Lightning Data Research Articles

Lightning strike characteristics of wind turbines in Japan

In recent years, as global warming advances, countermeasures for reducing gases of various greenhouse are needed. One of the countermeasures is a power generation using renewable energy that does not emit greenhouse gases. In particular, wind power generation is attracting attention due to its low cost compared to power generation using other renewable energies. However, as wind turbines become larger and the number of wind turbine increases, the probability of lightning strikes increases, it is important to establish more reliable lightning damage countermeasures. In response to this situation, the "Interpretation of Technical Standards for wind turbines" was revised in 2015 in Japan, installation of lightning detection systems to accurately detect lightning strikes and automatically shut down the wind turbine have been obligated in wind turbines in winter lightning regions in coastal regions in Japan. In addition, the performance of lightning detection systems has been improved by the results of recent research, and the systems with high detection accuracy are widely used in the market. In this study, we report the results of investigating the characteristics of lightning strikes using lightning data on approximately 450 wind turbines along the coast of Japan.

Development of Vertical Radar Reflectivity Profiles Based on Lightning Density Using the Geostationary Lightning Mapper Dataset in the Subtropical Region of Brazil

The study aims to develop vertical radar reflectivity profiles based on lightning density data from the Geostationary Lightning Mapper (GLM) on the GOES-16 satellite in the subtropical region of Brazil. The primary objective is to improve the assimilation of lightning data in numerical weather prediction models. The methodology involves the analysis of polarimetric radar data from Chapecó-SC and Jaraguari-MS, spanning from January 2019 to December 2023, and their correlation with lightning data from the GLM. Radar reflectivity profiles were created for different lightning density classes, categorized into six classes based on geometric progression. Results show a significant relationship between lightning activity and radar reflectivity, with distinct profiles for convective and stratiform events. These findings demonstrate the potential of using GLM data to enhance short-term weather forecasting, particularly for severe weather events. The study concludes that the integration of GLM data into weather models can lead to more accurate predictions of intense precipitation events, contributing to better preparedness and response strategies.

Design and application of omnidirectional mirror for catadioptric optical system dedicated to high-speed video registration of lightning

Omnidirectional optical mirrors are widely used in many scientific, industrial and military applications but there is still a lot to do to improve their projection characteristics. The paper presents design method for a novel class of omnidirectional mirrors characterized by their settable reflection angle and 3D/2D image projection. Such approach can effectively improve the mirrored image distribution on matrix of optical sensor. A complex mirror curvature was manufactured with application of computerized numerical control milling machines and Physical Vapor Deposition technique. Three prototypes with 15°, 30° and 45° vertical top view angles were tested. Mirrors were applied to get a set of wide range cloud-to-ground lightning video registrations. Analysis of the high-speed video confirmed design assumptions, and using lightning location system data, enabled dimensioning and measurement of the lightning channel geometry in 3D. Proposed method can be easily implemented in other applications involving omnidirectional observation and photogrammetry.

Assessing the Impact of Lightning Data Assimilation in the WRF Model

Assessing the Impact of Lightning Data Assimilation in the WRF Model

A Climatology of Convective Precipitation over Europe

Abstract The annual, seasonal, and diurnal spatiotemporal heavy convective precipitation patterns over a pan-European domain are analyzed in this study using a combination of datasets, including the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG) precipitation rate product, E-OBS ground-based precipitation gauge data, European climatological gauge-adjusted radar precipitation dataset (EURADCLIM), Operational Programme for the Exchange of Weather Radar Information (OPERA) ground-based radar-derived precipitation rates, and fifth major global reanalysis produced by ECMWF (ERA5) total and convective precipitation products. Arrival Time Difference Network (ATDnet) lightning data are used in conjunction with IMERG and EURADCLIM precipitation rates, with an imposed threshold of 10 mm h−1 to classify precipitation as convective. Annually, the largest convective precipitation accumulations are over the European seas and coastlines. In summer, convective precipitation is more common over the European continent, though relatively large accumulations exist over the northern coastal waters and the southern seas, with a seasonal localized maximum over the northern Adriatic Sea. Activity shifts southward to the Mediterranean and its coastlines in autumn and winter, with maxima over the Ionian Sea, the eastern Adriatic Sea, and the adjacent coastline. Over the continent, 1%–10% of the total precipitation accumulated is classified as convective, increasing to 10%–40% over the surrounding seas. In contrast, 30%–50% of ERA5 precipitation accumulations over land is produced by the convective parameterization scheme and 40%–60% over the seas; however, only 1% of ERA5 convective precipitation accumulations are from rain rates exceeding 10 mm h−1. Regional analyses indicate that convective precipitation rates over the inland mountains follow diurnal heating, though little to no diurnal pattern exists in convective precipitation rates over the seas and coastal mountains.

