Search Results (28)

This study examines the complex interactions among soil moisture, evaporation, extreme weather events, and lightning, and their influence on fire activity across the extratropical and Pan-Arctic regions. Leveraging reanalysis and remote-sensing datasets from 2000 to 2020, we applied cross-correlation analysis, a modified Mann–Kendall trend test, and assessments of interannual variability to key variables including soil moisture, fire frequency and risk, evaporation, and lightning. Results indicate a significant increase in dry days (up to 40%) and heatwave events across Central Eurasia and Siberia (up to 50%) and Alaska (25%), when compared to the 1980–2000 baseline. Upward trends have been detected in evaporation across most of North America, consistent with soil moisture trends, while much of Eurasia exhibits declining soil moisture. Fire danger shows a strong positive correlation with evaporation north of 60° N (r ≈ 0.7, p ≤ 0.005), but a negative correlation in regions south of this latitude. These findings suggest that in mid-latitude ecosystems, fire activity is not solely driven by water stress or atmospheric dryness, highlighting the importance of region-specific surface–atmosphere interactions in shaping fire regimes. In North America, most fires occur in temperate grasslands, savannas, and shrublands (47%), whereas in Eurasia, approximately 55% of fires are concentrated in forests/taiga and temperate open biomes. The analysis also highlights that lightning-related fires are more prevalent in Eastern Europe and Southeastern Asia. In contrast, Western North America exhibits high fire incidence in temperate conifer forests despite relatively low lightning activity, indicating a dominant role of anthropogenic ignition. These findings underscore the importance of understanding land–atmosphere interactions in assessing fire risk. Integrating surface conditions, climate extremes, and ignition sources into fire prediction models is crucial for developing more effective wildfire prevention and management strategies. Full article

This study investigates the latency of lightning-caused fires in the boreal coniferous forests of the Greater Khingan Mountains, employing advanced machine learning techniques to analyze the relationship between meteorological factors, lightning characteristics, and fire ignition and smoldering processes. Using the Random Forest Model (RFM) combined with Recursive Feature Elimination with Cross-Validation (RFECV) and SHapley Additive exPlanations (SHAP), the study identifies key factors influencing fire latency. Two methods, Min distance and Min latency, were used to determine ignition lightning, with the Min distance method proving more reliable. The results show that lightning-caused fires cluster spatially and peak temporally between May and July, aligning with lightning activity. The Fine Fuel Moisture Code (FFMC) and precipitation were identified as the most influential factors. This study underscores the importance of fuel moisture and weather conditions in determining latency of lightning-caused fire, offering valuable insights for enhancing early warning systems. Despite limitations in data resolution and the exclusion of topographic factors, this study advances our understanding of lightning-fire latency mechanisms and provides a foundation for more effective wildfire management strategies under climate change. Full article

The frequency of wildfires ignited by lightning is increasing due to global climate change. Since the forest ecological recovery is influenced by numerous factors, the process of post-fire vegetation recovery in Siberian dwarf pine shrublands remains unclear and demands in-depth study. This paper explored the short-term recovery process of vegetation after two lightning-ignited fires in the Great Xing’an Mountains that occurred in 2017 and 2020, respectively. The study was aimed at presenting a monitoring approach for estimating the post-fire vegetation state and assessing the influence of various driving factors on vegetation recovery. Spectral indices were computed to evaluate forest vegetation recovery dynamics. The differences in vegetation recovery under various fire severity and topography conditions were also examined. Correlation analysis was employed to assess the influence of moisture content on the recovery of fire sites. The results show that fire severity, topographic features, and moisture content significantly impacted the rate of vegetation recovery. Specifically, regeneration takes place more rapidly on warm, high-altitude, and gentle slopes within highly and moderately burned areas. Additionally, areas marked by high moisture content demonstrate rapid recovery. Our study enriches the research cases of global wildfires and vegetation recovery and provides a scientific basis for forest management and the restoration of post-fire ecosystems. Full article

