Cloud Droplet Number Research Articles

Model analysis of biases in the satellite-diagnosed aerosol effect on the cloud liquid water path

Abstract. The response in cloud water content to changes in cloud condensation nuclei remains one of the major uncertainties in determining how aerosols can perturb cloud properties. In this study, we used an ensemble of large eddy simulations of marine stratocumulus clouds to investigate the correlation between cloud liquid water path (LWP) and the amount of cloud condensation nuclei. We compare this correlation directly from the model to the correlation derived using equations which are used to retrieve liquid water path from satellite observations. Our comparison shows that spatial variability in cloud properties and instrumental noise in satellite retrievals of cloud optical depth and cloud effective radii results in bias in the satellite-derived liquid water path. In-depth investigation of high-resolution model data shows that in large part of a cloud, the assumption of adiabaticity does not hold, which results in a similar bias in the LWP–CDNC (cloud droplet number concentration) relationship as seen in satellite data. In addition, our analysis shows a significant positive bias of between 18 % and 40 % in satellite-derived cloud droplet number concentration. However, for the individual ensemble members, the correlation between the cloud condensation nuclei and the mean of the liquid water path was very similar between the methods. This suggests that if cloud cases are carefully chosen for similar meteorological conditions and it is ensured that cloud condensation nuclei concentrations are well-defined, changes in liquid water can be confidently determined using satellite data.

Exploring Causal Relationships and Adjustment Timescales of Aerosol‐Cloud Interactions in Geostationary Satellite Observations and CAM6 Using Wavelet Phase Coherence Analysis

AbstractWe present for the first time within the cloud physics context, the application of wavelet phase coherence analysis to disentangle counteracting physical processes associated with the lead‐lag phase difference between cloud‐proxy liquid water path (LWP) and aerosol‐proxy cloud droplet number concentration (Nd) in an Eulerian framework using satellite‐based observations and climate model outputs. This approach allows us to identify the causality and dominant adjustment timescales governing the correlation between LWP and Nd. Satellite observations indicate a more prevalent positive correlation between daytime LWP and Nd regardless of whether LWP leads or lags Nd. The positive cloud water response, associated with precipitation processes, typically occurs within 1 hr, while the negative response resulting from entrainment drying, usually takes 2–4 hr. CAM6 displays excessively rapid negative responses along with overly strong negative cloud water response and insufficient positive response, leading to a more negative correlation between LWP and Nd compared to observations.

Role of a key microphysical factor in mixed-phase stratocumulus clouds and their interactions with aerosols

Abstract. This study examines the ratio of ice crystal number concentration (ICNC) to cloud droplet number concentration (CDNC), that is ICNC / CDNC, in mixed-phase stratocumulus clouds. This examination is performed using a large-eddy simulation (LES) framework and is one of the efforts toward a more general understanding of mechanisms controlling cloud development and aerosol–cloud interactions, as well as the impacts of ice processes on them in mixed-phase stratocumulus clouds. For the examination, this study compares a case of polar mixed-phase stratocumulus clouds to one of midlatitude mixed-phase stratocumulus clouds with weak precipitation. It is found that ICNC / CDNC plays a critical role in causing differences in cloud development with respect to the relative proportion of liquid and ice mass between the cases by affecting in-cloud latent-heat processes. Note that this proportion has an important implication for cloud radiative properties and, thus, for climate. It is also found that ICNC / CDNC plays a critical role in causing differences in the interactions between clouds and aerosols and in the impacts of ice processes on clouds and their interactions with aerosols between the cases by affecting in-cloud latent-heat processes. Findings of this study suggest that ICNC / CDNC can be a simplified general factor that contributes to a more general understanding and parameterization of mixed-phase clouds, their interactions with aerosols and the roles of ice processes within them.

Structural Difference on the Response of Microphysical and Precipitation Processes to Aerosol Perturbation in a Quasi‐Stationary Southwest Vortex System