Impact of decreasing land–sea horizontal pressure gradient on the lightning activity over western India

AbstractWith future global warming projections, how lightning activity changes in the warmer world is still a debated and challenging question. During the Indian pre‐monsoon season (March–May), land surface heating and moisture availability due to prevailing winds from the neighbouring oceans provide favourable conditions for thunderstorm formation. Based on 24 years of lightning data from 2000 to 2023 detected by Lightning Imaging Sensor/Optical Transient Detector (LIS/OTD) and Indian Lightning Location Network (ILLN), the trend of lightning flashes over western India (15°–22°N, 72.5°–81°E) has been investigated. Our results demonstrate a steady decline in lightning activity during the pre‐monsoon season over western India, which contradicts the previous studies suggesting an increasing lightning trend over the Indian Subcontinent and other parts of the world. Our analysis has shown a falling trend of lightning activity at a rate of −0.066 flashes·km−2 year−1 from 2000 to 2013 (LIS/OTD) and −0.14 M flashes·year−1 from 2014 to 2023 (ILLN). Our observation and previous research strongly suggested that the pressure difference between the land and the neighbouring oceans during pre‐monsoon and monsoon has been weakening for a long time over the Indian region, and we have found a consistent reduction in wind speed over the study region. Here, we propose that the enhanced Indian Ocean warming potentially weakens the land–sea thermal contrast and, thereby, reduces the horizontal pressure gradient. Further, the decreasing trend in the land–sea horizontal pressure gradient resulted in a declining rate of wind speed over western India, affecting moisture transport over land. Thus, the study emphasizes the impact of the decreased land–sea horizontal pressure gradient on declining lighting activity in western India.

Assessing wind turbine lightning risk using data-driven methodology

This paper presents a methodology to conduct a risk assessment of lightning damage for wind farms using a data-driven methodology. Methods exist to address risks related to fire but this approach goes further to address lightning damage and related impacts to operations and maintenance comprehensively - monetizing the costs of these impacts. The process begins with lightning data analysis and strike rate calculation. Then, the lightning damage data is analyzed to gain insight into the repair cost and impact. Lastly, the process-based cost model takes lightning strike rate and impact data, resulting in risk provision. The paper presents two case studies, one for onshore wind farms and one for offshore wind farms. The relative importance of operations and maintenance costs versus lost revenues due to downtime (liquidated damages) differ between the two cases due to underlying technical drivers (turbine sizes, wind farm performance, lightning prevalence) as well as market drivers (labor costs, electricity prices). Thus, the study demonstrates both the viability of the method in providing monetary estimates of lightning damage costs over the lifteime of a wind farm as well as the importance of site-specific analysis and models to ensure accurate estimation of those costs.

Evaluation of Lightning Flash Rate Parameterizations in a Cloud‐Resolved WRF‐Chem Simulation of the 29–30 May 2012 Oklahoma Severe Supercell System Observed During DC3

