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Increased knowledge of the meteorological conditions that lead to mega-fires is important to prevent wildfires and improve firefighting. This study analyses the atmospheric conditions that led to the largest forest fire ever observed in Portugal in 2019. The fire burned an estimated total area of around 9000 hectares in 12 h. The study is based on two simulations performed with the Meso-NH atmospheric model. The control simulation was configured in a single and large domain with 2500 m resolution, whereas a second simulation was configured using the grid nesting technique with an inner domain with 500 m resolution. The fire developed under typical summer conditions, under the influence of the Azores anticyclone and the presence of the Iberian thermal low. The weather pattern included intense northwest winds in the western region of the Iberian Peninsula. In the fire area, the wind speed was around 7 m s−1 with maximum wind gusts of 15 m s−1, favouring the rapid spread of the fire and characterising the event as a wind-driven fire. This study demonstrates the benefits of the use of large domains and high-resolution numerical simulations to explore the regional and local effects, which are crucial for the evolution of some fires. [ABSTRACT FROM AUTHOR]

Fire activity in 288 areas (2.5° N × 10° E) in the Arctic region (50°–70° N, 0°–360° E) was analyzed using about 4.4 million satellite hotspot (HS) data from 2002 to 2021. A total of 21 high fire density areas from eastern Europe to western Canada were selected, and their fire–weather conditions during each active fire period were analyzed using about 1820 various weather maps at the upper and the lower air level. Analysis results showed that the active fires in the Arctic region occurred under the fire–weather conditions associated with the northward movement of cut-off high (COH) and warm air masses detached from the south caused by large westerly meandering (LWM). LWM is a sign of the beginning of an active fire period. Very active fires on HS peak days occurred several days after the start of the northward movement of COHs and under mainly high-pressure conditions in the upper air and strong wind conditions in the lower air. The time lag of these several days suggests that we may be prepared for very active fires. The fire–weather analysis approach described in this paper has shown that future large-scale fire outbreaks are predictable. [ABSTRACT FROM AUTHOR]

High‐resolution regional reanalysis datasets have the potential to provide valuable guidance to emergency management agencies, highlighting areas at risk of severe weather, including estimates of return periods of various hazardous weather phenomena. The BARRA regional reanalysis for Australia comprises a reanalysis for a broad region around Australia at moderately high spatial and temporal resolution (12 km/hourly), together with four subdomains at high resolution (1.5 km/1 h). Here, we document four applications of BARRA developed for emergency management: optimal placement of portable automatic weather stations for fire weather monitoring; climatology of low‐level wind shear conducive to cool‐season tornadogenesis; development of rainfall intensity–frequency–duration curves based on the gridded reanalysis data; and development of a climatology across Australia of parameters associated with severe thunderstorm occurrence. [ABSTRACT FROM AUTHOR]

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In many parts of the world, wildfires have become more frequent and intense in recent decades, raising concerns about the extent to which climate change contributes to the nature of extreme fire weather occurrences. However, studies seeking to attribute fire weather extremes to climate change are hitherto relatively rare and show large disparities depending on the employed methodology. Here, an empirical-statistical method is implemented as part of a global probabilistic framework to attribute recent changes in the likelihood and magnitude of extreme fire weather. The results show that the likelihood of climate-related fire risk has increased by at least a factor of four in approximately 40% of the world’s fire-prone regions as a result of rising global temperature. In addition, a set of extreme fire weather events, occurring during a recent 5-year period (2014–2018) and identified as exceptional due to the extent to which they exceed previous maxima, are, in most cases, associated with an increased likelihood resulting from rising global temperature. The study’s conclusions highlight important uncertainties and sensitivities associated with the selection of indices and metrics to represent extreme fire weather and their implications for the findings of attribution studies. Among the recommendations made for future efforts to attribute extreme fire weather events is the consideration of multiple fire weather indicators and communication of their sensitivities. [ABSTRACT FROM AUTHOR]

Fire-killed serotinous trees are often dominant species in fire-prone regions with contrasting wet and dry seasons. We studied a serotinous fire-killed conifer (Callitris preissii, Cupressaceae) to identify the influence of fire regime and climate on geographic variation in level of serotiny, recruitment and population structure. We measured population size distributions, seedling recruitment and level of serotiny for sample stands across a climatic gradient from mesic coastal (including two islands) to semi-arid inland sites in SW Australia. Trees on islands were mostly non-serotinous and were only weakly serotinous on the adjacent mainland in the higher rainfall West coast region. In the semi-arid Goldfields and South inland, and the higher rainfall South coast region, trees were more strongly serotinous with up to six cohorts of closed cones retained on trees. Level of serotiny was stronger at the drier end of the climatic gradient where severe to extreme fire danger weather occurs most frequently, and where vegetation type (e.g., shrublands) supports frequent crown-type, stand-replacing fires. Recruitment was most abundant post-fire in all regions, but seedlings also established inter-fire where there was regular seed fall due to low level of serotiny or spontaneous release of seeds from old cones on trees with a high cone load. Population structures for mainland stands shifted from approximately reverse-J (indicating continuous recruitment) in mesic regions to mainly unimodal (establishment mostly after fire) in drier, inland regions, although some long-unburned inland stands showed occasional inter-fire recruitment, likely linked to high rainfall years. Unimodal population structures characterized islands, where previous studies have identified herbivory on seedlings by refugial populations of native macropods as a limiting factor on inter-fire establishment. Understanding landscape context, response to disturbance, biotic interactions and reproductive traits of dominant species is essential in conservation planning in a rapidly changing global environment. [ABSTRACT FROM AUTHOR]