AbstractUsing the WRF coupled with Thompson aerosol‐aware microphysics scheme, a quasi‐stationary southwest vortex (SWV) precipitation process occurring in the Sichuan Basin is simulated. Based on three experiments with low aerosol concentration background (“Low”), medium aerosol concentration background (“Medium”), and high aerosol concentration background (“High”), the effects of hydrophilic aerosol serving as Cloud Condensation Nuclei (CCN) on microphysical and precipitation processes are investigated. Results indicate the impact of hydrophilic aerosol on clouds and precipitation structure exhibits structural difference. Aerosol increases from “Low” to “Medium”, precipitation in middle circle of SWV decreases, precipitation in outer circle of SWV increases. Because the outer circle of SWV with strong convection competes with the middle circle of SWV for liquid droplets, leading to a reduction in ice‐phase particles in middle circle of SWV. In contrast, more ice‐phase particles are formed in outer circle of SWV. The increased ice‐phase particles melt into raindrops, leading to an increase in precipitation. Aerosol increases from “Medium” to “High”, precipitation in middle circle of SWV increases, precipitation in outer circle of SWV decreases. The size of liquid droplets formed in outer circle of SWV further becomes smaller. This is not conducive to the formation of ice‐phase particles, leading to weaker convection, which makes it becomes less competitive. A large number of small cloud droplets in middle circle of SWV are transported above the freezing layer and participate in the formation of ice‐phase particles. The released latent heat promotes convective development, resulting in more precipitation.

Freeze-thaw process boosts penguin-derived NH3 emissions and enhances climate-relevant particles formation in Antarctica

Ammonia volatilized from penguin excreta is a significant nitrogen source in Antarctic ecosystems, influencing climate through new particle formation (NPF). Freeze-thaw events can trigger ammonia emissions, but their impact on penguin-derived ammonia is understudied and overlooked in models. Here we investigate the contribution of penguins to ammonia and their climatic impacts using cruise observations and GEOS-Chem-APM simulations. High ammonia concentrations, with a maximum exceeding 7000 ng/m3, were observed over the Southern Ocean and Prydz Bay, driven by air masses from penguin colonies. Simulations showed that incorporating freeze-thaw impact improves model performance, with penguin-derived ammonia emissions enhanced by up to 20-fold and reaching a total of 49 Gg across Antarctica in November. Elevated ammonia increased simulated secondary particle number concentrations by 30−300% through NPF, enhancing simulated cloud droplet number concentrations by 10−20% and altering cloud properties. This study underscores the importance of incorporating penguin emissions into models, particularly during freeze-thaw events.

Quantifying the impact of global nitrate aerosol on tropospheric composition fields and its production from lightning NOx

Abstract. Several global modelling studies have explored the effects of lightning-generated nitrogen oxides (LNOx) on gas-phase chemistry and atmospheric radiative transfer, but few have quantified LNOx's impact on aerosol, particularly when nitrate aerosol is included. This study addresses two key questions: (1) how does including nitrate aerosol affect properties such as tropospheric composition, and (2) how do these effects depend on lightning parameterisation and LNOx levels? Using the Met Office's Unified Model–United Kingdom Chemistry and Aerosol (UM–UKCA) global chemistry–climate model, which now includes a modal nitrate aerosol scheme, we investigate these effects with two lightning-flash-rate parameterisations. Our findings show that both nitrate aerosol and LNOx significantly impact tropospheric composition and aerosol responses. Including nitrate aerosol reduces global mean tropospheric OH by 5 %, decreases the tropospheric ozone burden by 4 %–5 %, increases methane lifetime by a similar amount, and alters the top-of-atmosphere (TOA) net downward radiative flux by −0.4 W m−2. The inclusion of nitrate also shifts the aerosol size distribution, particularly in the Aitken and accumulation modes. A 5.2 Tg N yr−1 increase in LNOx from a zero baseline results in global aerosol increases of 2.8 % in NH4, 4.7 % in fine NO3, 12 % in coarse NO3, and 5.8 % in SO4 mass burdens. This much LNOx increase causes relatively small positive changes in aerosol optical depth, TOA radiative flux, and cloud droplet number concentration compared to when nitrate is included. The results, based on a fast uptake rate for HNO3 to produce NH4NO3, likely represent an upper limit on nitrate effects.

On the Prediction of Aerosol‐Cloud Interactions Within a Data‐Driven Framework

AbstractAerosol‐cloud interactions (ACI) pose the largest uncertainty for climate projection. Among many challenges of understanding ACI, the question of whether ACI can be deterministically predicted has not been explicitly answered. Here we attempt to answer this question by predicting cloud droplet number concentration from aerosol number concentration and ambient conditions using a data‐driven framework. We use aerosol properties, vertical velocity fluctuations, and meteorological states from the ACTIVATE field observations (2020–2022) as predictors to estimate . We show that the campaign‐wide can be successfully predicted using machine learning models despite the strongly nonlinear and multi‐scale nature of ACI. However, the observation‐trained machine learning model fails to predict in individual cases while it successfully predicts of randomly selected data points that cover a broad spatiotemporal scale. This suggests that, within a data‐driven framework, the prediction is uncertain at fine spatiotemporal scales.

