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

Abstract:

An aerosol size distribution dataset (Marinescu et al., Atmos. Chem. Phys. 19, 11985–12006, 2019) was developed using measurements from a scanning mobility particle sizer (SMPS), an aerodynamic particle sizer (APS), and a condensation particle counter (CPC) at the Southern Great Plains (SGP) site for the years 2009 – 2013. We have expanded this data set to develop comprehensive cloud condensation nuclei (CCN) spectra, constrained by concurrent and colocated CCN measurements and size-resolved growth factor measurements from a humidified tandem differential mobility analyzer (HTDMA). It is further refined using comparisons to Aerosol Chemical Speciation Monitor (ACSM) and Nephelometer data. The CCN spectra product spans supersaturations from 0.0001% to 30%, a much higher and lower range than can be measured directly with a CCN counter. Daily and seasonal trends in CCN spectra are examined and considered in light of concurrent trends in size distribution and hygroscopicity. Particular attention is paid to the role of short-term variability, and its implications for interpreting long-term trends in CCN data. We find that generally the CCN spectrum is highly variable, with spectra being conserved only for several hours before becoming randomized, which has implications for the representation of aerosol processes in atmospheric models. The statistical distribution over time of CCN number concentration, at any given supersaturation, is examined and accurately fit with a low number of parameters and related to this randomization process.