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

2021 ◽  
Author(s):  
Russell J. Perkins ◽  
Peter J. Marinescu ◽  
Ezra J. T. Levin ◽  
Don R. Collins ◽  
Sonia M. Kreidenweis
Keyword(s):  
Great Plains ◽  
Statistical Power ◽  
Cloud Condensation Nuclei ◽  
Department Of Energy ◽  
Quality Data ◽  
Size Distributions ◽  
Condensation Nuclei ◽  
Seed Formation ◽  
Southern Great Plains ◽  
Seasonal And Diurnal Variations

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

scholarly journals Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

2021 ◽  
Vol 13 (12) ◽  
pp. 2309
Author(s):  
Jingjing Tian ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Likun Wang ◽  
Rusen Öktem ◽  
...  
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Detection Threshold ◽  
Department Of Energy ◽  
Surface Reflectance ◽  
Cloud Detection ◽  
Southern Great Plains ◽  
Clear Sky ◽  
Shallow Cumulus ◽  
Stereo Cameras

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ∆R. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

scholarly journals Estimating cloud condensation nuclei number concentrations using aerosol optical properties: role of particle number size distribution and parameterization

2019 ◽  
Vol 19 (24) ◽  
pp. 15483-15502 ◽  
Author(s):  
Yicheng Shen ◽  
Aki Virkkula ◽  
Aijun Ding ◽  
Krista Luoma ◽  
Helmi Keskinen ◽  
...  
Keyword(s):  
Optical Properties ◽  
Size Distribution ◽  
Cloud Condensation Nuclei ◽  
Size Distributions ◽  
Condensation Nuclei ◽  
Aerosol Optical Properties ◽  
Average Bias ◽  
Angstrom Exponent ◽  
Ångström Exponent ◽  
Ångstrom Exponent

Abstract. The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between NCCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (σsp) of PM10 particles. The analysis first showed that the dependence of NCCN on supersaturation (SS) can be described by a logarithmic fit in the range SS <1.1 %, without any theoretical reasoning. The relationship between NCCN and AOPs was parameterized as NCCN≈((286±46)SAE ln(SS/(0.093±0.006))(BSF − BSFmin) + (5.2±3.3))σsp, where BSFmin is the minimum BSF, in practice the 1st percentile of BSF data at a site to be analyzed. At the lowest supersaturations of each site (SS ≈0.1 %), the average bias, defined as the ratio of the AOP-derived and measured NCCN, varied from ∼0.7 to ∼1.9 at most sites except at a Himalayan site where the bias was >4. At SS >0.4 % the average bias ranged from ∼0.7 to ∼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, ∼1.4–1.9. In other words, at SS >0.4 % NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured NCCN varied from ∼0.5 to ∼0.8. To study the physical explanation of the relationships between NCCN and AOPs, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation showed that the relationships of NCCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of NCCN and AOPs were similar to those of the observed ones.

scholarly journals Quantifying aerosol size distributions and their temporal variability in the Southern Great Plains, USA

2019 ◽  
Vol 19 (18) ◽  
pp. 11985-12006 ◽  
Author(s):  
Peter J. Marinescu ◽  
Ezra J. T. Levin ◽  
Don Collins ◽  
Sonia M. Kreidenweis ◽  
Susan C. van den Heever
Keyword(s):  
Size Distribution ◽  
Great Plains ◽  
Diurnal Cycle ◽  
Particle Formation ◽  
Aerosol Size Distribution ◽  
Size Distributions ◽  
New Particle Formation ◽  
Scanning Mobility Particle Sizer ◽  
Southern Great Plains ◽  
Particle Sizer

Abstract. A quality-controlled, 5-year dataset of aerosol number size distributions (particles with diameters (Dp) from 7 nm through 14 µm) was developed using observations from a scanning mobility particle sizer, aerodynamic particle sizer, and a condensation particle counter at the Department of Energy's Southern Great Plains (SGP) site. This dataset was used for two purposes. First, typical characteristics of the aerosol size distribution (number, surface area, and volume) were calculated for the SGP site, both for the entire dataset and on a seasonal basis, and size distribution lognormal fit parameters are provided. While the median size distributions generally had similar shapes (four lognormal modes) in all the seasons, there were some significant differences between seasons. These differences were most significant in the smallest particles (Dp<30 nm) and largest particles (Dp>800 nm). Second, power spectral analysis was conducted on this long-term dataset to determine key temporal cycles of total aerosol concentrations, as well as aerosol concentrations in specified size ranges. The strongest cyclic signal was associated with a diurnal cycle in total aerosol number concentrations that was driven by the number concentrations of the smallest particles (Dp<30 nm). This diurnal cycle in the smallest particles occurred in all seasons in ∼50 % of the observations, suggesting a persistent influence of new particle formation events on the number concentrations observed at the SGP site. This finding is in contrast with earlier studies that suggest new particle formation is observed primarily in the springtime at this site. The timing of peak concentrations associated with this diurnal cycle was shifted by several hours depending on the season, which was consistent with seasonal differences in insolation and boundary layer processes. Significant diurnal cycles in number concentrations were also found for particles with Dp between 140 and 800 nm, with peak concentrations occurring in the overnight hours, which were primarily associated with both nitrate and organic aerosol cycles. Weaker cyclic signals were observed for longer timescales (days to weeks) and are hypothesized to be related to the timescales of synoptic weather variability. The strongest periodic signals (3.5–5 and 7 d cycles) for these longer timescales varied depending on the season, with no cyclic signals and the lowest variability in the summer.

