National Demonstration and Evaluation of a Real Time Lightning Jump Algorithm for Operational Use

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner
Tuesday, 4 February 2014: 8:30 AM
Room C202 (The Georgia World Congress Center )
Themis Chronis, University of Alabama, Huntsville, AL; and C. J. Schultz, E. V. Schultz, L. D. Carey, K. M. Calhoun, D. M. Kingfield, K. L. Ortega, M. T. Filiaggi, G. J. Stumpf, G. T. Stano, and S. Goodman

In severe storms, rapid increases in lightning flash rate, or “lightning jumps”, are coincident with pulses in the storm updraft and typically precede severe weather by tens of minutes. This study examines the relationship between trends in the total lighting activity (i.e., jumps) and severe weather occurrence (e.g. hail, high winds, and tornadoes) and extends the methodology used in previous works in real time from a viewpoint that is adaptable to the needs of the National Weather Service (NWS). The NWS Office of Science and Technology (OST) deemed it as a high priority to evaluate the LJA for operational implementation on an expanded LMA and radar data set, using fully automated methods for storm cell identification and tracking and lightning jump detection, and robust verification approaches. The total lightning data for the this analysis is based on the Lightning Mapping Array (LMA) networks located in central/SW Oklahoma, North Alabama, and Washington D.C The numerical computation of the “lightning jump” is based on the 2-sigma rule (a “running” standard deviation of the total lightning time series) with additional constraints that pertain to flash rates. The storm identification and tracking is performed by a K-means algorithm, which is scalable based on the observed -10oC 94th AMS Annual Meeting: National Demonstration and Evaluation of a Real Time Lightning Jump Algorithm for Operational Use radar reflectivity. In turn, reflectivities from multiple WSR-88D radars within the LMA domains are merged with a local temperature profile from the RAP model, producing gridded reflectivity information at isothermal values. Since the beginning of the study, the Hazardous Weather Testbed (HWT) in Norman, OK, has been the operational center where all related data are archived. The location and timing of the severe weather reports are retrieved from the NOAA Storm Prediction Center (SPC). The database for this study encompasses cases from Spring 2013 onwards. This multi-component analysis focuses on: a) Probability of Detection (PoD), Lead Time (LT) and especially the False Alarm Ratio (FAR). Using a high degree of automation, the analysis computes key-statistics for the severe weather nowcasting based on the Lightning Jump algorithm (LJA) employment in real time, b) addresses issues related to the real-time tracking algorithm and how these can interfere with the actual performance of the LJA, c) highlights the importance of lightning information as an additional constrain in the severe weather cluster tracking, and d) assesses the representativeness of SPC reports and their impact on FAR estimation using enhanced verification techniques that employ radar proxies of severe weather (e.g. Maximum Expected Hail Size-MESH) and Severe Hazards Analysis and Verification Experiment (SHAVE) data.