AbstractEighteen lightning flash rate parameterization schemes (FRPSs) were investigated in a Weather Research and Forecasting model coupled with chemistry cloud‐resolved simulation of the 29–30 May 2012 supercell storm system observed during the Deep Convective Clouds and Chemistry (DC3) field campaign. Most of the observed storm's meteorological conditions were well represented when the model simulation included both convective damping and lightning data assimilation techniques. Newly‐developed FRPSs based on DC3 radar observations and Lightning Mapping Array data are implemented in the model, along with previously developed schemes from the literature. The schemes are based on relationships between lightning and various kinematic, structural, and microphysical thunderstorm characteristics (e.g., cloud top height, hydrometeors, reflectivity, and vertical velocity) available in the model. The results suggest the model‐simulated graupel and snow/ice hydrometeors require scaling factors to more closely represent proxy observations. The model‐simulated lightning flash trends and total flashes generated by each scheme over the simulation period are compared with observations from the central Oklahoma Lightning Mapping Array. For this supercell system, 13 of the 18 schemes overpredicted flashes by >100% with the group of FRPSs based on storm kinematics and structure (particularly updraft volume) performing slightly better than the hydrometeor‐based schemes. During the storm's first 4 hr, the upward cloud ice flux FRPS, which is based on the combination of vertical velocity and hydrometeors, well represents the observed total flashes and flash rate trend; while, the updraft volume scheme well represents the observed flash rate peak and subsequent sharp decline in flash rate.

Possible Influence of Solar Activity on Lightning Occurrence: A Preliminary Study Over Nepal

One of the fundamental mysteries of lightning is its initiation mechanism. Many aspects of lightning phenomenon are well known; however, the exact processes that initiate lightning discharge are not fully understood. This study delves into a relatively underexplored domain: the relationship between solar activity specifically solar sunspots and F10.7 indices, as well as solar wind speed, on the occurrence of lightning events. The study utilizes a rich dataset spanning from 1998 to 2008, capturing an extensive period of solar activity during Solar Cycle 23. Multiple correlation analyses were conducted, comparing solar activity parameters with lightning occurrence. Lightning data was sourced from the Lightning Imaging Sensor (LIS) whereas Sunspot data was obtained from the Solar Influences Data Analysis Center (SIDC) and F10.7 as well as Solar wind data was obtained from the OMNI dataset. From this preliminary study, we observed that the correlation between solar parameters and the lightning occurrence over Nepal are found to vary at different time period from insignificant correlation to moderate correlation. Hence, further exploration is needed to shed more light to interpret the relationship between solar activity and the lightning occurrence in Nepal.

Relationship between radar reflectivity thresholds and very low frequency/low frequency total lightning for thunderstorm identification

AbstractTo improve our knowledge of the spatio‐temporal correspondence between radar reflectivity and VLF/LF total lightning data, this paper proposes indexes to quantify the horizontal distribution and temporal evolution characteristics between radar composite reflectivity images and total lightning density map, lightning clusters and radar cells with different radar reflectivity thresholds (30, 35, 40, 45 and 50 dBZ), respectively. It is found that the number of radar grid cells with radar reflectivity over 30 dBZ is ten times the number of lightning grid cells. At the identification stage, the lightning activity regions in a radar cell account for less than 30% using thresholds of 30, 35 and 40 dBZ, respectively, and the radar cell has more than one lightning cluster, which means that the mesoscale convective systems typically have more than one draft, and drafts are only small part of the convection. The majority of the centroid deviations is less than 10 km, indicating that there are some shifts between electrically active regions and convective regions. Results suggest that VLF/LF total lightning data are consistent with radar data and total lightning data can be used individually on a smaller spatio‐temporal scale than radar data.

Very high frequency radiation emitted by negative narrow bipolar events occurred over malacca strait

In this paper, Very-High Frequency (VHF) radiation pulses associated with 11 negative Narrow Bipolar Events (NBEs) produced by a tropical storm over Malacca Strait are examined. The lightning data were recorded from a measurement station (ST) which consisted of a fast antenna (FA) and three VHF sensors (two 5 m perpendicular baselines interferometer). The average rise time (RT), average zero-crossing time (ZCT), average pulse duration (PD), and range of peak currents of the negative NBEs were 1.4 ± 0.4 μs, 2.7 ± 1.0 μs, 12.0 ± 6.9 μs, and −10 to −64 kA, respectively. The key finding is that all VHF radiation pulses have been found to precede the negative NBEs with an average lead time of 0.7 ± 0.3 μs. An interferometer map for one negative NBE (labelled as NBE10) detected at 35.7 km from ST has shown a characteristic of mixed propagation direction of fast streamers. The first VHF radiation source was detected at 12.4 ± 0.4 km above sea level. The total length and estimated velocity of the main propagation of the VHF radiation sources were 2.2 ± 0.7 km and between 1.4 × 108 and 2.8 × 108 ms−1, respectively. Moreover, based on the Himawari satellite image, the maximum extent of the cloud top height was estimated to be around 20.9 km over sea level (over Malacca Strait). All the VHF radiation sources associated with NBE10 were suggested to be detected above the main negative charge region (6 km altitude that corresponds to −10 °C). Thus, it could be suggested that NBE10 was initiated most likely in the environment of the ice crystals alone, based on the first altitude of the VHF radiation source and maximum extent of cloud top height.

