Pseudo-GLMFrom DC-LMA

Bryan Jackson

General Forecaster WFO LWX

IntroductionUtilizing 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

Total LightningAll lightning flashesNLDN detects CG strikes onlyGLM/LMA detect ICCCCG flashesStudies have correlated thunderstorm

strength with total lightning source density and flash rate trends or “lightning jumps”.

DC-LMA10 VHF sites in

Baltimore-Washington DC metro

~100 km effective radiusResolution

2 minute temporal1 km spatial

Source densityEach segment of a flashNumber of flashes known The 10 DC-LMA sites

Dr. Geoffrey Stano’s presentation on total lightning and LMAhttp://weather.msfc.nasa.gov/sport/training/LMA/player.html

GLMOn-board GOES-R series

First sensor of this kind on GOESOptical pulse detection with imager

Lightning flashes across entire field of viewResolution

8-14 km spatial (~10 km near DC)High temporal (NWS delivery rate?)

2015 scheduled launch

Pseudo GLMFlash count per grid

cell10 km grids for DC

areaGreater counts near

cell coreStronger the core,

the more flashes expected.

Easy discriminator of cell intensity

Dr. Geoffrey Stano’s presentation on pseudo-GLMhttp://weather.msfc.nasa.gov/sport/training/pseudo_GLM/player.html

Washington D. C.

DC-LMA vs Pseudo GLM

Source Density from DC-LMA Flash Density from pseudo GLM

ProjectCOMET Partners ProjectScott Rudlosky, PhD CICS-MD College Park.

Dustin Shea, UMD Met grad student.Demonstrate utility of GLM in severe weather

via DC-LMA pseudo-GLMWES case(s) and job sheets

Work and PlansTwo 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

DiscussionQuestions?

What would you like to see for training modules?Particular storm typesLead time improvement over Reflectivity and

NLDN

Preferred training typeFormal WES caseJob Sheet (like dual-pol training)

DC-LMA example

July 18, 2012

First SVR 2019 UTC

Second SVR2029 UTC

Trees Down Fort Meade, MD2045 UTC

15 min severe report lead time

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.