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Saint Louis University: "Propagation and evolution of mesoscale convective systems producing flash floods"

Final Report

This project is a follow-on research effort to an earlier Partners Project in which over thirty warm season mesoscale convective systems (MCS) were examined to characterize the synoptic scale environment leading to their initiation and propagation in a forward, backward or quasi-stationary mode. This later project extends that work by using WSR-88D Doppler data and satellite imagery to examine the growth of MCSs and their discrete or continuous propagation with time. A primary focus was on how the convective storms interacted with their larger scale environment to create convection upstream from the original storms (the backbuilding process).

The Midwest flooding during the summer of 1993 provided eleven cases for study. In each case, the objective was to document the synoptic/mesoscale environment conducive to convective storms and systematically describe the vertical wind shear profiles, instability, and moisture flux patterns which favored either slow-moving MCSs or "training" of echoes over the same geographic area. Another area of investigation involved studying gridded numerical data from NMC operational models using PC-GRIDDS software to evaluate model parameters which might be useful to operational forecasters in predicting the type of MCS which will form, the timing of the MCS initiation, as well as the most likely propagation type.

The 11 heavy rain events that make up the case studies for this project represent a variety of MCS types and forcing mechanisms conducive to heavy rain, including: mesoscale convective complex; linear multi-clustered training echoes associated with a west-east stationary front with weak vertical wind shear; a heavy precipitation supercell thunderstorm; etc. Each of these systems represents a unique forecast challenge. For each case, the researchers attempted to identify the surface and upper air patterns, vertical wind shear, instability, and moisture characteristics so that forecasters might identify potential heavy rain situations under a variety of circumstances. In addition, they characterized the echo configuration depicted by the radar and the GOES infrared satellite imagery associated with each of the MCSs to aid in pattern recognition. The propagation and storm-inflow vectors for each case were investigated to see if computing them in real-time might aid in more accurately forecasting these events.

The researchers also developed a scheme for computing storm motion using estimates of the storm propagation vector and the cell motion vector. The cell motion vector can be approximated by the 850-300 mb density-weighted mean wind vector, while the storm propagation vector can be approximated by the vector opposite to the low-level jet and equal in magnitude. Understanding storm motion is critical to forecasting convective heavy rainfall since it can guide the forecaster as to whether the environment is conducive to upstream regeneration or "back-building".

Analysis of the cases is continuing under a Cooperative Project with the same researchers.