scholarly journals Evaluation of global simulations of aerosol particle number and cloud condensation nuclei, and implications for cloud droplet formation

2019 ◽  
Author(s):  
George S. Fanourgakis ◽  
Maria Kanakidou ◽  
Athanasios Nenes ◽  
Susanne E. Bauer ◽  
Tommi Bergman ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Aerosol Formation ◽  
Condensation Nuclei ◽  
Short Term ◽  
Near Surface

Abstract. A total of sixteen global chemistry transport models and general circulation models have participated in this study. Fourteen models have been evaluated with regard to their ability to reproduce near-surface observed number concentration of aerosol particle and cloud condensation nuclei (CCN), and derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations, located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments, and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters > 50 nm and > 120 nm and −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. Fifteen models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −17 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally-derived value at lower than at higher updraft velocities (index-of-agreement of 0.47 vs 0.50). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration and to updraft velocity. Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high.

scholarly journals Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

2019 ◽  
Vol 19 (13) ◽  
pp. 8591-8617 ◽  
Author(s):  
George S. Fanourgakis ◽  
Maria Kanakidou ◽  
Athanasios Nenes ◽  
Susanne E. Bauer ◽  
Tommi Bergman ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Aerosol Formation ◽  
Condensation Nuclei ◽  
Short Term ◽  
Near Surface

Abstract. A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011–2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of −24 % and −35 % for particles with dry diameters >50 and >120 nm, as well as −36 % and −34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB −13 % and −22 % for updraft velocities 0.3 and 0.6 m s−1, respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (∂Nd/∂Na) and to updraft velocity (∂Nd/∂w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities ∂Nd/∂Na and ∂Nd/∂w; models may be predisposed to be too “aerosol sensitive” or “aerosol insensitive” in aerosol–cloud–climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain inter-model biases on the aerosol indirect effect.

scholarly journals Cloud condensation nuclei in polluted air and biomass burning smoke near the mega-city Guangzhou, China – Part 1: Size-resolved measurements and implications for the modeling of aerosol particle hygroscopicity and CCN activity

2008 ◽  
Vol 8 (5) ◽  
pp. 17343-17392 ◽  
Author(s):  
D. Rose ◽  
A. Nowak ◽  
P. Achtert ◽  
A. Wiedensohler ◽  
M. Hu ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Biomass Burning ◽  
Particle Number ◽  
Size Range ◽  
Cloud Condensation Nuclei ◽  
Aerosol Particles ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Average Value ◽  
Ccn Activity

Abstract. Atmospheric aerosol particles serving as cloud condensation nuclei (CCN) are key elements of the hydrological cycle and climate, but their abundance, properties and sources are highly variable and not well known. We have measured and characterized CCN in polluted air and biomass burning smoke during the PRIDE-PRD2006 campaign on 1–30 July 2006 at a rural site ~60 km northwest of the mega-city Guangzhou in southeastern China. CCN efficiency spectra (activated fraction vs. dry particle diameter; 20–300 nm) were recorded at water vapor supersaturations (S) in the range of 0.07% to 1.27%. Depending on S, the dry CCN activation diameters were in the range of 30–200 nm, corresponding to effective hygroscopicity parameters κ in the range of 0.1–0.5. The hygroscopicity of particles in the accumulation size range was generally higher than that of particles in the nucleation and Aitken size range. The campaign average value of κ for all aerosol particles across the investigated size range was 0.3, which equals the average value of κ for other continental locations. During a strong local biomass burning event, the activation diameters increased by ~10% and the average value of κ dropped to 0.2, which can be considered as characteristic for freshly emitted smoke from the burning of agricultural waste. At low S (≤0.27%), the maximum activated fraction remained generally well below one, which indicates substantial proportions of externally mixed CCN-inactive particles with much lower hygroscopicity – most likely soot particles (up to ~60% at ~250 nm). The mean CCN number concentrations (NCCN,S) ranged from 1100 cm−3 at S=0.07% to 16 000 cm−3 at S=1.27%, representing ~7% to ~85% of the total aerosol particle number concentration. Based on the measurement data, we have tested different model approaches (power laws and κ-Köhler model) for the approximation/prediction of NCCN,S as a function of water vapor supersaturation, aerosol particle number concentration, size distribution and hygroscopicity. Depending on S and on the model approach, the relative deviations between measured and predicted NCCN,S ranged from a few percent to several hundred percent. The largest deviations occurred at low S and with power laws based on particle number concentration. With the κ-Köhler model and a constant hygroscopicity parameter of 0.3, the deviations were on average less than ~20%, which confirms that κ=0.3 may be suitable for approximating the hygroscopicity and CCN activity of continental aerosols in large scale models of the atmosphere and climate. On the other hand, the temporal variations of NCCN,S observed during the biomass burning event and in diurnal cycles could not be captured with constant κ (deviations up to ~80%). With variable κ values obtained from individual CCN efficiency spectra, the relative deviations were on average less than ~10% and hardly exceeded 20%, confirming the applicability of the κ-Köhler model approach for efficient description of the CCN activity of atmospheric aerosols. Note, however, that different types of κ-parameters have to be distinguished for external mixtures of CCN-active and -inactive aerosol particles.

