Evaluation of Fractional Cloudiness Parameterizations for Use in a Mesoscale Model

David M. Mocko Colorado State University, Fort Collins, Colorado

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William R. Cotton Colorado State University, Fort Collins, Colorado

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Abstract

The Regional Atmospheric Modeling System (RAMS), developed at Colorado State University, was used to predict boundary-layer clouds and diagnose fractional cloudiness. The primary case study for this project occurred on 7 July 1987 off the coast of southern California. On this day, a transition in the type of boundary-layer cloud was observed from a clear area, to an area of small scattered cumulus, to an area of broken stratocumulus, and finally, to an area of solid stratocumulus. This case study occurred during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment field study. RAMS was configured as a nested-grid mesoscale model with a fine grid having 5-km horizontal grid spacing covering the transition area.

Various fractional cloudiness schemes found in the literature were implemented into RAMS and tested against each other to determine which best represented observed conditions. The complexities of the parameterizations used to diagnose the fractional cloudiness varied from simple functions of relative humidity to a function of the model's subgrid variability. It was found that some of the simpler schemes identified the cloud transition better, while others performed poorly.

Abstract

The Regional Atmospheric Modeling System (RAMS), developed at Colorado State University, was used to predict boundary-layer clouds and diagnose fractional cloudiness. The primary case study for this project occurred on 7 July 1987 off the coast of southern California. On this day, a transition in the type of boundary-layer cloud was observed from a clear area, to an area of small scattered cumulus, to an area of broken stratocumulus, and finally, to an area of solid stratocumulus. This case study occurred during the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment field study. RAMS was configured as a nested-grid mesoscale model with a fine grid having 5-km horizontal grid spacing covering the transition area.

Various fractional cloudiness schemes found in the literature were implemented into RAMS and tested against each other to determine which best represented observed conditions. The complexities of the parameterizations used to diagnose the fractional cloudiness varied from simple functions of relative humidity to a function of the model's subgrid variability. It was found that some of the simpler schemes identified the cloud transition better, while others performed poorly.

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