Storm tracking & typing for lightning observations Kristin Calhoun, Don MacGorman, Ben Herzog.

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Presentation transcript:

Storm tracking & typing for lightning observations Kristin Calhoun, Don MacGorman, Ben Herzog

Storm tracking: Segmotion / k-means Identifies segments (or storm cells/clusters) of image & estimates motion Extracts properties of each cell Size of cell (# of pixels) Pull data from all grids, including radar, lightning, and derived properties such as maximum expected size of hail (MESH) Moves grid based on motion field Tracking: Lightning vs. Reflectivity vs. Hybrid Want a relatively stable area, without drops or mismatches Past track given by centroid of area, if loses section or adds will change centroid location and can account for difference in track

original: reflectivity at -10 C

thresholds & median filter applied

scale 0 (200 km 2 )

scale 1 (600 km 2 )

scale 2 (1000 km 2 )

Flash Extent Density vs Flash Rate vs Flashes per unit area? For assimilation: # of flash initiations (single point: lat / lon) # of flashes traversing a grid cell, or some measure of the summed density/duration of flashes at a particular grid cell?

Flash Extent Density vs Flash Rate vs Flashes per unit area?

Flash Extent Density vs Flash Rate GLM scale

Flash Extent Density vs Flash Rate vs Flashes per unit area? For assimilation: # of flash initiations, # of flashes traversing a grid cell, or some measure of the summed density/duration of flashes at a particular grid cell? For observations / lightning jump: # of flashes per cell, the max density of flashes in a cell, or the # of flashes per unit area of a cell Are the answers to these questions different for different types of storms or at different resolutions/spatial scales? How does this translate to pGLM and ultimately GLM?

6 years of data ( ) 3 domains (OKLMA, NALMA, DCLMA)

Speed tests! active weather week over 3 LMA domains On NSSL machine idealized for real-time processing: 21 single radars, processing: ~31 hrs/each 3 LMA domains, processing: ~29 hrs/each Multi-radar/sensor merger & storm tracking: ~155 hrs Onto supercomputing: ~67% faster + more parallel computing opportunities! Run multiple weeks at the same time Optimizing WDSS2 for supercomputing Can run in parallel

Storm typing Decision tree: based on training set from number of years across the CONUS (Hobson et al., 2012)

short-lived, multi-cell, supercell Storm typing: 19 May 2010, NW OK

a bit later: 2 supercell storms Storm typing: 19 May 2010, NW OK

Applying results to Data Assimilation: 3DVAR framework – real-time in the Hazardous Weather Testbed every 5 min (w/Jidong Gao) Parallel work by Ted Mansell, Blake Allen, and Alex Fierro utilizing EnKF and pGLM flash density Radar #2 Radar #3 Radar #1 Total Lightning satellite Surface obs