Lightning Ignitions Research Articles

Analysis of the Role of Lightning Activity in Triggering Forest Fires in Nepal

Forest fires have emerged as a significant and pressing issue in Nepal, jeopardizing its natural ecosystems, biodiversity, and communities. While human activities have been traditionally linked to these fires, this study explores the potential impact of lightning strikes, a natural factor that could contribute significantly to the problem. Using data from Vaisala's Global Lightning Dataset (GLD 360) and the Moderate Resolution Imaging Spectroradiometer (MODIS) dataset, we investigate the relationship between lightning strikes and forest fires over the five years’ period from 2015 to 2019. Advanced tools like ARC GIS and Python are employed for analysis. Preliminary findings indicate a noteworthy correlation, particularly during the pre-monsoon season. This investigation shows an interesting fact that positive lightning strokes are more likely to initiate forest fire as compared to their negative counter parts. This research offers a fresh perspective on lightning-induced forest fires in Nepal, paving the way for targeted fire management strategies and further investigation into lightning ignition mechanisms.

Blending Indigenous and western science: Quantifying cultural burning impacts in Karuk Aboriginal Territory.

The combined effects of Indigenous fire stewardship and lightning ignitions shaped historical fire regimes, landscape patterns, and available resources in many ecosystems globally. The resulting fire regimes created complex fire-vegetation dynamics that were further influenced by biophysical setting, disturbance history, and climate. While there is increasing recognition of Indigenous fire stewardship among western scientists and managers, the extent and purpose of cultural burning is generally absent from the landscape-fire modeling literature and our understanding of ecosystem processes and development. In collaboration with the Karuk Tribe Department of Natural Resources, we developed a transdisciplinary Monte Carlo simulation model of cultural ignition location, frequency, and timing to simulate spatially explicit cultural ignitions across a 264,399-ha landscape within Karuk Aboriginal Territory in northern California. Estimates of cultural ignition parameters were developed with Tribal members and knowledge holders using existing interviews, historical maps, ethnographies, recent ecological studies, contemporary maps, and generational knowledge. Spatial and temporal attributes of cultural burning were explicitly tied to the ecology of specific cultural resources, fuel receptivity, seasonal movement patterns, and spiritual practices. Prior to colonization, cultural burning practices were extensive across the study landscape with an estimated 6972 annual ignitions, averaging approximately 6.5 ignitions per Indigenous fire steward per year. The ignition characteristics we document align closely with data on historical fire regimes and vegetation but differ substantially from the location and timing of contemporary ignitions. This work demonstrates the importance of cultural burning for developing and maintaining the ecosystems present at the time of colonization and underscores the need to work collaboratively with Indigenous communities to restore ecocultural processes in these systems.

Lightning‐Ignited Wildfires in the Western United States: Ignition Precipitation and Associated Environmental Conditions

AbstractCloud‐to‐ground lightning with minimal rainfall (“dry” lightning) is a major wildfire ignition source in the western United States (WUS). Although dry lightning is commonly defined as occurring with <2.5 mm of daily‐accumulated precipitation, a rigorous quantification of precipitation amounts concurrent with lightning‐ignited wildfires (LIWs) is lacking. We combine wildfire, lightning and precipitation data sets to quantify these ignition precipitation amounts across ecoprovinces of the WUS. The median precipitation for all LIWs is 2.8 mm but varies with vegetation and fire characteristics. “Holdover” fires not detected until 2–5 days following ignition occur with significantly higher precipitation (5.1 mm) compared to fires detected promptly after ignition (2.5 mm), and with cooler and wetter environmental conditions. Further, there is substantial variation in precipitation associated with promptly‐detected (1.7–4.6 mm) and holdover (3.0–7.7 mm) fires across ecoprovinces. Consequently, the widely‐used 2.5 mm threshold does not fully capture lightning ignition risk and incorporating ecoprovince‐specific precipitation amounts would better inform WUS wildfire prediction and management.

