Javascript must be enabled to continue!
Global attribution of anthropogenic and lightning fires
View through CrossRef
<p>Fires can have anthropogenic or lightning origins. The spatiotemporal niches of anthropogenic and lightning fires are different. Lightning fires usually occur during a discrete apex in seasonal lightning occurrence. Conversely, anthropogenic fires have an expanded temporal niche and occur throughout the year. In addition, lightning and anthropogenic fires occupy different parts of the landscape. While human accessibility is a key determinant of anthropogenic ignitions, lightning ignitions prevail in remote landscapes.</p><p>We used these differing temporal and spatial niches between anthropogenic and lightning fires to construct random forest models that attribute causes, lightning vs. anthropogenic, to global fire activity. We built two separate models. The first model predicts the fraction of lightning fires, whereas the second model predicts the fraction of burned area from lightning. Our model ingests two geospatial predictor variables that quantify the differences between the temporal and spatial niches of lightning and anthropogenic fires. The first predictor is the seasonal correlation between lightning and burned area. The second predictor is the fraction of low impact land. These fire cause predictors capture 47 % of the spatial variability in ignition cause, and 40 % of the spatial variability in burned area cause, compared to reference data from six different parts of the world.</p><p>Our global fire cause attribution contrasts savannas and agricultural lands with human-dominated fire regimes from temperate and boreal forests with lightning-dominated fire regimes. Our global fire cause attribution can be implemented in fire and Earth system models to further optimize projections of future fire activity under changing socio-economic and climatological conditions.</p>
Title: Global attribution of anthropogenic and lightning fires
Description:
<p>Fires can have anthropogenic or lightning origins.
The spatiotemporal niches of anthropogenic and lightning fires are different.
Lightning fires usually occur during a discrete apex in seasonal lightning occurrence.
Conversely, anthropogenic fires have an expanded temporal niche and occur throughout the year.
In addition, lightning and anthropogenic fires occupy different parts of the landscape.
While human accessibility is a key determinant of anthropogenic ignitions, lightning ignitions prevail in remote landscapes.
</p><p>We used these differing temporal and spatial niches between anthropogenic and lightning fires to construct random forest models that attribute causes, lightning vs.
anthropogenic, to global fire activity.
We built two separate models.
The first model predicts the fraction of lightning fires, whereas the second model predicts the fraction of burned area from lightning.
Our model ingests two geospatial predictor variables that quantify the differences between the temporal and spatial niches of lightning and anthropogenic fires.
The first predictor is the seasonal correlation between lightning and burned area.
The second predictor is the fraction of low impact land.
These fire cause predictors capture 47 % of the spatial variability in ignition cause, and 40 % of the spatial variability in burned area cause, compared to reference data from six different parts of the world.
</p><p>Our global fire cause attribution contrasts savannas and agricultural lands with human-dominated fire regimes from temperate and boreal forests with lightning-dominated fire regimes.
Our global fire cause attribution can be implemented in fire and Earth system models to further optimize projections of future fire activity under changing socio-economic and climatological conditions.
</p>.
Related Results
Long-range Lightning Interferometry (A Simulation Study)
Long-range Lightning Interferometry (A Simulation Study)
Traditional long-range lightning detection and location networks use Time-of-Arrival (TOA) differences, and a single timestamp to locate lightning events. For long propagation dist...
Lightning Activity in China and Its Optical Characteristics Observed by Geostationary Satellite
Lightning Activity in China and Its Optical Characteristics Observed by Geostationary Satellite
Lightning now has designated as an Essential Climate Variable in the Global Climate Observing System to understand the climate change. Lightning detection from geostationary satell...
Influence of Aerosols on Lightning Activities in Java Island, Indonesia
Influence of Aerosols on Lightning Activities in Java Island, Indonesia
Lightning is one of the natural disasters that cause significant financial losses and even fatalities. Therefore, it is necessary to understand the characteristics of lightning and...
Characteristics of cloud-to-ground lightning (CG) and differences between +CG and −CG strokes in China regarding the China National Lightning Detection Network
Characteristics of cloud-to-ground lightning (CG) and differences between +CG and −CG strokes in China regarding the China National Lightning Detection Network
Abstract. A lightning location system consisting of multiple ground-based stations is an effective means of lightning observation. The dataset from CNLDN (China National Lightning ...
Lightning Activities near the Red Sea: Effects of Aerosols Morphology and Local Meteorology
Lightning Activities near the Red Sea: Effects of Aerosols Morphology and Local Meteorology
Lightning activity is one of the global natural hazards that pose significant risks to human life and numerous aspects of society's technological infrastructure. Understanding the ...
Experimental Study on Lightning Attachment Manner of the ice-melting Wind Turbine Blades
Experimental Study on Lightning Attachment Manner of the ice-melting Wind Turbine Blades
Wind turbines often suffer from lightning strikes, iceing and other
disasters. The installation of an electrothermal ice-melting device on
the blade can effectively remove icing, b...
Influence of Climatic Factors on Lightning Fires in the Primeval Forest Region of the Northern Daxing’an Mountains, China
Influence of Climatic Factors on Lightning Fires in the Primeval Forest Region of the Northern Daxing’an Mountains, China
Forest fires lead to permafrost degradation and localized drought, and regional droughts increase the probability of forest fires, leading to a positive feedback loop between clima...
Lightning Activity Observed by the FengYun-4A Lightning Mapping Imager
Lightning Activity Observed by the FengYun-4A Lightning Mapping Imager
The Lightning Mapping Imager (LMI) onboard the geostationary meteorological satelliteFengYun-4A (FY-4A) detects both intra-cloud (IC) and cloud-to-ground (CG) lightning continuousl...

