Lightning Imaging Sensor Data Research Articles

Long‐term assessment of ERA5 reanalysis rainfall for lightning events over India observed by Tropical Rainfall Measurement Mission Lightning Imaging Sensor

AbstractThe ability of numerical weather prediction models to accurately predict extreme weather events, such as thunderstorms marked by heavy rainfall and lightning activities, has consistently been of great importance for human life. The objective of this study is to assess the long‐term reliability of the European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) rainfall in comparison to the Indian gauge‐adjusted Global Satellite Mapping of Precipitation (GSMaP_ISRO) rainfall at the time of lightning flashes measured by the Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission satellite over the Indian region during the years 2001–2014. This analysis will provide valuable insights into the intricate relationship between lightning flashes and precipitation under various terrain conditions (low, mid, or high), across oceanic regions (Bay of Bengal, Arabian Sea), and during different monsoon phases (normal, active, or deficit). According to a prolonged examination of LIS data, April–June accounts for ~50% of the total flashes, with the largest number of flashes occurring over the Himalayan and the northeastern part of India. According to hourly GSMaP_ISRO rainfall, the most substantial lightning‐associated rainfall happens an hour prior to lightning flash (T − 1) and within three hours after (T + 3), indicating a robust correlation between heavy rainfall and lightning activity during this time frame. The rainfall in the ERA5 reanalysis misses the intensity as well as duration of the peak rainfall at the time of lightning flashes. Furthermore, the ERA5 reanalysis rainfall depicts under (over)‐estimation of rainfall in plain (orographic) regions. The underestimation of ERA5 rainfall is very pronounced over the Indian Ocean and Bay of Bengal regions, mainly between flash time (T) to two hours after the flash time (T + 2). The results indicate that there is a requirement for additional enhancements in the ERA5 reanalysis rainfall for lightning occurrences.

Mapping main risk areas of lightning fatalities between 2000 and 2020 over Odisha state (India): A diagnostic approach to reduce lightning fatalities using statistical and spatiotemporal analyses

This study analyzes the spatiotemporal variation of lightning flashes and lightning strike deaths from 2001 to 2020 among all 30 districts of Odisha State, India. Lightning flash data for the study area were acquired from Lightning Imaging Sensor (LIS) installed aboard the Tropical Rainfall Measuring Mission (TRMM) for the 2001–2014 period and from International Space Station for the 2017–2020 period. Deaths by lightning flashes were acquired from the annual report of natural calamities for the 2001–2020 period from the Revenue and Disaster Management Department, Government of Odisha. In this study, the spatial pattern of lightning flashes based on LIS data and resultant deaths were assessed using spatiotemporal statistical analysis, including the interpolation method and Sen's slope estimator. The geospatial heat maps of lightning strikes and deaths highlight the spatiotemporal heterogeneity of lightning strikes and induced deaths in Odisha State. Furthermore, statistical analyses demonstrate an apparent increase in lightning strikes in the state as a whole, with particular attention to the Mayurbhanj, Sundargarh, and Keonjhar districts, which had the highest incidence of lightning. Odisha State was hit by more than 10,000 lightning strikes every year between 2000 and 2020, excluding 2001, 2017, and 2018. The results show a moderate correlation (R = 0.61) between lightning strikes and lightning deaths in Odisha State during the analyzed period, which further needs to be investigated with respect to the seasonality of lightning, the locational vulnerability, and temporal risk.

Lightning Climatology and Human Vulnerability to Lightning Hazards in a School Community: A Case Study in Sri Lanka using LIS Data from TRMM Satellite

