A new single-moment microphysics scheme for cloud-resolving models using observed dependence of ice concentration on temperature.

Abstract:

The representation of microphysics, especially ice microphysics, remains one of the major uncertainties in cloud-resolving models (CRMs). Most of the cloud schemes use the so-called bulk microphysics approach, in which a few moments of such distributions are used as the prognostic variables. The System for Atmospheric Modeling (SAM) is the CRM that employs two such schemes. The single-moment scheme, which uses only mass for each of the water phases, and the two-moment scheme, which adds the particle concentration for each of the hydrometeor category. Of the two, the single-moment scheme is much more computationally efficient as it uses only two prognostic microphysics variables compared to ten variables used by the two-moment scheme. The efficiency comes from a rather considerable oversimplification of the microphysical processes. For instance, only a sum of the liquid and icy cloud water is predicted with the temperature used to diagnose the mixing ratios of different hydrometeors. The main motivation for using such simplified microphysics has been computational efficiency, especially in the applications of SAM as the super-parameterization in global climate models. Recently, we have extended the single-moment microphysics by adding only one additional prognostic variable, which has, nevertheless, allowed us to separate the cloud ice from liquid water. We made use of some of the recent observations of ice microphysics collected at various parts of the world to parameterize several aspects of ice microphysics that have not been explicitly represented before in our sing-moment scheme. For example, we use the observed broad dependence of ice concentration on temperature to diagnose the ice concentration in addition to prognostic mass. Also, there is no artificial separation between the pristine ice and snow, often used by bulk models. Instead we prescribed the ice size spectrum as the gamma distribution, with the distribution shape parameter controlled by the temperature using the analytic expression also derived from observations. The new scheme has been implemented in SAM and has been tested and compared against the SAM’s single and two moment microphysics schemes in the simulations using the forcing data from several field campaigns. The preliminary results of such simulations will be presented.