11th Conference on Atmospheric Radiation and the 11th Conference on Cloud Physics

Tuesday, 4 June 2002: 10:59 AM
Cirrus parcel model comparison Phase 2
Ruei-Fong Lin, UMBC/GEST Center, Greenbelt, MD; and D. O. Starr, P. J. DeMott, R. Cotton, E. Jensen, B. Karcher, and X. Liu
Poster PDF (96.7 kB)
The Cirrus Parcel Model Comparison Project, a project of GEWEX Cloud System Study Working Group on Cirrus Cloud Systems, is an international effort to assess current understanding of cirrus microphysical modeling. The project involves the systematic comparison of state-of-the-art parcel models of cirrus cloud microphysical initiation and development, specifically models that explicitly resolve size distributions of the ice crystals and aerosols. In Phase 1 of this project, we established the ranges of differences among models for a single assumed sulfuric acid haze particle distribution and identified the key components resulting in model variability; e.g., the homogeneous freezing formulation, particularly the gradient of the nucleation rate with respect to the solution concentration; haze particle growth modeling; and the deposition coefficient (accommodation coefficient) for water molecules on an ice surface. In Phase 2, the model response to specification of the background aerosol size distribution is investigated, including aerosol number density, modal radius and distribution width. In addition, the model sensitivity to a frequently-adopted empirical parameter which accounts for the non-ideal ionic effect on homogeneous nucleation temperature, is examined. This test can be roughly interpreted as a sensitivity study on the aerosol species (composition). Effects of aerosol size distribution on cirrus initiation and cirrus microphysical properties will be discussed. Moreover, the overall sensitivity of cirrus properties to aerosol distribution will be compared with the sensitivity to updraft speed and the deposition coefficient, which have been identified in Phase 1 as the two most critical parameters in cirrus initiation modeling.

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