This study reported lightning climatology and human vulnerability to lightning in a 20 km × 20 km high-density school area in Colombo city in Sri Lanka from 1998 to 2014 using Lightning Imaging Sensor (LIS) flash data of NASA’s Tropical Rainfall Measuring Mission (TRMM). An average annual flash density recorded over the study area was 9.43 flashes km-2 year-1. A maximum of 49% lightning flashes happened during the first inter-monsoon season. There were only 4% lightning flashes that occurred during 06.00-12.00 LT and during 18.00-24.00 LT, it was 67%, whereas 94% of lightning flashes within a day had occurred after 14.00 LT. It is recommended that, without having proper lightning hazard preventive measures, schools in the study area should avoid or minimalize scheduling their outdoor activities in high lightning risk months of April and November. Especially, after-school outdoor activities should be planned with proper safety measures during the aforementioned months as per the diurnal analysis. Moreover, May to September and December to February were the months with the least lightning risk levels. It is recommended to follow the proposed five-level lightning safety guideline which includes, schedule outdoor activities by considering the variation of lightning activities, follow the 30-30 rule whenever required, avoid staying at the most hazardous locations which are vulnerable to lightning accidents, crouching action if required and providing first-aid whenever necessary. Not only for the Sri Lankan context but also the study is crucial and highly applicable for all schools and other institutes especially in other tropical countries.

Early History of Using Total Lightning Data at NWS Melbourne, Florida

This forecaster’s note documents the early history (1989–1998) of the use of total lightning data within an operational forecast and warning environment. As early as 1989, the Melbourne field office of the National Weather Service had access to real-time cloud-to-ground lightning data. In 1993, the Lightning Detection and Ranging system (capable of detecting all types of lightning flashes) became available. In 1996, these two lightning data sets, along with radar data, were incorporated into the Lightning Imaging Sensor Data Applications Display (LISDAD) system. During a 3-y period (1996–1998 inclusive), the LISDAD permitted forecasters to observe relationships of total lightning with a variety of convective events, including pulse-severe thunderstorms in the warm season, cool-season tornadic supercells, tornadic mini-supercells in tropical cyclones, and non-severe storms. Major findings included: 1) “lightning jumps” with warm-season pulse-severe storms several minutes prior to reported severe weather; 2) cool-season tornadic supercell storms with very large total flash rates; and 3) tornadic mini-supercells in tropical cyclones produced only small amounts of lightning, however this sporadic activity benefited forecasters by implying stronger updraft development in a favorably sheared environment, in turn implying possible storm rotation and potential tornadogenesis. Finally, given the availability of total lightning datasets to operational forecasters, local forecast products could more effectively provide the public information about the overall lightning threat.

Visualizing the lightning flashes over the Republic of Azerbaijan by analyzing the lightning imaging sensor data

Visualizing the lightning flashes over the Republic of Azerbaijan by analyzing the lightning imaging sensor data

Satellite-observed lightning hotspots in India and lightning variability over tropical South India

Lightning characteristics in India are examined with satellite-based Lightning Imaging Sensor (LIS) and ground-based Indian Lightning Detection Network (ILDN). LIS observations indicated that synoptic weather systems are major contributors of lightning in Indian hotspots. Western disturbances (mid-tropospheric systems with extratropical origin) were the greatest contributor of lightning in the Himalayas (93%), tropical cyclonic storms and low-pressure systems (oceanic in origin) were key lightning contributors in parts of eastern India (43%), and lower tropospheric troughs were major contributors in other hotspots. For the first time, this study reported the occurrence of significantly high lightning activity before active monsoon spells in the Central India region (65–87° E, 18–27° N). Consequently, satellite-based lightning observations could be used to predict active monsoon spells. Harmonic analysis was used to study diurnal lightning-flash density. The maximum observed standardized diurnal amplitude of lightning activity was 0.35, and maximum explained diurnal variation was 15%. Also, for the first time, we compared the ILDN data and LIS observations, and found good agreement regarding lightning variability. LIS data showed an increase in annual lightning activity in tropical South-western India (SWI), and the results also suggested that during El Niño and negative Indian Ocean Dipole periods, SWI experiences above-average lightning activity.

Spatiotemporal Lightning Activity Detected by WWLLN over the Tibetan Plateau and Its Comparison with LIS Lightning

