Development and Testing of Physical Algorithms for Cloud Forecasting on the Mesoscale
Final rept. 15 Jan 95-14 Jan 98
COLORADO STATE UNIV FORT COLLINS DEPT OF ATMOSPHERIC SCIENCE
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This research has focused on the development of a comprehensive mesoscale numerical weather prediction NWP system for forecasting clouds anywhere in the world. The host model for performing this research, RAMS, has been extended to a global, interactive nested grid forecast model that is capable of running on both shared-memory and distributive memory computers. This unique NWP model is capable of being initialized globally and then being able to telescopically nest anywhere on earth and provide high resolution 24 to 48h forecasts of clouds and precipitation. Some of the physical modules developed under support of this project include a cumulus parameterization scheme designed specifically for use in an interactive nested grid model, a mesoscale convective system parameterization scheme that interfaces with the cumulus parameterization scheme, a new, computationally fast, two moment, stochastic microphysics parameterization scheme, and a new two-stream cloud-radiation model that interfaces directly with the hydrometeor distributions in the microphysics model. The new cloud forecasting scheme has been tested in applications to Arctic stratus clouds, and mid-latitude and tropical cirrus. The model has been shown to perform very well and moreover, provide new insights into the physics and dynamics of those cloud systems.