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

Slides:



Advertisements
Similar presentations
Institut für Physik der Atmosphäre 1 Evaluation of a numerical thunderstorm study with POLDIRAD and lightning observations Oberpaffenhofen, 8 February.
Advertisements

Future Radar and Satellite Technology Daniel C. Miller National Weather Service Columbia, SC.
Lightning data assimilation techniques for convective storm forecasting with application to GOES-R Geostationary Lightning Mapper Alexandre Fierro, Blake.
5 th International Conference of Mesoscale Meteor. And Typhoons, Boulder, CO 31 October 2006 National Scale Probabilistic Storm Forecasting for Aviation.
Lightning Imager and its Level 2 products Jochen Grandell Remote Sensing and Products Division.
Copyright C. Doswell A Few Issues Concerning Nowcasting Applications Based on Oklahoma Lightning Mapping Array Data Don MacGorman NOAA/National Severe.
Lightning Climatology Oklahoma Lightning Mapping Array May - September, Paul Krehbiel New Mexico Tech September 28, 2005.
Inter-comparison of Lightning Trends from Ground-based Networks during Severe Weather: Applications toward GLM Lawrence D. Carey 1*, Chris J. Schultz 1,
Transient Luminous Events and the 9 May 2007 Oklahoma Mesoscale Convective System Contact Info: Timothy J. Lang, CSU Atmospheric Science, Ft. Collins,
STEPS Severe Thunderstorm Electrification and Precipitation Study May-July 2000 S. Rutledge, S. Tessendorf, K. Wiens, T. Lang, J. Miller # Department of.
GOES-R Proving Ground NOAA’s Hazardous Weather Testbed Chris Siewert GOES-R Proving Ground Liaison OU-CIMMS / Storm Prediction Center.
1 Comparative Lightning Characteristics of a Tornadic and Non-Tornadic Oklahoma Thunderstorm on April , 2006 Amanda Sheffield Purdue University.
Lightning and Storm Electricity Research Don MacGorman February 25–27, 2015 National Weather Center Norman, Oklahoma.
Lightning The LDAR II Network Nicholas W. S. Demetriades, Ronald L. Holle and Martin J. Murphy Vaisala, Inc., Tucson, Arizona HEAT Project - First Planning.
The Rapid Evolution of Convection Approaching New York City and Long Island Michael Charles and Brian A. Colle Institute for Terrestrial and Planetary.
Proxy Data and VHF/Optical Comparisons Monte Bateman GLM Proxy Data Designer.
The Lightning Mapping Array 12 years of evolution and growth
Anticipating Cloud-to-Ground (CG) Lightning Utilizing Reflectivity Data from the WSR-88D. Pete Wolf, SOO National Weather Service Jacksonville, Florida.
The Lightning Warning Product Fifth Meeting of the Science Advisory Committee November, 2009 Dennis Buechler Geoffrey Stano Richard Blakeslee transitioning.
Earth-Sun System Division National Aeronautics and Space Administration SPoRT SAC Nov 21-22, 2005 Southern Thunder Alliance and LMA Assessments Steve Goodman.
Lightning Jump Algorithm Update W. Petersen, C. Schultz, L. Carey, E. Hill.
Toward a 4D Cube of the Atmosphere via Data Assimilation Kelvin Droegemeier University of Oklahoma 13 August 2009.
WWLLN (World Wide Lightning Location Network) By Prof. Robert Holzworth, Director of WWLLN, University of Washington.
Ken Cummins 1, with help from: Richard J. Blakeslee 2, Lawrence D. Carey 3, Jeff C. Bailey 3, Monte Bateman 4, Steven J. Goodman 5 1 University of Arizona,
Forecasting Lightning Initiation and Cessation at Kennedy Space Center
NASA SPoRT’s Pseudo Geostationary Lightning Mapper (PGLM) GOES-R Science Week Meeting September, 2011 Huntsville, Alabama Geoffrey Stano ENSCO, Inc./NASA.
IMPROVING VERY-SHORT-TERM STORM PREDICTIONS BY ASSIMILATING RADAR AND SATELLITE DATA INTO A MESOSCALE NWP MODEL Allen Zhao 1, John Cook 1, Qin Xu 2, and.
Vaisala Total Lightning Network Update / Nikki Hembury / Southern Thunder Conference 2011.
Christopher J. Schultz 1, Walter A. Petersen 2, Lawrence D. Carey 3* 1 - Department of Atmospheric Science, UAHuntsville, Huntsville, AL 2 – NASA Marshall.
OUTLINE Current state of Ensemble MOS
Total Lightning Detection Your Name & Affiliation.
Proving Ground Activities with Aviation Weather Center, Storm Prediction Center and NASA SPoRT GLM Science Meeting Huntsville, Alabama 20 September 2012.
Bryan Jackson General Forecaster WFO LWX. Introduction Utilizing Total Lightning data from the DC- Lightning Mapping Array (DC-LMA) to create a preview.
Transient Luminous Events above Two Mesoscale Convective Systems Timothy J. Lang, Steven A. Rutledge, Walt Lyons, Jingbo Li, Steven A. Cummer, and Don.
 Rapidly developing convection is a known source of CIT  Satellite derived cloud top infrared (IR) cooling rate, overshooting tops (OT)/enhanced-V and.
Vaisala TLS200 VHF total lightning mapping for safety and nowcasting applications Nick Demetriades 1, Ron Holle 2, and Nikki Hembury 2 Vaisala Inc. 1 Helsinki,
The Rapid Evolution of Convection Approaching the New York City Metropolitan Region Brian A. Colle and Michael Charles Institute for Terrestrial and Planetary.
Relationships between Lightning and Radar Parameters in the Mid-Atlantic Region Scott D. Rudlosky Cooperative Institute of Climate and Satellites University.