AbstractHerein, we compared data on the spatiotemporal distribution of lightning activity obtained from the World Wide Lightning Location Network (WWLLN) with that from the Lightning Imaging Sensor (LIS). The WWLLN and LIS both suggest intense lightning activity over the central and southeastern Tibetan Plateau (TP) during May–September. Meanwhile, the WWLLN indicates relatively weak lightning activity over the northeastern TP, where the LIS suggests very intense lightning activity, and it also indicates a high-density lightning center over the southwestern TP that is not suggested by the LIS. Furthermore, the WWLLN lightning peaks in August in terms of monthly variation and in late August in terms of 10-day variation, unlike the corresponding LIS lightning peaks of July and late June, respectively. Other observation data were also introduced into the comparison. The blackbody temperature (TBB) data from the Fengyun-2E geostationary satellite (as a proxy of deep convection) and thunderstorm-day data support the spatial distribution of the WWLLN lightning more. Meanwhile, for seasonal variation, the TBB data are more analogous to the LIS data, whereas the cloud-to-ground (CG) lightning data from a local CG lightning location system are closer to the WWLLN data. It is speculated that the different WWLLN and LIS observation modes may cause their data to represent different dominant types of lightning, thereby leading to differences in the spatiotemporal distributions of their data. The results may further imply that there exist regional differences and seasonal variations in the electrical properties of thunderstorms over the TP.

Three Years of the Lightning Imaging Sensor Onboard the International Space Station: Expanded Global Coverage and Enhanced Applications

AbstractThe 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.

Satellite-based observation of lightning climatology over Nepal

The lightning climatology over Nepal is analysed in detail for the first time. For the analysis, we utilised the satellite-based lightning imaging sensor data for the period from 1998 to 2013. A comparison of these climatological results is also performed with two ground-based lightning detection networks, namely, the World Wide Lightning Location Network and the Global Lightning Network for 3 yr from 2011 to 2013. On analysing the data obtained from the three sources, we conclude that the months of April and May are extremely vulnerable in the perspective of lightning hazards in Nepal, in contrast to the results reported previously which indicated that the maximum lightning activity occurred in the month of June. The central and eastern regions of the country receive the majority of lightning strikes during the months of April and May. The present finding is supported by the thunderstorm frequency data obtained from the disaster Information Management System, Nepal and also from thunder-day data from NOAA.

Spatiotemporal Variability of Lightning Flash Distribution over Sri Lanka

The variation of the lightning activities over Sri Lanka and surrounded costal belt (5.750N-10.000N and 79.50E-89.000E) is studied using lightning flash data of Lightning Imaging Sensor (LIS) which was launched in November 1997 for NASA’s Tropical Rainfall Measuring Mission (TRMM). The LIS data for the period of 1998 to 2014 are considered for this study. The spatial and temporal variation of lightning activities is investigated and respective results are presented. The diurnal variation over the studied area presents that maximum and minimum flash count recorded at 1530-1630 Local Time (10-11UTC) and 0530-0630LT (00-01UTC) respectively. Maximum lightning activities over the observed area have occurred after the 1330LT (08UTC) in every year during the considered time period. The seasonal variation of the lightning activities shows that the maximum lightning activities happened in First inter monsoon season (March to April) with 30.90% total lightning flashes and minimum lightning activities recorded in Northeast monsoon season (December to February) with 8.51% of total lightning flashes. Maximum flash density of 14.37fl km-2year-1 was observed at 6.980N/80.160E in First inter monsoon season. These seasonal lighting activities are agree with seasonal convective activities and temperature variation base on propagation of Intra-Tropical Convection Zone over the studied particular area. Mean monthly flash count presents a maximum in the month of April with 29.12% of lightning flashes. Variation pattern of number of lightning activities in month of April shows a tiny increment during the time period of 1998 to 2014. Maximum annual flash density of 28.09fl km-2yr-1 was observed at 6.980N/80.170E. The latitudinal variation of the lightning flash density is depicted that extreme lightning activities have happened at the southern part of the county and results show that there is a noticeable lack of lightning activities over the surrounded costal belt relatively landmass.

