Cloud Condensation Nuclei Concentrations Research Articles

Simulations of the impact of cloud condensation nuclei and ice-nucleating particles perturbations on the microphysics and radar reflectivity factor of stratiform mixed-phase clouds

Abstract. In this research, we delve into the influence of cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations on the morphology and abundance of ice particles in mixed-phase clouds, emphasizing the consequential impact of ice particle shape, number, and size on cloud dynamics and microphysics. Leveraging the synergy of the Advanced Microphysics Prediction System (AMPS) and the Kinematic Driver (KiD) model, we conducted simulations to capture cloud microphysics across diverse CCN and INP concentrations. The Passive and Active Microwave radiative TRAnsfer (PAMTRA) radar forward simulator further augmented our study, offering insights into how the concentrations of CCN and INPs affect radar reflectivities. Our experimental framework encompassed CCN concentrations ranging from 10 to 5000 cm−3 and INP concentrations from 0.001 to 10 L−1. Central to our findings is the observation that higher INP concentrations yield smaller ice particles, while an increase in CCN concentrations leads to a subtle growth in their dimensions. Consistent with existing literature, our results spotlight oblate-like crystals as dominant between temperatures of −20 and −16 °C. Notably, high-INP scenarios unveiled a significant prevalence of irregular polycrystals. The aspect ratio (AR) of ice particles exhibited a decline with the rise in both CCN and INP concentrations, highlighting the nuanced interrelation between CCN levels and ice particle shape, especially its ramifications on the riming mechanism. The forward-simulated radar reflectivities, spanning from −11.83 dBZ (low INP, 0.001 L−1) to 4.65 dBZ (high INP, 10 L−1), elucidate the complex dynamics between CCN and INPs in determining mixed-phase cloud characteristics. Comparable differences in radar reflectivity were also reported from observational studies of stratiform mixed-phase clouds in contrasting aerosol environments. Our meticulous analysis of KiD-AMPS simulation outputs, coupled with insights into aerosol-driven microphysical changes, thus underscores the significance of this study in refining our ability to understand and interpret observations and climate projections.

Impact of Anthropogenic Aerosol Transport on Cloud Condensation Nuclei Activity During Summertime in Qilian Mountain, in the Northern Tibetan Plateau

AbstractIn this study, we conducted field campaigns at two mountain‐top observatories on the Qilian Mountains (QLM) in the northeastern Tibetan Plateau of China, which plays a vital role in sustaining water resources for the downstream arid and semi‐arid regions. The two observatories, Waliguan Baseline Observatory (WLG) and Laohugou station (LHG), are situated on the eastern and western edge of the QLM, respectively. The objectives of this study were to examine the properties of atmospheric aerosols, CCN concentrations (NCCN) at varying supersaturation levels (SS = 0.2%–1.0%), and the hygroscopic nature of aerosols in the QLM, especially during the formation of orographic cloud. Notably, the average aerosol concentration and NCCN was approximately 2–3 factors higher at WLG compared to LHG. The chemical compositions of aerosols were primarily dominated by sulfate and organic aerosol (OA) at these two sites. A very high hygroscopicity parameter of aerosol calculated using chemical composition was observed at these two sites (0.37 ± 0.03 at LHG vs. 0.30 ± 0.04 at WLG). Enhanced aerosol loading episodes impacted by anthropogenic emission were observed at these two sites. Exploration on high‐loading cases at each site, we found that the CCN activity was dominated by aerosol size, but the chemical processes of aerosol during the formation of orographic cloud could also be important in CCN activity, especially for low SS conditions. These findings collectively underscore the significant impact of anthropogenic air plumes on CCN concentrations in the QLM and their potential influence on precipitation patterns.