Optimizing lightning location accuracy: A study of propagation velocity and time of arrival in long-range lightning location algorithms

The propagation velocity (v) and time of arrival (Ta) are the primary factors affecting long-range lightning location. In this paper, we have enhanced the Very Low Frequency Long-range Lightning Location Network (VLF-LLN) in China in terms of both pulse pairing methods and location algorithms. Then, the algorithm utilized in the VLF-LLN, and four other long-range lightning location algorithms were compared using lightning strike accidents, simulated lightning strike, and other lightning data as the reference values. Building on this foundation, the discussion centers on the effect of v and Ta on location accuracy, with the results showing that an appropriate Ta yields a more significant improvement in location accuracy compared to v. VLF-LLN uses the peak time of the ground wave as Ta avoids the significant lag caused by sky wave, which is present in other algorithms, and therefore has the best location accuracy with a median location accuracy of 1.81 km.

Space-based optical imaging of blue corona discharges on a cumulonimbus cloud top

The ILAN-ES (Imaging of Lightning And Nocturnal Emissions from Space) experiment was conducted in April 2022 as part of the Axiom company AX-1 private mission to the International Space Station, in the framework of Rakia, an Israeli set of experiments selected for flight by the Ramon Foundation and the Israeli Space Agency. The mission objective was to record transient luminous events from the Cupola window in the ISS, based on preliminary thunderstorm forecasts uploaded to the crew 24–36 h in advance. A Nikon D6 camera with a 50 mm lens was used, in a video mode of 60 fps. During the 12-day mission, 82 different targets were identified for the ISS, of which 20 were imaged by the astronauts, yielding a total harvest >80 TLEs: sprites, Elves and BLUEs (blue corona discharges). We report here on opportune nadir observation of a thunderstorm that produced multiple blue events near the Myanmar-Thailand border on April 21st, 2022, at 21:30 UT. The storm produced many visible blue discharges of varying sizes and durations, in diameters ranging from hundreds of meters to a few km2. The emissions were mostly in blue, however the brightest events had also a conspicuous broadband red component. We used meteorological and ENTLN lightning data to establish the relationship between lightning type and the observable properties of the blue corona discharges.

Employing optical lightning data to identify lightning flashes associated to terrestrial gamma-ray flashes

Terrestrial gamma-ray flashes (TGFs) are bursts of energetic X- and gamma-rays emitted from thunderstorms. The Atmosphere-Space Interactions Monitor (ASIM) mounted onto the International Space Station (ISS) is dedicated to measure TGFs and optical signatures of lightning; ISS LIS (Lightning Imaging Sensor) detects lightning flashes allowing for simultaneous measurements with ASIM. Whilst ASIM measures ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim $$\\end{document}300-400 TGFs per year, ISS LIS detects ∼106\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 10^6$$\\end{document} annual lightning flashes giving a disproportion of four orders of magnitude. Based on the temporal evolution of lightning flashes and the spatial pattern of the constituing events, we present an algorithm to reduce the number of space-detected flashes potentially associated with TGFs by ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim $$\\end{document} 60% and of associated LIS groups by ∼\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim $$\\end{document} 95%. We use ASIM measurements to confirm that the resulting flashes are indeed those associated with TGFs detected at approx. 400 km altitude and thus benchmark our algorithm preserving 70–80% of TGFs from concurrent ASIM-LIS measurements. We compare how the radiance, footprint size and the global distribution of lightning flashes of the reduced set relates to the average of all measured lightning flashes and do not observe any significant difference. Finally, we present a parameter study of our algorithm and discuss which parameters can be tweaked to maximize the reduction efficiency whilst keeping flashes associated to TGFs. In the future, this algorithm will hence be capable of facilitating the search for TGFs in a reduced set of lightning flashes measured from space.

