There is a newer version of the record available.

Published May 10, 2026 | Version v1.0.0

Enhanced BoLtFire Dataset (Consistent drivers of lightning-ignited wildfires across global boreal forests)

  • 1. ROR icon Technical University of Munich
  • 2. ROR icon Natural Resources Canada
  • 3. ROR icon Earth Networks (United States)

Description


Overview:
The Enhanced BoltFire dataset is an extension of the BoLtFire dataset. It was designed to investigate the predictor variables influencing the ignition of Lightning Ignited Wildfires (LIW). The dataset contains 5,251 lightning pairs (LIW and NoLIW) from across the global boreal region, enriched with meteorological, fuel, and land cover data. Lightning characteristic data (e.g., polarity, multiplicity, duration, peak current) are available upon request from the ENTLN team.

Dataset:
FireID: Unique identifier for the fire (LIW and NonLIW versions). Original LIW from the BoLtFire database
LIWType: Type of event: LIW (Lightning Ignited Wildfire) or NonLIW
offset: Days relative to the lightning event (0 = day of event)
holdover: Days between lightning event and fire observation 
FireSize: Size of the fire event 
fire_type: Binary indicator: 1 (fire), 0 (no fire)
continent: North America or Eurasia
year: Year of the lightning event 
LC_Name: Land cover name (derived from MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m (MCD12Q1))
LCDN: Land cover number (derived from MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m (MCD12Q1))
EcoName: Ecoregion name (Olson et al., 2001)
NPP: Net Primary Production (MOD17A3HGF.061 Terra)
tp_mean: mean total precipitation (mm) for the 24-hour offset day (calculated from ERA5-Land)
t2m_mean: mean maximum 2m temperature (°C) for the 24-hour offset day (calculated from ERA5-Land)
ws_mean: mean maximum wind speed (m/s) for the 24-hour offset day (calculated per Pettinari & Chuvieco, 2017)
rh_mean: mean relative humidity (%) for the 24-hour offset day (calculated per Wanielista et al., 1997)

Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'Amico, J. A., Itoua, I., Strand, H. A., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., & Kassem, K. R. (2001). Terrestrial Ecoregions of the World: A New Map of Life on Earth. BioScience, 51(11), 933–938. https://doi.org/10.1641/0006-3568(2001)051[0933:TEOTWA]2.0.CO;2

Pettinari, M., & Chuvieco, E. (2017). Fire Behavior Simulation from Global Fuel and Climatic Information. Forests, 8(6), 179. https://doi.org/10.3390/f8060179

Wanielista, M. P., Kersten, R., & Ealgin, R. (1997). Hydrology: Water Quantity and Quality Control (2nd ed.). John Wiley & Sons.

 

Files

EnhancedBoLtFireDataset.csv

Files (42.3 MB)

Name Size
md5:5669be89fbe4dc68d31cb4a255c02939
42.3 MB Preview Download

Additional details

Dates

Available
2026-05-10

Software

Programming language
Python