CCN spectra at ENA
1 June 2018 - 28 February 2019
Lead Scientist: James Hudson
One or two Desert Research Institute's (DRI) cloud condensation nuclei (CCN) spectrometers and a differential mobility analyzer (DMA) made continuous (24/7) measurements at ARM's Eastern North Atlantic observatory for a summer and winter month to obtain a record of CCN and aerosol spectra that, taken together, can provide continuous records of kappa, or particle hygroscopicity.
The DRI CCN spectrometers are continuous-flow, thermal-gradient, diffusion chambers that internally simulate supersaturations of natural clouds. Cloud droplets grow to micrometer sizes on the submicrometer CCN. These droplets pass out of the chamber through a white-light beam where they are detected by a photomultiplier at near-forward scattering angles. Droplets are counted according to their signal strength (voltage), which is proportional to their size, which is inversely related to crucial supersaturation, Sc, which is how CCN are parameterized. Signals are sorted into 128 or 256 channels and concentration within each channel is recorded. Instruments are calibrated with monodisperse hygroscopic particles of pure known composition (e.g., NaCl) and of various sizes for which Sc is known. The resulting calibration curve is used to convert voltage bin to Sc to continuously and simultaneously produce CCN spectra over the range 0.01 to 2% S, which is sufficient for most clouds.
The CCN spectrometers have often seen bimodal distributions similar to dry aerosol size distributions from a DMA. These distributions can be overlain by converting the sizes to Sc. This transformation requires kappa, so various kappa values are used to tune to the best match of the overlay of the two simultaneous measurements for each minute or so of the DMA measurement. CCN can be obtained at faster rates so several records are averages to compare with the DMA. Often this requires different kappa values at different parts of the spectra. When spectra are bimodal, typically a different kappa is used for each of the two modes.
Scientists have collected these measurements from aircraft and at the ground at ARM Southern Great Plains observatory. They have compared the modality of the CCN or DMA spectra with various measurements of clouds and cloudiness obtained from a total sky imager, multipulse lidar, scanning cloud radar, and pyranometer. They have found bimodal spectra to be associated with greater cloudiness and unimodal spectra associated with clear skies or few clouds. This field campaign extended these measurements to a maritime area—ARM's ENA observatory.
Campaign participants also compared remote cloud microphysics measurements available—mainly, at least, cloud droplet concentration, Nc. Comparisons between Nc and the detailed CCN spectra available from the DRI instruments reveal cloud effective supersaturations, Seff, which vary considerably. Seff then defines CCN for each cloud parcel. However, another estimate of Seff can be obtained from the Sc of the minimum concentration between the two modes of bimodal CCN spectra. Unlike such estimates from DMA spectra, particle composition estimates are not needed because the CCN spectra are directly read out in terms of Sc. Differences between these two Seff estimates can reveal interesting aspects of cloud microphysics and the cloud processes that cause bimodality. Kappa variations reveal information about particle composition and about the cloud processes that cause aerosol bimodality.