In 2024, the state with the most number of lightning strikes recorded across the United States was Texas, with over **** million lightning events. Texas always has a higher lightning count than any other state, partly due to its size and location. Ranking second that year was the state of Florida, with some **** million lightning events recorded.

Florida was the state with the highest lightning density across the United States in 2023, having recorded nearly *** lightning events per square kilometer. That year, Florida was also the state with the second-largest number of lightning strikes in total. Meanwhile, the state of Mississippi ranked second in terms lightning density, at about *** lightning events per square kilometer.

Oregon recorded the largest number of lightning-caused wildfires in the United States in 2024. That year, there were *** wildfires started by lightning in the southwestern state. For comparison, this represents almost ** percent of the total number of wildfires recorded in Oregon the same year. Arizona ranked second, with *** lightning-caused wildfires recorded. Lightning is the main natural cause of bush and forest fires.

This data set contains 5 minute maps of lightning strikes over the north central United States from the USPLN (United States Precision Lightning Network) operated by WSI. The imagery were developed by NCAR/EOL.

Lightning stroke data are collected in 1-hour reports which contain cloud-to-ground lightning stroke data and cloud flash discharges. The data are available in ASCII NAPLN extended data format. The reports have been combined into daily tar files and range from 1 May to 30 June 2012.

This file contains 1999 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier et al. (1983).

This dataset contains United States Precision Lightning imagery from the 2010 field phase of the VORTEX2 field catalog. The files are gif images. See the catalog link in the related links section below to access the field catalog.

Lightning Warning System Market Outlook

According to our latest research, the global lightning warning system market size reached USD 1.32 billion in 2024, reflecting the industryÂ’s robust expansion in recent years. The market is projected to grow at a CAGR of 7.4% from 2025 to 2033, culminating in a forecasted market size of USD 2.52 billion by 2033. This growth is primarily driven by increasing demand for advanced weather monitoring solutions across critical sectors such as aviation, energy, and public safety, as well as heightened awareness regarding the economic and human costs associated with lightning-related incidents.

The accelerating adoption of lightning warning systems is being propelled by a confluence of technological advancements and escalating climate volatility. As extreme weather events become more frequent and severe due to climate change, the need for real-time, precise lightning detection and warning capabilities has intensified across industries. Sectors such as aviation and energy are especially vulnerable to lightning strikes, which can lead to catastrophic equipment failures, operational disruptions, and even loss of life. This has prompted governments and private enterprises to invest heavily in state-of-the-art lightning warning technologies, including networked sensor arrays, AI-driven analytics, and integrated communication platforms. Furthermore, the proliferation of IoT devices and cloud-based monitoring has made it feasible to deploy comprehensive, scalable lightning detection solutions across geographically dispersed assets, further fueling market growth.

Another significant driver for the lightning warning system market is the growing emphasis on occupational safety and regulatory compliance. Regulatory bodies worldwide have introduced stringent guidelines mandating the installation of lightning protection and early warning systems in high-risk environments such as airports, power plants, mining sites, and sports complexes. Compliance with these regulations not only mitigates legal liabilities but also ensures business continuity by minimizing downtime and safeguarding personnel. The insurance industryÂ’s increasing scrutiny of lightning-related claims has also incentivized organizations to adopt proactive lightning risk management strategies, spurring demand for reliable and accurate warning systems. In addition, public awareness campaigns and educational initiatives have heightened the recognition of lightning hazards, leading to broader market penetration, especially in developing regions where infrastructure modernization is underway.

The regional outlook for the lightning warning system market reveals a dynamic landscape, with Asia Pacific emerging as the fastest-growing region due to rapid industrialization, urbanization, and government investments in disaster management infrastructure. North America and Europe continue to dominate the market in terms of revenue, owing to their mature aviation, energy, and sports sectors, as well as the presence of leading technology providers. Meanwhile, Latin America and the Middle East & Africa are witnessing steady growth, driven by the expansion of critical infrastructure and increasing vulnerability to severe weather events. The interplay of these regional trends is expected to shape the competitive dynamics and innovation trajectory of the global lightning warning system market over the next decade.

