1. Bryan Jackson General Forecaster WFO LWX

2. Introduction Utilizing Total Lightning data from the DC- Lightning Mapping Array (DC-LMA) to create a preview of the Geostationary Lightning Mapper (GLM) data via Pseudo GLM COMET Parnter’s Project – GOES-R Proving Ground Discussion on effective training modules

3. Total Lightning All lightning flashes NLDN detects CG strikes only GLM/LMA detect ICCCCG flashes Studies have correlated thunderstorm strength with total lightning source density and flash rate trends or “lightning jumps”.

4. DC-LMA 10 VHF sites in Baltimore- Washington DC metro ~100 km effective radius Resolution 2 minute temporal 1 km spatial Source density Each segment of a flash Number of flashes known The 10 DC-LMA sites Dr. Geoffrey Stano’s presentation on total lightning and LMA http://weather.msfc.nasa.gov/sport/training/LMA/player.html

5. GLM On-board GOES-R series First sensor of this kind on GOES Optical pulse detection with imager Lightning flashes across entire field of view Resolution 8-14 km spatial (~10 km near DC) High temporal (NWS delivery rate?) 2015 scheduled launch

6. Pseudo GLM Flash count per grid cell 10 km grids for DC area Greater counts near cell core Stronger the core, the more flashes expected. Easy discriminator of cell intensity Dr. Geoffrey Stano’s presentation on pseudo-GLM http://weather.msfc.nasa.gov/sport/training/pseudo_GLM/player.html

7. Washington D. C. DC-LMA vs Pseudo GLM Source Density from DC-LMAFlash Density from pseudo GLM

8. Project COMET Partners Project Scott Rudlosky, PhD CICS-MD College Park. Dustin Shea, UMD Met grad student. Demonstrate utility of GLM in severe weather via DC- LMA pseudo-GLM WES case(s) and job sheets

9. Work and Plans Two cases selected from DC region: April 20, 2008: low-topped QLCS tornadoes KLWX down for most of the event June 3, 2009: multi-cell clusters Hail, Wind, EF-1 tornado Utility of flash rates in severe weather decision making

10. Discussion Questions? What would you like to see for training modules? Particular storm types Lead time improvement over Reflectivity and NLDN Preferred training type Formal WES case Job Sheet (like dual-pol training)

12. DC-LMA example July 18, 2012 First SVR 2019 UTC Second SVR 2029 UTC Trees Down Fort Meade, MD 2045 UTC 15 min severe report lead time

13. Intro to GLM (stats about what the sensor will do and provide, particularly for NWS forecasters) Intro to the project (creating pseudo GLM data from DC-LMA data) Example slide of what pseudo GLM data will look like (from one of the cases). Project plan and future work (job sheets or Wes case) Discussion on what forecasters would like to see.