A General Framework for Convective Trigger Functions

Robert F. Rogers Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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J. M. Fritsch Department of Meteorology, The Pennsylvania State University, University Park, Pennsylvania

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Abstract

A general framework for the trigger function used in convective parameterization routines in mesoscale models is proposed. The framework is based on the diagnosis of the accessibility of potential buoyant energy. Specifically, the trigger function 1) estimates the magnitude of the largest vertical velocity perturbation from a source layer and 2) calculates the total amount of inhibition between the source layer and the level of free convection. The calculation of perturbation magnitude accounts for such factors as subgrid-scale inhomogeneities, a convective boundary layer, and convergence within the source layer. Specific formulations to quantify these factors are proposed.

The trigger is tested in a simulation using the PSU–NCAR mesoscale model MM5. The event chosen for simulation is a summertime case exhibiting a variety of environments. The results of this simulation are compared with a simulation using the Fritsch–Chappell (FC) trigger function. It is found that decisions made by the new trigger function are more physically consistent with the local environment than decisions made by the FC trigger.

Abstract

A general framework for the trigger function used in convective parameterization routines in mesoscale models is proposed. The framework is based on the diagnosis of the accessibility of potential buoyant energy. Specifically, the trigger function 1) estimates the magnitude of the largest vertical velocity perturbation from a source layer and 2) calculates the total amount of inhibition between the source layer and the level of free convection. The calculation of perturbation magnitude accounts for such factors as subgrid-scale inhomogeneities, a convective boundary layer, and convergence within the source layer. Specific formulations to quantify these factors are proposed.

The trigger is tested in a simulation using the PSU–NCAR mesoscale model MM5. The event chosen for simulation is a summertime case exhibiting a variety of environments. The results of this simulation are compared with a simulation using the Fritsch–Chappell (FC) trigger function. It is found that decisions made by the new trigger function are more physically consistent with the local environment than decisions made by the FC trigger.

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