Indications of a Decrease in the Depth of Deep Convective Cores with Increasing Aerosol Concentration During the CACTI Campaign

An aerosol indirect effect on deep convective cores (DCCs), by which increasing aerosol concentration increases cloud-top height via enhanced latent heating and updraft velocity, has been proposed in many studies. However, the magnitude of this effect remains uncertain due to aerosol measurement limitations, modulation of the effect by meteorological conditions, and difficulties untangling meteorological and aerosol effects on DCCs. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in 2018-19 produced concentrated aerosol and cloud observations in a location with frequent DCCs, providing an opportunity to examine the proposed aerosol indirect effect on DCC depth in a rigorous and robust manner. For periods throughout the campaign with well mixed boundary layers, we analyze relationships that exist between aerosol variables (condensation nuclei concentration >10 nm, 0.4% cloud condensation nuclei concentration, 55-1000 nm aerosol concentration, and aerosol optical depth) and meteorological variables [level of neutral buoyancy (LNB), convective available potential energy, mid-level relative humidity, and deep layer vertical wind shear] with the maximum radar echo top height and cloud-top temperature (CTT) of DCCs. Meteorological variables such as LNB and deep-layer shear are strongly correlated with DCC depth. LNB is also highly correlated with three of the aerosol variables. After accounting for meteorological correlations, increasing values of the aerosol variables (with the exception of one formulation of AOD) are generally correlated at a statistically significant level with a warmer CTT of DCCs. Therefore, for the study region and period considered, increasing aerosol concentration is mostly associated with a decrease in DCC depth.

Impact of dry intrusion events on the composition and mixing state of particles during the winter Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA)

Long-range transport of continental emissions has a far-reaching influence over remote regions, resulting in substantial change in the size, morphology, and composition of the local aerosol population and cloud condensation nuclei (CCN) budget. Here, we investigate the physicochemical properties of atmospheric particles collected on board a research aircraft flown over the Azores during the winter 2018 Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) campaign. Particles were collected within the marine boundary layer (MBL) and free troposphere (FT) after long-range atmospheric transport episodes facilitated by dry intrusion (DI) events. Chemical and physical properties of individual particles were investigated using complementary capabilities of computer-controlled scanning electron microscopy and X-ray spectromicroscopy to probe particle external and internal mixing state characteristics. Furthermore, real-time measurements of aerosol size distribution, cloud condensation nuclei (CCN) concentration, and back-trajectory calculations were utilized to help bring into context the findings from offline spectromicroscopy analysis. While carbonaceous particles were found to be the dominant particle type in the region, changes in the percent contribution of organics across the particle population (i.e., external mixing) shifted from 68 % to 43 % in the MBL and from 92 % to 46 % in FT samples during DI events. This change in carbonaceous contribution is counterbalanced by the increase in inorganics from 32 % to 57 % in the MBL and 8 % to 55 % in FT. The quantification of the organic volume fraction (OVF) of individual particles derived from X-ray spectromicroscopy, which relates to the multi-component internal composition of individual particles, showed a factor of 2.06 ± 0.16 and 1.11 ± 0.04 increase in the MBL and FT, respectively, among DI samples. We show that supplying particle OVF into the κ-Köhler equation can be used as a good approximation of field-measured in situ CCN concentrations. We also report changes in the κ values in the MBL from κMBL, non-DI=0.48 to κMBL, DI=0.41, while changes in the FT result in κFT, non-DI=0.36 to κFT, DI=0.33, which is consistent with enhancements in OVF followed by the DI episodes. Our observations suggest that entrainment of particles from long-range continental sources alters the mixing state population and CCN properties of aerosol in the region. The work presented here provides field observation data that can inform atmospheric models that simulate sources and particle composition in the eastern North Atlantic.

Long- and Short-Term Temporal Variability in Cloud Condensation Nuclei Spectra in the Southern Great Plains

When aerosol particles seed formation of liquid water droplets in the atmosphere, they are called cloud condensation nuclei (CCN). Different aerosols will act as CCN under different degrees of water supersaturation (relative humidity above 100 %) depending on their size and composition. In this work we build and analyze a best-estimate CCN spectrum product, tabulated at ~45 min resolution, generated using high quality data from eight independent instruments at the US Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The data product spans a large supersaturation range, from 0.0001 to ~30 %, and time period, 5 years from 2009–2013 and is available on the ARM data archive. We leverage this added statistical power to examine relationships that are unclear in smaller datasets. Probability distributions of many aerosol and CCN metrics are found to exhibit skewed log-normal distribution shapes. Clustering analyses of CCN spectra reveal that the primary drivers of CCN differences are aerosol number size distributions, rather than hygroscopicity or composition, especially at supersaturations above 0.2 %, while also allowing for simplified understanding of seasonal and diurnal variations in CCN behaviour. The predictive ability of using limited hygroscopicity data with accurate number size distributions to estimate CCN spectra is investigated and uncertainties of this approach are estimated. Finally, the dynamics of CCN spectral clusters and concentrations are examined with cross-correlation and autocorrelation analyses, which assist in determining the time scales of changing CCN concentrations at different supersaturations and are important for cloud modelling studies.