Variation of lightning-ignited wildfire patterns under climate change

Lightning is the main precursor of natural wildfires and Long-Continuing-Current (LCC) lightning flashes are proposed to be the main igniters of lightning-ignited wildfires (LIW). Previous studies predict a change of the global occurrence rate and spatial pattern of total lightning. Nevertheless, the sensitivity of lightning-ignited wildfire occurrence to climate change is uncertain. Here, we investigate space-based measurements of LCC lightning associated with lightning ignitions and present LCC lightning projections under the Representative Concentration Pathway RCP6.0 for the 2090s by applying a recent LCC lightning parameterization based on the updraft strength in thunderstorms. We find a 41% global increase of the LCC lightning flash rate. Increases are largest in South America, the western coast of North America, Central America, Australia, Southern and Eastern Asia, and Europe, while only regional variations are found in northern polar forests, where fire risk can affect permafrost soil carbon release. These results show that lightning schemes including LCC lightning are needed to project the occurrence of lightning-ignited wildfires under climate change.

Spatio-Temporal Assessment of Thunderstorms’ Effects on Wildfire in Australia in 2017–2020 Using Data from the ISS LIS and MODIS Space-Based Observations

The impact of thunderstorms on the wildfire situation in Australia in 2017–2020 was investigated using data from the ISS LIS and MODIS space-based observations. To determine lightning-caused wildfires, a Geographic Information System (GIS) method was carried out, which consisted of a combined investigation of the spatial and temporal distributions of strikes and ignition hotspots. The seasonal variability of thunderstorms and wildfire activity was analyzed. It was established that the maximum seasonal distribution of thunderstorm activity does not coincide with wildfire activity. The interannual changes in strikes were recorded, but this was not revealed for the major vegetation types. Of 120,829 flashes, recorded by the ISS LIS sensor, only 23 flashes could be characterized as lightning-caused wildfire events, i.e., the frequency of lightning ignition was equal to 0.00023 fires/stroke. The lightning ignitions usually took place along the boundary of a thunderstorm, in semiarid areas covered by open scrublands. During the dry Australian period (April–September), very few lightning events were detected by the ISS LIS sensor, while fire activity was quite high. Additionally, it was concluded that the impact of thunderstorms on the fire situation is too small to explain the numerous wildfires during the wet period.

Disentangling the last 1,000 years of human–environment interactions along the eastern side of the southern Andes (34–52°S lat.)

Researchers have long debated the degree to which Native American land use altered landscapes in the Americas prior to European colonization. Human-environment interactions in southern South America are inferred from new pollen and charcoal data from Laguna El Sosneado and their comparison with high-resolution paleoenvironmental records and archaeological/ethnohistorical information at other sites along the eastern Andes of southern Argentina and Chile (34-52°S). The records indicate that humans, by altering ignition frequency and the availability of fuels, variously muted or amplified the effects of climate on fire regimes. For example, fire activity at the northern and southern sites was low at times when the climate and vegetation were suitable for burning but lacked an ignition source. Conversely, abundant fires set by humans and infrequent lightning ignitions occurred during periods when warm, dry climate conditions coincided with ample vegetation (i.e., fuel) at midlatitude sites. Prior to European arrival, changes in Native American demography and land use influenced vegetation and fire regimes locally, but human influences were not widely evident until the 16th century, with the introduction of nonnative species (e.g., horses), and then in the late 19th century, as Euro-Americans targeted specific resources to support local and national economies. The complex interactions between past climate variability, human activities, and ecosystem dynamics at the local scale are overlooked by approaches that infer levels of land use simply from population size or that rely on regionally composited data to detect drivers of past environmental change.