Component Analysis

The component segment of the lightning warning system market is characterized by a diverse array of technologies, each playing a crucial role in the overall systemÂ’s performance and reliability. Sensors represent the foundational component, tasked with detecting the electromagnetic signatures of lightning discharges. These sensors have evolved from basic field mills to sophisticated, multi-parameter devices capable of capturing real-time data on lightning intensity, polarity, and proximity. The integration of advanced signal processing algorithms and machine learning has significantly enhanced the accuracy and sensitivity of these sensor

The immediate data, except the lightning flash data behind the figures, are available from https://doi.org/10.5281/zenodo.6493145

This link provides the description and the data files that were used to create the tables and figures in the product. This dataset is associated with the following publication: Kang, D., R. Mathur, G. Pouliot, R. Gilliam, and D. Wong. Significant ground-level ozone attributed to lightning-induced nitrogen oxides during summertime over the Mountain West States. npj Climate and Atmospheric Science. Springer Nature Group, New York, NY, 3: 6, (2020).

This file contains 1991 daily lightning activity data for the state of New Mexico. These data were collected by a network of lightning detection stations scattered throughout the western United States. More information regarding the LLP Lightning Locating System can be found in Maier et al. (1983).

1D test code: Files in folder "1D" will run grey body model if "Makefile" is made and run using command "./MAIN", along with the Villa current profile. To run P1 approximation the files from "NEC_or_P1" replace their equivalents currently in the main folder and rerun the Makefile. The NEC approximation uses the same file, uncomment the indicated lines, and comment out the P1 approximation. The relevant files for SP-3 approximation are in folder "SP3". The grey body model uses the file "mixtureFull19.txt", the other models use "P1ApproxEoS.txt" found in folder "NEC_or_P1".

The file "mixtureFull19.txt" was received from Frederik Träuble and contains the e and rho values used to calculate his EoS. The full EoS can be obtained on application to the authors of “An improved equation of state for air plasma simulations,” Physics of Fluids 33, 036112 (2021) F. Träuble, S. Millmore, and N. Nikiforakis. P1ApproxEoS add the columns for the band averaged absorption coefficients but the code has been submitted in the form that it need the missing lines, which would need to be obtained from the full EoS.

2D test code: The radiative source files are in their labelled folders, PoissonSolutions contains a sample code to pre-compute the magnetic field and current density for a 2D lightning arc with electrode for the ARP standard component D current profile

Absorption Coefficient and band averages for P1/SP3 approximations: There are a number of text files containing data for the absorption coefficient taken from the sources listed in the paper:

*MolecularNitrogen, MolecularOxygen: Kivel, "Bremsstrahlung in air"
*NIIPartition,NIlines,Nitrogen,NIPartition,OIIPartition,OIlines,OIPartition,Oxygen: Martins, "Etude expérimentale et théorique d’un arc de foudre et son interaction avec un matériau aéronautique", NIST database, Konjevic, "Experimental Stark Widths and Shifts for Spectral Lines of Neutral and Ionized Atoms" "Experimental Stark widths

and shifts for spectral lines of neutral and ionized atoms (a critical review of selected data for the period 1989 through 2000)" "Experimental Stark widths and shifts for spectral lines of neutral atoms (a critical review of selected data for the period 1976 to 1982)" *NOMolBands,NOPartitionFunction1,O2Molbands,O2PartitionFunction,N2Molbands,N2PartitionFunction: HITRAN database *PhotoAbsN2, PhotoAbsO2: Chauveau, "Radiative transfer in LTE air plasmas for temperatures up to 15; 000 K" *PhotodetachmentO2Chauveau: Chauveau, "Radiative transfer in LTE air plasmas for temperatures up to 15; 000 K" *PhotoionisationN, Photoionisation2Nnew, PhotoionisationO, Photoionisation2Onew, PhotoionisationNplus, Photoionisation2Nplusnew, PhotoionisationOplus, Photoionisation2Oplusnew: TOPBASE database *PhotoIonN2lambda, PhotoIonO2lambda: Fenelly, "Photoionization and photoabsorption cross sections of O, N2, O2, and N for aeronomic calculations" *SchumanRunge: Churchill "Absorption coefficients of heated air: a tabulation to 24 000 K"

All data accessed June-July 2018

Makefile runs:"Band Averages.C", "BoundBound.C", "BoundFree.C", "FreeFree.C", "LineProperties.C", "KappaTotal.C", "MolecularBands.C" and uses accompanying ".h" files and "Constants.h". It reads in from "mixtureFull19.txt" (again the reduced version is submitted here) and writes to "NECeos.txt" and "P1ApproxEoS.txt". The last column of NEC EoS is the NEC, the other columns are from "mixtureFull19.txt". The last 10 columns of "P1ApproxEoS.txt" are the band averaged values required for the P1 and SP3 approximations, alternating $K_{

u}$ and $K_{ u}B_{ u}$.