The goal of decreasing wildfire hazard as much as possible, using minimal fuel treatments, has led to increasing scholarly interest in fuel reduction spatial optimisation. Most models in the field rest on the assumption of a known wind direction and a corresponding dominant direction of fire spread, and plan firebreaks in perpendicular directions. This strategy is effective when the wind blows in the hypothesised direction, but is quite ineffective when the wind direction is parallel to the firebreaks. In this article, we re-examine this assumption using a global fire dataset covering more than a decade. We perform a variety of circular statistical analyses including circular variance and principal component analysis (PCA). We find that the direction of fire spread in most regions is not limited to a single direction. We also find that the wind direction during fire weather is characterised by a high variance in a substantial fraction of regions around the globe. We validate this finding with a dataset comprised of over a hundred meteorological stations in Israel. We conclude that forest management should consider regional historical data of wind directions and fire spread directions, but also should plan firebreaks so that they are effective in various fire scenarios. [ABSTRACT FROM AUTHOR]

The frequent occurrence of fatalities from wildfires is an ongoing problem in China, even though great improvements have been achieved in overall wildfire management in recent years. We analysed the occurrence patterns and correlative environments of fatalities from forest fires in China from 1951 to 2018. Changes in fire policies affected changes in the numbers of fires, forest area burned and number of fatalities before and after 1987, after the large Great Black Dragon Fire that burned in the Daxing'anling Mountains in northeastern China. Most fatalities occurred in the southern, southwestern and eastern forest regions of the country where population centres are concentrated, while most of the burned area was distributed in forests of northeast China with fewer population centres. Fatalities were correlated with higher values of fire weather indices, coniferous forests, coniferous and broad-leaved mixed forests, moderate-average slopes (5.1-15°), and primarily small fires of less than 100 ha in area. These results should be a first step to help improve awareness of inherent dangers during wildfires and to assist fire managers and policy-makers in strengthening safety procedures for both professional firefighters and the public to reduce wildfire fatalities in the future. [ABSTRACT FROM AUTHOR]

The suggestion has been made within the wildland fire community that the rate of spread in the upper portion of the fire danger spectrum is largely independent of the physical fuel characteristics in certain forest ecosystem types. Our review and analysis of the relevant scientific literature on the subject suggest that fuel characteristics have a gradual diminishing effect on the rate of fire spread in forest and shrubland fuel types with increasing fire danger, with the effect not being observable under extreme fire danger conditions. Empirical-based fire spread models with multiplicative fuel functions generally do not capture this effect adequately. The implications of this outcome on fire spread modelling and fuels management are discussed. [ABSTRACT FROM AUTHOR]

Wildfires are a major natural hazard that lead to deforestation, carbon emissions, and loss of human and animal lives every year. Effective predictions of wildfire occurrence and burned areas are essential to forest management and firefighting. In this paper we apply various machine learning (ML) methods on a 0.25° monthly resolution global dataset of wildfires. We test the prediction accuracies of four different fire occurrence classifiers: random forest (RF), eXtreme Gradient Boosting (XGBoost), multilayer perceptron (MLP) neural network, and a logistic regression. Our best ML model predicts wildfire occurrence with over 90% accuracy, compared to approximately 70% using a logistic regression. We then train ML regression models to predict the size of burned areas and obtain an MAE score of 3.13 km 2 , compared to 7.48 km 2 using a linear regression. To the best of our knowledge, this is the first study to be conducted in such resolution on a global dataset. We use the developed models to shed light on the influence of various factors on wildfire occurrence and burned areas. We suggest building upon these results to create ML-based fire weather indices. [ABSTRACT FROM AUTHOR]

This study was conducted to identify the fire weather conditions needed to assess future peatland fires under climate change. Recent peatland fires in Indonesia have resulted in globally significant environmental impacts. Nevertheless, fire weather in the peatlands has not been clarified. The objective of this study is to determine the fire weather needed to assess future peatland fires under climate change. We analyzed fire, rainfall, temperature, humidity, and wind in the fire-prone areas in Sumatra. Analysis results using 20 years of satellite hotspot data from 2003 showed that fires in Sumatra occur every other month except December and April when rainfall intensifies. Due to relatively low rainfall, peatland fires in North Sumatra occur not only from January to March (the main dry season), but also around June and August if short-term drought happens. These fire trends may suggest that the peatlands of Sumatra are mostly in a combustible state. Analysis results using diurnal weather data showed that active peatland fires tend to occur under high air temperatures (around above 34 °C), low relative humidity (lower than 50%), and high wind speeds (higher than 18 km h−1). We hope that this report will help improve future peat fire assessments and fire forecasting under rapid climate change.

