Cloud‐to‐ground lightning and near‐surface fire weather control wildfire occurrence in Arctic tundra

Abstract. Increasing drought conditions under global warming are expected to alter the frequency and distribution of large, high intensity wildfires. Yet, little is known regarding how it will affect fire weather and translate into wildfire behaviour. Here, we analysed the climatology of extreme wildfires that occurred during the exceptionally dry summers of 2003 and 2016 in Mediterranean France. We identified two distinct shifts in fire climatology towards fire weather spaces that had not been explored before, and which result from specific interactions between the types of drought and the types of fire. In 2016, a long-lasting press drought intensified wind-driven fires. In 2003, a hot drought combining a heatwave with a press drought intensified heat-driven fires. Our findings highlight that increasing drought conditions projected by climate change scenarios might affect the dryness of fuel compartments and create several new generations of wildfire overwhelming fire suppression capacities.

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Evolution of a pyrocumulonimbus event associated with an extreme wildfire in Tasmania, Australia

Natural Hazards and Earth System Science ◽

10.5194/nhess-20-1497-2020 ◽

2020 ◽

Vol 20 (5) ◽

pp. 1497-1511 ◽

Cited By ~ 2

Author(s):

Mercy N. Ndalila ◽

Grant J. Williamson ◽

Paul Fox-Hughes ◽

Jason Sharples ◽

David M. J. S. Bowman

Keyword(s):

Weather Forecasting ◽

Fire Severity ◽

Atmospheric Stability ◽

Lower Atmosphere ◽

Fire Weather ◽

Natural Ecosystems ◽

Near Surface ◽

South Eastern ◽

Crown Defoliation ◽

Extreme Fire

Abstract. Extreme fires have substantial adverse effects on society and natural ecosystems. Such events can be associated with the intense coupling of fire behaviour with the atmosphere, resulting in extreme fire characteristics such as pyrocumulonimbus cloud (pyroCb) development. Concern that anthropogenic climate change is increasing the occurrence of pyroCbs globally is driving more focused research into these meteorological phenomena. Using 6 min scans from a nearby weather radar, we describe the development of a pyroCb during the afternoon of 4 January 2013 above the Forcett–Dunalley fire in south-eastern Tasmania. We relate storm development to (1) near-surface weather using the McArthur forest fire danger index (FFDI) and the C-Haines index, the latter of which is a measure of the vertical atmospheric stability and dryness, both derived from gridded weather reanalysis for Tasmania (BARRA-TA); and (2) a chronosequence of fire severity derived from remote sensing. We show that the pyroCb rapidly developed over a 24 min period on the afternoon of 4 January, with the cloud top reaching a height of 15 km. The pyroCb was associated with a highly unstable lower atmosphere (C-Haines value of 10–11) and severe–marginally extreme (FFDI 60–75) near-surface fire weather, and it formed over an area of forest that was severely burned (total crown defoliation). We use spatial patterns of elevated fire weather in Tasmania and fire weather during major runs of large wildfires in Tasmania for the period from 2007 to 2016 to geographically and historically contextualise this pyroCb event. Although the Forcett–Dunalley fire is the only known record of a pyroCb in Tasmania, our results show that eastern and south-eastern Tasmania are prone to the conjunction of high FFDI and C-Haines values that have been associated with pyroCb development. Our findings have implications for fire weather forecasting and wildfire management, and they highlight the vulnerability of south-east Tasmania to extreme fire events.

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Climatic Variability of Near-Surface Turbulent Kinetic Energy over the United States: Implications for Fire-Weather Predictions

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-0226.1 ◽

2013 ◽

Vol 52 (4) ◽

pp. 753-772 ◽

Cited By ~ 4

Author(s):

Warren E. Heilman ◽

Xindi Bian

Keyword(s):

