A Large-Droplet Mode and Prognostic Number Concentration of Cloud Droplets in the Colorado State University Regional Atmospheric Modeling System (RAMS). Part II: Sensitivity to a Colorado Winter Snowfall Event

Abstract

This paper is the second in a two-part series describing recent additions to the microphysics module of the Regional Atmospheric Modeling System (RAMS) at Colorado State University. These changes include the addition of a large-cloud-droplet mode (40?80 ?m in diameter) into the liquid-droplet spectrum and the parameterization of cloud-droplet nucleation through activation of cloud condensation nuclei (CCN) and giant CCN (GCCN). The large-droplet mode was introduced to represent more precisely the natural dual mode of the cloud-droplet distribution. The parameterized droplet nucleation replaces the former estimation of cloud-droplet formation solely from supersaturation calculations. In Part I of this series, details of the improvements to the microphysics were presented, including the set of equations governing the development of cloud droplets in the Lagrangian parcel model that was employed to parameterize this complex process. Supercell simulations were examined with respect to the model sensitivity to the presence and concentration of large cloud droplets, CCN, and GCCN. Part II examines the sensitivity of the model microphysics to imposed aerosol variations in a wintertime snowfall event that occurred over Colorado on 28?29 February 2004. Model analyses and sensitivity are compared with the real-time forecast version 4.3 of RAMS as well as selected snowpack telemetry (SNOTEL) accumulated precipitation data and surface data from Storm Peak Laboratory in Steamboat Springs, Colorado.