The National Weather Service is responsible for alerting wildland fire management of meteorological conditions that create an environment conducive for extreme fire behavior. This is communicated via Red Flag Warnings (RFWs), which presently lack a national standardized methodology and rarely are explicitly linked to fuel conditions such those as provided by National Fire-Danger Rating System (NFDRS) indicators. The need for a revamped RFW has been expressed recently by both fire management and fire weather meteorologists. A decision matrix approach was developed to determine criteria that consistently and explicitly associates meteorological and fuels information to extreme fire behavior. Extreme fire behavior is defined here as maximum rates of spread (area per day) observed on documented large fires from 1999–2014 utilizing the ICS209 all-hazard dataset. Meteorological conditions occurring with these rates of spread were compared to historical percentiles of relative humidity, wind speed, and the NFDRS Energy Release Component. These percentiles were assigned a numerical score from one through five based on percentile rank. The additive result of all three scores was plotted against rates of spread yielding a two-step decision matrix of RFW categories where, for example, the highest score is the most extreme RFW case. Actual RFW issuances were compared to this matrix method.

Fire activity has significantly changed in Europe over the last decades (1980–2020s), with the emergence of summers attaining unprecedented fire prone weather conditions. Here we report a significant shift in the non-stationary relationship linking fire weather conditions and fire intensity measured in terms of CO2 emissions released during biomass burning across a latitudinal gradient of European IPCC regions. The reported trends indicate that global warming is possibly inducing an incipient change on regional fire dynamics towards increased fire impacts in Europe, suggesting that emerging risks posed by exceptional fire-weather danger conditions may progressively exceed current wildfire suppression capabilities in the next decades and impact forest carbon sinks. [ABSTRACT FROM AUTHOR]

Forest fires constitute a major environmental and socioeconomic hazard in the Mediterranean. Weather and climate are among the main factors influencing forest fire potential. As fire danger is expected to increase under changing climate, seasonal forecasting of weather conditions conductive to fires is of paramount importance for implementing effective fire prevention policies. The aim of the current study is to provide high resolution (~9km) probabilistic seasonal fire danger forecasts, utilizing the Canadian Fire Weather Index (FWI) for Attica region, one of the most fire prone regions in Greece and the Mediterranean, employing the fifth generation ECMWF seasonal forecasting system (SEAS5). Results indicate that FWI and its Initial Spread Index (ISI) sub-component, present statistically significant high discrimination scores and are proven respectively, marginally useful, and perfectly reliable in predicting above normal fire danger conditions. When comparing year-by-year the fire danger predictions with the historical fire occurrence obtained by the Hellenic Fire Service database, both seasonal FWI and ISI forecasts indicate a skill in identifying years with high fire occurrences. Overall, fire danger and its subcomponents can potentially be exploited by regional authorities in fire prevention management regarding preparedness and resources allocation in the Attica region. [ABSTRACT FROM AUTHOR]

Reconstructed weather datasets, such as reanalyses based on model output with data assimilation, often show systematic biases in magnitude when compared with observations. Postprocessing approaches can help adjust the distribution so that the reconstructed data resemble the observed data as closely as possible. In this study, we have compared various statistical bias-correction approaches based on quantile–quantile matching to correct the data from the Twentieth Century Reanalysis, version 2c (20CRv2c), with observation-based data. Methods included in the comparison utilize a suite of different approaches: a linear model, a median-based approach, a nonparametric linear method, a spline-based method, and approaches that are based on the lognormal and Weibull distributions. These methods were applied to daily data in the Australian region for rainfall, maximum temperature, relative humidity, and wind speed. Note that these are the variables required to compute the forest fire danger index (FFDI), widely used in Australia to examine dangerous fire weather conditions. We have compared the relative errors and performances of each method across various locations in Australia and applied the approach with the lowest mean-absolute error across multiple variables to produce a reliable long-term bias-corrected FFDI dataset across Australia. The spline-based data correction was found to have some benefits relative to the other methods in better representing the mean FFDI values and the extremes from the observed records for many of the cases examined here. It is intended that this statistical bias-correction approach applied to long-term reanalysis data will help enable new insight on climatological variations in hazardous phenomena, including dangerous wildfires in Australia extending over the past century. [ABSTRACT FROM AUTHOR]

Recent catastrophic fires in Australia and North America have raised broad‐scale questions about how the cessation of Indigenous burning practices has impacted fuel accumulation and structure. For sustainable coexistence with fire, a better understanding of the ancient nexus between humans and flammable landscapes is needed. We used novel palaeoecological modeling and charcoal compilations to reassess evidence for changes in land cover and fire activity, focusing on southeast Australia before and after British colonization. Here, we provide what we believe is the first quantitative evidence that the region's forests and woodlands contained fewer shrubs and more grass before colonization. Changes in vegetation, fuel structures, and connectivity followed different trajectories in different vegetation types. The pattern is best explained by the disruption of Indigenous vegetation management caused by European settlement. Combined with climate‐change impacts on fire weather and drought, the widespread absence of Indigenous fire management practices likely preconditioned fire‐prone regions for wildfires of unprecedented extent. [ABSTRACT FROM AUTHOR]

Climate projections indicate that dangerous fire weather will become more common over the coming century. We examine the potential of a network of temperature- and moisture-sensitive tree-ring sites in southeastern Australia to reconstruct the number of high fire-danger days for the January--March season. Using the Forest Fire Danger Index (FFDI), we show that modestly statistically skilful reconstructions for the far southeast of Australia (western Tasmania), where the majority of tree-ring predictors are located, can be developed. According to the averaged reconstructions for the 1590-2008 period, there have been 16 years prior to the start of the FFDI records (1950), and 7 years since 1950, with >48 (mean + 1σ) high fire-danger days in the 3-month season. The western Tasmanian reconstructions indicate extended relatively high firedanger periods in the 1650s-1660s and 1880s-1890s. Fire danger has also been relatively high since 2000 CE. A persistent increase in the number of high fire-danger days over the past four decades has not been matched over the previous 390 years. This work indicates it is possible to produce statistically useful reconstructions of high seasonal fire danger -- as opposed to fire occurrence -- but that availability of local proxy records is key. [ABSTRACT FROM AUTHOR]

