Our project for the Atmospheric Radiation Measurement (ARM) Program consists of developing and demonstrating improved cloud formation parameterizations using a single-column model (SCM), a cumulus ensemble model CEM and ARM data. These two models can be driven with large-scale forcing (e.g., vertical motion) as observed in ARM. Each model produces a field of clouds and the associated radiation and precipitation fields. The SCM does so through its physical parameterizations, while the CEM does so by directly simulating convective cloud circulations. The improved parameterizations tested in this way will be further tested and applied in the Colorado State University (CSU) general circulation model (GCM). To carry out this research plan, we need to attend to several tasks: develop improved cloudiness parameterizations, develop improvements to the CEM, with emphasis on cloud-radiation interactions, drive both models with the ARM data, transfer the improved parameterizations developed in this way to the CSU GCM. In this brief report, we mention our efforts and progress in each of these areas.

Single-column model and cumulus ensemble model simulations of GATE data

In this article, we present the first maps of the global distribution of the cloud liquid and ice water contents of the atmosphere. It is shown that the cloud microphysics package produces realistic distributions of both moisture variables. We axe presently adapting the present model so that long-term simulations with the CSU GCM may be made. In the near future, we plan to couple the cloud liquid and ice water contents prognosed by the cloud microphysics package with the cloud fraction and cloud optical properties.

Impact of cloud microphysics on the CSU GCM atmospheric moisture budget

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Impact of cloud microphysics on the CSU GCM atmospheric moisture budget