18th Conference on Weather and Forecasting, 14th Conference on Numerical Weather Prediction, and Ninth Conference on Mesoscale Processes

Thursday, 2 August 2001: 4:00 PM
Use of a Mesoscale Model to Forecast Tornadic Storms Associated with a Cold Front Aloft
Stan Rose, University of Washington, Seattle, WA; and M. T. Stoelinga, J. D. Locatelli, and P. V. Hobbs
An analysis of current severe weather forecasting methods was performed for a specific case of a mid-latitude cyclone developing in the lee of the Rocky Mountains. Current methods place emphasis on surface boundaries (surface fronts, drylines, outflow boundaries, etc.) as sites where convection may be triggered. The prevalence of large-scale balanced flow theory (e.g., quasigeostrophy, jet-streak dynamics) as an explanation for the dynamics of the free troposphere has overshadowed the potential role of frontal features aloft as a triggering mechanism for organized convection. The present study applies a conceptual model that emphasizes the lower-tropospheric mesoscale ascent associated with a cold front aloft (CFA) as a potential triggering mechanism for tornadic supercell convection, and examines the utility of the CFA model as a forecasting tool.

A simple scheme is applied that examines the potential triggering role of a CFA in the presence of a favorable environment for severe convection. This involves first an evaluation of indices related to two important parameters for tornadic supercells: convective available potential energy (CAPE) and vertical wind shear [as measured by storm relative helicity and bulk Richardson number shear]. These parameters can be derived and evaluated from mesoscale model output. The existence and location of the CFA can also be determined from mesoscale model output, by evaluating the horizontal temperature gradient at multiple pressure levels in the troposphere. The position of the CFA can then be matched to critical values of shear and CAPE to determine the region where a potential CFA trigger mechanism coincides with favorable environmental conditions, and thus where tornadic development is most likely to occur. Initial results indicate that this method could lead to improved forecasting of tornadoes associated with cyclones in the lee of the Rockies

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