Wednesday, 25 January 2012
Convective Mode Prediction Using Boundary/Shear Vector Orientation: An Evaluation of Tornado Events From the 2011 Season
Hall E (New Orleans Convention Center )
Kimberly Hoogewind, Purdue University, West Lafayette, IN; and M. E. Baldwin
The ability to correctly anticipate convective storm mode remains a significant challenge for weather forecasters. Because multiple modes of convection can exist in seemingly similar thermodynamic and kinematic environments, the traditional method of evaluating the vertical wind shear to discriminate between nonsupercell and supercell storm modes (given sufficient instability) may introduce substantial uncertainty, particularly when a synoptic boundary is present and may influence convective initiation and evolution. However, a relatively new technique in convective mode forecasting has emerged within operations in the past decade. The procedure utilizes the relationship between the orientation of the deep-layer shear vector—perpendicular, oblique, or parallel—with respect to the initiating boundary to evaluate the likely convective mode. This relationship may be of significance, particularly when the magnitude of vertical shear is such that convective mode may be may be difficult to determine beforehand.
Here, real-time high-resolution (4.25 km) forecasts using the experimental Purdue Weather Research and Forecasting model (WRF) will be used to demonstrate the utility of the technique by means of several case studies of severe weather events during 2011. An objective method to identify synoptic boundaries will be employed; it is the contention that the identification of these features and their associated forcing characteristics will provide useful guidance for forecasters, particularly in relation to convective initiation and organization. A comparison between the predicted and observed mode, as identified from Doppler radar data, will be assessed in a subjective manner for each case. Preliminary results have shown the practice to be useful, especially in conjunction with other forms of forecast guidance, such as simulated radar reflectivity.
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