Human‐mediated trophic mismatch between fire, plants and herbivores

Trophic mismatches are commonly reported across a wide array of taxa and can have important implications for species participating in the interaction. However, to date, examples of trophic mismatch have centrally focused on those induced by shifts in climate. Here we report on the potential for humans to induce trophic mismatch by shifting the phenology of fire. Globally, anthropogenic fire ignitions are phenologically mismatched to that of historic lightning ignitions but the effects of this phenological mismatch on trophic interactions are poorly understood. Using fire records from 1980 to 2016 from the southeastern USA, a hotspot of anthropogenic fire, we demonstrate that there is a temporal mismatch between anthropogenic and lightning lit fires in this region. The peak of anthropogenic ignitions (i.e. 45% during March and April) occurred 3 months earlier than the peak in lightning‐ignited fires (i.e. 44% occurred during June and July), a pattern consistent with reports from several other regions and continents. We demonstrate with a field experiment conducted at a nutrient‐poor site in the southeastern U.S., that anthropogenic fire phenology shifts nutrient pulses in resprouting plants so that they mismatch herbivore reproductive demands. Consequently, plant nutrient quality in four commonly consumed forages was below the threshold to meet lactation requirements. Neonates subsequently were more likely to starve when born far from areas burned during the peak month of lightning fire phenology. Our data indicate that human activities may be an additional causative agent of trophic mismatch.

Ignition frequency and climate controlled Alaskan tundra fires during the Common Era

Recent fire events in Alaskan tundra ecosystems have been identified as harbingers of climate change and have caused reassessment of more traditional thinking about fire activity in this high-latitude biome. Although some work has demonstrated the novelty of these fires and linked weather, climate, and environmental variables to their occurrence, our understanding of their long-term (multi-decadal and centennial-scale) and spatially broad-scale climatic controls remains preliminary. We address this gap by comparing paleofire records with relevant climate, vegetation, and environmental datasets to identify the most important controls of tundra fire and assess their relative importance (using machine learning techniques). Additionally, we assess likely causal relationships of these environmental variables and fire activity using structural equation models (SEMs). We find that atmospheric CO2 is the primary control of tundra fire, followed by summer temperature, and precipitation. We infer that atmospheric CO2 directly increases lightning ignition frequencies while also promoting warm, dry climatic conditions conducive to fire. This inference is supported by analyses of observational lightning and fire data and is further supported by recent work identifying lightning as the dominant control of tundra fire occurrence. These findings are alarming in light of rising atmospheric CO2 and climate projections.

Characteristics of lightning-caused wildfires in central Brazil in relation to cloud-ground and dry lightning

Lightning ignition is the major cause of natural wildfires in several regions worldwide. Determining if wildfires in remote uncontrolled areas result from natural lightning as opposed to anthropic action is a relevant and yet-unsolved challenge for large regions of the planet, with scientific and management implications ranging from environmental conservation to mitigation of climate-related emissions of gases and aerosols. Brazil is the country with one of the highest occurrences of lightning (50 to 100 million/year) and which is also subject to numerous and vast wildfires (up to ∼600 × 103 km2/year) affecting all its biomes. To quantify natural fires we combined cloud-to-ground (CG) lightning and CG dry-lightning (CGDL) detected by a ground network, with fire pixels mapped by satellite remote sensing (AQUA, S-NPP and NOAA-20) over ∼1,8 × 106 km2 in Central Brazil, between 2015 to 2019. Lightning ignition candidates were selected based on the distance between fires and lightning in time and space. The selected cases were investigated according to annual and monthly distributions in space and time, to local weather at the time of occurrence and, electrical characteristics related to ignition. Space-time distributions of CG lightning, CGDL and of active fires were also analyzed. Results showed that the CGDLs pattern is not different from that of the overall CG lightning, with both presenting similar kernel density, polarity and peak current. The lightning candidates indicated predominance of negative polarity and peak current frequency below 20 kA. In this range, average values for weather conditions for CG lightning matched to fires (CGDL matched to fires) had: precipitation 6 mm (< 1 mm), relative humidity 57 % (48 %), and temperature ∼30°C and wind speed of ∼ 2 m.s−1 for both. The results showed that satellite detection of active fires is a useful tool to identify lightning-induced wildfires.