Efficient droplet activation of ambient black carbon particles in a suburban environment

Abstract. The cloud condensation nuclei (CCN) activity of black carbon (BC) particles importantly determines their impacts on cloud microphysics and atmospheric lifetime. This process is crucially influenced by the number of hygroscopic coating materials that BC acquire during the ageing process. It remains a challenge for ambient measurements to capture this process and link this with CCN activity of BC. Here, we directly measured the droplet activation diameter (D50) and activation fraction of BC-containing (BCc) particles (Fact,BC) in suburban Beijing using coupled measurements of size-resolved number concentrations of CCN at configured water supersaturation (SS) and BCc particles. The number concentration of BCc particles was found to peak at diameter 180–210 nm after acquiring coatings, larger than that for all particles (50–150 nm). Consequently, the initially smaller BC particles become enlarged and more hygroscopic, thereby exhibiting CCN activities than other particles. The Fact,BC increased from 42 % to 69 % in number and from 67 % to 85 % in mass as SS increased from 0.1 % to 0.2 % but tended to reach a plateau when SS > 0.2 %. Notably, Fact,BC and D50 linearly correlated with equivalent photochemical age, at a rate of +2 % h−1 and −3 nm h−1, respectively. The results suggest BCc particles from anthropogenic sources can readily serve as CCN at a relatively low SS, and more than half of the BC population can be activated within a few hours, indicating that the surface-sourced BC can efficiently incorporate into clouds and potentially exert important indirect radiative impacts.

Quantifying structural errors in cloud condensation nuclei activity from reduced representation of aerosol size distributions

Aerosol effects on clouds and radiation are a large source of uncertainty in our understanding of human impacts on the climate system. Uncertainty in aerosol effects results from uncertainty in parameter values, known as parametric uncertainty, and from uncertainty from the model’s structure, known as structural uncertainty. While previous studies have assessed the impact of parametric uncertainty on modeled forcing, structural errors from the numerical representation of particle distributions and their dynamics have not been well quantified. Here we present a framework for quantifying error in aerosol size distributions and cloud condensation nuclei activity, which we apply to the widely used 4-mode version of the Modal Aerosol Module (MAM4). Box model predictions from the MAM4 are evaluated against the Particle Monte Carlo Model for Simulating Aerosol Interactions and Chemistry (PartMC-MOSAIC), a benchmark model that tracks the evolution of individual particles. We show that size distributions simulated by MAM4 diverge from those simulated by PartMC-MOSAIC after only a few hours of aging by condensation and coagulation in polluted conditions, which leads to large errors in modeled cloud condensation nuclei concentrations. We find that differences between MAM4 and PartMC-MOSAIC are largest under polluted conditions, where the size distribution evolves rapidly though aging. These findings indicate that structural error in modeled aerosol properties is a key factor contributing to uncertainty in aerosol forcing.

Effects of a Vertical Cloud Condensation Nuclei Concentration Explosion in an Idealized Hailstorm Simulation

AbstractDetermination of the key vertical level for cloud condensation nuclei concentration (CCNC) explosions has been a long‐term issue in CCN‐cloud interaction studies. An idealized hailstorm is simulated with 37 sensitivity runs, including an initial CCNC grouping vertically from the ground to the cloud top, increasing from 100 to 3,000 mg−1. The results reveal a key zone from 750 to 800 hPa near the median boundary layer, where an explosion of CCNC plays a dominant role in the nonmonotonic response of the hail precipitation rate. The explosion of CCNC in this zone could initially result in the condensation of more water vapor into the clouds, which could be transported to a greater vertical extent to significantly affect the riming collection efficiency. However, the dominant zone for the total precipitation rate is wider at heights of 700–800 hPa due to the lower sensitivity of the riming collection efficiency.

Observational constraints on the parameterization of particle dry deposition over bare cropland

Dry deposition affects the removal rates and lifetimes of atmospheric particles. Bare cropland, a surface cover type representing cultivated land after harvesting and ploughing, is widespread around the world, but the parameterizations of dry deposition velocity for this land type have not been well constrained. In this study, we integrate existing observational data of particle dry deposition for bare cropland to constrain the corresponding parameterization scheme. Considering that strong disparities exist between the calculated dry deposition velocity from existing parameterizations and the observations, a range of empirical parameters employed are adjusted to best match the model simulations with the observations. The results from the revised parameterization match much more closely with the observations for the different particle sizes than those obtained when using the existing one. As a result, particles smaller than 0.5 μm in diameter exhibit a decrease in dry deposition velocity by roughly one order of magnitude, while that of larger particles increase. Among the processes contributing to the dry deposition, the impaction and interception are dominant for particles with aerodynamic diameters between 0.1 and 10 μm, due to the roughness characteristics and large clod size of bare cropland, in contrast to smooth bare soils. Applying our revised scheme in an atmospheric chemical transport model over the North China Plain leads to a general increase in PM2.5 mass concentrations across the domain, reaching up to 11.2% over the croplands. Particularly, the number concentrations of particle in Aitken and accumulation modes are increased by 12.9% and 16.8%, respectively. The associated increase in cloud condensation nuclei concentrations reaches as high as 39.6%.

