Lightning can give forecasters an early clue that a thunderstorm is strengthening. A rapid rise in a storm’s total lightning flash rate—called a lightning jump—often accompanies a pulse in its updraft and has been observed tens of minutes before severe weather reaches the ground. It is a reason to watch a storm more closely, not a guarantee that it will produce damaging wind, hail, or a tornado.
What a lightning jump tells forecasters
Thunderstorm lightning forms through electrical processes involving ice particles inside the storm. As those particles grow and move, the storm’s electrical activity changes. Tracking the rate and patterns of flashes can therefore help reveal how a storm is evolving, including changes associated with its updraft.
NOAA’s National Severe Storms Laboratory (NSSL) says, “We have shown that rapid increases in total lightning activity are often observed tens of minutes in advance of severe weather occurring at the ground.” A lightning jump is that rapid increase in a storm’s total flash rate. Because it can occur alongside an updraft pulse, it can flag a storm that may be intensifying while forecasters assess other evidence.
“Total lightning” includes intracloud flashes as well as cloud-to-ground strikes. Looking only for ground strikes misses some of the electrical activity that lightning-monitoring systems can track. NSSL also describes mapped patterns that may help researchers and forecasters study storm structure: some supercells have lightning holes near updrafts where precipitation is scarce, flashes near updrafts may be smaller, and flash altitudes can change over a storm’s life cycle. These are clues seen in some storms, not rules that apply to every thunderstorm. NOAA NSSL: Lightning research
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How lightning data fits into storm monitoring
Lightning observations add a view of storm activity; they do not replace radar or other weather data. Forecasters combine lightning trends with radar, satellite imagery, surface observations, and forecast guidance to judge whether a storm is changing and what hazards may be developing.
Satellite and ground-based observations
NOAA’s Geostationary Lightning Mapper (GLM), aboard the GOES-R series, provides rapidly updated, broad-area lightning observations. That coverage can be especially useful where radar or surface observations are limited, such as rural or mountainous areas and the open ocean. Ground-based networks provide another way to observe lightning; each observing system contributes data that forecasters interpret alongside other sources rather than as a complete picture on its own. NOAA NESDIS: Geostationary Lightning Mapper
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Lightning jumps and lightning-occurrence guidance answer different questions
A lightning-jump product looks for a rapid increase in a storm’s flash rate relative to a recent baseline, helping forecasters identify storms that may be intensifying. One NOAA Warning Decision Training Division product description specifies a flag when the current rate is more than two standard deviations above the previous 10-minute period, for storms producing at least 10 flashes per minute. Those are settings for that product configuration—not a universal definition of a lightning jump.
NOAA’s experimental LightningCast guidance addresses a different question: where lightning is likely to occur, including before the first observed flash. It provides probability guidance about lightning occurrence; a lightning jump is a monitoring signal for possible storm intensification. NOAA NESDIS: LightningCast
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Can lightning predict severe weather?
It can support short-term situational awareness, but it cannot determine by itself whether a storm will produce severe weather. A jump raises a concern to investigate; forecasters check whether radar, satellite, surface observations, and other guidance support the same interpretation. Lightning-based signals are probabilistic, so a jump may occur without a severe-weather report, and severe weather can occur without a forecaster treating a jump as a decisive signal.
Performance depends on the algorithm, data source, region, time period, and how outcomes are verified. In a study of the 2015 convective season in the northeastern United States, Pamela Eck, Brian H. Tang, and Lance F. Bosart reported a 75% probability of detection and a 55% false alarm rate for lightning jumps. Those figures describe that study’s sample and method, not the expected performance everywhere. The authors also noted that severe-weather reports can have gaps and that lightning jumps have limited value when used alone. Eck, Tang, and Bosart (2017): Lightning jumps in the northeastern United States
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Operational guidance also depends on the data and product. NOAA’s Warning Decision Training Division says the false-alarm rate increased at lower sigma levels, including two standard deviations, after its lightning-jump product switched to Earth Networks Total Lightning data. For that product, the guide says jumps of at least three standard deviations—and possibly four to five—may be more useful. These are product-specific operational observations, not settled thresholds for every network or storm. NOAA WDTD Virtual Lab: Lightning Jump
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Why lightning forecasts remain uncertain
Forecasters cannot predict individual lightning strikes. Lightning is frequent, widespread, and unpredictable at the strike-by-strike level. Estimating where lightning is likely instead relies on patterns and probabilities, informed by a storm’s history, growth, movement, age, height relative to freezing temperatures, and the presence of ice and updrafts. The atmosphere is chaotic, so modest changes in a storm or its environment can alter what happens next. NOAA NSSL: Severe weather and lightning forecasting
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The time horizon depends on the question. A lightning jump can be a short-term clue to possible severe weather tens of minutes ahead in observed cases. Model-based approaches can estimate lightning probabilities farther out, but there is no single lead time that applies to all lightning or severe-storm forecasts. NSSL also describes combining lightning with radar data in model data assimilation to improve storm initial conditions and forecasts. NOAA Hazardous Weather Testbed: EWP projects
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