Spatiotemporal Variability of Lightning Flash Distribution over Sri Lanka

The variation of the lightning activities over Sri Lanka and surrounded costal belt (5.750N-10.000N and 79.50E-89.000E) is studied using lightning flash data of Lightning Imaging Sensor (LIS) which was launched in November 1997 for NASA’s Tropical Rainfall Measuring Mission (TRMM). The LIS data for the period of 1998 to 2014 are considered for this study. The spatial and temporal variation of lightning activities is investigated and respective results are presented. The diurnal variation over the studied area presents that maximum and minimum flash count recorded at 1530-1630 Local Time (10-11UTC) and 0530-0630LT (00-01UTC) respectively. Maximum lightning activities over the observed area have occurred after the 1330LT (08UTC) in every year during the considered time period. The seasonal variation of the lightning activities shows that the maximum lightning activities happened in First inter monsoon season (March to April) with 30.90% total lightning flashes and minimum lightning activities recorded in Northeast monsoon season (December to February) with 8.51% of total lightning flashes. Maximum flash density of 14.37fl km-2year-1 was observed at 6.980N/80.160E in First inter monsoon season. These seasonal lighting activities are agree with seasonal convective activities and temperature variation base on propagation of Intra-Tropical Convection Zone over the studied particular area. Mean monthly flash count presents a maximum in the month of April with 29.12% of lightning flashes. Variation pattern of number of lightning activities in month of April shows a tiny increment during the time period of 1998 to 2014. Maximum annual flash density of 28.09fl km-2yr-1 was observed at 6.980N/80.170E. The latitudinal variation of the lightning flash density is depicted that extreme lightning activities have happened at the southern part of the county and results show that there is a noticeable lack of lightning activities over the surrounded costal belt relatively landmass.

Lightning, rainfall, AOD, and convection variabilities in the monsoon zone of India

ABSTRACTLightning, rainfall, aerosol optical depth (AOD), and convection variabilities in the monsoon zone of India are studied during the period 2001–2012. Accumulated rain is used to study rainfall and the parameters surface temperature, convective available potential energy (CAPE), and outgoing longwave radiation (OLR) are used to study convection. Principal component analysis (PCA) is performed for the first time in order to understand the variability and interrelations among the parameters lightning (flash rates derived from the Tropical Rainfall Measuring Mission Satellite [TRMM] Lightning Imaging Sensor data products), rainfall, AOD, and convection (surface temperature, CAPE, and OLR), in the monsoon zone of India. The results of PCA show that lightning is very well correlated with CAPE and surface temperature. Lightning is poorly correlated with AOD and accumulated rain. This indicates that buoyancy due to heating of land during daytime is the best predictor for lightning occurrence in the monsoon zone. Very good correlation between AOD and accumulated rain suggests the significance of AOD in the monsoon zone precipitation.

Spatial and temporal analysis of a 17-year lightning climatology over Bangladesh with LIS data

Using NASA’s TRMM Lightning Imaging Sensor (LIS) data from 1998 to 2014, this paper presents a 17-year lightning climatology of Bangladesh, at 0.5° × 0.5° spatial resolution. Diurnal, seasonal, monthly and annual variations in the occurrence of lightning flashes were explored. The diurnal regime of lightning is dominated by afternoon/evening events. Overall, peak lightning activity occurs in the early morning (0200 LST) and evening (1900 LST). The distribution of lightning flash counts by season over Bangladesh landmass is as follows: pre-monsoon (69.2%), monsoon (24.1%), post-monsoon (4.6%) and winter (2.1%). Flash rate density (FRD) hotspots were primarily located in the north and north-eastern parts of Bangladesh, with a maximum of 72 fl km−2 year−1. Spatially, the distribution of FRD increases from the Bay of Bengal in the south to relatively higher elevations (of the Himalayan foothills) in the north. A spatial shift in FRD hotspots occurs with change in season. For example, in monsoon season, hotspots of lightning activity move in a south-westerly direction from their pre-monsoon location (i.e. north-eastern Bangladesh) towards West Bengal in India. South and south-eastern parts of Bangladesh experience high lightning activity during post-monsoon season due to regional orographic lifting and low-pressure systems (i.e. cyclone) in the Bay of Bengal. To the best of our knowledge, this is the first study focused on LIS-based lightning climatology over Bangladesh. This baseline study, therefore, is an essential first step towards effective management of lightning-related hazards in Bangladesh.