scholarly journals Cloud activation properties of aerosol particles in a continental Central European urban environment

2021 ◽  
Vol 21 (14) ◽  
pp. 11289-11302
Author(s):  
Imre Salma ◽  
Wanda Thén ◽  
Máté Vörösmarty ◽  
András Zénó Gyöngyösi
Keyword(s):  
Chemical Composition ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Aerosol Particles ◽  
Number Concentration ◽  
Urban Aerosol ◽  
Condensation Nuclei ◽  
Frequency Distributions ◽  
Remote Locations ◽  
Cloud Activation

Abstract. Collocated measurements using a condensation particle counter, differential mobility particle sizer and cloud condensation nuclei counter were realised in parallel in central Budapest from 15 April 2019 to 14 April 2020 to gain insight into the cloud activation properties of urban aerosol particles. The median total particle number concentration was 10.1 × 103 cm−3. The median concentrations of cloud condensation nuclei (CCN) at water vapour supersaturation (S) values of 0.1 %, 0.2 %, 0.3 %, 0.5 % and 1.0 % were 0.59, 1.09, 1.39, 1.80 and 2.5 × 103 cm−3, respectively. The CCN concentrations represented 7–27 % of all particles. The CCN concentrations were considerably larger but the activation fractions were systematically substantially smaller than observed in regional or remote locations. The effective critical dry particle diameters (dc,eff) were derived utilising the CCN concentrations and particle number size distributions. Their median values at the five supersaturation values considered were 207, 149, 126, 105 and 80 nm, respectively; all of these diameters were positioned within the accumulation mode of the typical particle number size distribution. Their frequency distributions revealed a single peak for which the geometric standard deviation increased monotonically with S. This broadening indicated high time variability in the activating properties of smaller particles. The frequency distributions also showed fine structure, with several compositional elements that seemed to reveal a consistent or monotonical tendency with S. The relationships between the critical S and dc,eff suggest that urban aerosol particles in Budapest with diameters larger than approximately 130 nm showed similar hydroscopicity to corresponding continental aerosol particles, whereas smaller particles in Budapest were less hygroscopic than corresponding continental aerosol particles. Only modest seasonal cycling in CCN concentrations and activation fractions was seen, and only for large S values. This cycling likely reflects changes in the number concentration, chemical composition and mixing state of the particles. The seasonal dependencies of dc,eff were featureless, indicating that the droplet activation properties of the urban particles remained more or less the same throughout the year. This is again different from what is seen in non-urban locations. Hygroscopicity parameters (κ values) were computed without determining the time-dependent chemical composition of the particles. The median values for κ were 0.15, 0.10, 0.07, 0.04 and 0.02, respectively, at the five supersaturation values considered. The averages suggested that the larger particles were considerably more hygroscopic than the smaller particles. We found that the κ values for the urban aerosol were substantially smaller than those previously reported for aerosols in regional or remote locations. All of these characteristics can be linked to the specific source composition of particles in cities. The relatively large variability in the hygroscopicity parameters for a given S emphasises that the individual values represent the CCN population in ambient air while the average hygroscopicity parameter mainly corresponds to particles with sizes close to the effective critical dry particle diameter.