Mobility data to aid assessment of human responses to extreme environmental conditions

Mobility data to aid assessment of human responses to extreme environmental conditions

Experimental study on artificial lightning ignition phenomenon and model of the fuel bed

As global warming continues, wildland lightning fires have exhibited an increasing trend. The phenomenon of lightning ignition and a model are urgent research fields. In this study, an impulse current generator was used to study artificial lightning ignition. Ignition phenomena for several fuel beds were compared. Flames in the grass bed existed in the form of particles, but these particle flames had a short duration and were extinguished by the shock waves from the artificial lightning. It is noteworthy that a 10/350 μs impulse current could ignite a cotton fibre bed and produce sustained and stable combustion. An artificial lightning ignition model for the fuel bed was established. The model was verified by artificial lightning ignition experiments. The results show that the model could be applied to grass and needle fuel beds and waveforms of 10/350 μs impulse current and short continuing current. The findings of this study provide valuable information for understanding the mechanism of lightning ignition.

Using machine learning to predict fire‐ignition occurrences from lightning forecasts

AbstractLightning‐caused wildfires are a significant contributor to burned areas, with lightning ignitions remaining one of the most unpredictable aspects of the fire environment. There is a clear connection between fuel moisture and the probability of ignition; however, the mechanisms are poorly understood and predictive methods are underdeveloped. Establishing a lightning–ignition relationship would be useful in developing a model that would complement early warning systems designed for fire control and prevention. A machine learning (ML) approach was used to define a predictive model for wildfire ignition based on lightning forecasts and environmental conditions. Three different binary classifiers were adopted: a decision tree, an AdaBoost and a Random Forest, showing promising results, with both ensemble methods (Random Forest and AdaBoost) exhibiting an out‐of‐sample accuracy of 78%. Data provided by a Western Australia wildfire database allowed a comprehensive verification on over 145 lightning‐ignited wildfires in regions of Australia during 2016. This highlighted that in a minimum of 71% of the cases the ML models correctly predicted the occurrence of an ignition when a fire was actually initiated. The super‐learner developed is planned to be used in an operational context to the enhance information connected to fire management.

Experimental analysis of artificial lightning breakdown and ignition characteristics in grassland

Lightning fire is an important influencing factor of grassland ecology. It is one of the important ignition sources of grassland fire. The previous researches on lightning fires were mainly focused on forests, but researches on grassland were insufficient. In this paper, the impulse voltage generator was used to evaluate the breakdown characteristics of grass bed. The relationship of breakdown voltage to moisture content and bulk density was obtained. Based on the impulse current generator, an artificial lightning ignition prediction model of impulse current was derived. Results show that the breakdown voltage of grass bed decreases rapidly with the increase of moisture content. With the increase of peak current, the total lightning energy increases, while the heating efficiency decreases.

Anthropogenic and lightning‐started fires are becoming larger and more frequent over a longer season length in the U.S.A.

AbstractAimOver the past several decades, wildfires have become larger, more frequent, and/or more severe in many areas. Simultaneously, anthropogenic ignitions are steadily growing. We have little understanding of how increasing anthropogenic ignitions are changing modern fire regimes.LocationConterminous United States.Time period1984–2016.Major taxa studiedVegetation.MethodsWe aggregated fire radiative power (FRP)‐based fire intensity, event size, burned area, frequency, season length, and ignition type data from &gt; 1.8 million government records and remote sensing data at a 50‐km resolution. We evaluated the relationship between fire physical characteristics and ignition type to determine if and how modern U.S.A. fire regimes are changing sensu stricto given increased anthropogenic ignitions, and how those patterns vary over space and time.ResultsAt a national scale, wildfires occur over longer fire seasons (17% increase) and have become larger (78%) and more frequent (12%), but not necessarily more intense. Further, human ignitions have increased 9% proportionally. The proportion of human ignitions has a negative relationship with fire size and FRP and a positive relationship with fire frequency and season length. Areas dominated by lightning ignitions experience fires that are 2.4 times more intense and 9.2 times larger. Areas dominated by human ignitions experience fires that are twice as frequent and have a fire season that is 2.4 times longer. The effect of human ignitions on fire characteristics varies regionally. Ecoregions in the eastern U.S.A. and in some parts of the coastal western U.S.A. have no areas dominated by lightning ignitions. For the remaining ecoregions, more intense and larger fires are associated with lightning ignitions, and longer season lengths are associated with human ignitions.Main conclusionsIncreasing anthropogenic ignitions – in tandem with climate and land cover change – are contributing to a ‘new normal’ of fire activity across continental scales.