Estimating cloud condensation nuclei concentrations from CALIPSO lidar measurements

We present a novel methodology to estimate cloud condensation nuclei (CCN) concentrations from spaceborne CALIPSO lidar measurements. The algorithm utilizes (i) the CALIPSO-derived backscatter and extinction coefficient, depolarization ratio, and aerosol subtype information, (ii) the normalized volume size distributions and refractive indices from the CALIPSO aerosol model, and (iii) the MOPSMAP optical modelling package. For each CALIPSO height bin, we first select the aerosol-type specific size distribution and then adjust it to reproduce the extinction coefficient derived from the CALIPSO retrieval. The scaled size distribution is integrated to estimate the aerosol number concentration which is then used in the CCN parameterizations to calculate CCN concentrations at different supersaturations. To account for the hygroscopicity of continental and marine aerosols, we use the kappa parameterization and correct the size distributions before the scaling step. We have studied the sensitivity of the thus derived CCN concentration to the effect of variations of the initial size distributions. It is found that the uncertainty associated with the algorithm can range between a factor of 2 and 3. We have also compared our results with the POLIPHON and found comparable results for extinction coefficients larger than 0.05 km−1. An initial application to a case with coincident airborne in-situ measurements for independent validation shows promising results and illustrates the potential of CALIPSO for constructing a global height-resolved CCN climatology.

Rapid cloud removal of dimethyl sulfide oxidation products limits SO2 and cloud condensation nuclei production in the marine atmosphere

Oceans emit large quantities of dimethyl sulfide (DMS) to the marine atmosphere. The oxidation of DMS leads to the formation and growth of cloud condensation nuclei (CCN) with consequent effects on Earth’s radiation balance and climate. The quantitative assessment of the impact of DMS emissions on CCN concentrations necessitates a detailed description of the oxidation of DMS in the presence of existing aerosol particles and clouds. In the unpolluted marine atmosphere, DMS is efficiently oxidized to hydroperoxymethyl thioformate (HPMTF), a stable intermediate in the chemical trajectory toward sulfur dioxide (SO2) and ultimately sulfate aerosol. Using direct airborne flux measurements, we demonstrate that the irreversible loss of HPMTF to clouds in the marine boundary layer determines the HPMTF lifetime (τHPMTF < 2 h) and terminates DMS oxidation to SO2. When accounting for HPMTF cloud loss in a global chemical transport model, we show that SO2 production from DMS is reduced by 35% globally and near-surface (0 to 3 km) SO2 concentrations over the ocean are lowered by 24%. This large, previously unconsidered loss process for volatile sulfur accelerates the timescale for the conversion of DMS to sulfate while limiting new particle formation in the marine atmosphere and changing the dynamics of aerosol growth. This loss process potentially reduces the spatial scale over which DMS emissions contribute to aerosol production and growth and weakens the link between DMS emission and marine CCN production with subsequent implications for cloud formation, radiative forcing, and climate.

Aerodynamic size-resolved composition and cloud condensation nuclei properties of aerosols in Beijing suburban region

The size-resolved physiochemical properties of aerosols determine their atmospheric lifetime, cloud interactions, and the deposition rate on human respiratory system, however most atmospheric composition studies tend to evaluate these properties in bulk. This study investigated size-resolved constituents of aerosols on mass and number basis, and their droplet activation properties, by coupling a suite of online measurements with an aerosol aerodynamic classifier (AAC) based on aerodynamic diameter (Da) in Pinggu, a suburb of Beijing. While organic matter accounted for a large fraction of mass, a higher contribution of particulate nitrate at larger sizes (Da > 300 nm) was found under polluted cases. By applying the mixing state of refractory black carbon containing particles (rBCc) and composition-dependent densities, aerosols including rBCc were confirmed nearly spherical at Da > 300 nm. Importantly, the number fraction of rBCc was found to increase with Da at all pollution levels. The number fraction of rBC is found to increase from ~3 % at ~90 nm to ~15 % at ~1000 nm, and this increasing rBC number fraction may be caused by the coagulation during atmospheric aging. The droplet activation diameter at a water supersaturation of 0.2 % was 112 ± 6 nm and 193 ± 41 nm for all particles with Da smaller than 1 μm (PM1) and rBCc respectively. As high as 52 ± 6 % of rBCc and 50 ± 4 % of all PM1 particles in number could be activated under heavy pollution due to enlarged particle size, which could be predicted by applying the volume-mixing of substance hygroscopicity within rBCc. As rBCc contributes to the quantity of aerosols at larger particle size, these thickly coated rBC may contribute to the radiation absorption significantly or act as an important source of cloud condensation nuclei (CCN). This size regime may also exert important health effects due to their higher deposition rate.