1. Project Name: The GOES-R GLM Lightning Jump Algorithm: Research to Operational Algorithm
(GOES-R3 Project # 064)
1.1. Principal Investigators
Dr. Lawrence D. Carey (PI), UAHuntsville, Email: lcarey@nsstc.uah.edu
Mr. Christopher J. Schultz (unfunded Co-I), UAHuntsville/NASA-MSFC, Email: schultz@nsstc.uah.edu
Dr. Daniel Cecil (Co-I), UAHuntsville, Email: cecild@uah.edu
Dr. Monte Bateman (Co-I), USRA (NASA-MSFC), Email: monte.bateman@nasa.gov
Dr. Geoffrey Stano (Co-I), ENSCO (NASA-MSFC), Email: geoffery.stano@nasa.gov
Dr. Valliappa Lakshmanan (Co-I), CIMMS, University of Oklahoma,
Email: Valliappa.Lakshmanan@noaa.gov
Dr. Steven J. Goodman (unfunded Co-I), NOAA NESDIS, Email: steve.j.goodman@noaa.gov
2. Project Description
The feasibility of a thunderstorm cell-oriented lightning-trending technique for application to operational severe weather warning decision support is investigated. Using a large set (many hundreds) of thunderstorm case types (supercell, linear systems, tropical, air-mass etc.) for a variety of environments
(N. Alabama, Houston, Mid Atlantic, High Plains, Oklahoma, warm/cold season), a prototype lightning jump algorithm (LJA) driven by lightning mapping array (LMA) and radar-based cell tracking datasets has been developed (Schultz et al. 2009, 2011). The prototype LJA produced robust warning verification statistics including a POD of 79% and a FAR of 36% with severe storm warning lead-time of ~20 minutes. To mature the LJA for transition to GOES-R algorithm readiness and to establish a path to operations, the following objectives are being pursued: a) identify and fill performance gaps in the LJA related to variations in thunderstorm environment and type; b) merge the LJA with automated advanced storm-intensity cell/object-tracking efforts; c) explore a physically-based fusion and testing of new data inputs into the LJA, including coincident radar and GOES IR/VIS (in collaboration with Project 067); d) transition Geostationary Lightning Mapper (GLM) Flash Proxy algorithms for use with a quasi-real-time
LJA and adjust LJA trigger thresholds as needed; e) demonstrate the GLM proxy-based LJA within the framework of the GOES-R Proving Ground (PG) through direct collaboration with the NASA Short Term
Prediction Research and Transition Center (SPoRT) and regional National Weather Service (NWS)
Forecast Offices (WFOs) Huntsville, Birmingham Nashville, and Morristown; and f) participate in the planning and development of the NOAA Lightning Jump Test (LJT) Project.
3. Summary of Accomplishments
3.1 Accomplishments in Year 1 and Partial Year 2

Identified the environments (tropical/cold season/low-topped) that limit our ability to use the
LJA. These particular environments comprise 40% of our misses. The mere presence of lightning in these situations may clue a forecaster into the potential for severe weather (e.g., outer rainbands of tropical cyclone typically have lightning activity prior to a tornado).

Developed version 2 (v2) of the GLM proxy. The proxy data were enhanced in the following ways: using statistics from real LIS (Lightning Imaging Sensor) and LMA (Lightning Mapping
Array) data for flash size, shape, temporal distribution, and number of pixels. The proxy also now uses the "official" GLM pixel grid, with fixed Earth coordinates. So far, 27 storm event days of v2 GLM optical-proxy have been generated for use with the LJA, including hundreds of cells.

The proxy generation tools are now turn-key and GLM proxy data can be generated from
Northern Alabama LMA (NA-LMA) as needed.

Analyzed 102 storms in 20 of the GLM proxy events, and comparisons between NA-LMA flash trend and GLM-proxy flash trends are strong (R=0.89). The GLM proxy and LMA flash rates have a near 1:1 relationship at low-to-moderate flash rates. At moderate-to-high flash rates, the
GLM proxy flash rates for cells tend to be less than the original LMA flash rates. At very high
LMA flash rates, the GLM proxy tends to limit to flash rates < 100 min -1 with only a few exceptions. Lightning jump trends observed in the LMA data are also found in the GLM proxy data, most of the time. The main difference is the magnitude of the jump. As anticipated, the
GLM proxy jumps are less than the original LMA flash rate jumps but still detectable.

Explored issues associated with objective tracking of lightning (or combined lightning-radar) features when using GLM resolution and GLM proxy data. Issues explored with GLM feature tracking include dropped feature tracks, delayed feature identification, split features, and feature mergers. Compared and contrasted both TITAN in the NCAR Autonowcaster and segmotion/Kmeans method in WDSSII and found similar performance and issues. Both identify and track supercells well but have some tracking problems with lesser organized ordinary cells.