During DC-3 TEST lightning stroke data were collected in 1-hour reports which contain cloud-to-ground lightning stroke data and cloud flash discharges. The data are available in ASCII NAPLN extended data format. The reports have been combined into daily tar files. Data are available for May 1-15 of 2011. All users must read and agree to the ERAU-USPLN Data Access Policy associated with this proprietary data set.

Meta Data of the dataset for “Assessing the Impact of Lightning NOx Emissions in CMAQ Using Lightning Flash Data from WWLLN over the Contiguous United States” Figure 2: ThreeYear_NLDN2WWLLN_byNOAAcr_Region_anal.xlsx. The names of the variable are self-explanatory and the original figure is included. Figure 3: NLDN_flash_Monthly_mean_2016_07.ncf.gz, WWLLN_flash_Monthly_mean_2016_07.ncf.gz, WWLLNs_flash_Monthly_mean_2016_07.ncf.gz. These netcdf files contain the monthly mean values of gridded lightning flash rate for all the cases and the figure can be created using any netcdf visualization tool (such as VERDI) or statistical package (such as R). Figures 4,5,6: CMAQ_*_.rds.gz files. These files contain the paired observation-model O3 concentrations from all the model cases for hourly, daily max-8hr, and other statistics. The rds datasets can be read into R as data frame to make these figures. Figure 7 & 8: CCTM_CONC*.nc.gz. The vertical profiles (CONC) contain model data to make Figures 7 and 8. While the observation data are available publicly. Figure 9: NADP_v532_intel18_0_2016_CONUS_.csv. Figure 10: avg_DEP_concentrations.nc.gz. These files contain the monthly mean vet deposition of NO3. Figure 11: NADP_v532_intel18_0_2016_CONUS_.csv. Figure 12: DDEP_TNO3_.nc.gz. These files contain hourly dry deposition of TNO3 over the CONUS domain

• Update Frequency: Weekly

Data from this dataset can be downloaded/accessed through this dataset page and Kaggle's API.

Context

Severe weather is defined as a destructive storm or weather. It is usually applied to local, intense, often damaging storms such as thunderstorms, hail storms, and tornadoes, but it can also describe more widespread events such as tropical systems, blizzards, nor'easters, and derechos.

The Severe Weather Data Inventory (SWDI) is an integrated database of severe weather records for the United States. The records in SWDI come from a variety of sources in the NCDC archive. SWDI provides the ability to search through all of these data to find records covering a particular time period and geographic region, and to download the results of your search in a variety of formats. The formats currently supported are Shapefile (for GIS), KMZ (for Google Earth), CSV (comma-separated), and XML.

Content

The current data layers in SWDI are:
- Filtered Storm Cells (Max Reflectivity >= 45 dBZ) from NEXRAD (Level-III Storm Structure Product)
- All Storm Cells from NEXRAD (Level-III Storm Structure Product)
- Filtered Hail Signatures (Max Size > 0 and Probability = 100%) from NEXRAD (Level-III Hail Product)
- All Hail Signatures from NEXRAD (Level-III Hail Product)
- Mesocyclone Signatures from NEXRAD (Level-III Meso Product)
- Digital Mesocyclone Detection Algorithm from NEXRAD (Level-III MDA Product)
- Tornado Signatures from NEXRAD (Level-III TVS Product)
- Preliminary Local Storm Reports from the NOAA National Weather Service
- Lightning Strikes from Vaisala NLDN

Disclaimer:
SWDI provides a uniform way to access data from a variety of sources, but it does not provide any additional quality control beyond the processing which took place when the data were archived. The data sources in SWDI will not provide complete severe weather coverage of a geographic region or time period, due to a number of factors (eg, reports for a location or time period not provided to NOAA). The absence of SWDI data for a particular location and time should not be interpreted as an indication that no severe weather occurred at that time and location. Furthermore, much of the data in SWDI is automatically derived from radar data and represents probable conditions for an event, rather than a confirmed occurrence.

Acknowledgements

Dataset Source: NOAA. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source — http://www.data.gov/privacy-policy#data_policy — and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.