Thinning young forest stands is a common practice to improve the future development of the remaining trees and enhance their resistance to abiotic and biotic disturbances. The objective of this study was to consider the effectiveness of precommercial thinning, over time, implemented on Pinus halepensis (Aleppo pine) thickets, regarding fuel evolution and potential fire behavior. For this purpose, we established 44 plots on untreated and thinned Aleppo pine stands, measured all of the relevant fuel characteristics and simulated fire behavior under average and extreme fire weather scenarios. The plots were at different stages of fuel evolution (0.5 to 10 years since treatment, plus untreated stands), so that the evolution of the variables defining forest structure and the amount and distribution of surface fuels could be captured. The results show that precommercial thinning, when accompanied with pruning and surface fuel management, had a clear impact on fire behavior and on the potential of fire crowning during the first two to four years after the treatment. After that initial period, the buildup of understory vegetation minimized treatment effectiveness in mitigating potential fire behavior. In general, it can be stated that precommercial thinning has a positive impact on fire mitigation, but the impact that opening the tree canopy has on ground vegetation development must be considered in order to plan more efficient management strategies. [ABSTRACT FROM AUTHOR]

Climate change is expected to enhance weather conditions prone to wildfires. Climate regionalized projections for the Canary Islands were performed, using as boundary conditions some of the results provided by the Coupled Model Intercomparison Project (CMIP5) initiative, and covering the recent past (1980–2009) and future (2070–2099) periods, under two Representative Concentration Pathways, 4.5 and 8.5. All fire risk indicators derived from the Canadian Forest Fire Weather Index (FWI) are foreseen to worsen by the end of the century. The fire season could increase its length up to 75 days per year, being more noticeable as altitude increases. The extreme risk days (FWI > 60) show an average increase of 58%, reaching 12 days a year, and the area with high risk could increase by 44%. Analyzing the contribution of the different meteorological variables, it is observed that the main parameter in the fire danger index result is the temperature (currently weights 46%). However, in the future, the importance of precipitation will increase, since the rainfall reduction in some areas could reach 41%. The high dependence of the expected changes on land height, and the small size of the islands, demonstrates the necessity of using high-resolution climate regionalizations. [ABSTRACT FROM AUTHOR]

Five of California's 10 largest wildfires occurred in 2020, with the largest complex exceeding the previous largest by more than 100%. The year follows a decade containing extraordinary fire activity. Previous trend investigations focused on changes in human activities and atmospheric thermodynamics, while the impacts of changing atmospheric dynamics are largely unknown. Here, we identify weather types (WTs) associated with historically large daily burned areas in eight Californian regions. These WTs characterize dominant fire weather regimes varying in fire behavior types (plume‐driven vs. wind‐driven fires) and seasonality. Most of the strongly large‐scale forced WTs such as Santa Ana and Diablo events increased in frequency during the 20th century particularly in the San Diego and Bay Area regions. These changes are likely not anthropogenically caused and the frequency of such events is projected to decrease under continuing climate change. However, significant future increases are found for WTs associated with thermal‐low‐pressure systems along the California coast and in the Sierra west region. These increases in southern California are mainly due to increasing greenhouse‐gas forcing and arise from the larger ocean‐land temperature gradient while aerosol forcing changes are driving most of the increased frequency in central and northern California due to a reduction of relative humidity over land and a strengthening of low‐pressure anomalies over the coast. These WT frequency changes could permit more weather favorable for large fire growth in summer and less in fall, further enhancing the risk of catastrophic fires due to hotter and drier summers in future climates. Key Points: Fire weather types (WTs) are shown to be related to the largest burned area days in recent decades in eight Californian regionsIncreases in Diablo and Santa Ana WT events during the 20th century are primarily caused by natural climate variabilityChanging greenhouse gas and aerosol forcing significantly increase thermal‐low WTs in coastal regions and the western Sierra [ABSTRACT FROM AUTHOR]

California has experienced a rapid increase in burned area over the past several decades. Although fire behavior is known to be closely tied to ecosystem impacts, most analysis of changing fire regimes has focused solely on area burned. Here we present a standardized database of wildfire behavior, including daily fire rate-of-spread and fire radiative power for large, multiday wildfires in California during 2012–2018 using remotely-sensed active fire observations. We observe that human-ignited fires start at locations with lower tree cover and during periods with more extreme fire weather. These characteristics contribute to more explosive growth in the first few days following ignition for human-caused fires as compared to lightning-caused fires. The faster fire spread, in turn, yields a larger ecosystem impact, with tree mortality more than three times higher for fast-moving fires (>1 km day−1) than for slow moving fires (<0.5 km day−1). Our analysis shows how human-caused fires can amplify ecosystem impacts and highlights the importance of limiting human-caused fires during period of extreme fire weather for meeting forest conservation targets under scenarios of future change. 'Human-caused fires and natural fires could have different impacts. Here the authors report a geospatial analysis of lightning-ignited and human-ignited fires in California between 2012 and 2018, finding that the latter were more likely to develop under extreme conditions with larger ecosystem impacts.' [ABSTRACT FROM AUTHOR]