High-resolution physicochemical dataset of atmospheric aerosols over the Tibetan Plateau and its surroundings

Abstract. Atmospheric aerosol in the Tibetan Plateau (TP) and its surroundings has attracted significant scientific interest in recent decades due to its notable impacts on regional climatic and cryospheric changes, ecological and environmental security, and the hydrological cycle. However, our understanding of the atmospheric aerosol in this remote region is highly limited by the scarcity of available datasets owing to the extremely harsh natural conditions. This challenge has been mitigated in recent decades by establishing field observatories at typical sites within the TP and its surroundings. A continuous project initiated in 2015 aims to explore the properties and sources of atmospheric aerosols, as well as their regional differences, through multiple short-term intensive observations obtained across this vast region utilizing a suite of high-time-resolution online instruments. This paper presents a systematic and hourly scale dataset of aerosol physicochemical and optical properties at eight sites across the TP and its surroundings that is derived from the project. It includes size-resolved chemical compositions of submicron aerosols, high-resolution mass spectra and sources of organic aerosols, size distributions of particle number concentrations, particle light-scattering and light-absorption coefficients, particle light absorptions attributed to different carbonaceous substances including black carbon and brown carbon, and number concentrations of cloud condensation nuclei. In brief, atmospheric aerosols in these remote sites were all well mixed and highly aged, reflecting their dominant regional transport sources. However, the southern TP region exhibited high contributions of carbonaceous organic aerosols, neutralized bulk submicron aerosols, and a relatively high light-absorption capacity, whereas in the northern TP region, secondary inorganic species were the main contributors to the overall acidic submicron aerosols. Beyond providing insights into the regional differences in aerosol sources and properties across the TP and its surroundings, the datasets will also benefit simulations of aerosol radiative forcing and evaluations of interactions among different Earth system components in numerical models for this region. The datasets are accessible through the National Cryosphere Desert Data Center, Chinese Academy of Sciences (https://doi.org/10.12072/ncdc.NIEER.db2200.2022; Xu, 2022).

Role of Iodine-Assisted Aerosol Particle Formation in Antarctica.

New particle formation via the ion-mediated sulfuric acid and ammonia molecular clustering mechanism remains the most widely observed and experimentally verified pathway. Recent laboratory and molecular level observations indicate iodine-driven nucleation as a potentially important source of new particles, especially in coastal areas. In this study, we assess the role of iodine species in particle formation using the best available molecular thermochemistry data and coupled to a detailed 1-d column model which is run along air mass trajectories over the Southern Ocean and the coast of Antarctica. In the air masses traversing the open ocean, ion-mediated SA-NH3 clustering appears insufficient to explain the observed particle size distribution, wherein the simulated Aitken mode is lacking. Including the iodine-assisted particle formation improves the modeled Aitken mode representation with an increase in the number of freshly formed particles. This implies that more particles survive and grow to Aitken mode sizes via condensation of gaseous precursors and heterogeneous reactions. Under certain meteorological conditions, iodine-assisted particle formation can increase cloud condensation nuclei concentrations by 20%-100%.

CCN activation and droplet growth in Pi chamber simulations with Lagrangian particle-based microphysics