United States ◽

Kinetic Energy ◽

Turbulent Kinetic Energy ◽

Atmospheric Turbulence ◽

Climatic Variability ◽

Fire Behavior ◽

The United States ◽

Spatial And Temporal Variability ◽

Fire Weather ◽

Near Surface

AbstractRecent research suggests that high levels of ambient near-surface atmospheric turbulence are often associated with rapid and sometimes erratic wildland fire spread that may eventually lead to large burn areas. Previous research has also examined the feasibility of using near-surface atmospheric turbulent kinetic energy (TKEs) alone or in combination with the Haines index (HI) as an additional indicator of anomalous atmospheric conditions conducive to erratic or extreme fire behavior. However, the application of TKEs-based indices for operational fire-weather predictions in the United States on a regional or national basis first requires a climatic assessment of the spatial and temporal patterns of the indices that can then be used for testing their operational effectiveness. This study provides an initial examination of some of the spatial and temporal variability patterns across the United States of TKEs and the product of HI and TKEs (HITKEs) using data from the North American Regional Reanalysis dataset covering the 1979–2008 period. The analyses suggest that there are regional differences in the behavior of these indices and that regionally dependent threshold values for TKEs and HITKEs may be needed for their potential use as operational indicators of anomalous atmospheric turbulence conditions conducive to erratic fire behavior. The analyses also indicate that broad areas within the northeastern, southeastern, and southwestern regions of the United States have experienced statistically significant positive trends in TKEs and HITKEs values over the 1979–2008 period, with the most substantial increases in values occurring over the 1994–2008 period.

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Lightning-induced high temperature and pressure microstructures in surface and subsurface fulgurites

Scientific Reports ◽

10.1038/s41598-021-01559-x ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Li-Wei Kuo ◽

Steven A. F. Smith ◽

Chien-Chih Chen ◽

Ching-Shun Ku ◽

Ching-Yu Chiang ◽

...

Keyword(s):

High Pressure ◽

High Temperature ◽

Reference Sample ◽

Near Surface ◽

Landing Point ◽

High Pressure Metamorphism ◽

High Temperature And Pressure ◽

Cloud To Ground Lightning ◽

Temperature And Pressure ◽

First Time

AbstractCloud-to-ground lightning causes both high-temperature and high-pressure metamorphism of rocks, forming rock fulgurite. We demonstrate that a range of microstructural features indicative of high temperatures and pressures can form in fulgurites at the surface and in fractures up to several meters below the surface. In comparison to a granite reference sample collected from a borehole at a depth of 138 m, microstructures in both the surface and fracture fulgurite are characterized by: (i) the presence of glass, (ii) a phase transformation in K-feldspar with the presence of exsolution lamellae of plagioclase, and (iii) high residual stresses up to 1.5 GPa. Since this is the first time that fracture-related fulgurite has been described, we also carried out a 1-D numerical model to investigate the processes by which these can form. The model shows that the electric current density in fractures up to 40 m from the landing point can be as high as that on the surface, providing an explanation for the occurrence of fracture-related fulgurites. Our work broadens the near-surface environments in which rock fulgurite has been reported, and provides a detailed description of microstructures that can be compared to those formed during other types of extreme metamorphic events.

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A bias corrected WRF mesoscale fire weather dataset for Victoria, Australia 1972-2012

Journal of Southern Hemisphere Earth System Science ◽

10.1071/es16020 ◽

2016 ◽

Vol 66 (3) ◽

pp. 281

Author(s):

Timothy Brown ◽

Graham Mills ◽

Sarah Harris ◽

Domagoj Podnar ◽

Hauss Reinbold ◽

...

Keyword(s):

Wind Speed ◽

Relative Humidity ◽

Fire Danger ◽

Management Decision ◽

Fire Weather ◽

Near Surface ◽

Australian Water ◽

Hourly Temperature ◽

Extensive Evaluation ◽

Correction Technique

Climatology data of fire weather across the landscape can provide science-based evidence for informing strategic decisions to ameliorate the impacts (at times extreme) of bushfires on community socio-economic wellbeing and to sustain ecosystem health and functions. A long-term climatology requires spatial and temporal data that are consistent to represent the landscape in sufficient detail to be useful for fire weather studies and management purposes. To address this inhomogeneity problem for analyses of a variety of fire weather interests and to provide a dataset for management decision-support, a homogeneous 41-year (1972-2012), hourly interval, 4 km gridded climate dataset for Victoria has been generated using a combination of mesoscale modelling, global reanalysis data, surface observations, and historic observed rainfall analyses. Hourly near-surface forecast fields were combined with Drought Factor (DF) fields calculated from the Australian Water Availability Project (AWAP) rainfall analyses to generate fields of hourly fire danger indices for each hour of the 41-year period. A quantile mapping (QM) bias correction technique utilizing available observations during 1996-2012 was used to ameliorate any model biases in wind speed, temperature and relative humidity. Extensive evaluation was undertaken including both quantitative and case study qualitative assessments. The final dataset includes 4-km surface hourly temperature, relative humidity, wind speed, wind direction, Forest Fire Danger Index (FFDI), and daily DF and Keetch-Byram Drought Index (KBDI), and a 32-level full three-dimensional volume atmosphere.

