Chemical and physical influences on aerosol activation in liquid clouds: a study based on observations from the Jungfraujoch, Switzerland

Hoyle, C. R.; Webster, Clare; Rieder, Harald E.; Nenes, Athanasios; Hammer, E.; Herrmann, Erik; Gysel, M.; Bukowiecki, Nicolas; Weingärtner, E.; Steinbacher, Martin; Baltensperger, Urs

doi:10.5194/acp-16-4043-2016

Cited by 20 publications

(23 citation statements)

References 73 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The black solid line represents the precipitation rate (mm h -1 ) recorded from the MeteoSwiss observation station for each 10-min interval at WFJ between 1 and 8 of March 2019. Figure 3, the observed CCN concentrations tend to be low (∽10 2 cm −3 ) even at the highest SS (0.74%), which is expected given that WFJ is a remote continental measurement site with CCN concentrations that are typical of FT continental air (Jurányi et al, 2010(Jurányi et al, , 2011Hoyle et al, 2016;Fanourgakis et al, 2019). This is again in line with the measured monthly median values of CCN (at SS=0.71%) reported by Jurányi et al is a site frequently located in the FT, sudden fluctuations in the CCN concentrations could be related to the vertical transport of freshly emitted particles (e.g., wood burning or vehicle emissions) from the valley floor in Davos.…”

Section: Resultssupporting

confidence: 52%

“…Given the importance of droplet number for the radiative cloud properties and microphysical evolution of Alpine MPCs, it is essential to understand the main aerosol and dynamics properties that drive droplet formation. A limited number of studies exist that discuss this very important topic, focusing though on liquid-phase clouds (Hammer et al, 2014(Hammer et al, , 2015Hoyle et al, 2016). Hoyle et al (2016) demonstrated that 79% of the variance in droplet number observed in warm tropospheric clouds formed over the high-altitude research station of Jungfraujoch (3450 m a.s.l.)…”

Section: Introductionmentioning

confidence: 99%

“…A limited number of studies exist that discuss this very important topic, focusing though on liquid-phase clouds (Hammer et al, 2014(Hammer et al, , 2015Hoyle et al, 2016). Hoyle et al (2016) demonstrated that 79% of the variance in droplet number observed in warm tropospheric clouds formed over the high-altitude research station of Jungfraujoch (3450 m a.s.l.) in the Swiss Alps can be explained by the potential CCN number concentrations (i.e.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the drivers of droplet variability in Alpine mixed-phase clouds

Georgakaki¹,

Bougiatioti²,

Wieder³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Droplet formation provides a direct microphysical link between aerosols and clouds (liquid or mixed phase), and its adequate description poses a major challenge for any atmospheric model. Observations are critical for evaluating and constraining the process. Towards this, aerosol size distributions, cloud condensation nuclei, hygroscopicity and lidar-derived vertical velocities were observed in Alpine mixed-phase clouds during the Role of Aerosols and Clouds Enhanced by Topography on Snow (RACLETS) field campaign in the Davos, Switzerland region during February and March 2019. Data from the mountain-top site of Weissfluhjoch (WFJ) and the valley site of Davos Wolfgang are studied. These observations are coupled with a state-of-the art droplet activation parameterization to investigate the aerosol-cloud droplet link in mixed-phase clouds. The mean CCN-derived hygroscopicity parameter, κ, at WFJ ranges between 0.2–0.3, consistent with expectations for continental aerosol. κ tends to decrease with size, possibly from an enrichment in organic material associated with the vertical transport of fresh ultrafine particle emissions (likely from biomass burning) from the valley floor in Davos. The parameterization provides droplet number that agrees with observations to within ~25 %. We also find that the susceptibility of droplet formation to aerosol concentration and vertical velocity variations can be appropriately described as a function of the standard deviation of the distribution of updraft velocities, σw, as the droplet number never exceeds a characteristic limit, termed limiting droplet number, of ~150–550 cm−3, which depends solely on σw. We also show that high aerosol levels in the valley, most likely from anthropogenic activities, increase cloud droplet number, reduce cloud supersaturation (<0.1 %) and shift the clouds to a state that is less susceptible to aerosol and become very sensitive to vertical velocity variations. The transition from aerosol to velocity-limited regime depends on the ratio of cloud droplet number to the limiting droplet number, as droplet formation becomes velocity-limited when this ratio exceeds 0.5. Under such conditions, droplet size tends to be minimal, reducing the likelihood that large drops are present that promote glaciation through rime splintering and droplet shattering. Identifying regimes where droplet number variability is dominated by dynamical – rather than aerosol – changes is key for interpreting and constraining when and which types of aerosol effects on clouds are active.