Cover photo by NASA on Unsplash
Unsplash Images are distributed under a unique Unsplash License.

The global market size of LED Lightning is $XX million in 2018 with XX CAGR from 2014 to 2018, and it is expected to reach $XX million by the end of 2024 with a CAGR of XX% from 2019 to 2024.
Global LED Lightning Market Report 2019 - Market Size, Share, Price, Trend and Forecast is a professional and in-depth study on the current state of the global LED Lightning industry. The key insights of the report:
1.The report provides key statistics on the market status of the LED Lightning manufacturers and is a valuable source of guidance and direction for companies and individuals interested in the industry.
2.The report provides a basic overview of the industry including its definition, applications and manufacturing technology.
3.The report presents the company profile, product specifications, capacity, production value, and 2013-2018 market shares for key vendors.
4.The total market is further divided by company, by country, and by application/type for the competitive landscape analysis.
5.The report estimates 2019-2024 market development trends of LED Lightning industry.
6.Analysis of upstream raw materials, downstream demand, and current market dynamics is also carried out
7.The report makes some important proposals for a new project of LED Lightning Industry before evaluating its feasibility.
There are 4 key segments covered in this report: competitor segment, product type segment, end use/application segment and geography segment.
For competitor segment, the report includes global key players of LED Lightning as well as some small players. At least 20 companies are included:
* HPL
* Philips
* Eveready Industries
* Havells
* Charlston Lights
* GE Lighting
For complete companies list, please ask for sample pages.
The information for each competitor includes:
* Company Profile
* Main Business Information
* SWOT Analysis
* Sales, Revenue, Price and Gross Margin
* Market Share

For product type segment, this report listed main product type of LED Lightning market
* Product Type I
* Product Type II
* Product Type III

For end use/application segment, this report focuses on the status and outlook for key applications. End users sre also listed.
* Automotive Application
* Backlight Sources Application
* Display Screen Application
* Electronic Equipment Application
* General Lighting Application

For geography segment, regional supply, application-wise and type-wise demand, major players, price is presented from 2013 to 2023. This report covers following regions:
* North America
* South America
* Asia & Pacific
* Europe
* MEA (Middle East and Africa)
The key countries in each region are taken into consideration as well, such as United States, China, Japan, India, Korea, ASEAN, Germany, France, UK, Italy, Spain, CIS, and Brazil etc.

Reasons to Purchase this Report:
* Analyzing the outlook of the market with the recent trends and SWOT analysis
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* Market value (USD Million) and volume (Units Million) data for each segment and sub-segment
* Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
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In 2023, there were a total of 14 fatalities and 56 injuries reported due to lighting in the United States. In the previous year, there were 19 deaths and 53 injuries reported due to lightning nationwide.

The Geostationary Lightning Mapper (GLM) is the first optical lightning detector in geostationary orbit, and GLM sensors operate aboard the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellites (GOES R-series: GOES-16, -17, -18, and -19). The first to launch was GOES-16 on November 19, 2016 and it was placed in the GOES-East position. On March 1, 2018 GOES-17 launched and would eventually become operational in the GOES-West position. Since that time, the United States has maintained one satellite in each position. Currently, GOES-18 (west) and GOES-19 (east) are the operational satellites. With these instruments, the combined monthly thunder hour dataset has been created. A thunder hour is an hour during which thunder can be heard at a given location. Thunder hours represent a historical measure of lightning occurrence and a metric of thunderstorm frequency that is comparatively less sensitive to geographic variations in the detection capabilities of a lightning location system. The GLM thunder hour dataset will provide a long-term means of tracking trends in lightning occurrence over the Americas and surrounding oceans. The GLM Combined Monthly Thunder Hour dataset is calculated from lightning detections from 1 January 2019 onward, during which time GLMs are operating from GOES-West and GOES-East positions, providing continuous lightning detection for a broad region from the Aleutian Islands and New Zealand eastward to the western tip of Africa. The data are provided at 0.05° latitude/longitude resolution in netCDF-4 format.

These rasters depict the predicted human- and lightning-caused ignition probability for the state of California. Ignition is regulated by complex interactions among climate, fuel, topography, and humans. Considerable studies have advanced our knowledge on patterns and drivers of total areas burned and fire frequency, but much is less known about wildfire ignition. To better design effective fire prevention and management strategies, it is critical to understand contemporary ignition patterns and predict the probability of wildfire ignitions from different sources. UC Davis researchers modeled and analyzed human- and lightning-caused ignition probability across the whole state and sub-ecoregions of California, USA.

