Articles | Volume 22, issue 9
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

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Cited articles

Alexandrov, M. D., Marshak, A., Cairns, B., Lacis, A. A., and Carlson, B. E.: Scaling Properties of Aerosol Optical Thickness Retrieved from Ground-Based Measurements, J. Atmos. Sci., 61, 1024–1039,<1024:SPOAOT>2.0.CO;2, 2004. 
Alexandrov, M. D., Geogdzhayev, I. V., Tsigaridis, K., Marshak, A., Levy, R., and Cairns, B.: New Statistical Model for Variability of Aerosol Optical Thickness: Theory and Application to MODIS Data over Ocean, J. Atmos. Sci., 73, 821–837,, 2016. 
Anderson, T. L., Charlson, R. J., Winker, D. M., Ogren, J. A., and Holmén, K.: Mesoscale Variations of Tropospheric Aerosols, J. Atmos. Sci., 60, 119–136,<0119:MVOTA>2.0.CO;2, 2003. 
Box, G. E. P., Jenkins, G. M., Reinsel, G. C., and Ljung, G. M.: Time Series Analysis: Forecasting and Control, 5th Edition, John Wiley and Sons Inc., Hoboken, New Jersey, 712 pp., ISBN 978-1-118-67502-1, 2015. 
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.
Final-revised paper