The Split wildfire in July 2017, which was one of the most severe wildfires in Croatian history of this World Heritage site, is the focus in this study. The Split fire is a good example of wildfire-urban interface, with unexpected fire behavior including rapid downslope spread to the coastal populated area. Thus, it is critical to clarify the meteorological conditions behind the fire event, those that have limited the effectiveness of firefighting operations and the rapid escalation and expansion of the fire zones within thirty hours. First, the Split fire propagation was reconstructed using radio logs, interviews with firefighters and pilots involved in the intervention, eye-witness statements, digital photographs from fire detection cameras, media and firefighting monthly journal. Four phases of fire development have been identified. Then, weather observations and numerical simulations using an enhanced-resolution operational model are utilized to analyze the dynamics in each phase of the fire runs. The synoptic background of the event includes large surface pressure gradient between the Azores anticyclone accompanied by cold front and a cyclone over southeastern Balkan Peninsula. At the upper level, there was a deep shortwave trough extending from the Baltic Sea to the Adriatic Sea, which developed into a cut-off low. Such synoptic conditions have resulted in the annual maximum of Fire Weather Index and the highest monthly severity rating for July in the period 1981-2020. Combined with topography, they also provoke locally the formation of the strong northeasterly bura wind along the Adriatic coast. During the fire event, wind gust of nearly 25 m s-1 occurred. Low level jet (LLJ) has also been formally identified during an extended period, with a peak prior to the fire event possessing wind speed of over 21 m s-1 at a height of 600-700 m. Analysis of the upper-level jet also reveals that there was a deep tropospheric bura, which has facilitated the subsidence of dry air from the upper troposphere. In the mid to lower level, gravity wave breaking and turbulence mixing (as in the hydraulic jump theory) in the downslope bura wind further enabled the rapid drying at the surface. Low level jet and strong downslope wind such as the bura are known to be related to many severe wildfire events worldwide, besides the antecedent hot and dry weather conditions and fuel loads. As has been demonstrated in this study, numerical guidance that indicates the spatial and temporal occurrence of low level jet is highly implicative to explain the Split fire evolution from the ignition potential to its extinguishment stage. Thus, in addition to the conventional fire weather indexes, such products are able to improve fire weather behavior forecast and in general more effective decision-making in fire management. [ABSTRACT FROM AUTHOR]

The meteorological conditions over the South Coast of New South Wales, Australia, are investigated on 18 March 2018, the day of the Tathra bushfire. We present an analysis of the event based on high-resolution (100- and 400-m grid-length) simulations with the Bureau of Meteorology's ACCESS numerical weather prediction system and available observations. Through this analysis we find several mesoscale features that likely contributed to the extreme fire event. Key among these was the development of horizontal convective rolls, which emanated from inland and aided the fire's spread toward Tathra. The rolls interacted with the terrain to produce complex regions of strongly ascending and descending air, likely accelerating the lofting of firebrands and potentially contributing to the significant lee-slope fire behavior observed. Mountain waves, specifically trapped lee waves, occurred on the day and are hypothesized to have contributed to the strong winds around the time the fire began. These waves may also have influenced conditions during the period of peak fire activity when the fire spotted across the Bega River and impacted Tathra. Finally, the passage of the cold front through the fireground was complex, with frontal regression observed at a nearby station and likely also through Tathra. We postulate that interactions between the strong prefrontal flow and the initially weak change resulted in highly variable and dangerous fire weather across the fireground for a significant period after the change initially occurred. Significance Statement: The town of Tathra on the South Coast of New South Wales, Australia, was devastated on 18 March 2018, when a wildfire ignited in nearby bushland and quickly intensified to impact the town. Using high-resolution numerical weather simulations, we investigate the conditions that led to the extreme fire behavior. The simulations show that the fire ignited and intensified under highly variable conditions driven by complex interactions between the flow over nearby mountains and the passage of a strong cold front. This case study highlights the value of such models in understanding high-impact weather for the purpose of hazard preparedness and emergency response. Additionally, it contributes to a growing number of case studies that indicate the future direction of high-impact forecast services. [ABSTRACT FROM AUTHOR]

Wildfire is one of the most complex natural hazards. Its origin is a combination of anthropogenic factors, urban development and weather plus climate factors. In particular, weather and climate factors possess many spatiotemporal scales and various degrees of predictability. Due to the complex synergy of the human and natural factors behind the events, every wildfire is unique. However, there are indeed common meteorological and climate factors leading to the high fire risk before certain ignition mechanismfigures occur. From a scientific point of view, a better understanding of the meteorological and climate drivers of wildfire in every region would enable more effective seasonal to annual outlook of fire risk, and in the long term, better applications of climate projections to estimate future scenarios of wildfire. This review has performed a comparison study of two fire-prone regions: southeast Australia including Tasmania, and the Adriatic coast in Europe, especially events in Croatia. The former is well known as part of the 'fire continent', and major resources have been put into wildfire research and forecasting. The Adriatic coast is a region where some of the highest surface wind speeds, under strong topographic effect, have been recorded and, over the years, have coincided with wildfire ignitions. Similar synoptic background and dynamic origins of the meso-micro-scale meteorological conditions of these high wind events as well as the accompanied dryness have been identified between some of the events in the two regions. We have also reviewed how the researchers from these two regions have applied different weather indices and numerical models. The status of estimating fire potential under climate change for both regions has been evaluated. This review aims to promote a global network of information exchange to study the changing anthropogenic and natural factors we have to confront in order to mitigate and adapt the impacts and consequences from wildfire. [ABSTRACT FROM AUTHOR]