Can general circulation models (GCMs) represent cloud liquid water path adjustments to aerosol–cloud interactions?

Abstract. General circulation models (GCMs), unlike other lines of evidence, indicate that anthropogenic aerosols cause a global-mean increase in cloud liquid water path (ℒ) and thus a negative adjustment to radiative forcing of the climate by aerosol–cloud interactions. In part 1 of this series of papers, we showed that this is true even in models that reproduce the negative correlation observed in present-day internal variability in ℒ and cloud droplet number concentration (Nd). We studied several possible confounding mechanisms that could explain the noncausal cloud–aerosol correlations in GCMs and that possibly contaminate observational estimates of radiative adjustments. Here, we perform single-column and full-atmosphere GCM experiments to investigate the causal model-physics mechanisms underlying the model radiative adjustment estimate. We find that both aerosol–cloud interaction mechanisms thought to be operating in real clouds – precipitation suppression and entrainment evaporation enhancement – are active in GCMs and behave qualitatively in agreement with physical process understanding. However, the modeled entrainment enhancement has a negligible global-mean effect. This raises the question of whether the GCM estimate is incorrect due to parametric or base-state representation errors or whether the process understanding gleaned from a limited set of canonical cloud cases is insufficiently representative of the diversity of clouds in the real climate. Regardless, even at limited resolution, the GCM physics appears able to parameterize the small-scale microphysics–turbulence interplay responsible for the entrainment enhancement mechanism. We suggest ways to resolve tension between current and future (storm-resolving) global modeling systems and other lines of evidence in synthesis climate projections.

Impact of stochastic collisions on cloud droplet number concentration and relative dispersion during Meiyu frontal system

Impact of stochastic collisions on cloud droplet number concentration and relative dispersion during Meiyu frontal system

Improving Prediction of Marine Low Clouds Using Cloud Droplet Number Concentration in a Convolutional Neural Network

AbstractMarine low clouds play a crucial role in cooling the climate, but accurately predicting them remains challenging due to their highly non‐linear response to various factors. Previous studies usually overlook the effects of cloud droplet number concentration (Nd) and the non‐local information of the target grids. To address these challenges, we introduce a convolutional neural network model (CNNMet‐Nd) that uses both local and non‐local information and includes Nd as a cloud‐controlling factor to enhance the predictive ability of daily cloud cover, albedo, and cloud radiative effects (CRE) for global marine low clouds. CNNMet‐Nd demonstrates superior performance, explaining over 70% of the variance in these three cloud variables for scenes of 1° × 1°, a notable improvement over past efforts. CNNMet‐Nd also accurately replicates geographical patterns of trends in marine low clouds from 2003 to 2022. In contrast, a similar model without Nd (CNNMet) struggles to predict long‐term trends in cloud properties effectively. Permutation importance analysis further highlights the critical role of Nd in CNNMet‐N's predictive success. Further comparisons with an artificial neural network (ANNMet‐Nd) model, which uses the same inputs but without considering spatial dependence, show CNNMet‐Nd's superior performance with R2 values for cloud cover, albedo, and CRE being 0.16, 0.12, and 0.18 higher, respectively. This highlights the importance of incorporating non‐local information, at least on a daily scale, into low cloud predictions to enhance climate model parameterizations.

Modeling analysis and experiments of dual-FOV multiple scattering Raman lidar for detecting water cloud microphysical properties

Clouds are the primary regulators of the Earth’s climate, but the mechanisms through which they influence climate are poorly understood. Probing the microphysical properties of liquid water clouds is an urgent need for research on the Earth’s atmospheric system and atmospheric physics. In this paper, an iterative inversion of water cloud microphysical properties for a multiple scattering Raman lidar is presented, which can enable continuous, vertical measurements of the extinction coefficient of water clouds, the liquid water content (LWC), the effective radius of the cloud droplets, and cloud droplet number concentration (CDNC). The technique based on a constructed dual-field-of-view (dual-FOV) device combined with a quasi-small-angle (QSA) approximation model was investigated. The determination method of the optimal field of view (FOV) for lidar detection was discussed to enhance the sensitivity of the measured signals to the observed cloud microphysical parameters. Field observations with a co-located microwave radiometer (MWR) were carried out to verify the effectiveness of the lidar system, also an error analysis of the measurement examples was performed. The dual FOV Raman lidar experimental LWC measurement has an average deviation of 0.034 g/m3 and the relative error is 27.2% relative to the MWR measurement. The system has important potential applications in aerosol-cloud interactions and provides new ideas and methods for studying water cloud microphysical properties, further studying aerosol indirect effects.