Assessing Flash Characteristics in Lightning-Initiated Wildfire Events between 1995 and 2020 within the Contiguous United States

Abstract Twenty-six years of lightning data were paired with over 68 000 lightning-initiated wildfire (LIW) reports to understand lightning flash characteristics responsible for ignition in between 1995 and 2020. Results indicate that 92% of LIW were started by negative cloud-to-ground (CG) lightning flashes and 57% were single stroke flashes. Moreover, 62% of LIW reports did not have a positive CG within 10 km of the start location, contrary to the science literature’s suggestion that positive CG flashes are a dominant fire-starting mechanism. Nearly ⅓ of wildfire events were holdovers, meaning 1 or more days elapsed between lightning occurrence and fire report. However, fires that were reported less than a day after lightning occurrence statistically burned more acreage. Peak current was not found to be a statistically significant delineator between fire starters and non–fire starters for negative CGs but was for positive CGs. Results highlighted the need for reassessing the role of positive CG lightning and subsequently long-continuing current in wildfire ignition started by lightning. One potential outcome of this study’s results is the development of real-time tools to identify ignition potential during lightning events to aid in fire mitigation efforts.

Improving the lightning forecast with the WRF model and lightning data assimilation: Results of a two-seasons numerical experiment over Italy

We show, for the first time over Italy and over part of the central Mediterranean Basin, the impact of lightning data assimilation (LDA) on the strokes forecast for a long period. We use the Weather Research and Forecasting (WRF) model coupled with the Dynamic Lightning Scheme (DLS) at convection allowing horizontal resolution (3 km). We carried out a two-seasons experiment (summer 2020 and fall 2021) providing the forecast of lightning and precipitation for the next 6 h (nowcasting), considering two sub-periods (0-3 h and 3-6 h) for verification. The LDA is done through a nudging scheme that increases the water vapor mass in the mixed-phase region based on observed flash density rates and simulated graupel mixing ratio. No changes are made to the model run if spurious convection is predicted or no flashes are observed. LDA can trigger convection missed by the control forecast, without LDA, and/or can redistribute the strokes predicted to be more consistent with observations. LDA has a positive impact on strokes forecast, improving correct forecasts and reducing false alarms. This improvement is however confined to the first three-hours of forecast with negligible to negative impact for longer time ranges, in line with other studies. The improvement pattern is different in summer and fall, depending on the convection development.The analysis of the Fraction Skill Score shows the usefulness of the forecast for practical purposes, considering the current areas used by the Civil Protection Department to issue meteorological alerts for intense convective events over Italy. Finally, it is shown that the forecast at the short-range (0−3h) using LDA can improve the strokes forecast issued on the previous day, not using LDA, and the methodology of this paper can be applied to issue warnings and alerts as the storm is approaching.A brief examination of rainfall forecast shows positive impact of LDA at the short-range (0-3 h), with neutral impact for longer time ranges. The different impact of LDA on the strokes and precipitation forecasts is also highlighted.

Lightning-Induced Wildfires: An Overview

Wildfire causes environmental, economic, and human problems or losses. This study reviewed wildfires induced by lightning strikes. This review focuses on the investigations of lightning mechanisms in the laboratory. Also, the paper aims to discuss some of the modeling studies on lightning-induced wildfires at different geographical locations using satellite-recorded lightning data and different statistical analyses. This review established that irrespective of the different models used to predict lightning wildfires, there is still a lack of understanding of the lightning-strike ignition mechanism; few experiments have been modeled to establish the dynamics of lightning-strike ignition. Therefore, further research needs to be carried out in this area to understand lightning ignition. It was ascertained from the various statistical modeling that lightning-induced wildfires are exacerbated by the abundant availability of fuel with a lower moisture content and high lightning efficiency. Moreover, because of changes in the climate and weather conditions, i.e., harsh weather and climate conditions due to anthropogenic activities, lightning-induced ignition wildfires have increased over the years, and they are expected to increase in the future if the climate and weather conditions continue to aggravate. Although various modeling studies have identified that lightning-induced wildfires have increased recently, no preventive measures have been conclusively proposed to reduce lightning-caused wildfires. Hence, this aspect of research has to be given critical attention. This review presents information that gives a profound understanding of lightning-induced wildfires, especially factors that influence lightning wildfires, and the state-of-the-art research that has been completed to understand lightning-induced wildfires.