Lightning is responsible for the most area annually burned by wildfires in the extratropical region of the Northern Hemisphere. Hence, predicting the occurrence of wildfires requires reliable forecasting of the chance of cloud-to-ground lightning strikes during storms. Here, we describe the development and verification of a probabilistic lightning-strike algorithm running on a uniform 20 km grid over the continental USA and Alaska. This is the first and only high-resolution lightning forecasting model for North America derived from 29-year-long data records. The algorithm consists of a large set of regional logistic equations parameterized on the long-term data records of observed lightning strikes and meteorological reanalysis fields from NOAA. Principal Component Analysis was employed to extract 13 principal components from a list of 611 potential predictors. Our analysis revealed that the occurrence of cloud-to-ground lightning strikes primarily depends on three factors: the temperature and geopotential heights across vertical pressure levels, the amount of low-level atmospheric moisture, and wind vectors. These physical variables isolate the conditions that are favorable for the development of thunderstorms and impact the vertical separation of electric charges in the lower troposphere during storms, which causes the voltage potential between the ground and the cloud deck to increase to a level that triggers electrical discharges. The results from a forecast verification using independent data showed excellent model performance, thus making this algorithm suitable for incorporation into models designed to forecast the chance of wildfire ignitions. Full article

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. Full article

The study evaluated the ECMWF model ability in forecasting lightning in Portugal during four fire seasons (2019–2022). 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. Full article

The analysis of the spatio-temporal variability of lightning-ignited wildfires and meteorological conditions preceding their occurrence from both dry lightning and lightning with precipitation in Western Siberia for the warm seasons (May–September) of 2016–2021 was carried out. In the Arctic zone, fires from lightnings occur in most cases (83%) almost without precipitation (<2.5 mm/day), whereas in the forest and steppe zones the number of cases is less (81% and 74%, respectively). The most significant changes in meteorological conditions before the ignition were also revealed in the northern part 3–4 days before. Among all considered parameters, the most important role in the occurrence of dry lightning-ignited wildfires belongs to mid-tropospheric instability, lower-tropospheric dryness, and the moisture content of the top soil and surface floor layer. Moreover, in the Arctic zone of Western Siberia, more extreme (hotter and drier) meteorological conditions should be observed for the occurrence of ignition from lightning. The threshold values for the considered meteorological parameters were derived for our region for the first time. Obtained results can be used in the development of models for potential fire hazards prediction in various landscapes, which will have a practical application in various spheres of the national economy. Full article

This paper concerns eighty (80) lightning-ignited wildfires on Mount Mainalo, Greece, during the period from 1998 to 2022. Descriptive statistics of the dataset, frequency distribution histograms, and maps were used to describe the number of fires per year, the burned area per fire, the total burned area per year, the elevation of lightning-caused fire occurrences, the wildfire detection time, and the holdover time (the phase between the ignition and fire detection). The analysis shows an increased frequency of lightning-caused wildfires in August and July. Most of the fires took place in the southern part of the mountain and were detected in the afternoon hours. These preliminary findings and conclusions provide a comprehensive understanding of the past regime of natural fire on Mount Mainalo, and they can support improving wildfire prevention and management policies in the region. Full article

The horizontal storm structure surrounding 92,512 lightning-ignited wildfires is examined in the mid to eastern sections of the United States from 2003 to 2015 using Vaisala’s National Lightning Detection Network (NLDN), NCEP’s Stage IV gauge-corrected radar precipitation mosaic, and the US Forest Service’s Fire Occurrence Database. Though lightning flash density peaks strongly around fire ignitions on the instantaneous 1 km scale, on the hourly 10 km scale, both the lightning and precipitation peaks are typically offset from fire ignitions. Lightning density is higher, and precipitation is lower around ignition points compared to non-ignition points. The average spatial distribution of total lightning flashes around fire ignitions is symmetrical, while that of precipitation and positive flashes is not. Though regression is consistent with the claim that positive flashes have a stronger association with ignition than negative flashes, the statistical significance is ambiguous and is contradicted by an unchanging positive flash fraction in the vicinity of wildfires. Full article