The Cycle 46 Configuration of the HARMONIE-AROME Forecast Model

The aim of this technical note is to describe the Cycle 46 reference configuration of the HARMONIE-AROME convection-permitting numerical weather prediction model. HARMONIE-AROME is one of the canonical system configurations that is developed, maintained, and validated in the ACCORD consortium, a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale numerical weather prediction. This technical note describes updates to the physical parametrizations, both upper-air and surface, configuration choices such as lateral boundary conditions, model levels, horizontal resolution, model time step, and databases associated with the model, such as for physiography and aerosols. Much of the physics developments are related to improving the representation of clouds in the model, including developments in the turbulence, shallow convection, and statistical cloud scheme, as well as changes in radiation and cloud microphysics concerning cloud droplet number concentration and longwave cloud liquid optical properties. Near real-time aerosols and the ICE-T microphysics scheme, which improves the representation of supercooled liquid, and a wind farm parametrization have been added as options. Surface-wise, one of the main advances is the implementation of the lake model FLake. An outlook on upcoming developments is also included.

The Transition from Aerosol- to Updraft-Limited Susceptibility Regime in Large-Eddy Simulations with Bulk Microphysics

Large-eddy simulation (LES) is often used as a benchmark simulation in climate science and is suggested as a fundamental tool to examine, e.g., marine cloud brightening. Therefore, it is necessary to critically evaluate if these high-resolution models can skillfully simulate expected physical phenomena. This study focuses on the first indirect aerosol effect in warm stratocumulus clouds. We investigate if an LES code with explicit aerosol-cloud interactions and a widely used two-moment bulk microphysical scheme can reproduce well-known cloud droplet number susceptibility regimes previously identified by observations and supported by detailed parcel model simulations—the updraft-limited regime (typically occurring at high aerosol number concentrations and low updraft speeds) and the aerosol-limited regime (typically occurring at low aerosol number concentrations and high updraft speeds). Our simulations show that the LES in its default configuration cannot reproduce the two regimes if the initial droplet radius of newly activated droplets (rid) is estimated by integrating the wet aerosol size distribution. The main reason is related to the relatively coarse (but commonly used) time step in the model (Δt ≈ 1s), which is too long to resolve relevant microphysical processes adequately at high aerosol concentrations. A regime transition does occur if the timestep is decreased to Δt ≈ 0.1s and if a renormalization procedure is applied, which limits the number of activated droplets so that the water mass of the newly activated droplets cannot exceed the available amount of supersaturated water vapor. Another way to obtain a regime transition is to increase rid to values >1 µm. However, a clear recommendation for the choice of rid cannot be made upon physical arguments. An alternative solution could be to introduce a sub-time-stepping or adaptive time-stepping algorithm to calculate droplet formation and growth, particularly for updraft-limited conditions. Our study highlights the importance of critically evaluating LES results to guarantee that relevant physical processes are properly represented.

Analysis of the Meteorological Conditions and Atmospheric Numerical Simulation of an Aircraft Icing Accident

With the rapid development of the general aviation industry in China, the influence of high-impact aeronautical weather events, such as aircraft icing, on flight safety has become more and more prominent. On 1 March 2021, an aircraft conducting weather modification operations crashed over Ji’an City, due to severe icing. Using multi-source meteorological observations and atmospheric numerical simulations, we analyzed the meteorological causes of this icing accident. The results indicate that a cold front formed in northwestern China and then moved southward, which is the main weather system in the icing area. Based on the icing index, we conducted an analysis of the temperature, relative humidity, cloud liquid water path, effective particle radius, and vertical flow field, it was found that aircraft icing occurred behind the ground front, where warm-moist airflows rose along the front to result in a rapid increase of water vapor in 600–500 hPa. The increase of water vapor, in conjunction with low temperature, led to the formation of a cold stratiform cloud system. In this cloud system, there were a large number of large cloud droplets. In addition, the frontal inversion increased the atmospheric stability, allowing cloud droplets to accumulate in the low-temperature region and forming meteorological conditions conducive to icing. The Weather Research and Forecasting model was employed to provide a detailed description of the formation process of the atmospheric conditions conducive to icing, such as the uplifting motion along the front and supercooled water. Based on a real case, we investigated the formation process of icing-inducing meteorological conditions under the influence of a front in detail in this study and verified the capability of a numerical model to simulate the meteorological environment of frontal icing, in order to provide a valuable reference for meteorological early warnings and forecasts for general aviation.