Seasonality and trends in human- and lightning-caused wildfires ≥ 2 ha in Canada, 1959–2018

We examined the seasonal distribution of lightning- and human-caused wildfires ≥ 2ha in Canada for two time periods: 1959–2018 and 1981–2018. Furthermore, we investigated trends in seasonality, number of fires per year and number of days with fire starts per year for human- and lightning-caused fires. Nationally, lightning fires peaked from June to August, whereas human fires peaked during May. There was, however, notable variation in the seasonal distributions of human- and lightning-caused fires between ecozones. Likewise, trends in season start and end dates varied among ecozones and time series, with trends generally being stronger for human-caused fires. Trends in the number of fires from 1959 to 2018 suggested significant increases in the number of lightning-caused fires and days with lightning ignitions across almost all ecozones, while from 1981 to 2018 there was a significantly decreasing trend in the number of human-caused fires and days with human ignitions in almost all ecozones. The highest densities of human-caused fires occurred in the Montane Cordillera and Atlantic Maritime, while the highest density of lightning-caused fires occurred in the Boreal Shield West. The Montane Cordillera and Taiga Shield West showed significant increases in the number of lightning fires and days with lightning ignitions across both time series.

Investigation of lightning ignition characteristics based on an impulse current generator.

Lightning strike is an important ignition source of forest fires. Artificial lightning discharge is a method for studying lightning fires. However, there is not enough data on the ignition of combustible materials caused by artificial lightning discharge. Previous studies on lightning ignition have focused on the heating and ignition effects of long continuing current (LCC), but the function of the impulse current that occurs before the LCC has not been taken into account. In this paper, an impulse current generator of 8/20 μs was used to simulate the ignition effect of impulse current on conifer needle beds. Different current waveforms have different ignition characteristics. We compared five kinds of conifer needle beds. The average of the current needed to ignite the needle bed of Larix gmelinii (Ruprecht) Kuzeneva was the smallest, and the average of the breakdown voltage was the smallest for the needle bed of Pinus massoniana Lamb. The total energy input to the conifer needle beds was fitted as a multiple log‐linear regression model. The heating energy proportion value varies with different bulk densities, current amplitudes, and moisture contents. Based on this data, the heating energy of the impulse current transferred to the needles can be predicted. This information in conjunction with previous research on LCC was used to derive a lightning ignition prediction model of the full waveform for conifer needle beds.

Quantifying fire trends in boreal forests with Landsat time series and self-organized criticality

Boreal forests are globally extensive and store large amounts of carbon, but recent climate change has led to drier conditions and increasing fire activity. The objective of this study is to quantify trends in fire size and frequency using data spanning multiple scales in space and time. We use multi-temporal Landsat image compositing on Google Earth Engine and validate results with reference fire maps from the Canadian Park Service. We also interpret general fire trends through the concept of Self-Organized Criticality (SOC). Our study site is Wood Buffalo National Park, which is a fire hot spot in Canada due to frequent lightning ignitions. The relativize differenced normalized burn ratio (RdNBR) was the most accurate Landsat-based burn severity metric we evaluated (52.2% producer's accuracy, 87.6% user's accuracy). The Landsat-based burn severity maps provided a better fit for a linear relationship on the log-log scale of fire size and frequency than a manually drawn fire map. Landsat-based fire trends since 1990 conformed to a power-law distribution with a slope of 1.9, which is related to fractal dimensions of the satellite-based fire perimeter shapes. The unburned and low-severity patches within the burn severity mosaic influenced the power-law slope and associated fractal dimensionality. This study demonstrates a multi-scale and multi-dataset technique to quantify general fire trends and changing fire cycles in remote locations and establishes a baseline database for assessing future fire activity. Testing criticality by power laws helps to quantify emergent trends of contemporary fire regimes, which could inform the strategic application of prescribed fire and other management activities. Natural resource managers can utilize information from this study to understand local ecosystem adaptability to large fire events and ecosystem stability in the context of recent increasing fire activity.