Abstract Numerical simulations of turbulent moist Rayleigh–Bénard convection driving CCN activation and droplet growth in the laboratory Pi chamber are discussed. Supersaturation fluctuations come from isobaric mixing of warm and humid air rising from the lower boundary with colder air featuring lower water vapor concentrations descending from the upper boundary. Lagrangian particle-based microphysics is used to represent growth of haze CCN and cloud droplets with kinetic, solute, and surface tension effects included. Dry CCN spectra in the range between 2 to 200 nm radius from field observations are considered. Increasing the total CCN concentration from pristine to polluted conditions results in the increase of the droplet concentration and reductions of the mean droplet radius and spectral width. These are in agreement with Pi chamber observations and numerical simulations, as well as with numerous past studies of CCN cloud-base activation in natural clouds. The key result is that a relatively small fraction of the available CCN is activated in the Pi chamber fluctuating supersaturations, from about a half in pristine case to only a tenth in the polluted case. The activation fraction as a function of the dry CCN radius is similar in all simulations, close to zero at the CCN small end, increasing to a maximum at CCN radius around 50 nm, and decreasing to close to zero at the large CCN end. This is explained as too small supersaturations to activate small CCN as in natural clouds, and insufficient time to allow large CCN reaching the critical radius.

Effects of South Asian outflow on aerosol hygroscopicity and cloud droplet activation over the northern Indian Ocean

As a part of the Integrated Campaign for Aerosols, gases and Radiation Budget (ICARB-2018), shipborne measurements of aerosol properties were carried out to study the influence of South Asian outflow on cloud condensation nuclei (CCN) characteristics over the South East Arabian Sea (SEAS) and equatorial Indian Ocean (EIO) during winter, 2018. The poor association between CCN concentration and mass concentrations of the major aerosol species (organic matter, sulfate, and elemental carbon) is observed over SEAS, where airmass is mostly continental. In comparison, the CCN is well-correlated with aerosol mass concentrations over remote EIO. The dependence of CCN activation (at lower supersaturations) on the ultrafine particle fraction differs between SEAS and EIO depending on the mass concentration of organic aerosols. The coexistence of small and hydrophobic aerosols (organics) decreased the CCN activation ratio during ultrafine particle events. The hygroscopicity estimated using the chemical composition of aerosols is comparable to that estimated from CCN measurements over the Indian Ocean, except for the SEAS, where organic aerosols dominate. The effect of outflow aerosols on cloud droplet number concentration (CDNC) is simulated using a parcel model, which showed a good association (R ∼0.96) with CCN measurements over the EIO; however, the estimated CDNC did not follow the CCN variation over the SEAS region. This study highlights the importance of aerosol chemical composition, especially organics, in CCN activation and cloud droplet formation in the South Asian outflow over the Indian Ocean.

Exploring the excess of cloud condensation nuclei and rain suppression using a minimal three-dimensional Boussinesq model with bulk cloud microphysics

Over the years, there have been discussions about the possibility of air pollution affecting the process of rain formation. In this study, we have developed a simplified model that represents the atmospheric dynamics and cloud microphysics to explore the impact of pollution on rain formation. We used an existing three-dimensional minimal model consisting of five equations, for which we added a simple bulk parametrization that represents the role of cloud condensation nuclei (CCN) in cloud formation processes. We conducted numerical tests using two CCN profiles, with either one or two accumulation layers and modified their abundance to explore the effects of different CCN concentrations and distributions. We conducted four numerical tests corresponding to the two aforementioned profiles with polluted and low-polluted scenarios. The numerical simulations suggested that a layer with high CCN concentration close to the surface tends to suppress precipitation, while the same concentration distributed over two layers tends to enhance the efficiency of rain formation. The simulations also showed that CCN particles far from the surface produced higher cloud tops and longer events, consistent with previous research. Although the model includes a stable representation of precipitating turbulent convection with bulk cloud microphysics, we expect its simplicity and conservation properties to allow for deeper theoretical analyses that can help us better understand the physical processes involved in the studied phenomenon. We hope this model will serve as a tool to explore different aerosol-related scenarios within the context of minimal models.