Evaluation of Autoconversion Representation in E3SMv2 Using an Ensemble of Large‐Eddy Simulations of Low‐Level Warm Clouds

AbstractIn numerical atmospheric models that treat cloud and rain droplet populations as separate condensate categories, precipitation initiation in warm clouds is often represented by an autoconversion rate , which is the rate of formation of new rain droplets through the collisions of cloud droplets. Being a function of the cloud droplet size distribution (DSD), the local is commonly parameterized as a function of DSD moments: cloud droplet number and mass concentrations. When applied in a large‐scale model, the grid‐mean must also include a correction, or enhancement factor, to account for the horizontal variability of the cloud properties across the model grid. In this study, we evaluate the Au representation in the Energy Exascale Earth System Model version 2 (E3SMv2) climate model using large‐eddy simulations (LES), which explicitly resolve cloud droplet spectra, and therefore the local , as well as its spatial variability. The analysis of an ensemble of warm low‐level cloud cases shows that the E3SMv2 formulation represents the reasonably well compared to the horizontally averaged explicitly computed rate from LES. The agreement, however, comes from a combination of an underestimated E3SM‐tuned local rate and an overestimated subgrid cloud variability enhancement factor. The latter bias is traced to neglecting the horizontal variability of and its co‐variability with in parameterizing the grid‐mean .

Microphysical Evolution in Mixed-Phase Midlatitude Marine Cold-Air Outbreaks

Abstract Five cold-air outbreaks are investigated with aircraft offshore of continental northeast America. Flight paths aligned with the cloud-layer flow from January through March span cloud-top temperatures from −5° to −12°C, in situ liquid water paths of up to 500 g m−2, while in situ cloud droplet number concentrations exceeding 500 cm−3 maintain effective radii below 10 μm. Rimed ice is detected in the four colder cases within the first cloud pass. After further fetch, ice particle number concentrations reaching 2.5 L−1 support an interpretation that secondary ice production is occurring. Rime splintering is clearly evident, with dendritic growth increasing ice water contents within deeper clouds with colder cloud-top temperatures. Buoyancy fluxes reach 400–600 W m−2 near the Gulf Stream’s western edge, with 1-s updrafts reaching 5 m s−1 supporting closely spaced convective cells. Near-surface rainfall rates of the three more intense cold-air outbreaks are a maximum near the Gulf Stream’s eastern edge, just before the clouds transition to more open-celled structures. The milder two cold-air outbreaks transition to lower-albedo cumulus with little or no precipitation. The clouds thin through cloud-top entrainment. Significance Statement Cold-air outbreaks off of the eastern U.S. seaboard are visually spectacular in satellite imagery, with overcast, high-albedo clouds transitioning to more broken cloud fields. We use data from the recent NASA Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) aircraft campaign to examine the microphysics and environmental context of five such outbreaks. We find the clouds are not ice-deprived, but updrafts still supply significant liquid water. Cloud transitions are encouraged through near-surface rain for the deeper clouds, and otherwise, clouds thin and break through mixing in drier air from above. These observations support understanding and further modeling examining how mixed-phase cloud microphysics affect cloud reflectivity and surface rainfall rates, important for both weather and climate forecasting.

Research on Housing Market Risk Management Based on Multidimensional Evaluation

The housing market is a high-risk industry with too many factors influenced by the outside world, and if these risks are not effectively managed, it will bring serious impacts on the stability of the economy and society. This paper takes the risk management of housing market as the research object, utilizes the information entropy model and ANP combined method to combine and assign the risk indicators, and constructs the cloud model of housing market risk evaluation. And the cloud model is applied to the GJ housing case for practical evaluation, and it is found that the cloud droplets of the comprehensive risk of the GJ housing market are mainly distributed in the medium-risk interval from 31 to 54, focusing on 41, and a small number of risk cloud droplets appear in the higher-risk cloud map, which is in line with the actual evaluation results, and further verifies the feasibility and validity of the method. Finally, based on the evaluation results, the risk control strategy of the relevant housing market is proposed, which can be used as a reference in the development process of subsequent housing projects.

