6.3
Comparing lightning activity in different storm types and to radar-based observations

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Wednesday, 9 January 2013: 11:00 AM
Comparing lightning activity in different storm types and to radar-based observations
Room 14 (Austin Convention Center)
Benjamin S. Herzog, CIMMS/Univ. of Oklahoma, Norman, OK; and K. M. Calhoun and D. R. MacGorman

Previous studies have found total lightning flash rates to be proportional to several measures of storm intensity. Due to this proportionality, lightning data may serve as a supplement to more traditional means of accessing storm intensity, such as the WSR-88D radar network. Lightning data will be available with a higher temporal resolution than that of the radar network once the Geosynchronous Lightning Mapper (GLM) on GOES-R is implemented for operational use. The lightning data from the GLM will also be available in data-sparse areas such as oceans or mountainous areas. The enhanced temporal resolution and availability of a proxy for storm intensity may be exploited to both enhance the situational awareness of forecasters in an operational setting, and to allow for additional data to be assimilated into forecast models to improve their output. However, there is much work to be done to investigate exactly how lightning activity is relevant to operational forecasters and to determine how lightning activity relates to model state variables. Furthermore, little work has been done examining how lightning varies across different storm types and different climatological regions.

The goals of this research are twofold. First, this work will examine how lightning parameters vary across 4 different storm types (isolated supercell, multi-cell, short lived, and convective line) and 3 different geographic domains (the Central Oklahoma, Northern Alabama, and Washington, D.C. lightning mapping array (LMA) networks). Second, the research will attempt to compare trends in lightning data with trends observed by radar to help understand relationships between lightning and model state variables and to provide insight into physical processes occurring in the storm. The Warning Decision Support System-Integrated-Information (WDSS-II) will be utilized to identify storm types and to track the lightning and radar parameters within the three aforementioned LMA networks.