A cloud-by-cloud approach for studying aerosol–cloud interaction in satellite observations

Abstract. The effective radiative forcing (ERF) due to aerosol–cloud interactions (ACIs) and rapid adjustments (ERFaci) still causes the largest uncertainty in the assessment of climate change. It is understood only with medium confidence and is studied primarily for warm clouds. Here, we present a novel cloud-by-cloud (C×C) approach for studying ACI in satellite observations that combines the concentration of cloud condensation nuclei (nCCN) and ice nucleating particles (nINP) from polar-orbiting lidar measurements with the development of the properties of individual clouds by tracking them in geostationary observations. We present a step-by-step description for obtaining matched aerosol–cloud cases. The application to satellite observations over central Europe and northern Africa during 2014, together with rigorous quality assurance, leads to 399 liquid-only clouds and 95 ice-containing clouds that can be matched to surrounding nCCN and nINP respectively at cloud level. We use this initial data set for assessing the impact of changes in cloud-relevant aerosol concentrations on the cloud droplet number concentration (Nd) and effective radius (reff) of liquid clouds and the phase of clouds in the regime of heterogeneous ice formation. We find a Δln⁡Nd/Δln⁡nCCN of 0.13 to 0.30, which is at the lower end of commonly inferred values of 0.3 to 0.8. The Δln⁡reff/Δln⁡nCCN between −0.09 and −0.21 suggests that reff decreases by −0.81 to −3.78 nm per increase in nCCN of 1 cm−3. We also find a tendency towards more cloud ice and more fully glaciated clouds with increasing nINP that cannot be explained by the increasingly lower cloud top temperature of supercooled-liquid, mixed-phase, and fully glaciated clouds alone. Applied to a larger number of observations, the C×C approach has the potential to enable the systematic investigation of warm and cold clouds. This marks a step change in the quantification of ERFaci from space.

Effect of Long‐Range Transported Fire Aerosols on Cloud Condensation Nuclei Concentrations and Cloud Properties at High Latitudes

AbstractActive vegetation fires in south‐eastern (SE) Europe resulted in a notable increase in the number concentration of aerosols and cloud condensation nuclei (CCN) particles at two high latitude locations—the SMEAR IV station in Kuopio, Finland, and the Zeppelin Observatory in Svalbard, high Arctic. During the fire episode aerosol hygroscopicity κ slightly increased at SMEAR IV and at the Zeppelin Observatory κ decreased. Despite increased κ in high CCN conditions at SMEAR IV, the aerosol activation diameter increased due to the decreased supersaturation with an increase in aerosol loading. In addition, at SMEAR IV during the fire episode, in situ measured cloud droplet number concentration (CDNC) increased by a factor of ∼7 as compared to non‐fire periods which was in good agreement with the satellite observations (MODIS, Terra). Results from this study show the importance of SE European fires for cloud properties and radiative forcing in high latitudes.

Above-cloud concentrations of cloud condensation nuclei help to sustain some Arctic low-level clouds

Abstract. Previous studies have found that low-level Arctic clouds often persist for long periods even in the face of very low surface cloud condensation nuclei (CCN) concentrations. Here, we investigate whether these conditions could occur due to continuous entrainment of aerosol particles from the free troposphere (FT). We use an idealized large eddy simulation (LES) modeling framework, where aerosol concentrations are low in the boundary layer (BL) but increased up to 50× in the free troposphere. We find that the tests with higher tropospheric aerosol concentrations simulated clouds, which persisted for longer and maintained higher liquid water paths (LWPs). This is due to direct entrainment of the tropospheric aerosol into the cloud layer, which results in a precipitation suppression from the increase in cloud droplet number and in stronger cloud-top radiative cooling, which causes stronger circulations maintaining the cloud in the absence of surface forcing. Together, these two responses result in a more well-mixed boundary layer with a top that remains in contact with the tropospheric aerosol reservoir and can maintain entrainment of those aerosol particles. The surface aerosol concentrations, however, remained low in all simulations. The free-tropospheric aerosol concentration necessary to maintain the clouds is consistent with concentrations that are frequently seen in observations.

The impact of aerosols and model grid spacing on a supercell storm from Swabian MOSES 2021

