Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (4)

Search Parameters:
Keywords = holdover fires

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
5 pages, 2959 KiB  
Proceeding Paper
Lightning-Caused Wildfires: The Case of Mount Mainalo, Arcadia, Greece
by Miltiadis Athanasiou, Panagiotis Nastos, Ioannis Kouretas and Athanasios Karadimitris
Environ. Sci. Proc. 2023, 26(1), 114; https://doi.org/10.3390/environsciproc2023026114 - 29 Aug 2023
Viewed by 1327
Abstract
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, [...] Read more.
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
Show Figures

Figure 1

17 pages, 5214 KiB  
Article
ERA5 Reanalysis of Environments Conducive to Lightning-Ignited Wildfires in Catalonia
by Nicolau Pineda and Oriol Rodríguez
Atmosphere 2023, 14(6), 936; https://doi.org/10.3390/atmos14060936 - 26 May 2023
Cited by 4 | Viewed by 3270
Abstract
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 [...] Read more.
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
(This article belongs to the Special Issue Atmospheric Electricity and Fire in a Changing Climate)
Show Figures

Figure 1

19 pages, 6862 KiB  
Article
Flash Characteristics and Precipitation Metrics of Western U.S. Lightning-Initiated Wildfires from 2017
by Brittany R. MacNamara, Christopher J. Schultz and Henry E. Fuelberg
Fire 2020, 3(1), 5; https://doi.org/10.3390/fire3010005 - 26 Feb 2020
Cited by 14 | Viewed by 3576
Abstract
This study examines 95 lightning-initiated wildfires and 1170 lightning flashes in the western United States between May and October 2017 to characterize lightning and precipitation rates and totals near the time of ignition. Eighty-nine percent of the wildfires examined were initiated by negative [...] Read more.
This study examines 95 lightning-initiated wildfires and 1170 lightning flashes in the western United States between May and October 2017 to characterize lightning and precipitation rates and totals near the time of ignition. Eighty-nine percent of the wildfires examined were initiated by negative cloud-to-ground (CG) lightning flashes, and 66% of those fire starts were due to single stroke flashes. Average flash density at the fire locations was 1.1 fl km−2. The fire start locations were a median distance of 5.3 km away from the maximum flash and stroke densities in the 400 km2 area surrounding the fire start location. Fire start locations were observed to have a smaller 2-min precipitation rate and 24-h total rainfall than non-fire start locations. The median 2-min rainfall rate for fire-starting (FS) flash locations was 1.7 mm h−1, while the median for non-fire-starting (NFS) flash locations was 4.7 mm h−1. The median total 24-h precipitation value for FS flash locations was 2.9 mm, while NFS flash locations exhibited a median of 8.6 mm. Wilcoxon–Mann–Whitney rank sum testing revealed statistically different Z-Scores/p-values for the FS and NFS flash populations. These values were −5.578/1.21 × 10−8 and −7.176/3.58 × 10−13 for the 2-min precipitation rate and 24-h total rainfall, respectively. Additionally, 24-h and 2-min precipitation rates were statistically significantly greater for holdover versus non-holdover fire events. The median distances between the fire start location and greatest 2-min precipitation rate and greatest 24-h precipitation total were 7.4 and 10.1 km, respectively. Full article
Show Figures

Figure 1

15 pages, 2727 KiB  
Article
Spatial, Temporal and Electrical Characteristics of Lightning in Reported Lightning-Initiated Wildfire Events
by Christopher J. Schultz, Nicholas J. Nauslar, J. Brent Wachter, Christopher R. Hain and Jordan R. Bell
Fire 2019, 2(2), 18; https://doi.org/10.3390/fire2020018 - 3 Apr 2019
Cited by 43 | Viewed by 9957
Abstract
Analysis was performed to determine whether a lightning flash could be associated with every reported lightning-initiated wildfire that grew to at least 4 km2. In total, 905 lightning-initiated wildfires within the Continental United States (CONUS) between 2012 and 2015 were analyzed. [...] Read more.
Analysis was performed to determine whether a lightning flash could be associated with every reported lightning-initiated wildfire that grew to at least 4 km2. In total, 905 lightning-initiated wildfires within the Continental United States (CONUS) between 2012 and 2015 were analyzed. Fixed and fire radius search methods showed that 81–88% of wildfires had a corresponding lightning flash within a 14 day period prior to the report date. The two methods showed that 52–60% of lightning-initiated wildfires were reported on the same day as the closest lightning flash. The fire radius method indicated the most promising spatial results, where the median distance between the closest lightning and the wildfire start location was 0.83 km, followed by a 75th percentile of 1.6 km and a 95th percentile of 5.86 km. Ninety percent of the closest lightning flashes to wildfires were negative polarity. Maximum flash densities were less than 0.41 flashes km2 for the 24 h period at the fire start location. The majority of lightning-initiated holdover events were observed in the Western CONUS, with a peak density in north-central Idaho. A twelve day holdover event in New Mexico was also discussed, outlining the opportunities and limitations of using lightning data to characterize wildfires. Full article
Show Figures

Figure 1

Back to TopTop