Warming-driven lightning frequency increases may influence the burning rate within the circumpolar Arctic and influence vegetation productivity (GPP). We considered wildfire occurrence within the different Arctic sectors (Russian, North American, and Scandinavian). We used satellite-derived (MODIS) data to document changes in the occurrence and geographic extent of wildfires and vegetation productivity. Correlation analysis was used to determine environmental variables (lightning occurrence, air temperature, precipitation, soil and terrestrial moisture content) associated with a change in wildfires. Within the Arctic, the majority (>75%) of wildfires occurred in Russia (and ca. 65% in Eastern Siberia). We found that lightning occurrence increase and moisture are primary factors that meditate the fire frequency in the Arctic. Throughout the Arctic, warming-driven lightning influences fire occurrence observed mainly in Eastern Siberia (>40% of explained variance). Similar values (ca. 40%) at the scale of Eurasia and the entire Arctic are attributed to Eastern Siberia input. Driving by increased lightning and warming, the fires’ occurrence boundary is shifting northward and already reached the Arctic Ocean coast in Eastern Siberia. The boundary’s extreme shifts synchronized with air temperature extremes (heat waves). Despite the increased burning rate, vegetation productivity rapidly (5–10 y) recovered to pre-fire levels within burns. Together with increasing GPP trends throughout the Arctic, that may offset fires-caused carbon release and maintain the status of the Arctic as a carbon sink. Full article

In the climate change context, wildfires are an increasing hazard in the Mediterranean Basin, especially those triggered by lightning. Although lightning activity can be predicted with a reasonable level of confidence, the challenge remains in forecasting the thunderstorm’s probability of ignition. The present work aims to characterise the most suitable predictors to forecast lightning-ignited wildfires. Several ERA5 parameters were calculated and compared for two different samples, thunderstorm episodes that caused a wildfire (n = 961) and ordinary thunderstorms (n = 1023) that occurred in Catalonia (NE Iberian Peninsula) in the 2006–2020 period. Lightning wildfires are mostly associated with dry thunderstorms, characterised by: weak-to-moderate Mixed-Layer Convective Available Potential Energy (MLCAPE, 150–1100 J kg⁻¹), significant Dew Point Depression at 850 hPa (DPD₈₅₀, 3.3–10.1 °C), high Most-Unstable Lifted Condensation Level (MULCL, 580–1450 m) and steep 500–700 hPa Lapse Rate (LR, −7.0–−6.3 °C). Under these conditions, with relatively dry air at lower levels, thunderstorms tend to be high-based, the rain evaporating before reaching the ground and lightning occurring without significant rainfall. Specifically forecasting the probability of LIW occurrence would be of great assistance to the forest protection tactical decision-making process, preparing for “dry” thunderstorm days where multiple ignitions can be expected. Full article

The Sierra Nevada region has experienced substantial wildfire impacts. Uncertainty pertaining to fire risk may be reduced by better understanding how air temperature (Ta: °C) influences wildfire ignitions independently of other factors. We linked lightning-ignited wildfires to Ta patterns across the region from 1992 to 2015 and compared monthly high- and low-air-temperature patterns between ignition and non-ignition locations at local scales (4 km). Regionally, more ignitions occurred in springs with a greater number of high-Ta months and fewer cool Ta months (analyzed separately) and in summers with fewer cool Ta months. Locally, summer ignition locations experienced warmer summer months on a normalized scale than non-ignition locations. The probability of a wildfire ignition was positively associated with a greater number of high-Ta months during and prior to fire seasons. Regionally, springs with a greater number of high-Ta months had more wildfire ignitions. Locally, as individual locations in the region experienced a greater number of high-Ta months preceding and including the fire season, they exhibited substantial increases in spring (+1446%), summer (+365%), and fall (+248%) ignitions. Thus, the frequent occurrence of high-Ta months is positively associated with lightning-ignited wildfires in the Sierra Nevada region. Full article