AbstractThe supercell storm that occurred in southwestern Germany on June 23, 2021, had an exceptionally long lifetime of 7.5 hr, travelled a distance of nearly 190 km, and produced large amounts of hail. During that summer, the Swabian MOSES field campaign was held in that area, and several hydro‐meteorological measurements are available, as the storm passed directly over the main observation site. We present hindcasts of this event with the Icosahedral Non‐hydrostatic model using two horizontal grid spacings (i.e., 2 km, 1 km) with a single‐moment and an advanced double‐moment microphysics scheme. Numerical results show that all 2 km model realizations do not simulate convective precipitation at the correct location and time. For the 1 km grid spacing, changes in aerosol concentration resulted in large changes in convective precipitation. Only the 1 km run assuming a low cloud condensation nuclei (CCNs) concentration is able to realistically capture the storm, whereas no supercell is simulated in the more polluted scenarios. Observed aerosol particle concentrations indicate that CCNs values were the lowest of the month, which suggests that the low aerosol concentration is a reasonable assumption. The thermodynamic structure of the pre‐convective environment, as well as other observations, showed the best agreement to this model run as well, indicating that the good representation of the supercell was obtained for the right reason. The automatic tracking of individual clouds revealed that more convective cells with longer lifetimes are simulated at finer resolution. We also find a negative aerosol–precipitation effect that is not only due to a reduced collision–coalescence process, but also to weaker cold‐rain processes. These findings demonstrate the benefits of using an aerosol‐aware double‐moment microphysics scheme for convective‐scale predictability and that the use of different CCNs concentrations can determine whether a supercell is successfully simulated or not.

Roles of marine biota in the formation of atmospheric bioaerosols, cloud condensation nuclei, and ice-nucleating particles over the North Pacific Ocean, Bering Sea, and Arctic Ocean

Abstract. We investigated the association of marine biological indicators (polysaccharides, protein-like gel particles, and chl a) with the formation of fluorescent aerosol particles, cloud condensation nuclei (CCNs), and ice-nucleating particles (INPs) over the North Pacific Ocean, Bering Sea, and Arctic Ocean during September–November 2019. The abundance of bioindicators was high in the North Pacific Ocean and the Bering Sea (e.g., up to 1.3 mg m−3 of chl a), suggesting high biological activity due to a phytoplankton bloom. In the North Pacific Ocean, particles were characterized by high mass fractions of organics and sulfate with a predominance of terrestrial air masses. Conversely, in the Bering Sea and the Arctic Ocean, particles were characterized by high mass fractions of sea salt and sulfate with a predominance of maritime air masses. The averaged range/value of the CCN concentration at 0.4 % supersaturation were 99–151, 43–139, and 36 cm−3 over the North Pacific Ocean with terrestrial influences, over the Bering Sea with marine biogenic influences, and over the Arctic Ocean with marine influences, respectively, and the corresponding range/value of the hygroscopicity parameter κ were 0.17–0.59, 0.42–0.68, and 0.66, respectively. The averaged INP concentration (NINP) measured at temperatures of −18 and −24 ∘C with marine sources in the North Pacific and Bering Sea was 0.01–0.09 and 0.1–2.5 L−1, respectively, and that over the Arctic Ocean was 0.001–0.016 and 0.012–0.27 L−1, respectively. When marine sources were dominant, fluorescent bioaerosols in the fine mode were strongly correlated with all bioindicator types (R: 0.81–0.88) when the effect of wind-induced uplift from the sea surface to the atmosphere was considered. Correlations between NINP measured at −18 and −24 ∘C and all bioindicator types (R: 0.58–0.95 and 0.79–0.93, respectively) were positive, even when the extreme outlier point was omitted, as were those between NINP and fluorescent bioaerosols (R: 0.50 and 0.60, respectively), suggesting that marine bioindicators contributed substantially as sources of bioaerosols and to cloud formation.

