A41F-0123
Classification and Analysis of Four Types of Elevated Nocturnal Convective Initiation During Summer 2015

Thursday, 17 December 2015
Poster Hall (Moscone South)
Sean Andrew Stelten and William A Gallus Jr, Iowa State University, Ames, IA, United States
Abstract:
A large portion of precipitation seen in the Great Plains region of the United States falls from nocturnal convection. Quite often, nocturnally initiated convection may grow upscale into a Mesoscale Convective System (MCS) that in turn may cause high impact weather events such as severe wind, flooding, and even tornadoes. Thus, correctly predicting nocturnal convective initiation is an integral part of forecasting for the Great Plains. Unfortunately, it is also one of the most challenging aspects of forecasting for this region. Many forecasters familiar with the Great Plains region have noted that elevated nocturnal convective initiation seems to favor a few distinct and rather diverse modes, which pose varying degrees of forecasting difficulties. This study investigates four of these modes, including initiation caused by the interaction of the low level jet and a frontal feature, initiation at the nose of the low level jet without the presence of a frontal feature, linear features ahead of and perpendicular to a forward propagating MCS, and initiation occurring with no discernible large scale forcing mechanism. Improving elevated nocturnal convective initiation forecasts was one of the primary goals of the Plains Elevated Convection At Night (PECAN) field campaign that took place from June 1 to July 15, 2015, which collected a wealth of convective initiation data. To coincide with these data sets, nocturnal convective initiation episodes from the 2015 summer season were classified into each of the aforementioned groups. This allowed for a thorough investigation of the frequency of each type of initiation event, as well as identification of typical characteristics of the atmosphere (forcing mechanisms present, available instability, strength/location of low level jet, etc.) during each event type. Then, using archived model data and the vast data sets collected during the PECAN field campaign, model performance during PECAN for each convective initiation mode was compared to the high quality data sets in order to flesh out why certain convective initiation modes may be more difficult to forecast than others.