scholarly journals Seasonality of the particle number concentration and size distribution: a global analysis retrieved from the network of Global Atmosphere Watch (GAW) near-surface observatories

2021 ◽  
Vol 21 (22) ◽  
pp. 17185-17223
Author(s):  
Clémence Rose ◽  
Martine Collaud Coen ◽  
Elisabeth Andrews ◽  
Yong Lin ◽  
Isaline Bossert ◽  
...  
Keyword(s):  
Seasonal Variations ◽  
Particle Number ◽  
Aerosol Particles ◽  
Number Concentration ◽  
Data Availability ◽  
Diel Cycle ◽  
Particle Number Concentration ◽  
Near Surface ◽  
Diel Cycles ◽  
The Impact

Abstract. Aerosol particles are a complex component of the atmospheric system which influence climate directly by interacting with solar radiation, and indirectly by contributing to cloud formation. The variety of their sources, as well as the multiple transformations they may undergo during their transport (including wet and dry deposition), result in significant spatial and temporal variability of their properties. Documenting this variability is essential to provide a proper representation of aerosols and cloud condensation nuclei (CCN) in climate models. Using measurements conducted in 2016 or 2017 at 62 ground-based stations around the world, this study provides the most up-to-date picture of the spatial distribution of particle number concentration (Ntot) and number size distribution (PNSD, from 39 sites). A sensitivity study was first performed to assess the impact of data availability on Ntot's annual and seasonal statistics, as well as on the analysis of its diel cycle. Thresholds of 50 % and 60 % were set at the seasonal and annual scale, respectively, for the study of the corresponding statistics, and a slightly higher coverage (75 %) was required to document the diel cycle. Although some observations are common to a majority of sites, the variety of environments characterizing these stations made it possible to highlight contrasting findings, which, among other factors, seem to be significantly related to the level of anthropogenic influence. The concentrations measured at polar sites are the lowest (∼ 102 cm−3) and show a clear seasonality, which is also visible in the shape of the PNSD, while diel cycles are in general less evident, due notably to the absence of a regular day–night cycle in some seasons. In contrast, the concentrations characteristic of urban environments are the highest (∼ 103–104 cm−3) and do not show pronounced seasonal variations, whereas diel cycles tend to be very regular over the year at these stations. The remaining sites, including mountain and non-urban continental and coastal stations, do not exhibit as obvious common behaviour as polar and urban sites and display, on average, intermediate Ntot (∼ 102–103 cm−3). Particle concentrations measured at mountain sites, however, are generally lower compared to nearby lowland sites, and tend to exhibit somewhat more pronounced seasonal variations as a likely result of the strong impact of the atmospheric boundary layer (ABL) influence in connection with the topography of the sites. ABL dynamics also likely contribute to the diel cycle of Ntot observed at these stations. Based on available PNSD measurements, CCN-sized particles (considered here as either >50 nm or >100 nm) can represent from a few percent to almost all of Ntot, corresponding to seasonal medians on the order of ∼ 10 to 1000 cm−3, with seasonal patterns and a hierarchy of the site types broadly similar to those observed for Ntot. Overall, this work illustrates the importance of in situ measurements, in particular for the study of aerosol physical properties, and thus strongly supports the development of a broad global network of near surface observatories to increase and homogenize the spatial coverage of the measurements, and guarantee as well data availability and quality. The results of this study also provide a valuable, freely available and easy to use support for model comparison and validation, with the ultimate goal of contributing to improvement of the representation of aerosol–cloud interactions in models, and, therefore, of the evaluation of the impact of aerosol particles on climate.

scholarly journals A global analysis of climate-relevant aerosol properties retrieved from the network of GAW near-surface observatories