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Regional variation in fire weather controls the reported occurrence of Scottish wildfires

PeerJ ◽

10.7717/peerj.2649 ◽

2016 ◽

Vol 4 ◽

pp. e2649 ◽

Cited By ~ 5

Author(s):

G. Matt Davies ◽

Colin J. Legg

Keyword(s):

Habitat Management ◽

Fire Risk ◽

Management Tool ◽

Fire Weather ◽

Fuel Moisture ◽

Fire Weather Index ◽

Mahalanobis Distances ◽

Wildfire Occurrence ◽

Fire Activity ◽

In Fire

Fire is widely used as a traditional habitat management tool in Scotland, but wildfires pose a significant and growing threat. The financial costs of fighting wildfires are significant and severe wildfires can have substantial environmental impacts. Due to the intermittent occurrence of severe fire seasons, Scotland, and the UK as a whole, remain somewhat unprepared. Scotland currently lacks any form of Fire Danger Rating system that could inform managers and the Fire and Rescue Services (FRS) of periods when there is a risk of increased of fire activity. We aimed evaluate the potential to use outputs from the Canadian Fire Weather Index system (FWI system) to forecast periods of increased fire risk and the potential for ignitions to turn into large wildfires. We collated four and a half years of wildfire data from the Scottish FRS and examined patterns in wildfire occurrence within different regions, seasons, between urban and rural locations and according to FWI system outputs. We used a variety of techniques, including Mahalanobis distances, percentile analysis and Thiel-Sen regression, to scope the best performing FWI system codes and indices. Logistic regression showed significant differences in fire activity between regions, seasons and between urban and rural locations. The Fine Fuel Moisture Code and the Initial Spread Index did a tolerable job of modelling the probability of fire occurrence but further research on fuel moisture dynamics may provide substantial improvements. Overall our results suggest it would be prudent to ready resources and avoid managed burning when FFMC > 75 and/or ISI > 2.

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Development of a Fire Weather Index Using Meteorological Observations within the Northeast United States

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-15-0046.1 ◽

2016 ◽

Vol 55 (2) ◽

pp. 389-402 ◽

Cited By ~ 5

Author(s):

Michael J. Erickson ◽

Joseph J. Charney ◽

Brian A. Colle

Keyword(s):

Logistic Regression ◽

Wind Speed ◽

Relative Humidity ◽

Logistic Regression Model ◽

Daily Maximum ◽

Fire Weather ◽

Weather Index ◽

Fire Weather Index ◽

Wildfire Occurrence ◽

Binomial Logistic Regression

AbstractA fire weather index (FWI) is developed using wildfire occurrence data and Automated Surface Observing System weather observations within a subregion of the northeastern United States (NEUS) from 1999 to 2008. Average values of several meteorological variables, including near-surface temperature, relative humidity, dewpoint, wind speed, and cumulative daily precipitation, are compared on observed wildfire days with their climatological average (“climatology”) using a bootstrap resampling approach. Average daily minimum relative humidity is significantly lower than climatology on wildfire occurrence days, and average daily maximum temperature and average daily maximum wind speed are slightly higher on wildfire occurrence days. Using the potentially important weather variables (relative humidity, temperature, and wind speed) as inputs, different formulations of a binomial logistic regression model are tested to assess the potential of these atmospheric variables for diagnosing the probability of wildfire occurrence. The FWI is defined using probabilistic output from the preferred binomial logistic regression configuration. Relative humidity and temperature are the only significant predictors in the binomial logistic regression. The binomial logistic regression model is reliable and has more probabilistic skill than climatology using an independent verification dataset. Using the binomial logistic regression output probabilities, an FWI is developed ranging from 0 (minimum potential) to 3 (high potential) and is verified independently for two separate subdomains within the NEUS. The climatology of the FWI reproduces observed fire occurrence probabilities between 1999 and 2008 over a subdomain of the NEUS.

