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Cloud Flash Evaluation Issues and Progress Report Don MacGorman, NOAA/NSSL Al Nierow, FAA Dennis Boccippio, NASA/MSFC.

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Presentation on theme: "Cloud Flash Evaluation Issues and Progress Report Don MacGorman, NOAA/NSSL Al Nierow, FAA Dennis Boccippio, NASA/MSFC."— Presentation transcript:

1 Cloud Flash Evaluation Issues and Progress Report Don MacGorman, NOAA/NSSL Al Nierow, FAA Dennis Boccippio, NASA/MSFC

2 Evaluation of NLDN Cloud Flashes Compare times and reliability of first storm detection (various definitions of detection) Compare with higher cloud flash detection efficiency Determine whether NLDN cloud flash detection is biased Develop prototype cloud flash products for AWIPS and WDSSII

3 PROGRESS Improved OK-LMA network - added station and real-time link to old station - improved real-time data retrieval Collected LMA data and NLDN cloud flash data for May – data collection continuing Set up real-time OK-LMA data feed to NSSL and to Norman NWSFO (AWIPS and WDSSII) Generation of real-time LMA products for WDSSII and AWIPS ready to begin FSL’s development of prototype AWIPS NLDN cloud flash products to begin in June

4 Real-time Data from OK-LMA

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11 Comparison of CG versus All Lightning 21 June min accumulations ending at 0015 UTC & 0300 UTC 10 km X 10 km grid Ground Strike Points OnlyAll Lightning

12 Convective Region Flash TELEX Mesoscale Convective System 19 June 2004

13 Modeled CLD DE: NLDN-based Test Network – Spring 2004

14 Lightning Comparisons 0141: :07 UTC 1 May 2004 Fort Worth WSR-88D Base Reflectivity Image from 0204 UTC 13 October 2001 DFW LDAR II Sources DFW LDAR II Flash Initiation Points LF Cloud Sources (Red), High DE Poly (Blue), Low DE Poly (Green)

15 NLDN CG Flashes LF Cloud Sources (Red) and NLDN CG Strokes (Green)

16 Quantitative Determination of CLD DE Steps: Remove all LF CLD events associated with CG (1 sec) Determine LDAR flash initiation points Remove all except one event LF CLD event per LDAR initiation point (1 sec) Move small positives (< 10kA) into LF CLD category Compute statistics

17 “Good” example – Various supercells The higher performance periods are when the storms are closer to the heart of the network (need to confirm)

18 “Poor” Example – large squall line We typically see a limit of LF CLD events/second from a local region, presumably due to communication rate limitations and the simple location algorithm (non-RPS)

19 “Good” Example –airmass cells

20 Climatological differences will affect comparative thunderstorm-detection performance of using CG only versus using all types of lightning.

21 CG TIME LAG FOR OKLAHOMA STORMS 7% had no CG flashes 18% had CG within 1 min 50% had CG within 5 min 75% had CG within 11 min

22 CG TIME LAG FOR DFW STORMS 10% had no CG flashes 14% had CG within 1 min 50% had CG within 8 min 74% had CG within 23 min

23 CG TIME LAG FOR HIGH PLAINS STORMS 41% had no CG flashes 4% had CG within 1 min 50% had CG within 37 min 59% had CG within 55 min

24 Cloud Flash to Ground Flash Ratio from Boccippio et al. (2001) %

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26 Mapped Points Color-coded by Time

27 Grided Points Color-coded By Density

28 Lightning Comparison 0141: :07 UTC 1 May 2004 Fort Worth WSR-88D Base Reflectivity Image from 0204 UTC 13 October 2001 DFW LDAR II Sources DFW LDAR II Flash Initiation Points

29 Plan Projection of Lightning Density June 2000 Kansas Supercell Storm

30 8 May 2003 Tornadic Supercell Lightning density in 5-minute moving interval NORTH (km) EAST (km) ALTITUDE (km) 20 ALTITUDE (km)

31 Overshooting Top 13 June 1998 Oklahoma Supercell Storm EAST 125 km NORTH 20 km ALTITUDE 20 km Lightning density for moving 3-minute interval Courtesy of New Mexico Institute of Mining and Technology

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33 +CG to All CG Ratio Orville and Huffines (2001)


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