show abstract

Section: Resultssupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

On the drivers of droplet variability in Alpine mixed-phase clouds

Georgakaki¹,

Bougiatioti²,

Wieder³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…The same data can be used to derive the direct sensitivity of cloud to aerosol perturbations for model and satellite evaluation 72,79 , and to understand the relative contribution of aerosol and dynamic parameters in the variability of droplet formation 80 .…”

Section: Usage Notesmentioning

confidence: 99%

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

et al. 2017

Self Cite

View full text Add to dashboard Cite

Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.

show abstract

“…Table 1 also lists the collection efficiency (CE) of each mass spectrometer. The CE depends on the transmission of particles into the instrument and their chemical composition and is hence an instrument and site-specific factor (Huffman et al, 2005;Middlebrook et al, 2012).…”

Section: Measurement Sites and Instrumentationmentioning

confidence: 99%

Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories

et al. 2018

Self Cite

View full text Add to dashboard Cite

Abstract. Aerosol–cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Here we present a data set – ready to be used for model validation – of long-term observations of CCN number concentrations, particle number size distributions and chemical composition from 12 sites on 3 continents. Studied environments include coastal background, rural background, alpine sites, remote forests and an urban surrounding. Expectedly, CCN characteristics are highly variable across site categories. However, they also vary within them, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behaviour, most continental stations exhibit very similar activation ratios (relative to particles > 20 nm) across the range of 0.1 to 1.0 % supersaturation. At the coastal sites the transition from particles being CCN inactive to becoming CCN active occurs over a wider range of the supersaturation spectrum. Several stations show strong seasonal cycles of CCN number concentrations and particle number size distributions, e.g. at Barrow (Arctic haze in spring), at the alpine stations (stronger influence of polluted boundary layer air masses in summer), the rain forest (wet and dry season) or Finokalia (wildfire influence in autumn). The rural background and urban sites exhibit relatively little variability throughout the year, while short-term variability can be high especially at the urban site. The average hygroscopicity parameter, κ, calculated from the chemical composition of submicron particles was highest at the coastal site of Mace Head (0.6) and lowest at the rain forest station ATTO (0.2–0.3). We performed closure studies based on κ–Köhler theory to predict CCN number concentrations. The ratio of predicted to measured CCN concentrations is between 0.87 and 1.4 for five different types of κ. The temporal variability is also well captured, with Pearson correlation coefficients exceeding 0.87. Information on CCN number concentrations at many locations is important to better characterise ACI and their radiative forcing. But long-term comprehensive aerosol particle characterisations are labour intensive and costly. Hence, we recommend operating “migrating-CCNCs” to conduct collocated CCN number concentration and particle number size distribution measurements at individual locations throughout one year at least to derive a seasonally resolved hygroscopicity parameter. This way, CCN number concentrations can only be calculated based on continued particle number size distribution information and greater spatial coverage of long-term measurements can be achieved.

show abstract

Chemical and physical influences on aerosol activation in liquid clouds: a study based on observations from the Jungfraujoch, Switzerland

Cited by 20 publications

References 73 publications

On the drivers of droplet variability in Alpine mixed-phase clouds

On the drivers of droplet variability in Alpine mixed-phase clouds

Collocated observations of cloud condensation nuclei, particle size distributions, and chemical composition

Long-term cloud condensation nuclei number concentration, particle number size distribution and chemical composition measurements at regionally representative observatories

Contact Info

Product

Resources

About