The frequent occurrence of fatalities from wildfires is an ongoing problem in China, even though great improvements have been achieved in overall wildfire management in recent years. We analysed the occurrence patterns and correlative environments of fatalities from forest fires in China from 1951 to 2018. Changes in fire policies affected changes in the numbers of fires, forest area burned and number of fatalities before and after 1987, after the large Great Black Dragon Fire that burned in the Daxing'anling Mountains in northeastern China. Most fatalities occurred in the southern, southwestern and eastern forest regions of the country where population centres are concentrated, while most of the burned area was distributed in forests of northeast China with fewer population centres. Fatalities were correlated with higher values of fire weather indices, coniferous forests, coniferous and broad-leaved mixed forests, moderate–average slopes (5.1–15°), and primarily small fires of less than 100 ha in area. These results should be a first step to help improve awareness of inherent dangers during wildfires and to assist fire managers and policy-makers in strengthening safety procedures for both professional firefighters and the public to reduce wildfire fatalities in the future. Fatalities decreased significantly after the establishment of fire management systems. Annual fatalities had a strong positive correlation with number of fires. Fatalities mainly occurred in south and east regions of China with high population densities. Most fatalities occurred in fires with sizes less than 100 ha. Coniferous forest types and 5.1–15° slopes are the main factors related to fatalities. [ABSTRACT FROM AUTHOR]

Anticipating fire behavior as climate change and fire activity accelerate is an increasingly pressing management challenge in fire‐prone landscapes. In subalpine forests adapted to infrequent, stand‐replacing fire, self‐limitation of burn severity in short‐interval fire is incompletely understood. Spatially explicit fuels data can support assessments of landscape‐scale fire risk and fuel feedbacks on burn severity. For a ~1450‐km2 largely forested landscape in the US Northern Rocky Mountains, we used airborne lidar and imagery to predict and map canopy and surface fuels. In a fire that burned mature (>125‐year‐old) and also reburned young (~30‐year‐old) subalpine forest, we then asked: (1) How do prefire fuels and burn severity compare between young and mature forests that burned under similar fire weather conditions? (2) How well do prefire fuels and forest structure predict burn severity under extreme versus moderate fire weather? Lidar–imagery fusion predicted fuel characteristics with high accuracy across forest and shrubland vegetation. Young postfire forests had abundant, densely packed canopy fuels, and both young and mature forests had similar canopy fuel loads and coarse wood biomass. Under similar weather conditions, young and mature forests burned at similar severity. Overall, fuels were weak predictors of burn severity and, surprisingly, better predicted severity under extreme rather than moderate fire weather. Our findings are relevant for subalpine landscapes increasingly dominated by young lodgepole pine (Pinus contorta var. latifolia) forests vulnerable to short‐interval fire and provide a benchmark to assess how fuels influence burn severity in future fires. Fire managers should continually reassess fuels and update expectations about fire behavior as landscapes change. Although recovering postfire forests can limit fire spread and severity for a period of time, our results suggest that young subalpine forests in the Northern Rocky Mountains have sufficient fuel loads to burn at high severity and should not be considered effective fire breaks. [ABSTRACT FROM AUTHOR]

Fire weather indices are widely used to understand and assess meteorological fire hazard. However, in complex regions such as Switzerland with mountainous and hilly terrain, it is difficult to select an appropriate index. In this study, we validate the performance of 14 fire weather indices, four meteorological variables, and a logistic regression model to predict wildfire occurrence for different ecoregions in the canton of Bern in Northern Switzerland with respect to historical fire records from 1981 to 2020. We find that the performance of the indices varies seasonally and regionally. The spring season (March-May) shows that the Canadian Fine Fuel Moisture Content and other indices that respond readily to weather changes perform best. In summer (June-August) and autumn (September-November), the Canadian Buildup Index and Drought Code - indices that describe persistent hot and dry conditions - perform best. Overall, seasonal differences in performance are larger than interregional differences. Finally, we show that a logistic regression model trained on local historical fire activity can outperform existing fire weather indices and can be used for medium-range weather forecasting or climate change studies, using only daily averages of meteorological variables as input. [ABSTRACT FROM AUTHOR]

An analysis of a dataset (n = 58) of high-intensity wildfire observations in cured grasslands from southern Australia revealed a simple relationship suitable for quickly obtaining a first approximation of a fire's spread rate under low dead fuel moisture contents and strong wind speeds. It was found that the forward rate of fire spread is approximately 20% of the average 10-m open wind speed. The data on rate of fire spread and 10 m open wind speed ranged from 1.6 to 17 and 20 to 62 km h−1, respectively. The validity of the resulting rule of thumb was examined across a spectrum of burning conditions and its performance was contrasted against that of established empirical-based fire spread models for three different grassland fuel conditions currently used operationally in Australia. The 20% rule of thumb for grassfires produced error statistics comparable to that of the fire spread rate model for grazed or cut grass fuel conditions as recommended for general use during the summer fire season in southern Australia. [ABSTRACT FROM AUTHOR]

