Suchergebnisse

Abstract. Large wildfires across parts of France can cause devastating damage which
puts lives, infrastructure, and the natural ecosystem at risk. In the climate
change context, it is essential to better understand how these large
wildfires relate to weather and climate and how they might change in a warmer
world. Such projections rely on the development of a robust modeling
framework linking large wildfires to present-day atmospheric variability.
Drawing from a MODIS product and a gridded meteorological dataset, we derived
a suite of biophysical and fire danger indices and developed generalized
linear models simulating the probability of large wildfires (>100 ha) at
8 km spatial and daily temporal resolutions across the entire country over
the last two decades. The models were able to reproduce large-wildfire
activity across a range of spatial and temporal scales. Different
sensitivities to weather and climate were detected across different
environmental regions. Long-term drought was found to be a significant
predictor of large wildfires in flammability-limited systems such as the
Alpine and southwestern regions. In the Mediterranean, large wildfires were
found to be associated with both short-term fire weather conditions and
longer-term soil moisture deficits, collectively facilitating the occurrence
of large wildfires. Simulated probabilities on days with large wildfires were
on average 2–3 times higher than normal with respect to the mean seasonal
cycle, highlighting the key role of atmospheric variability in wildfire
spread. The model has wide applications, including improving our
understanding of the drivers of large wildfires over the historical period
and providing a basis on which to estimate future changes to large wildfires
from climate scenarios.