Articles | Volume 22, issue 9
https://doi.org/10.5194/acp-22-6197-2022
https://doi.org/10.5194/acp-22-6197-2022
Research article
 | 
11 May 2022
Research article |  | 11 May 2022

Long- and short-term temporal variability in cloud condensation nuclei spectra over a wide supersaturation range in the Southern Great Plains site

Russell J. Perkins, Peter J. Marinescu, Ezra J. T. Levin, Don R. Collins, and Sonia M. Kreidenweis

Data sets

Southern Great Plains Merged and Extended Cloud Condensation Nuclei Data Russell J. Perkins, Peter J. Marinescu, Ezra J. T. Levin, Don R. Collins, and Sonia M. Kreidenweis https://doi.org/10.5439/1832908

ARM: AOS: condensation particle counter C. Salwen, M. Boyer, S. Springston, C. Kuang, and E. Andrews https://doi.org/10.5439/1025152

ARM: Aerosol Observing System (AOS): aerosol data, 1-min, mentor-QC applied D. Hageman, B. Behrens, S. Smith, J. Uin, C. Salwen, A. Koontz, A. Jefferson, T. Watson, A. Sedlacek, C. Kuang, M. Dubey, S. Springston, and G. Senum https://doi.org/10.5439/1025259

ARM: Tandem Differential Mobility Analyzer: size-resolved concentrations D. Collins https://doi.org/10.5439/1025303

ARM: Tandem Differential Mobility Analyzer Aerosol Particle Sizer D. Collins https://doi.org/10.5439/1150275

AOS humidified nephelometer, harmonized A. Koontz, C. Flynn, J. Uin, and A. Jefferson https://doi.org/10.5439/1228051

Aerosol Chemical Speciation Monitor, mentor processed, .c2 M. Zawadowicz and J. Howie https://doi.org/10.5439/1763029524

SGP Merged Aerosol Size Distribution (CPC+SMPS+APS) P. Marinescu and E. Levin https://doi.org/10.5439/1511037

Southern Great Plains Merged and Extended Cloud Condensation Nuclei Data R. Perkins https://doi.org/10.5439/1832908

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Short summary
We used 5 years (2009–2013) of aerosol and cloud condensation nuclei (CCN) data from a total of seven instruments housed at the Southern Great Plains site, which were merged into a quality-controlled, continuous dataset of CCN spectra at ~45 min resolution. The data cover all seasons, are representative of a rural, agricultural mid-continental site, and are useful for model initialization and validation. Our analysis of this dataset focuses on seasonal and hourly variability.
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