A severe outbreak of wildfire across the US Pacific Coast during August 2020 led to persistent fire activity through the end of summer. In late September, Fire Weather Outlooks predicted higher than usual fire activity into the winter in parts of California, with concomitant elevated fire danger in the Southeastern US. To help inform the regional and national allocation of firefighting personnel and equipment, we developed visualizations of resource use during recent late season, high-demand analogs. Our visualizations provided an overview of the crew, engine, dozer, aerial resource, and incident management team usage by geographic area. While these visualizations afforded information that managers needed to support their decisions regarding resource allocation, they also revealed a potentially significant gap between resource demand and late-season availability that is only likely to increase over time due to lengthening fire seasons. This gap highlights the need for the increased assessment of suppression resource acquisition and allocation systems that, to date, have been poorly studied. [ABSTRACT FROM AUTHOR]

We developed spatially explicit models of the daily probability of aircraft use in initial attack (IA) on a fire (hereafter the conditional models), and estimates of the unconditional probability of daily aircraft IA targets to support preparedness planning in the province of British Columbia, Canada, using a grid cell × day lasso-logistic framework. Novel aspects of our work include: (1) inclusion of an historical aircraft baseline covariate to account for missing or poorly estimated factors in our models; and of 2 day lead weather and Forest Fire Weather Index (FWI) covariates as proxies for fire potential trend, and (2) linking the conditional models of aircraft use in IA to models of daily fire occurrence to estimate the daily number of aircraft IA targets. The baseline risk of using an aircraft, population and road density were highly influential spatial covariates in both aircraft conditional models. The probability of sustained flaming, temperature, and FWI lead, and Sheltered Duff Moisture Code, temperature, and the Showalter Index were the three most influential meteorological variables in the conditional airtanker and helicopter IA models, respectively. We demonstrate the application of the models to portray the distribution of the expected number of daily aircraft IA targets. [ABSTRACT FROM AUTHOR]

Wildfire occurrence and behaviour are difficult to predict locally for the next day. In the present work, we propose relying on fire spread simulations to provide a fire danger index representative of the potential for fire spread that includes not only weather but also surrounding vegetation and orography. This is achieved using an artificial neural network emulator called DeepFire, trained based on simulated fire sizes. To determine how relevant this index can be in the assessment of next-day fire danger, the application of DeepFire to fire danger mapping using actual weather forecasts is studied. DeepFire forecasts for 13 fairly large fires that occurred in Corsica are analysed and compared with corresponding forecasts using another fire danger index used in operational conditions, highlighting the differences in terms of precision and the expected results of such predictions. The weather forecasts from which the weather inputs of DeepFire are determined have high spatial resolution and high frequency, which also applies to the fire danger predictions. Additionally, input uncertainty is propagated through DeepFire, resulting in ensembles of emulated fire size. Several approaches are proposed to analyse the results and provide fire danger maps and ratings using this new simulation-based prediction system. [ABSTRACT FROM AUTHOR]

As increasing wildfire activity puts pressure on wildland fire suppression resources both nationally and within the state of California, further development of programs and infrastructure that emphasize preventative fuels treatments, e.g. prescribed burning, is critical for mitigating the impacts of wildfire at large spatial scales. Among many factors that limit the use of prescribed fire, weather and fuel moisture conditions are among the most critical. We analyzed a 2-km gridded hourly surface weather dataset over a 23-yr period to explore the relationship between climatological trends and prescribed fire weather windows. Pairing this dataset with burn prescription parameters provided by experienced regional fire practitioners, we seek to identify the timing and extent of changes in weather-related opportunities for prescribed fire in two distinct geographic regions within California. We found an increasing trend in opportunities for prescribed fire use in Sonoma County, a representative coastal Mediterranean region of CA, and a decreasing trend in Plumas County, a montane region that extends through the Northern Sierra Nevada. Seasonally, we see more nuances—increased winter opportunities in both counties, as well as increased summer opportunities in Sonoma. Most notably, we see great variation spatially in the occurrence of suitable weather windows for prescribed burning. Fire management resource availability and air quality regulations further constrain burn windows. We observed a greater influence of these factors in Sonoma County vs. Plumas. Resource availability is the greatest constraint in the Summer and Fall, during wildfire season, and air quality regulations are a greater constraint in the Winter. Our findings provide information to decision-makers and regulators at the county and other government levels to more effectively support use of prescribed fire to achieve land management and fuels reduction goals. • Prescribed fire weather windows increased in the coastal area for the study period. • Prescribed fire weather windows decreased in the montane region for the study period. • Wintertime weather windows increased for both Plumas and Sonoma counties. • Resource availability and air quality regulations had a greater influence on prescribed burn windows in Sonoma County than in Plumas County. [ABSTRACT FROM AUTHOR]