Towards a comprehensive wildfire management strategy for Mediterranean areas: Framework development and implementation in Catalonia, Spain

Southern European countries rely largely on fire suppression and ignition prevention to manage a growing wildfire problem. We explored a more wholistic, long-term approach based on priority maps for the implementation of diverse management options aimed at creating fire resilient landscapes, restoring cultural fire regimes, facilitating safe and efficient fire response, and creating fire-adapted communities. To illustrate this new comprehensive strategy for fire-prone Mediterranean areas, we developed and implemented the framework in Catalonia (northeastern Spain). We first used advanced simulation modeling methods to assess various wildfire exposure metrics across spatially changing fire-regime conditions, and these outputs were then combined with land use maps and historical fire occurrence data to prioritize different fuel and fire management options at the municipality level. Priority sites for fuel management programs concentrated in the central and northeastern high-hazard forestlands. The suitable areas for reintroducing fires in natural ecosystems located in scattered municipalities with ample lightning ignitions and minimal human presence. Priority areas for ignition prevention programs were mapped to populated coastal municipalities and main transportation corridors. Landscapes where fire suppression is the principal long-term strategy concentrated in agricultural plains with a high density of ignitions. Localized programs to build defensible space and improve self-protection on communities could be emphasized in the coastal wildland-urban interface and inner intermix areas from Barcelona and Gerona. We discuss how the results of this study can facilitate collaborative landscape planning and identify the constraints that prevent a longer term and more effective solution to better coexist with fire in southern European regions.

Exploratory analysis of lightning-ignited wildfires in the Warren Region, Western Australia

An exploratory analysis of lightning-ignited wildfire data for the Warren Region of Western Australia was carried out for the period from April 1976 to December 2016. Temporal patterns in the series were examined in terms of characterizing the seasonal cycle, and detecting long-term trends and changes in seasonality over time. A generalized additive modelling approach was used to ensure that temporal features were determined by the data rather than a priori assumed mathematical forms (e.g. linear or low-order polynomial functions). The spatial organization of the data was evaluated using concepts from the theory of stochastic point processes. Results indicate a strong seasonality in the monthly lightning ignition series, the presence of a long-term trend and an interaction between trend and seasonality. There is also strong evidence of spatial variation in the number of ignitions per unit area in terms of location and distance from nearest ignition. Within the Warren Region, observation platforms for fire detection and reporting protocols have remained stable over the period of record, and changes in land use are unlikely to have altered the pattern of lightning ignition. Thus, the above results might reflect an interplay between: landscape attributes (e.g. vegetation classes, elevation, slope, aspect); changes in rainfall and fuel moisture; changes in fuel management practices; and, perhaps, an increase in the frequency of dry thunderstorms and fire weather conditions.

Lightning as a major driver of recent large fire years in North American boreal forests

Changes in climate and fire regimes are transforming the boreal forest, the world’s largest biome. Boreal North America recently experienced two years with large burned area: 2014 in the Northwest Territories and 2015 in Alaska. Here we use climate, lightning, fire and vegetation data sets to assess the mechanisms contributing to large fire years. We find that lightning ignitions have increased since 1975, and that the 2014 and 2015 events coincided with a record number of lightning ignitions and exceptionally high levels of burning near the northern treeline. Lightning ignition explained more than 55% of the interannual variability in burned area, and was correlated with temperature and precipitation, which are projected to increase by mid-century. The analysis shows that lightning drives interannual and long-term ignition and burned area dynamics in boreal North America, and implies future ignition increases may increase carbon loss while accelerating the northward expansion of boreal forest. The boreal forest is being transformed by changes in its climate–fire regime. Analysis now shows that lightning drives year-to-year and long-term ignition and burned area trends in boreal North America.