scholarly journals Classification of aerosol population type and cloud condensation nuclei properties in a coastal California littoral environment using an unsupervised cluster model

2019 ◽  
Author(s):  
Samuel A. Atwood ◽  
Sonia M. Kreidenweis ◽  
Paul J. DeMott ◽  
Markus D. Petters ◽  
Gavin C. Cornwell ◽  
...  
Keyword(s):  
Cluster Model ◽  
Particle Number ◽  
Cloud Condensation Nuclei ◽  
Sea Breeze ◽  
Northern Coast ◽  
Size Distributions ◽  
Condensation Nuclei ◽  
Entire Study ◽  
Total Particle Number ◽  
Total Particle

Abstract. Aerosol particle and cloud condensation nuclei (CCN) measurements from a littoral location on the northern coast of California at Bodega Bay Marine Laboratory (BML) are presented for approximately six weeks of observations during the CalWater-2015 field campaign. A combination of aerosol microphysical and meteorological parameters was used to classify variability in the properties of the BML surface aerosol using a K-means cluster model. Eight aerosol population types were identified that were associated with a range of impacts from both marine and terrestrial sources. Average measured total particle number concentrations, size distributions, hygroscopicities, and activated fraction spectra between 0.08 % and 1.1 % supersaturation are given for each of the identified aerosol population types, along with meteorological observations and transport pathways during time periods associated with each type. Five terrestrially influenced aerosol population types represented different degrees of aging of the continental outflow from the coast and interior of California and their appearance at the BML site was often linked to changes in wind direction and transport pathway. In particular, distinct aerosol populations, associated with diurnal variations in source region induced by land/sea-breeze shifts, were classified by the clustering technique. A terrestrial type representing fresh emissions, and/or a recent new particle formation event, occurred in approximately 10 % of the observations. Over the entire study period, three marine influenced population types were identified that typically occurred when the regular diurnal land/sea-breeze cycle collapsed and BML was continuously ventilated by air masses from marine regions for multiple days. These marine types differed from each other primarily in the degree of cloud processing evident in the size distributions, and in the presence of an additional large-particle mode for the type associated with the highest wind speeds. One of the marine types was associated with a multi-day period during which an atmospheric river made landfall at BML. The generally higher total particle number concentrations but lower activated fractions of four of the terrestrial types yielded similar CCN number concentrations to two of the marine types for supersaturations below about 0.4 %. Despite quite different activated fraction spectra, the two remaining marine and terrestrial types had CCN spectral number concentrations very similar to each other, due in part to higher number concentrations associated with the terrestrial type.

scholarly journals Simultaneous measurements of aerosol size distributions at three sites in the European high Arctic

2019 ◽  
Vol 19 (11) ◽  
pp. 7377-7395 ◽  
Author(s):  
Manuel Dall'Osto ◽  
David C. S. Beddows ◽  
Peter Tunved ◽  
Roy M. Harrison ◽  
Angelo Lupi ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Cloud Condensation Nuclei ◽  
High Arctic ◽  
The Arctic ◽  
Research Station ◽  
Size Distributions ◽  
Aerosol Formation ◽  
Condensation Nuclei ◽  
Main Mode ◽  
Accumulation Mode

Abstract. Aerosols are an integral part of the Arctic climate system due to their direct interaction with radiation and indirect interaction through cloud formation. Understanding aerosol size distributions and their dynamics is crucial for the ability to predict these climate relevant effects. When of favourable size and composition, both long-range-transported – and locally formed particles – may serve as cloud condensation nuclei (CCN). Small changes of composition or size may have a large impact on the low CCN concentrations currently characteristic of the Arctic environment. We present a cluster analysis of particle size distributions (PSDs; size range 8–500 nm) simultaneously collected from three high Arctic sites during a 3-year period (2013–2015). Two sites are located in the Svalbard archipelago: Zeppelin research station (ZEP; 474 m above ground) and the nearby Gruvebadet Observatory (GRU; about 2 km distance from Zeppelin, 67 m above ground). The third site (Villum Research Station at Station Nord, VRS; 30 m above ground) is 600 km west-northwest of Zeppelin, at the tip of north-eastern Greenland. The GRU site is included in an inter-site comparison for the first time. K-means cluster analysis provided eight specific aerosol categories, further combined into broad PSD classes with similar characteristics, namely pristine low concentrations (12 %–14 % occurrence), new particle formation (16 %–32 %), Aitken (21 %–35 %) and accumulation (20 %–50 %). Confined for longer time periods by consolidated pack sea ice regions, the Greenland site GRU shows PSDs with lower ultrafine-mode aerosol concentrations during summer but higher accumulation-mode aerosol concentrations during winter, relative to the Svalbard sites. By association with chemical composition and cloud condensation nuclei properties, further conclusions can be derived. Three distinct types of accumulation-mode aerosol are observed during winter months. These are associated with sea spray (largest detectable sizes, >400 nm), Arctic haze (main mode at 150 nm) and aged accumulation-mode (main mode at 220 nm) aerosols. In contrast, locally produced particles, most likely of marine biogenic origin, exhibit size distributions dominated by the nucleation and Aitken mode during summer months. The obtained data and analysis point towards future studies, including apportioning the relative contribution of primary and secondary aerosol formation processes and elucidating anthropogenic aerosol dynamics and transport and removal processes across the Greenland Sea. In order to address important research questions in the Arctic on scales beyond a singular station or measurement events, it is imperative to continue strengthening international scientific cooperation.

Sign in / Sign up

Export Citation Format

Share Document