Storm tracking & typing for lightning observations Kristin Calhoun, Don MacGorman, Ben Herzog.
Geoffrey Stano – ENSCO / SPoRT David Hotz and Anthony Cavalluci– WFO Morristown, TN Tony Reavley – Director of Emergency Services & Homeland Security of.
Don MacGorman 1,2, Ted Mansell 1, Kristin Kuhlman 2, Alex Fierro 2, Conrad Ziegler 1, Stephanie Weiss 2, Dave Rust 2 1 NOAA/National Severe Storms Laboratory.
Methods for Incorporating Lightning NO x Emissions in CMAQ Ken Pickering – NASA GSFC, Greenbelt, MD Dale Allen – University of Maryland, College Park,
Cloud to Ground Lightning Climatology and Hail Prediction in the Mid-South Matthew Reagan Mississippi State University.
Discriminating Between Severe and Non-Severe Storms Scott D. Rudlosky Henry E. Fuelberg Department of Meteorology Florida State University.
A NASA Model for Improving the Lightning NOx Emission Inventory for CMAQ William Koshak 1, Maudood Khan 2, Arastoo Biazar 3, Michael Newchurch 3, Richard.
Lightning Jump Evaluation RITT Presentation Tom Filiaggi (NWS – MDL) 11/28/12 Evaluation of “2σ” as Predictor for Severe Weather.
Analysis of Cloud-to-Ground Lightning Within 16 Landfalling Hurricanes Danielle Nagele.
Comparison of WTLN and OKLMA Data William H. Beasley 1, Stephanie Weiss 1, Stan Heckman 2 1. School of Meteorology University of Oklahoma Norman, OK
NOAA-MDL Seminar 7 May 2008 Bob Rabin NOAA/National Severe Storms Lab Norman. OK CIMSS University of Wisconsin-Madison Challenges in Remote Sensing to.
Early Evaluation and Operational Applications of Total Lightning in AWIPS-2 Al Cope NOAA/National Weather Service Forecast Office Mount Holly, NJ
HRV (70-100%)IR10.8 (Tb 35dBz HRV cloud (HRV,HRV,IR10.8) radar Zmax > 35dBz (CC+CG) 10-minute lightning data (CC+CG) Simultaneous.
Applied Meteorology Unit 1 High Resolution Analysis Products to Support Severe Weather and Cloud-to-Ground Lightning Threat Assessments over Florida 31.
1 86 th Annual American Meteorological Society Meeting Atlanta, Georgia January 29 – February 2, 2006 The Severe Weather Data Inventory (SWDI): A Geospatial.
Lightning Mapping Technology & NWS Warning Decision Making Don MacGorman, NOAA/NSSL.
Total Lightning AWIPS II Operational Demonstration Fifth Meeting of the Science Advisory Committee November, 2009 Geoffrey Stano, Matt Smith, and.
Investigating Lightning Cessation at KSC Holly A. Melvin Henry E. Fuelberg Florida State University GOES-R GLM Workshop September 2009.
Total Lightning Characteristics in Mesoscale Convective Systems Don MacGorman NOAA/NSSL & Jeff Makowski OU School of Meteorology.
© 2000 Roger Edwards Investigating the Potential of Using Radar to Nowcast Cloud-to-Ground Lightning Initiation over Southern Ontario 18 th Annual GLOMW.
Assimilation of Pseudo-GLM Observations Into a Storm Scale Numerical Model Using the Ensemble Kalman Filter Blake Allen University of Oklahoma Edward Mansell.
C. Schultz, W. Petersen, L. Carey GLM Science Meeting 12/01/10.
GOES-R ABI AS A WARNING AID Louie Grasso, Renate Brummer, and Robert DeMaria CIRA, Fort Collins, CO Dan Lindsey, Don Hillger, NOAA/NESDIS/RAMMB, Fort Collins,
Holle | NWA Annual Meeting | October 06 Cloud Lightning from the National Lightning Detection Network (NLDN) Ronald L. Holle, Nicholas Demetriades, and.
Operational Use of Lightning Mapping Array Data Fifth Meeting of the Science Advisory Committee November, 2009 Geoffrey Stano, Dennis Buechler, and.
Authors: Christopher J Schultz, Walter A. Petersen, and Lawrence D
Paper Review Jennie Bukowski ATS APR-2017
Long Range Lightning Detection Estimated Median Location Accuracy
Severe Weather in Egypt near Alexandria
Nic Wilson’s M.S.P.M. Research
A Real-Time Learning Technique to Predict Cloud-To-Ground Lightning
Use of Lightning Data for Electricity Transmission Operations
Presentation transcript:

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

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

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

Real-time Data from OK-LMA

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

Convective Region Flash TELEX Mesoscale Convective System 19 June 2004

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

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)

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

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

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

“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)

“Good” Example –airmass cells

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

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

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

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

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

Mapped Points Color-coded by Time

Grided Points Color-coded By Density

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

Plan Projection of Lightning Density June 2000 Kansas Supercell Storm

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

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

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