Affected by global warming, permafrost degradation releases a large amount of methane gas, and this part of flammable methane may increase the frequency of wildfires. To study the influence mechanism of methane emission on wildfires in degraded permafrost regions, we selected the northwest section of Xiaoxing’an Mountains in China as the study area, and combined with remote sensing data, we conducted long-term monitoring of atmospheric electric field, temperature, methane concentration, and other observation parameters, and further carried out indoor gas–solid friction tests. The study shows that methane gas (the concentration of methane at the centralized leakage point is higher than 10,000 ppm) in the permafrost degradation area will release rapidly in spring, and friction with soil, surface plant residues, and water vapor will accelerate atmospheric convection and generate electrostatic and atmospheric electrodischarge phenomena on the surface. The electrostatic and atmospheric electrodischarge accumulated on the surface will further ignite the combustibles near the surface, such as methane gas and plant residues. Therefore, the gradual release of methane gas into the air promotes the feedback mechanism of lightning–wildfire–vegetation, and increases the risk of wildfire in degraded permafrost areas through frictional electrification (i.e., electrostatic and atmospheric electrodischarge). Full article

Wildfires are increasingly understood as an ecological driver within the entire Arctic biome. Arctic soils naturally store large quantities of C, as peat has formed throughout the Holocene. For the Siberian Arctic, we used observations from the MODIS remote sensing instrument to document changes in frequency, geographic extent, and seasonal timing of wildfires as well as vegetation productivity (GPP, NPP, EVI). We also used correlation and regression analysis to identify environmental factors of temperature, precipitation, and lightning occurrence associated with these changes. For the Siberian Arctic as a whole, we found that the decadal frequency of wildfire tripled from the 2001–2010 to the 2011–2020 periods. Increased decadal frequency was accompanied by the increased extent of the burnt area by a factor of 2.6. This increase in fire frequency and extent was not uniform, with the greatest increase in western Siberia with no marked increase for the Siberian Far East. These changes were accompanied by the northward migration of the northern limit of wildfire occurrence and an increase in duration of the wildfire season. We found that annual fire frequency and the extent of burnt areas were related to various combinations of seasonal air temperature, precipitation, ground moisture, and lightning frequency. After fires, vegetation productivity rapidly recovered to pre-fire levels. The northward spread of wildfire into the tundra will release carbon long-stored as peat. The enhanced vegetation productivity, rapid recovery of carbon fixation for burnt areas and the northward migration of boreal forest tree species may offset that release and maintain the current status of the Siberian Arctic as a C sink. Increased wildfire and loss of permafrost may threaten ongoing settlement and industrialization, particularly for western Siberia. Full article

Wildfires are not only a natural part of many ecosystems, but they can also have disastrous consequences for humans, including in Australia. Rugged terrain adds to the difficulty of predicting fire behavior and fire spread, as fires often propagate contrary to expectations. Even though fire models generally incorporate weather, fuels, and topography, which are important factors affecting fire behavior, they usually only consider the surface wind; however, the more elevated winds should also be accounted for, in addition to surface winds, when predicting fire spread in rugged terrain because valley winds are often dynamically altered by the interaction of a layered atmosphere and the topography. Here, fire spread in rugged terrain was examined in a case study of the Riveaux Road Fire, which was ignited by multiple lightning strikes in January 2019 in southern Tasmania, Australia and burnt approximately 637.19 km². Firstly, the number of conducive wind structures, which are defined as the combination of wind and temperature layers likely to result in enhanced surface wind, were counted by examining the vertical wind structure of the atmosphere, and the potential for above-surface winds to affect fire propagation was identified. Then, the multiple fire propagations were simulated using a new fire simulator (Prototype 2) motivated by the draft specification of the forthcoming new fire danger rating system, the Australian Fire Danger Rating System (AFDRS). Simulations were performed with one experiment group utilizing wind fields that included upper-air interactions, and two control groups that utilized downscaled wind from a model that only incorporated surface winds, to identify the impact of upper air interactions. Consequently, a detailed analysis showed that more conducive structures were commonly observed in the rugged terrain than in the other topography. In addition, the simulation of the experiment group performed better in predicting fire spread than those of the control groups in rugged terrain. In contrast, the control groups based on the downscaled surface wind model performed well in less rugged terrain. These results suggest that not only surface winds but also the higher altitude winds above the surface are required to be considered, especially in rugged terrain. Full article