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Forcing factors of cloud-to-ground lightning over Iberia: regional-scale assessments

Natural Hazards and Earth System Science ◽

10.5194/nhess-13-1745-2013 ◽

2013 ◽

Vol 13 (7) ◽

pp. 1745-1758 ◽

Cited By ~ 19

Author(s):

J. A. Santos ◽

M. A. Reis ◽

F. De Pablo ◽

L. Rivas-Soriano ◽

S. M. Leite

Keyword(s):

Regional Scale ◽

Convective Available Potential Energy ◽

High Elevation ◽

Climatic Conditions ◽

Late Spring ◽

Near Surface ◽

Air Temperatures ◽

Mediterranean Regions ◽

Cloud To Ground Lightning ◽

Current Polarity

Abstract. Cloud-to-ground lightning in a sector covering the Iberian Peninsula, the Balearic Islands and nearby seas (36–44° N, 10° W–5° E) is analysed in the period from 2003 to 2009 (7 yr). Two Iberian lightning detection networks, composed of 18 sensors over Portugal and Spain, are combined for the first time in the present study. The selected characteristics are cloud-to-ground flashes (CGFs), first stroke peak current, polarity and multiplicity (number of strokes in a given flash). This study examines the temporal (on hourly, monthly and seasonal timescales) and spatial variability of CGFs. The influence of five forcing factors on lightning (elevation, lifted index, convective available potential energy and daily minimum and maximum near-surface air temperatures) over the Iberian sector is also assessed. For regional-scale assessments, six subsectors with different climatic conditions were analysed separately. Despite important regional differences, the strongest lightning activity occurs from late spring to early autumn, and mostly in the afternoon. Furthermore, CGFs are mainly located over high-elevation areas in late spring to summer, while they tend to occur over the sea in autumn. The results suggest that (1) orographically forced thunderstorms over mountainous areas, mostly from May to September, (2) tropospheric buoyancy forcing over western-central and northern regions in summer and over the Mediterranean regions in autumn, and (3) near-surface thermal contrasts from October to February largely control the location of lightning in Iberia. There is no evidence of different forcings by polarity. A clear correspondence between summertime precipitation patterns and CGFs is also found.

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Evaluation and Postprocessing of Ensemble Fire Weather Predictions over the Northeast United States

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-17-0180.1 ◽

2018 ◽

Vol 57 (5) ◽

pp. 1135-1153 ◽

Cited By ~ 2

Author(s):

Michael J. Erickson ◽

Brian A. Colle ◽

Joseph J. Charney

Keyword(s):

United States ◽

Bias Correction ◽

Specific Humidity ◽

Surface Model ◽

Fire Weather ◽

Near Surface ◽

Weather Regimes ◽

Mean Error ◽

Synoptic Weather ◽

Ensemble Mean

AbstractThe Short-Range Ensemble Forecast (SREF) system is verified and bias corrected for fire weather days (FWDs) defined as having an elevated probability of wildfire occurrence using a statistical Fire Weather Index (FWI) over a subdomain of the northeastern United States (NEUS) between 2007 and 2014. The SREF is compared to the Rapid Update Cycle and Rapid Refresh analyses for temperature, relative humidity, specific humidity, and the FWI. An additive bias correction is employed using the most recent previous 14 days [sequential bias correction (SBC)] and the most recent previous 14 FWDs [conditional bias correction (CBC)]. Synoptic weather regimes on FWDs are established using cluster analysis (CA) on North American Regional Reanalysis sea level pressure, 850-hPa temperature, 500-hPa temperature, and 500-hPa geopotential height. SREF severely underpredicts FWI (by two indices at FWI = 3) on FWDs, which is partially corrected using SBC and largely corrected with CBC. FWI underprediction is associated with a cool (ensemble mean error of −1.8 K) and wet near-surface model bias (ensemble mean error of 0.46 g kg−1) that decreases to near zero above 800 hPa. Although CBC improves reliability and Brier skill scores on FWDs, ensemble FWI values exhibit underdispersion. CA reveals three synoptic weather regimes on FWDs, with the largest cool and wet biases associated with a departing surface low pressure system. These results suggest the potential benefit of an operational analog bias correction on FWDs. Furthermore, CA may help elucidate model error during certain synoptic weather regimes.

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