The effect of El Nino and La Nina on lightning activity: its relation with meteorological and cloud microphysical parameters

The decadal variation of lightning activity over Northeast India (NEI) from the year 2002 to 2011 is studied with the help of satellite-based lightning imaging sensor (LIS) data. An anomalous 56 % increase in lightning activity is observed in the year 2010 with respect to the previous years. To investigate the reason behind this increase, the LIS data are analyzed with several meteorological and cloud microphysical parameters. These parameters are convective sources of cloud ice, cloud top temperature, surface temperature, convective precipitation rate and total ice water content and convective available potential energy. On a synoptic scale, the period of anomalous lightning activity could be related to the development of an El Nino event at the middle of 2009 that broke down in the early months of the next year with a rapid transition to La Nina by August 2010. Analyses expose that El Nino Southern Oscillation might have diversely modified the local meteorological and cloud microphysical parameters. It comes out that this rapid transition from El Nino to La Nina condition could be the possible reason behind the dramatic increase in lightning activity, which was not previously documented over NEI.

Microphysical processes and hydrometeor distributions associated with thunderstorms over India: WRF (cloud-resolving) simulations and validations using TRMM

Thunderstorms are one of the disastrous weather events that affect various parts of the Indian region during the pre-monsoon summer months of March–April–May (MAM). Keeping this societal impact in account, this paper has documented the vertical distribution of cloud microphysical properties and dynamical fields associated with number of thunderstorms over different thunderstorm-prone regions of India. The main objective of this study was to bring out the spatial heterogeneity in the structure of thunderstorms during MAM. In spite of being such an important weather system, the present-day skill of forecasting such systems is particularly poor. This as such prompts us to ponder whether any existing microphysical scheme is able to capture the inherent heterogeneous structure of thunderstorms over different parts of India. To find an answer to this question, the regions are divided based on pre-monsoon lightning distribution obtained from the tropical rainfall measuring mission lightning imaging sensor data. Keeping this observation in background, cloud-resolving simulations are performed using the Weather Research and Forecasting-Advanced Research Weather Model (version 3.2) along with three explicit microphysical schemes for a number of thunderstorm cases those occurred over five different regions of India. The composite structure of all thunderstorms simulated over a region is compared with observation to identify the systematic model bias. It is clearly brought out that the Thompson scheme with the present form is not able to capture different phases of thunderstorms over different parts of the country. However, WDM6 and Morrison are able to capture some of the features reasonably well, along with some degree of uncertainty. The inner structure of thunderstorms is very well brought out by contour frequency altitude diagram. This study therefore provides a framework and a basis of further modifications of WDM6 and Morrison for improving the model forecast for thunderstorms over the Indian region.

Timing Uncertainty of the Lightning Imaging Sensor

AbstractThe timing uncertainty of the Lightning Imaging Sensor (LIS), on orbit, is not currently accurately known. This is due to an imprecise value of the frame rate in the literature; the conceptual design value of 500 frames per second (fps) is often quoted. As researchers explore more ways to apply LIS data—in particular, the utility of group-level data, which correspond to strokes—a more precise value of the frame rate and timing uncertainty is important for proper understanding and use of the data. In this study, the average on-orbit frame rate was documented. From this, the timing uncertainty for LIS data was determined. Using on-orbit LIS data, the average frame rate of LIS is 558.58 fps and the timing uncertainty for LIS groups and events is 250 μs. It is shown that this uncertainty is associated with the quantization of the time of each frame. Further, the source time of optical pulses from lightning can have a bias that is not currently accounted for in the LIS data. This study shows how this correction can be on the order of the timing uncertainty, and a method in which this correction can be determined is outlined.

Investigation of Lightning Distribution Using LIS Data from TRMM Satellite

This paper presents an investigation on lightning distribution using Lightning Imaging Sensor (LIS) data from Tropical Rainfall Measuring Mission (TRMM) satellite. The investigation is carried out on distribution and variability of total lightning occurred in the area of Washington DC (38.54°N, 77.2°W) during January to April 2011. LIS captures emissions that occurred in the atmosphere which emitted by lightning discharge by covering the most between ±35o in latitude. The lightning distributions are characterized based on monthly, daily, hourly and seasonal basis. The maps of global distribution of lightning flashes have been used as initial data. This analysis shows that a total number of 3.5 million flashes were detected during four months observation. The highest number of flashes recorded in April is about 3.4 million flashes compared to the 3,993 flashes in January. In terms of seasonal, this observation show that the spring season during March and April has highest occurrence of lightning which is 53.2% compared to the winter season in January and February which only 46.8%. This study can provides expected variations of the lightning distribution on the diurnal and seasonal basis, thus make it useful in describing the Earth’s climate.

