Use of proximity sounding parameters to improve the prediction of Mesoscale Convective system (MCS) speed and dissipation

This presentation will discuss the development and testing of empirical forecast tools designed to improve the prediction of quasi-stationary versus fast forward-propagating mesoscale convective systems (MCSs) and the prediction of MCS dissipation. To form the basis for the forecast tools, composite WSR-88D reflectivity data is examined for the years of 1998-2004 to identify over 600 MCS events that occurred east of the Rocky Mountains during the months of May-August. Only those MCSs that maintain quasi-linear convective updrafts > 100 km in length and persist for > 5 h are examined in this study. These events are inspected for the existence of operational radiosonde observations (soundings) that represent the inflow environment to the MCSs. A set of 348 proximity soundings are obtained from this MCS subset (and a past dataset of severe MCSs), from which differences in the environments among the mature and demise stages of the MCSs and between the quasi-stationary and fast-forward propagating systems are examined.

Using nonparametric hypothesis testing and discriminant function analyses among a large number of sounding parameters, it is found that deep vertical wind shear (~0-10 km) and the mean temperature lapse rate between low and mid-upper levels (e.g. 3-8 km) has considerable discriminatory value between the mature and demise stages of the systems in both an absolute and standard normal framework. This agrees with recent evidence from numerical simulations that deep-layer wind shear has a significant control over the maintenance of quasi-linear MCSs. It is also found that the deep-layer shear in the cloud-bearing layer and the minimum difference in equivalent potential temperature between the low and mid-levels (converted to z-scores) has considerable discriminatory value between the MCSs that move at speeds < 18 m s^-1 and those that move at speeds > 18 m s^-1. Forecast tools that use these results will be tested this summer at the NOAA/Storm Prediction Center and preliminary results from this forecast experiment will be presented at the conference.