Optimized the WDSSII-based (w2segmotionll1) feature tracking methodology based on extensive testing on GLM proxy data and inter-comparison with TITAN radar tracks from Schultz et al.
(2011). WDSSII tracking is accomplished on a merged GLM proxy flash rate density and radarderived VIL product in which the GLM proxy is given larger weighting. The approach gives coherent cell tracks and is consistent with radar storm locations.

Initial testing and adjustment of LJA in GLM proxy tracked features for select case studies have begun. Results are benchmarked against Schultz et al. (2011), which used radar-based tracks and native LMA lightning flashes to compute the jump.

Radar data from the 711 cases in Schultz et al. (2011) have been processed using WDSSII in order to explore the fusion of lightning and radar observations in order to relate the jump to commonly used severe weather parameters, like MESH, VIL and increases in the mean vertical reflectivity profile and to explore fused methods and algorithms for situational awareness and warning operations. For select cases, this operational data fusion will also be placed in the context of dual-Doppler derived storm kinematics and dual polarization inferred microphysics in order to physically tie the lightning jump into the dynamics and microphysics of the studied storms, thus providing excellent training material for Proving Ground (PG).

Operational Transition Work : Supported the planning, development and implementation of the
NOAA Lightning Jump Test (LJT) Project at the Hazardous Weather Testbed (HWT), which is objectively testing the Schultz et al. (2009, 2011) algorithm on VHF-based flash data at LMAnative (non-GLM) resolution. Worked with LJT team to implement an objective (“hands off”) version of the LJA at NSSL and to develop enhanced verification methods.
3.2. Ongoing and Future Work in Remainder Year 2
With the exception of planning for PG, all Year 2 objectives are underway and on schedule to be completed during Year 2. PG activities will begin toward the end of Year 2 and continue in Year 3, pending funding. Ms. Sarah Stough (UAHuntsville GRA) has joined our lightning jump team as of
August 2012 and will assist with LJA development, testing and evaluation.
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
Complete lightning jump algorithm (LJA), including modification of LJA thresholds for representative GLM optical-proxy data at GLM resolution [ Schultz, Stough, Carey ] o Deliver LJA Algorithm Theoretical Basis Document (ATBD) [ Carey, Schultz, Cecil,
Stough ]

Complete the merger of LJA with ongoing cell tracking work of Cecil/ Lakshmanan [ Cecil,
Lakshmanan, Stough, Carey, Schultz ] o Coordinate with Lakshmanan to deliver cell-tracking ATBD for LJA [ Cecil ]

Complete combined lightning-radar data studies in order to explore fused lightning-radar methods for operational storm monitoring, physically tie the lightning jump into known severe storm conceptual models and hence to provide training material [ Schultz, Carey ]

Continue research testing of LJA within GLM proxy cell-tracker in post-event mode, including simulations of “real-time” objective (hands-off) tracking [ Cecil, Stough, Carey, Schultz ]