Thunderstorm incidence in southeastern Brazil estimated from different data sources

Abstract. This paper describes a comparative analysis of the thunderstorm incidence in southeastern Brazil obtained from thunderstorm days observed at two different epochs (from 1910 to 1951 and from 1971 to 1984) and from lightning data provided by the Brazilian lightning location system RINDAT (from 1999 to 2006) and the Lightning Imaging Sensor (LIS) on board the Tropical Rainfall Measuring Mission (TRMM) satellite (from 1998 to 2010). The results are interpreted in terms of the main synoptic patterns associated with thunderstorm activity in this region, indicating that the prevailing synoptic pattern associated with thunderstorm activity is the occurrence of frontal systems and their modulation by the South Atlantic Convergence Zone (SACZ) and topography. Evidence of urban effects is also found. The results are also discussed in the context of practical applications involving their use in the Brazilian lightning protection standards, suggesting that the present version of the Brazilian standards should be revised incorporating RINDAT and LIS data. Finally, the results are important to improve our knowledge about the limitations of the different techniques used to record the thunderstorm activity and support future climatic studies.

The lightning activity associated with the dry and moist convections in the Himalayan Regions

AbstractLightning activity in the dry environment of northwest India and Pakistan (NW) and in the moist environment of northeast India (NE) has been examined from the Optical Transient Detector and Lightning Imaging Sensor data obtained from the Tropical Rainfall Measuring Mission satellite during 1995–2010. In the NW region, seasonal variation of flash rate is annual with a maximum in July but is semi‐annual with a primary maximum in April and a secondary maximum in September, in the NE region. On diurnal scale, flash rate is the maximum in the afternoons, in both the NE and NW regions. The correlation of flash rate with convective parameters, viz. surface temperature, convective available potential energy (CAPE) and outgoing long‐wave radiation is better with convective activity in the NW than in the NE region. Mean value of aerosol optical depth at 550 nm is ~ 26% higher and is highly correlated with flash rate in NW as compared to that in NE. Results indicate that CAPE is ~ 120 times more efficient in NW than in the NE region for production of lightning. The empirical orthogonal function analysis of flash rate, surface temperature, and CAPE shows that variance of lightning activity in these regions cannot be fully explained by the variance in the surface temperature and CAPE alone, and that some other factors, such as orographic lifting, precipitation, topography, etc., may also contribute to this variance in these mountainous regions. Further, the increase in CAPE due to orographic lifting in the Himalayan foothills in the NE region may contribute to ~ 7.5% increase in lightning activity. Relative roles of the thermally induced and moisture‐induced changes in CAPE are examined in these regions. This study merely raises the questions, and that additional research is required for explaining the fundamental reasons for the reported observations here.

Optimized regional and interannual variability of lightning in a global chemical transport model constrained by LIS/OTD satellite data

Nitrogen oxides (NOx ≡ NO + NO2) produced by lightning make a major contribution to the global production of tropospheric ozone and OH. Lightning distributions inferred from standard convective parameterizations in global chemical transport models (CTMs) fail to reproduce observations from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) satellite instruments. We present an optimal regional scaling algorithm for CTMs to fit the lightning NOxsource to the satellite lightning data in a way that preserves the coupling to deep convective transport. We show that applying monthly scaling factors over ∼37 regions globally significantly improves the tropical ozone simulation in the GEOS‐Chem CTM as compared to a simulation unconstrained by the satellite data and performs equally well to a simulation with local scaling. The coarse regional scaling preserves sufficient statistics in the satellite data to constrain the interannual variability (IAV) of lightning. After processing the LIS data to remove their diurnal sampling bias, we construct a monthly time series of lightning flash rates for 1998–2010 and 35°S–35°N. We find a correlation of IAV in total tropical lightning with El Niño but not with the solar cycle or the quasi‐biennial oscillation. The global lightning NOxsource ± IAV standard deviation in GEOS‐Chem is 6.0 ± 0.5 Tg N yr−1, compared to 5.5 ± 0.8 Tg N yr−1 for the biomass burning source. Lightning NOx could have a large influence on the IAV of tropospheric ozone because it is released in the upper troposphere where ozone production is most efficient.