Increased understanding of how mechanical thinning, prescribed burning, and wildfire affect subsequent wildfire severity is urgently needed as people and forests face a growing wildfire crisis. In response, we reviewed scientific literature for the US West and completed a meta-analysis that answered three questions: (1) How much do treatments reduce wildfire severity within treated areas? (2) How do the effects vary with treatment type, treatment age, and forest type? (3) How does fire weather moderate the effects of treatments? We found overwhelming evidence that mechanical thinning with prescribed burning, mechanical thinning with pile burning, and prescribed burning only are effective at reducing subsequent wildfire severity, resulting in reductions in severity between 62% and 72% relative to untreated areas. In comparison, thinning only was less effective – underscoring the importance of treating surface fuels when mitigating wildfire severity is the management goal. The efficacy of these treatments did not vary among forest types assessed in this study and was high across a range of fire weather conditions. Prior wildfire had more complex impacts on subsequent wildfire severity, which varied with forest type and initial wildfire severity. Across treatment types, we found that effectiveness of treatments declined over time, with the mean reduction in wildfire severity decreasing more than twofold when wildfire occurred greater than 10 years after initial treatment. Our meta-analysis provides up-to-date information on the extent to which active forest management reduces wildfire severity and facilitates better outcomes for people and forests during future wildfire events. • Forest treatments that reduce surface fuels decrease subsequent wildfire severity. • Thinning with prescribed burning was the most effective and persistent treatment. • Treatment efficacy for reducing wildfire severity declined for older treatments. • Prior low or moderate severity wildfire can reduce subsequent wildfire severity. [ABSTRACT FROM AUTHOR]

• Warmer, drier weather due to climate change increases the risk of large wildfires. • Unprecedently large wildfires broke out earlier than the usual forest fire season. • Wildfires increased PM 2.5 by more than 20 times and CO by 4–12 times more than usual. • Biomass burning aerosols have a high fraction of PM 1.0 , contributing 95.7 % to PM 2.5. • Climate change makes fire-prone conditions and causes more severe fires than before. In March 2022, three weeks earlier than the usual forest fire season, a wildfire of unprecedented scale broke out in South Korea, spreading rapidly over a large forest area and burning 22,477 hectares in two weeks. This event was likely related to climate change; however, the relevance of climate change in the occurrence of such large fire events is not yet clearly understood. In this study, we assessed how climate change affects the regional climate and the extent to which it enhances the potential risk of wildfires based on the analysis of long-term meteorological observation data from 1923 to 2022 and the calculation of fire weather indices (FWIs). Results showed that the climate regime has shifted from cold and wet to warm and dry winters, with this shift involving a 4 °C increase in temperature, an 8 % decrease in relative humidity, and a 17 mm decrease in precipitation. Dry winter weather has become increasingly severe, resulting in extreme drought in winter 2021 and early spring 2022, with the FWI calculations revealing great potential dangers from fires. However, no major fires were reported in 2021, which is attributable to a reduction in accidental ignition sources owing to the restrictions on human activity caused by the COVID-19 pandemic. This demonstrates the importance of managing artificial ignition. The 2022 wildfires produced substantial quantities of ultrafine aerosols, which consisted mainly of particles smaller than 1.0 µm. These particles have raised the level of air pollution by more than 20 times compared to before the fires. The CO concentrations were also found to be 4 to 12 times higher than the typical local background concentrations. This study highlights that climate change may make forests more vulnerable to fire in temperate and mid-latitude monsoon-affected regions, where large-scale wildfires were not previously a concern. [Display omitted] [ABSTRACT FROM AUTHOR]

Fuel and wildfire management decisions related to fuel break construction, maintenance, and use in fire suppression suffer from limited information on fuel break success rates and drivers of effectiveness. We built a dataset of fuel break encounters with recent large wildfires in Southern California and their associated biophysical, suppression, weather, and fire behavior characteristics to develop statistical models of fuel break effectiveness with boosted regression. Our results suggest that the dominant influences on fuel break effectiveness are suppression, weather, and fire behavior. Variables related to fuel break placement, design, and maintenance were less important but aligned with manager expectations for higher success with wider and better maintained fuel breaks, and prior research findings that fuel break success increases with accessibility. Fuel breaks also held more often if burned by a wildfire during the previous decade, supporting the idea that fuel breaks may be most effective if combined with broader fuel reduction efforts.

Recent years have seen unprecedented fire activity at high latitudes and knowledge of future wildfire risk is key for adaptation and risk management. Here we present a systematic characterization of the probability distributions (PDFs) of fire weather conditions, and how it arises from underlying meteorological drivers of change, in five boreal forest regions, for pre-industrial conditions and different global warming levels. Using initial condition ensembles from two global climate models to characterize regional variability, we quantify the PDFs of daily maximum surface air temperature (SAT _max ), precipitation, wind, and minimum relative humidity (RH _min ), and their evolution with global temperature. The resulting aggregate change in fire risk is quantified using the Canadian Fire Weather Index (FWI). In all regions we find increases in both means and upper tails of the FWI distribution, and a widening suggesting increased variability. The main underlying drivers are the projected increase in mean daily SAT _max and decline in RH _min , marked already at +1 and +2 °C global warming. The largest changes occur in Canada, where we estimate a doubling of days with moderate-or-higher FWI between +1 °C and +4 °C global warming, and the smallest in Alaska. While both models exhibit the same general features of change with warming, differences in magnitude of the shifts exist, particularly for RH _min , where the bias compared to reanalysis is also largest. Given its importance for the FWI, RH _min evolution is identified as an area in need of further research. While occurrence and severity of wildfires ultimately depend also on factors such as ignition and fuel, we show how improved knowledge of meteorological conditions conducive to high wildfire risk, already changing across the high latitudes, can be used as a first indication of near-term changes. Our results confirm that continued global warming can rapidly push boreal forest regions into increasingly unfamiliar fire weather regimes.