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End-User Assessment of the NASA SPoRT Lightning AI ProductThe NASA Short-term Prediction Research and Transition (SPoRT) Center has begun to develop products to address operational challenges and enhance safety during the lifecycle of lightning activity, and conduct evaluations in concentrated R2O/O2R efforts. The product evaluated for this study is Lightning Artificial Intelligence (A.I.), which predicts the probability of lightning out to 15 minutes in advance and spatially maps it using filled color contours. Lightning A.I. uses reflectivity, differential reflectivity, and correlation coefficient data from a subset of radars within the NEXRAD network to generate lightning probabilities at approximately 2 km resolution. The domains, spanning 145 x 145 km are centered over NASA-affiliated centers across the CONUS and use radar data which are closest in proximity.

Lightning A.I. was developed with intended use by emergency managers at NASA centers. However, National Weather Service (NWS) offices are also often tasked with monitoring and forecasting the threat for lightning within their County Warning Areas for various impact-based decision support services. These forecasts are typically provided for aviation operations and large-scale, outdoor events, which may have varying safety requirements for decision-making based on lightning proximity and recency. The NASA SPoRT center conducted an assessment of the operational uses of Lightning A.I by various collaborative NWS Offices from late July into early September. This assessment included feedback from participants on both the product itself as well as its accessibility within the new, interactive NASA SPoRT Lightning Viewer. This presentation will include background information about Lightning A.I. and highlight results from this assessment. The feedback from the assessment will be used to inform research on any necessary modifications to this and future lightning products to assist end users.
Document ID
20240001151
Acquisition Source
Marshall Space Flight Center
Document Type
Poster
Authors
Kelley Murphy
(University of Alabama in Huntsville Huntsville, United States)
Kristopher White
(NOAA National Weather Service Silver Spring, United States)
Christopher Schultz
(Marshall Space Flight Center Redstone Arsenal, United States)
Andrew White
(University of Alabama in Huntsville Huntsville, United States)
Roger Allen
(Jacobs (United States) Dallas, Texas, United States)
Michael Antia
(Jacobs (United States) Dallas, Texas, United States)
Date Acquired
January 25, 2024
Subject Category
Meteorology and Climatology
Meeting Information
Meeting: American Meteorological Society 104th Annual Meeting
Location: Baltimore, MD
Country: US
Start Date: January 28, 2024
End Date: February 1, 2024
Sponsors: American Meteorological Society
Funding Number(s)
WBS: 281945
Distribution Limits
Public
Copyright
Portions of document may include copyright protected material.
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