Ice Initiation by Aerosol Particles: Measured and Predicted Ice Nuclei Concentrations versus Measured Ice Crystal Concentrations in an Orographic Wave Cloud

Creators: Eidhammer, T.; DeMott, P. J.; Prenni, A. J.; Petters, M. D.; Twohy, C. H.; Rogers, D. C.; Stith, J.; Heymsfield, A.; Wang, Z.; Pratt, K. A.; Prather, K. A.; Murphy, S. M.; Seinfeld, J. H.; Subramanian, R.; Kreidenweis, S. M.

Abstract

The initiation of ice in an isolated orographic wave cloud was compared with expectations based on ice nucleating aerosol concentrations and with predictions from new ice nucleation parameterizations applied in a cloud parcel model. Measurements of ice crystal number concentrations were found to be in good agreement both with measured number concentrations of ice nuclei feeding the clouds and with ice nuclei number concentrations determined from the residual nuclei of cloud particles collected by a counterflow virtual impactor. Using lognormal distributions fitted to measured aerosol size distributions and measured aerosol chemical compositions, ice nuclei and ice crystal concentrations in the wave cloud were reasonably well predicted in a 1D parcel model framework. Two different empirical parameterizations were used in the parcel model: a parameterization based on aerosol chemical type and surface area and a parameterization that links ice nuclei number concentrations to the number concentrations of particles with diameters larger than 0.5 μm. This study shows that aerosol size distribution and composition measurements can be used to constrain ice initiation by primary nucleation in models. The data and model results also suggest the likelihood that the dust particle mode of the aerosol size distribution controls the number concentrations of the heterogeneous ice nuclei, at least for the lower temperatures examined in this case.

Additional Information

© 2010 American Meteorological Society. Manuscript received 20 July 2009, in final form 16 April 2010. This work has been supported by the National Science Foundation (NSF) Science and Technology Center for Multi-Scale Modeling of Atmospheric Processes,managed by Colorado State University under cooperative agreement ATM-0425247, NSF Grant ATM-0611936, and by the NASA MAP (Modeling and Analysis Program) Grant NNG06GB60G. C. Twohy was supported by NSF Grant ATM-0612605. K. A. Pratt and K. A. Prather acknowledge NSF for support of ICE-L (ATM-0650659), A-ATOFMS development (ATM-0321362), and a graduate research fellowship for K. A. Pratt. S. M. Murphy and J. H. Seinfeld were supported by NSF Grant ATM-0340832. R. Subramanian was supported by NSF Grant ATM-0612605. Z. Wang was supported by NSF Grant ATM-0645644. The primary sponsor of ICE-L is the U.S. National Science Foundation. The involvement of the NSF-sponsored Lower Atmospheric Observing Facilities from the University of Wyoming and those managed and operated by the National Center for Atmospheric Research (NCAR) Earth Observing Laboratory (EOL) is acknowledged. The data were downloaded from the ICE-L data archive, which is maintained by NCAR EOL. Sam Haimov is acknowledged for providing the radar data; finally, we also would like to thank Jeff Snider for helpful review of a draft version of this paper.

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