Begin initial planning for PG operational training and evaluation (OT&E) of GOES-R GLM proxy LJA. [ Carey, Cecil, Stough, Schultz ]
3.3. References
3.3.1. Conferences, Workshops and Meetings
Calhoun, K. M., L. D. Carey, M. T. Filiaggi, K. L. Ortega, C. J. Schultz, and G. J. Stumpf, 2012: Implementation and initial evaluation of a real-time lightning jump algorithm for operational use. Sixth Conference on the
Meteorological Applications of Lightning Data . 93 rd AMS Annual Meeting, January 6-10, 2013, Austin, TX.
Carey, L. D., and C. J. Schultz, 2011: Lightning jump algorithm and national field demo. GLM Annual Science
Meeting , September 19-20, 2011, Huntsville, AL.
Cecil, D., L. Carey and C. Schultz, 2011: Cell Identification and Tracking for Geostationary Lightning Mapper,
Poster at 2011 GLM Annual Science Meeting and 2011 GOES-R Risk Reduction Annual Meeting , Huntsville,
AL, September 19-23, 2011, Huntsville, AL.
Cecil, D: 2011: "Geostationary Lightning Mapper for GOES-R - Building Tools for Severe Thunderstorm and
Tornado Warnings", invited seminar at University of Utah Department of Meteorology.
Cecil, D. J., C. J. Schultz, and L. Carey, 2012: Lightning jump algorithm for proxy GOES-R lightning mapper data.
Joint Session between the Ninth Annual Symposium on Future Operational Environmental Satellite Systems and the Sixth Conference on the Meteorological Applications of Lightning Data . 93 rd AMS Annual Meeting,
January 6-10, 2013, Austin, TX.
Schultz, C. J., W. A. Petersen, and L. Carey, 2011: Advancements in the development of an operational lightning jump algorithm for GOES-R GLM, Paper 8.3, AMS Fifth Conference on the Meteorological Applications of
Lightning Data , Seattle, WA, January 24-26, 2011.
Schultz, C., W. Petersen, and L. Carey, 2011: Overview of the Total Lightning Jump Algorithm: Past, Present, and
Future Work, Session 3: Operational Technology and Experience, Southern Thunder 2011 (ST11) , Norman,
OK, July 11-14, 2011.
Schultz, C., L. D. Carey, W. A. Petersen, D. Cecil, M. Bateman, S. Goodman, G. Stano, and V. Lakshmanan, 2011:
Lightning jump algorithm and national field demo: Past, present and future work. Poster, GOES-R Risk
Reduction Annual Meeting , September 21-23, 2011, Huntsville, AL.
Schultz, C. J., W. A. Petersen, L. D. Carey, W. Deierling, and C. Kessinger, 2011: An overview of the total lightning jump algorithm: Past, present and future work, 3 6 th NWA Annual Meeting , P1.9, October 15-20, 2011,
Birmingham, AL.
Schultz, C. J., L. D. Carey, W. A. Petersen, W. Deierling, and C. Kessinger, 2012: An overview of the total lightning jump algorithm: past, present and future work, 10 th Annual Southeast Severe Storms Symposium ,
March, 3, 2012, Starkville, MS.
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Schultz, C., L. Carey, D. Cecil, M. Bateman, G. Stano, S. Goodman, 2012: The GOES-R GLM Lightning Jump
Algorithm (LJA): Research to Operational Algorithm. Poster and Oral Presentation, 2012 NOAA Satellite
Science Week , April 30 – May 4, 2012, Kansas City, MO.
Schultz, C. J., L. D. Carey, E. V. Schultz, G. T. Stano, P. N. Gatlin, D. Kozlowski, and S. Goodman, 2012:
Integration of the total lightning jump algorithm into current operational warning environment conceptual models. AMS, 26 th Conference on Severe Local Storms , 5 – 8 November 2012, Nashville, TN.
Schultz, C. J., L. D. Carey, E. V. Schultz, G. T. Stano, P. N. Gatlin, D. Kozlowski, R. J. Blakeslee, and S. Goodman,
2012: Integration of the total lightning jump algorithm into current operational warning environment conceptual models. Joint Session between the Ninth Annual Symposium on Future Operational Environmental Satellite
Systems and the Sixth Conference on the Meteorological Applications of Lightning Data . 93 rd AMS Annual
Meeting, January 6-10, 2013, Austin, TX.
Stano, Geoffrey T., B. Carcione, K. D. White, and C. J. Schultz, 2012: Low topped convection and total lightning observations from north Alabama. Sixth Conference on the Meteorological Applications of Lightning Data .
93 rd AMS Annual Meeting, January 6-10, 2013, Austin, TX.
3.3.2. Peer Reviewed
Schultz, C. J., W. A. Petersen, and L. D. Carey, 2009: Preliminary development and evaluation of lightning jump algorithms for the real-time detection of severe weather. J. Appl. Meteor. Climatol.
, 48 , 2543-2563.
Schultz, C. J., W. A. Petersen, and L. D. Carey, 2011: Lightning and severe weather: A comparison between total and cloud-to-ground lightning trends. Wea. Forecasting , 26, 744-755.
4. Plans for Year 3

Prepare for and implement PG demonstration of LJA. PG demonstration for this award will use
GLM optical-proxy at GLM resolution, thus providing a clear pathway to operations. OT&E of
LJA/Cell-tracker in PG and local WFO’s [Stano, Cecil, Stough, Schultz, Carey]

Leverage SPoRT’s expertise/capability in transitioning NASA products to the NWS/PG as well as creating software plug-ins for the next generation decision support tool; AWIPS II [ Stano ]

Develop training material to educate end users on the theory, methods, and pros and cons of the
LJA, which will provide a more informed evaluation [ Stano, Schultz, Cecil, Carey, Stough ]

Incorporate feedback from OT&E activities at SPoRT and PG into LJA/Cell-tracker updates and improvements [ Stough, Carey, Cecil, Schultz ]
4.1 Year 3 Proposed Budget Summary
1. Grants (name the CI)
CIMMS, U. of Oklahoma
Total CIMMS (Lakshmanan travel only)
2. Transfer to other agency through an MOU
NASA MSFC (UAHuntsville, ENSCO)
UAHuntsville (12% Carey, 35% Cecil, 100% Stough, Travel) loaded
ENSCO (20% Stano) loaded
NASA CM&O Agency Rate and F&A Costs
Total NASA MSFC (Carey, Stough, Cecil, Stano FTEs, travel)
3. Total budget request for FY12 (sum of 1-6)
$ 3,000
$ 138,997
$ 27,003
$ 11,540
$ 177,540
$ 180,540
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