Cloud condensation nuclei concentrations derived from the CAMS reanalysis

Abstract. Determining number concentrations of cloud condensation nuclei (CCN) is one of the first steps in the chain in analysis of cloud droplet formation, the direct microphysical link between aerosols and cloud droplets, and a process key for aerosol–cloud interactions (ACI). However, due to sparse coverage of in situ measurements and difficulties associated with retrievals from satellites, a global exploration of their magnitude, source as well as temporal and spatial distribution cannot be easily obtained. Thus, a better representation of CCN numbers is one of the goals for quantifying ACI processes and achieving uncertainty-reduced estimates of their associated radiative forcing. Here, we introduce a new CCN dataset which is derived based on aerosol mass mixing ratios from the latest Copernicus Atmosphere Monitoring Service reanalysis (CAMSRA) in a diagnostic model that uses CAMSRA aerosol properties and a simplified kappa-Köhler framework suitable for global models. The emitted aerosols in CAMSRA are not only based on input from emission inventories using aerosol observations, they also have a strong tie to satellite-retrieved aerosol optical depth (AOD) as this is assimilated as a constraining factor in the reanalysis. Furthermore, the reanalysis interpolates for cases of poor or missing retrievals and thus allows for a full spatiotemporal quantification of CCN numbers. The derived CCN dataset captures the general trend and spatial and temporal distribution of total CCN number concentrations and CCN from different aerosol species. A brief evaluation with ground-based in situ measurements demonstrates the improvement of the modelled CCN over the sole use of AOD as a proxy for CCN as the overall correlation coefficient improved from 0.37 to 0.71. However, we find the modelled CCN from CAMSRA to be generally high biased and find a particular erroneous overestimation at one heavily polluted site which emphasises the need for further validation. The CCN dataset (https://doi.org/10.26050/WDCC/QUAERERE_CCNCAMS_v1, Block, 2023), which is now freely available to users, features 3-D CCN number concentrations of global coverage for various supersaturations and aerosol species covering the years 2003–2021 with daily frequency. This dataset is one of its kind as it offers lots of opportunities to be used for evaluation in models and in ACI studies.

Investigating the contribution of grown new particles to cloud condensation nuclei with largely varying preexisting particles – Part 1: Observational data analysis

Abstract. This study employed multiple techniques to investigate the contribution of grown new particles to the number concentration of cloud condensation nuclei (CCN) at various supersaturation (SS) levels at a rural mountain site in the North China Plain from 29 June to 14 July 2019. On 8 new particle formation (NPF) days, the total particle number concentrations (Ncn) were 8.4 ± 6.1×103 cm−3, which was substantially higher compared to 4.7 ± 2.6×103 cm−3 on non-NPF days. However, the CCN concentration (Nccn) at 0.2 % SS and 0.4 % SS on the NPF days was significantly lower than those observed on non-NPF days (p<0.05). This was due to the lower cloud activation efficiency of preexisting particles resulting from organic vapor condensation and smaller number concentrations of preexisting particles on NPF days. A case-by-case examination showed that the grown new particles only yielded a detectable contribution to Nccn at 0.4 % SS and 1.0 % SS during the NPF event on 1 July 2019, accounting for 12 % ± 11 % and 23 % ± 12 % of Nccn, respectively. The increased Nccn during two other NPF events and at 0.2 % SS on 1 July 2019 were detectable but determined mainly by varying preexisting particles rather than grown new particles. In addition, the hygroscopicity parameter values, concentrations of inorganic and organic particulate components, and surface chemical composition of different sized particles were analyzed in terms of chemical drivers to grow new particles. The results showed that the grown new particles via organic vapor condensation generally had no detectable contribution to Nccn but incidentally did. However, this conclusion was drawn from a small size of observational data, leaving more observations, particularly long-term observations and the growth of preexisting particles to the CCN required size, needed for further investigation.

Detection of dilution due to turbulent mixing vs. precipitation scavenging effects on biomass burning aerosol concentrations using stable water isotope ratios during ORACLES