2020 ◽  
Author(s):  
Paolo Laj ◽  
Clémence Rose ◽  
Alessandro Bigi ◽  
Martine Collaud Coen ◽  
Elisabeth Andrews ◽  
...  
Keyword(s):  
Light Scattering ◽  
Particle Number ◽  
Aerosol Particles ◽  
Number Concentration ◽  
Particle Number Concentration ◽  
Absorption Coefficients ◽  
Near Surface ◽  
The Earth ◽  
Aerosol Properties

&lt;p&gt;Aerosol particles are essential constituents of the Earth&amp;#8217;s atmosphere, impacting the earth radiation balance directly by scattering and absorbing solar radiation, and indirectly by acting as cloud condensation nuclei. In contrast to most greenhouse gases, aerosol particles have short atmospheric residence time resulting in a highly heterogeneous distribution in space and time. There is a clear need to document this variability at regional scale through observations involving, in particular, the in-situ near-surface segment of the atmospheric observations system. This paper will provide the widest effort so far to document variability of climate-relevant in-situ aerosol properties (namely wavelength dependent particle light scattering and absorption coefficients, particle number concentration and particle number size distribution) from all sites connected to the Global Atmosphere Watch network. High quality data from more than 90 stations worldwide have been collected and controlled for quality and are reported for a reference year in 2017, providing a very extended and robust view of the variability of these variables worldwide. The range of variability observed worldwide for light scattering and absorption coefficients, single scattering albedo and particle number concentration are presented together with preliminary information on their long-term trends and comparison with model simulation for the different stations. The scope of the present paper is also to provide the necessary suite of information including data provision procedures, quality control and analysis, data policy and usage of the ground-based aerosol measurements network. It delivers to users of the World Data Centre on Aerosol, the required confidence in data products in the form of a fully-characterized value chain, including uncertainty estimation and requirements for contributing to the global climate monitoring system.&lt;/p&gt;

scholarly journals The challenge of simulating the sensitivity of the Amazonian clouds microstructure to cloud condensation nuclei number concentrations

2019 ◽  
Author(s):  
Pascal Polonik ◽  
Christoph Knote ◽  
Tobias Zinner ◽  
Florian Ewald ◽  
Tobias Kölling ◽  
...  
Keyword(s):  
Cloud Condensation Nuclei ◽  
Regional Scale ◽  
Cloud Droplet ◽  
Number Concentration ◽  
Effective Radius ◽  
Cloud Base ◽  
Condensation Nuclei ◽  
Aerosol Cloud ◽  
Microphysical Properties

Abstract. The realistic representation of cloud-aerosol interactions is of primary importance for accurate climate model projections. The investigation of these interactions in strongly contrasting clean and polluted atmospheric conditions in the Amazon area has been one of the motivations for several field observations, including the airborne Aerosol, Cloud, Precipitation, and Radiation Interactions and DynamIcs of CONvective cloud systems – Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON-CHUVA) campaign based in Manaus, Brazil in September 2014. In this work we combine in situ and remotely sensed aerosol, cloud, and atmospheric radiation data collected during ACRIDICON-CHUVA with regional, online-coupled chemistry-transport simulations to evaluate the model’s ability to represent the indirect effects of biomass burning aerosol on cloud microphysical properties (droplet number concentration and effective radius). We found agreement between modeled and observed median cloud droplet number concentrations (CDNC) for low values of CDNC, i.e., low levels of pollution. In general, a linear relationship between modeled and observed CDNC with a slope of two was found, which means a systematic underestimation of modeled CDNC as compared to measurements. Variability in cloud condensation nuclei (CCN) number concentrations and cloud droplet effective radii (reff) was also underestimated by the model. Modeled effective radius profiles began to saturate around 500 CCN per cm3 at cloud base, indicating an upper limit for the model sensitivity well below CCN concentrations reached during the burning season in the Amazon Basin. Regional background aerosol concentrations were sufficiently high such that the additional CCN emitted from local fires did not cause a notable change in modelled cloud microphysical properties. In addition, we evaluate a parameterization of CDNC at cloud base using more readily available cloud microphysical properties, aimed at in situ observations and satellite retrievals. Our study casts doubt on the validity of regional scale modeling studies of the cloud albedo effect in convective situations for polluted situations where the number concentration of CCN is greater than 500 cm−3.

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