong et al. (1998), the daytime layer-mean cloud-droplet
effective radius (
Surface aerosol properties were collected from the aerosol observing system
(AOS), a platform consisting of an array of instruments to monitor real-time
aerosol information. The total condensation nuclei number concentration
(
The optical particle counter developed by Droplet Measurement Technologies
is used to measure the CCN number concentration (
Given the fact that the aerosol properties were measured at the surface,
there is a question of whether surface aerosols can be linked to what
actually happens in clouds aloft. This study adopts the method presented in
Dong et al. (2015), which sorts the boundary-layer condition into two
categories: coupled and decoupled. The vertical sounding profiles at a 1 min
temporal resolution were collected from the ARM Merged Sounding product, with
a vertical resolution of 20 m below 3 km (Mace et al., 2006; Troyan, 2012).
The vertical profiles of liquid water potential temperature (
Vertical profiles of liquid water potential temperature (
A study that was conducted by Delle Monache et al. (2004) used in situ aerosol
measurements from 59 flights from March 2000 to March 2001 to compare with
the surface aerosol measurements. Their results showed that the daytime layer-mean aerosol
extensive properties such as the total extinction by particles measured
within the well-mixed boundary layer were well-correlated with surface measurements (
The lower-tropospheric stability (LTS), which is defined as the potential
temperature difference between the surface and 700 hPa, is used to represent
the large-scale thermodynamic condition. The LTS is obtained from the ECMWF
model output, which specifically provides for analysis at the ARM SGP site.
The value is obtained by averaging over a grid box of
The surface-measured broadband downwelling shortwave (SW) radiation fluxes
and estimated clear-sky SW fluxes were collected from radiative flux
analysis value-added products (Long and Ackerman, 2000; Long and Turner,
2008), with an uncertainty of 10 W m
As previously discussed, the selection of cloud cases is limited by the
following criteria: non-precipitating and cloud-top height less than 3 km
with a lifetime of more than 3 h under the limitation of 20 g m
Dates and time periods of selected low-level stratus cloud cases
and their air mass source
The probability density functions (PDFs) of aerosol and cloud properties from all 16 cases are shown in Fig. 2; note that the distributions include each of the 5 min data points. For the aerosol properties shown in Fig. 2a–d, the Ångström exponent (AE) was calculated based on the nephelometer-aerosol
extensive properties observed spectral scattering coefficient (
Probability distribution functions (PDFs), mean and median values of low-level stratus cloud, and aerosol properties for all cases:
The variation in aerosol single-scattering albedo (SSA) suggests different
roles of the fine-mode aerosol absorptive properties that influence total
light extinction, which in turn is a result of different aerosol species in
the plume. This is further explained in Sect. 3.3. The distributions of
To examine the microphysical response of cloud to aerosol loading, the
quantitative ACI term can be expressed as
As suggested by previous studies, the
Previous studies have focused on the aerosol–cloud interaction in
stratocumulus clouds at the ARM SGP site. Based on the analysis of seven
selected stratocumulus cases during the period 1998–2000, Feingold et al. (2003) reported the first ground-based measured
In order to better understand the aerosol particle activation process in
typical continental low-level stratus clouds, the ratios between
The measured absorptive properties of aerosols can aid in inferring the general information of different aerosol species, since different types of aerosols can demonstrate different absorptive behaviors at certain wavelengths. Aerosol plumes dominated by organic carbonaceous particles tend to represent strong absorptive capabilities in the visible spectrum but weakly absorb in the near-infrared spectrum (Dubovik et al., 2002; Lewis et al., 2008), while black carbon particles (e.g., soot) absorb across the entire solar spectrum with a weak dependence on wavelength (Schuster et al., 2005; Lack and Cappa, 2010). However, when the aerosol plume is dominated by anthropogenic inorganic pollution, the absorbing ability becomes even weaker (Clarke et al., 2007), partly due to sulfate chemical species (Mian Chin et al., 2009). Therefore, the general existence of carbonaceous and pollution particles can be inferred via absorptive properties.
In this study, we adopt the classification method involving the AE and the ratio
of the aerosol absorption coefficient to the total extinction coefficient or single-scattering co-albedo, (
Ångström exponent (AE
Within the 693 selected samples, 360 data points are classified in the weakly absorptive aerosol regime, while the remaining data points are in the strongly absorptive aerosol regime. It is interesting to note that the majority of the winter cases are dominated by weakly absorbing aerosols, while most of the spring cases exhibit a strongly absorbing aerosol dominance, which suggests that the aerosol plumes over the SGP site also have a seasonal dependence. In spring, owing to the upper-level ridge centered over the western Atlantic, the SGP is located at the northwestern edge of the sub-tropical high. Under this synoptic pattern, the SGP is under the influence of relatively frequent southerly transport of the air masses from Central America, which is characterized by strongly absorbing carbonaceous aerosols produced from biomass burning, as well as the moisture transported from the Gulf of Mexico. During the winter, the SGP site experiences the transported air masses from higher latitudes, with less intrusion of air masses from the south (Andrews et al., 2011; Parworth et al., 2015; Logan et al., 2018).