Findings reinforce the importance of varying humans vs biophysical controls in different fire regimes, highlighting the need for locally optimized land management to reduce ignition probability. Based on the most complete ignition database available, researchers developed maximum entropy models to predict the spatial distribution of long-term human- and lightning-caused ignition probability at 1 km and investigated how a set of biophysical and anthropogenic variables controlled their spatial variation in California and across its sub-ecoregions. Results showed that the integrated models with both biophysical and anthropogenic drivers predicted well the spatial patterns of both human- and lightning-caused ignitions in statewide and sub-ecoregions of California. Model diagnostics of the relative contribution and marginalized response curves showed that precipitation, slope, human settlement, and road network were the most important variables for shaping human-caused ignition probability, while snow water equivalent, lightning density, and fuel amount were the most important variables controlling the spatial patterns of lightning-caused ignition probability. The relative importance of biophysical and anthropogenic predictors differed across various sub-ecoregions of California.

Ground Station Lightning Protection Systems Market Outlook

According to our latest research, the global ground station lightning protection systems market size reached USD 1.38 billion in 2024, reflecting robust demand across critical infrastructure sectors. The market is experiencing a healthy expansion with a CAGR of 6.2% projected from 2025 to 2033. By the end of 2033, the market is forecasted to attain a value of USD 2.37 billion. This growth is primarily driven by the increasing deployment of satellite and telecommunication ground stations worldwide, coupled with the rising frequency of severe weather events necessitating advanced lightning protection solutions.

One of the principal growth factors for the ground station lightning protection systems market is the rapid proliferation of satellite-based communication and observation networks. As governments and private enterprises continue to invest in satellite constellations for broadband internet, Earth observation, and defense applications, the number of ground stations is rising steadily. These stations, often located in remote or exposed areas, are highly susceptible to lightning strikes, which can cause catastrophic equipment failures and data losses. As a result, the demand for sophisticated lightning protection systems—encompassing lightning rods, surge protection devices, and advanced grounding systems—has surged, becoming an integral component of ground station infrastructure projects globally. The adoption of new materials and smart technologies in lightning protection further enhances system effectiveness, driving market growth.

Another significant factor propelling the market is the increasing regulatory emphasis on safety and operational continuity in mission-critical sectors such as aerospace & defense, telecommunications, and meteorology. Regulatory bodies and industry standards now mandate stringent lightning protection measures for ground-based assets, especially those supporting national security and public safety. This has led to widespread retrofitting of existing ground stations with advanced lightning protection systems and the integration of state-of-the-art solutions in new installations. Additionally, the growing awareness of the economic impact of lightning-induced downtimes and equipment damage is motivating operators to invest in reliable protection systems, further boosting market expansion.

Technological advancements in surge protection and grounding systems are also contributing to the positive outlook of the ground station lightning protection systems market. Innovations such as real-time monitoring of grounding resistance, predictive analytics for surge events, and the use of corrosion-resistant materials have significantly improved the longevity and effectiveness of these systems. These advancements not only ensure the safety of sensitive electronic equipment but also reduce long-term maintenance costs, making them highly attractive to end-users. Furthermore, the integration of IoT-enabled sensors and cloud-based monitoring platforms allows for remote diagnostics and preventive maintenance, enhancing operational efficiency and minimizing the risk of unexpected failures.

From a regional perspective, the Asia Pacific region is emerging as a key growth driver due to rapid infrastructure development, expanding satellite communication networks, and heightened investments in weather monitoring stations. North America and Europe continue to dominate the market owing to their established aerospace, defense, and telecommunications sectors, along with stringent regulatory frameworks. Meanwhile, Latin America and the Middle East & Africa are witnessing gradual adoption of lightning protection systems, supported by increasing awareness and infrastructure modernization initiatives. The interplay of these regional dynamics is shaping the competitive landscape and growth trajectory of the global market.

In the aerospace sector, the importance of Lightning Strike Protection for Aircraft cannot be overstated. Aircraft are particularly vulnerable to lightning strikes, which can cause significant damage to both structural components and onboard electronic systems. As a result, the aviation industry has developed comprehensive lightning protection measures, including conductive paths and shielding, to ensure