Microburst Composite Parameter A Forecasting and Analysis Approach to Determine Favorable Days For Microbursts across the Southern States
Chad Entremont, NOAA / NWS  Jackson, MS, Flowood, MS
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Abstract
Microburst Composite Parameter

A Forecasting and Analysis Approach to Determine Favorable Days For Microbursts across the Southern States

Chad Entremont, Eric Carpenter, Brad Bryant, David Cox

Anna Wolverton, Jared Allen

National Weather Service Jackson, MS

During the summer months, forecasters across the southeast United States often face challenges when trying to predict which days are favorable for severe convective weather. The summer is dominated  by periods during which scattered afternoon thunderstorms are common and develop almost daily in a moderately unstable environment.  Determining which days are favorable for severe storms and which are not is a continuous challenge.

A comprehensive study was conducted that focused on an area across portions of several southeastern states. Within this defined geographic domain, storm reports (wind & hail) from 2009 to 2013 were compiled and organized into daily listings. These reports were also grouped into highlighted days with a large number of severe events,  days with just a few events, as well as days when no events were reported. Twenty-one  different parameters were calculated for the three groups using observed soundings modified for representative surface conditions. These multiple parameters were analyzed using different statistical approaches to determine if each, or a combination of each, provided any skill in predicting severe weather event days versus days that did not produce severe weather.

This presentation will discuss our methodology and define which parameters showed skill to determine microbursts and severe weather events. We will also show how the study results were compiled into the Microburst Composite Parameter and how this is used daily, through morning sounding analysis, and with near storm environment analyses available from The Storm Prediction Centers mesoanalysis web page.