Figure 5a–c show the PDFs of total
Aerosol and cloud properties under the strongly absorptive (in red) and the weakly absorptive (in blue) aerosol regimes. PDFs, mean values, and standard deviations of
The measured
Relationship between
Although it is generally considered that the role of aerosol particle size distribution is more important than the chemical component in terms of becoming CCN (Seinfeld and Pandis, 2012; Dusek et al., 2006), many studies have found that aerosol chemical composition can also have a non-negligible impact on the aerosol activating ability under polluted and low-supersaturation conditions (Rose et al., 2011; Che et al., 2016). According to Köhler theory, the critical level of supersaturation for aerosol activation depends on the aerosol solubility, which decreases with increasing soluble particle number concentration. Hence, the role of aerosol chemical composition is more important at lower supersaturation and diminishes with increasing supersaturation levels (Zhang et al., 2012).
As discussed in Sect. 3.3.1, both weakly and strongly absorptive regimes are linked to aerosol plumes that are dominated by pollution and carbonaceous aerosols, respectively. Therefore, the difference in the ability of aerosol activation between the two regimes can be explained by the different hygroscopicity factors of the particle types. For example, anthropogenic pollution is associated with inorganic particles that are highly hygroscopic and have great ability in taking up water (Hersey et al., 2009; Massling et al., 2009; Liu et al., 2014), while carbonaceous species (e.g., black and organic carbon) exhibit varying degrees of hygroscopicity, with species dominated by hydrophobic soot and black carbon being the least hygroscopic (Shinozuka et al., 2009; Rose et al., 2010). Thus, for the given amount of aerosol loading, aerosols in the weakly absorptive regime can better attract water vapor molecules and result in more aerosol particles activating as CCN.
As shown in Fig. 6, for three
Due to the lack of detailed chemical observations for all the cloud sample
periods, as well as the uncertainties among aerosol optical and
microphysical properties induced by aerosol transformation processes such as
aging and mixing (Wang et al., 2010, 2018b), the bulk activation ratios revealed from this study cannot be significantly distinguished from each other. However, the effect of different aerosol species inferred by the absorptive properties with respect to aerosol activation is evident, especially at the 0.2 % supersaturation level. Furthermore, in the following section, the values of
In order to better understand the role of aerosol activation ability in the
microphysical process from aerosol to CCN and then to cloud droplets,
comparisons must be considered under similar available moisture conditions
due to the discrepancy in the LWP between the two regimes. Accordingly, the
sorted
Taking the variation in
As for the process from CCN to cloud droplets, a similar assessment is
presented in Fig. 7b, which illustrates the
The overall differences in CCN conversion fractions are likely a result of
the combined effects of meteorological factors and the aerosol heating effect on
the cloud environment. To examine the meteorological influence on CCN
conversion, the LTS parameter is used to investigate the difference in the
large-scale thermodynamic condition. By sorting the LTS by the LWP for the two
absorptive regimes, the LWP dependence on LTS can be ruled out, which can
provide a better understanding of the potential role of LTS in cloud-droplet
development. For each given LWP bin, the weakly absorptive regime has higher
LTS values than the strongly absorptive regime (figure not shown). The LTS
is largely impacted by the potential temperature difference throughout the
mixed layer. If a strong capping boundary-layer temperature inversion is
present, it will result in high LTS values and, in turn, a well-mixed
boundary layer (Wood and Bretherton, 2006). Such results indicate that even under
similar available moisture conditions, the more sufficient turbulence can
transport the below-cloud moisture as well as the CCN that activated from
weakly absorbing aerosols into the cloud more efficiently, contributing to a
higher ratio of
In addition, the vertical velocity in pressure coordinate (
Furthermore, the heating effect of light-absorbing aerosols on the cloud
environment cannot be neglected. Strongly light-absorbing aerosols can
absorb solar radiation and heat the in-cloud atmosphere by emission, which
results in the reduction of relative humidity (or supersaturation) in the
cloud layer (Bond et al., 2013; Wang et al., 2013b). This effect is evident
in the observation, as the values of in-cloud relative humidity in the
strongly absorptive regime are slightly lower than those in the weakly
absorptive regime. Additionally, this aerosol heating effect disrupts the
boundary-layer temperature structure by enhanced warming aloft and,
consequently, inhibits the vertical transport of sensible and latent heat
between surface and cloud layer. The impacts of light-absorbing aerosol on
cloud-scale thermodynamics and the dynamics state might eventually dampen the
conversion process from CCN to cloud droplets. Unfortunately, due to the lack
of measurement of cloud-base vertical velocity throughout the studying
period, this competing effect of cloud thermodynamic and dynamic cannot be
fully untangled from the aerosol effect given the currently available
dataset. The differences in
In the previous section, we examined the activation ratios of aerosol to CCN
and then from CCN to cloud droplets between the two regimes as well as their
dependencies on the LWP, which eventually led to the cloud-droplet variation for
a given LWP range. Figure 7c and d demonstrate that
The combination of cloud thermodynamic, dynamic, and light-absorbing aerosol heating effects impact the conversion process from CCN to cloud droplets. Under a given moisture availability, a higher number of CCN in the weakly absorptive regime can be converted to cloud droplets. This results in higher number concentrations of smaller cloud droplets, while the dampened CCN conversion process in the strongly absorptive regime leads to fewer and larger cloud droplets at a fixed LWP.