Abstract. The interaction between biomass burning aerosols and clouds remains challenging to accurately determine, in part because of difficulties using direct observations to account for influences on aerosol concentrations from precipitation scavenging and dilution due to air mass mixing and separating those signals from source contributions. The prevalence of mixing versus precipitation processes in air laden with biomass burning aerosol (BBA) in the southeast Atlantic lower free troposphere (FT) and marine boundary layer (MBL) is assessed during three observation periods (September 2016, August 2017, and October 2018) during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign. Significant sources of BBAs over the African continent combined with regional circulation patterns result in BBA-laden air flowing from the continent over the southeast Atlantic in the lower FT, then subsiding onto the semi-permanent stratocumulus cloud deck, and entraining into the MBL. This study is broken into two parts, first analyzing hydrologic histories of the BBA air in the lower FT and then carrying out a similar assessment in the underlying MBL. Both analyses leverage joint measurements of water concentration and its heavy isotope ratio, interpreted in the previously established (q, δD) phase space framework. For the lower-FT analysis, in situ observations (water concentration, water isotope ratios) in the lower FT are combined with satellite and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), global reanalysis data into simple analytical models to constrain hydrologic histories. We find that even simple models are capable of detecting and constraining the primary processes at play, e.g., distinguishing air masses that experienced moist convection and precipitation (likely over the continent) from those that underwent dry convection and turbulent mixing. Regression of the aircraft data onto a simple model of convective detrainment is used to develop a metric of total precipitation for the in situ measurements and then compared to an aerosol metric of black carbon scavenging also derived from the in situ measurements (the ratio of black carbon to carbon monoxide, BC/CO). There is a strong correlation between the two, suggesting black carbon scavenging has been detected and partially quantified, if only in a relative manner. In comparison, weak correlation is found between BC/CO and the total water concentration itself. The above method is expanded to test for entrainment and precipitation influences on BBA concentrations in the MBL. This is more difficult than the FT analysis since signals are subtle and limited by imperfect knowledge of the water and isotope ratios of the entrained air mass at cloud top. For some of the MBLs observed during 2016 and 2018, lower cloud condensation nuclei (CCN) concentrations occur in the sub-cloud layer coincident with isotopic evidence of precipitation, indicating aerosol scavenging, but more complex models are needed to produce definitive conclusions. For the 2017 observation period, with the highest sub-cloud CCN concentrations, there is no connection between precipitation signals and CCN concentrations, likely indicating the importance of different geographic sampling and air mass history in that year. Nonetheless, these findings along with the FT analysis suggest that utilizing isotope ratio signals may be an aid in addressing cloud–aerosol challenges. Especially for the FT case, these findings support the pursuit of more complex models combined with targeted in situ data to constrain BC scavenging coefficients in a manner which can guide model parameterizations, leading to improvements in the accuracy of simulated BC concentrations and lifetimes in climate models.

On the Impact of a Dry Intrusion Driving Cloud-Regime Transitions in a Midlatitude Cold-Air Outbreak

Abstract Marine cold-air outbreaks (CAOs) occur in the postfrontal sector of midlatitude storms, usually accompanied by dry intrusions (DIs) shaping the free-tropospheric (FT) air aloft. Substantial rain initiates overcast to broken regime transitions in marine boundary layer (MBL) cloud decks that form where cold air first meets relatively high sea surface temperatures. An exemplary CAO in the northwest Atlantic shows earlier transitions (corresponding to reduced extents of overcast clouds) closer to the low pressure center. We hypothesize that gradients in the meteorological pattern imposed by the prevailing DI induced a variability in substantial rain onset and thereby transition. We compile satellite observations, reanalysis fields, and Lagrangian large-eddy simulations (LES) translating along MBL trajectories to show that postfrontal trajectories closer to the low pressure center are more favorable to rain formation (and thereby cloud transitions) because of 1) weaker FT subsidence rates, 2) greater FT humidity, 3) stronger MBL winds, and 4) a colder MBL with reduced lower-tropospheric stability. LES confirms the observed variability in transitions, with substantial rain appearing earlier where there is swifter reduction of cloud condensation nucleus (CCN) concentration and increase of liquid water path (LWP). Prior to substantial rain, CCN budgets indicate dominant loss terms from FT entrainment and hydrometeor collisions. LWP-enhancing cloud thickness increases more rapidly for weaker large-scale subsidence that enables faster MBL deepening. Mere MBL warming and moistening cannot explain cloud thickness increases. The generality of such a DI-imposed cloud transition pattern merits further investigation with more cases that may additionally be convoluted by onshore aerosol gradients. Significance Statement Cold-air outbreaks (CAOs) lead to marine boundary layer (MBL) clouds that commonly undergo rain-initiated overcast to broken cloud regime transitions that can drastically impact reflected solar radiation. We aim to better understand what mechanisms control these transitions. For a CAO event in the northwest Atlantic that shows earlier transitions closer to the low pressure center, we find the transition timing to be largely governed by the coinciding dry intrusion that imposes an inhomogeneous large-scale meteorological pattern onto the overlying free troposphere and thereby affects MBL rain formation. Our findings update conceptual understanding of extratropical cyclones and motivate analyzing observations and conducting simulations for more postfrontal cases through a Lagrangian perspective as done here for one case, to assess the generality of our findings.