Combined impacts of aerosols and urbanization on a highly threatened extreme precipitation event in Beijing, China

On July 21, 2012, a catastrophic precipitation event occurred in Beijing, highlighting the serious threat of extreme precipitation on socio-economic development and human health under climate change. Nevertheless, whether, how and to what extent aerosols and urbanization, as the two main influencing factors of urban extreme precipitation, have affected this highly damaging extreme event remains largely unexplored. Here, we employed the weather research and forecasting model coupled with chemistry (WRF-Chem) and a single-layer urban canopy model to investigate the influences of urbanization, aerosols and their interactions on this extreme precipitation event. We found that the joint intensification effects of urbanization and aerosols on extreme precipitation events greatly enhance its negative influence on megacities. The results indicate that aerosols are enhanced by increasing cloud droplet numbers, thereby intensifying the feedback between precipitation and latent heating. Consequently, the total precipitation increased by 22.6%, raising the precipitation in the Beijing area increase by at least 50 mm. By stimulating atmospheric instability and strengthening vertical air motion (over 0.25 m s−1), the urban heat island effect considerably influences the temporal and spatial distributions of extreme precipitation events, resulting in an increase in warm cloud precipitation (80%) and a decrease (30%) in frontal precipitation. Consequently, joint intensification effects resulted in more concentrated precipitation in the southwest of Beijing, leading to a substantial increase (more than 40%, ∼80 mm). This condition may be an important reason for the most severe disasters in the southwest of Beijing.

Cloud water adjustments to aerosol perturbations are buffered by solar heating in non-precipitating marine stratocumuli

Abstract. Marine low-level clouds are key to the Earth's energy budget due to their expansive coverage over global oceans and their high reflectance of incoming solar radiation. Their responses to anthropogenic aerosol perturbations remain the largest source of uncertainty in estimating the anthropogenic radiative forcing of climate. A major challenge is the quantification of the cloud water response to aerosol perturbations. In particular, the presence of feedbacks through microphysical, dynamical, and thermodynamical pathways at various spatial and temporal scales could augment or weaken the response. Central to this problem is the temporal evolution in cloud adjustment, governed by entangled feedback mechanisms. We apply an innovative conditional Monte Carlo subsampling approach to a large ensemble of diurnal large-eddy simulation of non-precipitating marine stratocumulus to study the role of solar heating in governing the evolution in the relationship between droplet number and cloud water. We find a persistent negative trend in this relationship at night, confirming that the role of microphysically enhanced cloud-top entrainment. After sunrise, the evolution in this relationship appears buffered and converges to ∼-0.2 in the late afternoon. This buffering effect is attributed to a strong dependence of cloud-layer shortwave absorption on cloud liquid water path. These diurnal cycle characteristics further demonstrate a tight connection between cloud brightening potential and the relationship between cloud water and droplet number at sunrise, which has implications for the impact of the timing of advertent aerosol perturbations.

Aerosol mixing state, new particle formation, and cloud droplet number concentration in an urban environment

Anthropogenically derived aerosols have been hypothesized to influence convective precipitation by increasing the available pool of cloud condensation nuclei. Here, we present a synthesis of aerosol size distribution and subsaturated hygroscopicity measurements between 15 and 250 nm diameter particles during the TRacking Aerosol Convection interactions ExpeRiment (TRACER). We found that the aerosol is externally mixed and can be described by a quasi-two-component description comprising a more and less hygroscopic mode. The mean hygroscopicity parameters for these modes across all sizes were 0.03 ± 0.04 and 0.22 ± 0.08 with no significant dependence on particle size. The number fraction of the more hygroscopic mode is 40 % for particles between 15 and 40 nm and gradually increases to ~70 % for particles >100 nm. Winds from the southerly direction feature particles with larger hygroscopicity parameters and have a larger fraction of particles in the more hygroscopic mode. The hygroscopicity parameter exhibits diurnal cycles that are consistent with condensation of a species with a hygroscopicity parameter ~0.1 which corresponds to values expected for secondary organic aerosol. We also identified nine small particle events that were attributed to particle formation by nucleation. The data are consistent with new particle formation having occurred aloft, followed by downward mixing with daytime turbulence. The species that are responsible for modal growth had hygroscopicity parameters varying between 0.05 and 0.34. These values systematically depended on the wind sector, suggesting that the chemical composition of the precursors differed. Hourly cloud condensation nuclei (CCN) and cloud droplet number concentration (CDNC) values derived from the aerosol size distribution, subsaturated hygroscopicity measurements, and adiabatic parcel model simulations showed a dynamic range of a factor of 2–3 in CDNC depending on the wind sector, with lower values associated with southerly onshore flow.