To examine the sensitivity of clouds to both weakly and strongly absorbing
aerosol loading, the relationships between cloud
Based on the sensitivity study, the 10 % change of the cloud LWP and downward
SW at the surface would result in the 10 % uncertainty in
Note that the LTS values from the weakly absorptive regime (22.91 and
19.78 K) are higher than those from the strongly absorptive regime (21.72 and 17.83 K) for the selected two LWP bins. As discussed in the previous
section, owing to the stronger temperature inversion indicated by the higher
LTS values, low clouds are more closely connected to weakly absorbing
aerosols and moisture below cloud by sufficient turbulence. In order to
quantify the impact of LTS on
Furthermore, with the presence of strongly light-absorbing aerosols, the
cloud-layer heating induced by the aerosol absorptive effect can result in
the reduction of in-cloud supersaturation and leads to the damping of cloud
microphysical sensitivity to strongly absorbing aerosols. A previous
modeling study conducted at the ARM SGP site by Lin et al. (2016) estimated
the shortwave heating rates in cloud layers by contrasting the simulations
with and without light-absorbing aerosols. The inclusion of light-absorbing
aerosols was represented by an internal aerosol mixture with a mass
combination of 95 % ammonium sulfate and 5 % black carbon. The SSA of
this mixture is calculated to be roughly 0.9, as documented in the previous
study of Wang et al. (2014). The different values of SSA used in their study
(0.9 for light-absorbing and 1.0 for non-absorbing) are comparable to this
study (0.89 for strongly absorbing and 0.97 for weakly absorbing). The
induced increments in cloud-layer shortwave heating rates have a maximum
value of 3 K d
Aerosols with different absorptive properties can alter the ability of
clouds to reflect incoming shortwave radiation. Accordingly, cloud radiative
effects on shortwave radiation for the two absorptive regimes are
investigated. Both cloudy and clear-sky downwelling shortwave fluxes for
samples in the weakly absorptive regimes are generally higher than those in
the strongly absorptive regime (not shown in here), largely owing to the
discrepancies in solar zenith angle, seasonal variation in insolation, and
surface albedo. Therefore, to ensure that the comparison is under minimum
influence of non-cloud factors, the shortwave relative cloud radiative
effects (rCREs) are introduced and their dependencies on the LWP between the two
regimes are examined. With all else being equal, as shown in Fig. 9, rCREs
in both regimes noticeably increase with the LWP, especially for LWPs less than
150 g m
Relative cloud radiative effect (rCRE) as a function of liquid water path (LWP) under the strongly absorptive (in red) and weakly absorptive (in blue) aerosol regimes. Whiskers denote 1 standard deviation for each bin.
A total of 16 non-precipitating overcast low-level stratiform cloud cases under daytime coupled boundary-layer conditions were selected in order to investigate the sensitivity of cloud microphysical properties to aerosol physicochemical properties. The Ångström exponent and fine-mode fraction distributions indicate that the aerosol plumes that advected to the SGP site during all the selected cases were dominated by fine-mode
particles, while the variation in aerosol single-scattering albedo suggests different characteristics of optical properties among the aerosol plumes. In
terms of the sensitivity of cloud droplets to aerosol number concentration,
the values of
The analysis of the
The ratios of
Under low-LWP conditions, the measured
DOE ARM's Data Discovery at
The original idea of this study was discussed by XZ, BX, and XD. XZ performed the analyses and wrote the paper. XD, TL, YW, and PW participated in further scientific discussion and provided substantial comments on and edits to the paper.
The authors declare that they have no conflict of interest.
The ground-based measurements were obtained from the Atmospheric Radiation Measurement (ARM) Program sponsored by the US Department of Energy (DOE) Office of Energy Research, Office of Health and Environmental Research, and Environmental Sciences Division. The reanalysis data were obtained from the ECMWF model output, which specifically provides analysis at the ARM SGP site. The data can be accessed from
This research has been supported by the National Science Foundation (grant nos. AGS-1700728, AGS-1700796 and AGS-1700727).
This paper was edited by Graham Feingold and reviewed by two anonymous referees.