The Lightning Imaging Sensor (LIS) was launched to the International Space Station (ISS) in February 2017, detecting optical signatures of lightning with storm‐scale horizontal resolution during both day and night. ISS LIS data are available beginning 1 March 2017. Millisecond timing allows detailed intercalibration and validation with other spaceborne and ground‐based lightning sensors. Initial comparisons with those other sensors suggest flash detection efficiency around 60% (diurnal variability of 51–75%), false alarm rate under 5%, timing accuracy better than 2 ms, and horizontal location accuracy around 3 km. The spatially uniform flash detection capability of ISS LIS from low‐Earth orbit allows assessment of spatially varying flash detection efficiency for other sensors and networks, particularly the Geostationary Lightning Mappers. ISS LIS provides research data suitable for investigations of lightning physics, climatology, thunderstorm processes, and atmospheric composition, as well as real‐time lightning data for operational forecasting and aviation weather interests. ISS LIS enables enrichment and extension of the long‐term global climatology of lightning from space and is the only recent platform that extends the global record to higher latitudes (±55°). The global spatial distribution of lightning from ISS LIS is broadly similar to previous data sets, with globally averaged seasonal/annual flash rates about 5–10% lower. This difference is likely due to reduced flash detection efficiency that will be mitigated in future ISS LIS data processing, as well as the shorter ISS LIS period of record. The expected land/ocean contrast in the diurnal variability of global lightning is also observed.

A detailed case study analysis of four thunderstorms is performed using polarimetric and multi-Doppler capabilities to provide specificity on the physical and dynamical drivers behind lightning jumps. The main differences between small increases in the total flash rate and a lightning jump are the increases in graupel mass and updraft volumes ≥10 m s⁻¹ between the −10° and −40°C isotherms. Updraft volumes ≥10 m s⁻¹ increased in magnitude at least 3–5 min in advance of the increase in both graupel mass and total flash rate. Updraft volumes ≥10 m s⁻¹ are more robustly correlated to total flash rate than maximum updraft speed over a thunderstorm’s entire life cycle. However, peak updraft speeds increase prior to 8 of the 12 lightning jumps examined. Decreases in mean and median flash footprint size during increases in total lightning are observed in all four thunderstorms and are most notable during development stages within the most intense storms. However, this inverse relationship breaks down on larger storm scales as storms mature and anvils and stratiform regions developed with time. Promisingly, smaller flash sizes are still collocated with the strongest updraft speeds, while larger flash sizes are observed within weaker updraft regions. The results herein emphasize the following for lightning jump applications: both the lightning jump sigma level and the resultant magnitude of the total flash rate must be employed in conjunction to assess storm intensity using lightning data. The sigma-level magnitude of the lightning jump is the early warning that indicates that rapid intensification is occurring, while the magnitude of the total flash rate provides insight into the size and maintenance of the updraft volume and graupel mass. These cases serve as conceptual models for future applications of the lightning jump algorithm for hazardous weather monitoring.

Analysis was performed to determine whether a lightning flash could be associated with every reported lightning-initiated wildfire that grew to at least 4 km². In total, 905 lightning-initiated wildfires within the Continental United States (CONUS) between 2012 and 2015 were analyzed. Fixed and fire radius search methods showed that 81–88% of wildfires had a corresponding lightning flash within a 14 day period prior to the report date. The two methods showed that 52–60% of lightning-initiated wildfires were reported on the same day as the closest lightning flash. The fire radius method indicated the most promising spatial results, where the median distance between the closest lightning and the wildfire start location was 0.83 km, followed by a 75th percentile of 1.6 km and a 95th percentile of 5.86 km. Ninety percent of the closest lightning flashes to wildfires were negative polarity. Maximum flash densities were less than 0.41 flashes km² for the 24 h period at the fire start location. The majority of lightning-initiated holdover events were observed in the Western CONUS, with a peak density in north-central Idaho. A twelve day holdover event in New Mexico was also discussed, outlining the opportunities and limitations of using lightning data to characterize wildfires.

Thirty-nine thunderstorms are examined using multiple-Doppler, polarimetric, and total lightning observations to understand the role of mixed-phase kinematics and microphysics in the development of lightning jumps. This sample size is larger than those of previous studies on this topic. The principal result of this study is that lightning jumps are a result of mixed-phase updraft intensification. Larger increases in intense updraft volume (≥10 m s−1) and larger changes in peak updraft speed are observed prior to lightning jump occurrence when compared to other nonjump increases in total flash rate. Wilcoxon–Mann–Whitney rank sum testing yields p values ≤ 0.05, indicating statistical independence between lightning jump and nonjump distributions for these two parameters. Similar changes in mixed-phase graupel mass magnitude are observed prior to lightning jumps and nonjump increases in total flash rate. The p value for the graupel mass change is p = 0.096, so jump and nonjump distributions for the graupel mass change are not found to be statistically independent using the p = 0.05 significance level. The timing of updraft volume, speed, and graupel mass increases is found to be 4–13 min in advance of lightning jump occurrence. Also, severe storms without lightning jumps lack robust mixed-phase updrafts, demonstrating that mixed-phase updrafts are not always a requirement for severe weather occurrence. Therefore, the results of this study show that lightning jump occurrences are coincident with larger increases in intense mixed-phase updraft volume and peak updraft speed than smaller nonjump increases in total flash rate.

On 15 January 2022, Hunga Volcano in Tonga produced the most violent eruption in the modern satellite era, sending a water‐rich plume at least 58 km high. Using a combination of satellite‐ and ground‐based sensors, we investigate the astonishing rate of volcanic lightning (>2,600 flashes min⁻¹) and what it reveals about the dynamics of the submarine eruption. In map view, lightning locations form radially expanding rings. We show that the initial lightning ring is co‐located with an internal gravity wave traveling >80 m s⁻¹ in the stratospheric umbrella cloud. Buoyant oscillations of the plume's overshooting top generated the gravity waves, which enhanced turbulent particle interactions and triggered high‐current electrical discharges at unusually high altitudes. Our analysis attributes the intense lightning activity to an exceptional mass eruption rate (>5 × 10⁹ kg s⁻¹), rapidly expanding umbrella cloud, and entrainment of abundant seawater vaporized from magma‐water interaction at the submarine vent.

Lightning flash rate parameterizations based on polarimetric and multi-Doppler radar inferred microphysical (e.g., graupel volume, graupel mass, 35 dBZ volume) and kinematic (e.g., updraft volume, maximum updraft velocity) parameters have important applications in atmospheric science. Although past studies have established relations between flash rate and storm parameters, their expected performance in a variety of storm and flash rate conditions is uncertain due to sample limitations. Radar network and lightning mapping array observations over Alabama of a large and diverse sample of 33 storms are input to hydrometeor identification, vertical velocity retrieval and flash rate algorithms to develop and test flash rate relations. When applied to this sample, prior flash rate linear relations result in larger errors overall, including often much larger bias (both over- and under-estimation) and root mean square errors compared to the new linear relations. At low flash rates, the new flash rate relations based on kinematic parameters have larger errors compared to those based on microphysical ones. Sensitivity of error to the functional form (e.g., zero or non-zero intercept) is also tested. When considering all factors (e.g., low errors including at low flash rate, consistency with past linear relations, and insensitivity to functional form), the flash rate parameterization based on graupel volume has the best overall performance.