Hydrological Verification of Two Rainfall Short-Term Forecasting Methods with Floods Anticipation Perspective

Abstract Flood forecasting remains a significant challenge, particularly when dealing with basins characterized by small drainage areas (i.e., 103 km2 or lower with response time in the range 0.5–10 h) especially because of the rainfall prediction uncertainties. This study aims to investigate the performances of streamflow predictions using two short-term rainfall forecast methods. These methods utilize a combination of a nowcasting extrapolation algorithm and numerical weather predictions by employing a three-dimensional variational assimilation system, and nudging assimilation techniques, meteorological radar, and lightning data that are frequently updated, allowing new forecasts with high temporal frequency (i.e., 1–3 h). A distributed hydrological model is used to convert rainfall forecasts into streamflow prediction. The potential of assimilating radar and lightning data, or radar data alone, is also discussed. A hindcast experiment on two rainy periods in the northwest region of Italy was designed. The selected skill scores were analyzed to assess their degradation with increasing lead time, and the results were further aggregated based on basin dimensions to investigate the catchment integration effect. The findings indicate that both rainfall forecast methods yield good performance, with neither definitively outperforming the other. Furthermore, the results demonstrate that, on average, assimilating both radar and lightning data enhances the performance.

Comparative Study on Lightning Data between the Fengyun-4A Satellite and the National Lightning Monitoring Network in Guizhou, China

Clustered data from the Lightning Mapping Imager (LMI) onboard the Fengyun-4A satellite were compared with lightning strike data from the National Lightning Monitoring Network (NLMN) for the period of 22 June–21 September 2020 over Guizhou Province, China. Spatial and temporal distributions of lightning counts for LMI and NLMN were mostly consistent, although the NMLN detected approximately ten times more lightning per hour than LMI. Influenced by background solar radiation, LMI data exhibited strong diurnal variations in lightning radiance, with significantly higher values during daytime. In contrast, NLMN lightning peak currents showed no similar variations. While no clear relationship was observed between the spatial distributions of LMI lightning density and radiance, a negative correlation was found between NLMN lightning density and peak current. Additionally, the matching rate (MR) for LMI and NLMN data, dependent on spatiotemporal matching criteria, was analyzed. The MR increased sharply with the extension of the temporal interval up to 2 s, then stabilized for longer intervals. In contrast, the MR was strongly influenced by the spatial matching grid cell size. For instance, within a 2-s temporal interval, an MR of 81.1% was estimated for NLMN data within a 27.5-km radius, compared to an MR of 79.8% for LMIG data within a 42.5-km radius. Furthermore, the MR was consistently higher for NLMN compared to LMI. Finally, using Bayes' theorem, we conducted a preliminary assessment of LMI's conditional detection efficiency, employing NLMN lightning data as prior information. The LMI detection efficiency was found to be significantly higher during nighttime than daytime, with values of 50.06% and 100% for daytime and nighttime detections, respectively, within a 2-s temporal interval and a 37.5-km grid cell.

ECMWF Lightning Forecast in Mainland Portugal during Four Fire Seasons

The study evaluated the ECMWF model ability in forecasting lightning in Portugal during four fire seasons (019–2022). The evaluation was made based on lightning data from the national lightning detector network, which was aggregated into resolutions of 0.5° and 1° over 3 h periods and analyzed from statistical indices using two contingency tables. The results showed that the model overestimates the lightning occurrence, with a BIAS greater than 1, with a success rate of 57.7% (49%) for a horizontal resolution of 1° (0.5°). The objective analysis was complemented by the spatial lightning distribution analysis, which indicated a time lag between the two data, i.e., the model started predicting lightning before its occurrence and finished the prediction earlier. Furthermore, such analysis revealed the lightning distribution being consistent with some weather patterns. The findings of this study provide insights into the applicability of the ECMWF lightning forecast data in the context of forecasting natural forest fires in Portugal.