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Discussion papers
https://doi.org/10.5194/nhess-2018-283
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2018-283
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 24 Oct 2018

Research article | 24 Oct 2018

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).

Simulating the effects of weather and climate on large wildfires in France

Renaud Barbero, Thomas Curt, Anne Ganteaume, Eric Maillé, Marielle Jappiot, and Adeline Bellet Renaud Barbero et al.
  • Irstea, Mediterranean Ecosystems and Risks, Aix-en-Provence, France

Abstract. Large wildfires across parts of France can cause devastating damages which put lives, infrastructures, and natural ecosystem at risk. One of the most challenging questions in the climate change context is 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 wildfires to 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 (>100ha) at 8-km spatial and daily temporal resolutions across the entire country over the MODIS period. The models were skillful in reproducing the main spatio-temporal patterns of large wildfires 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 Southwest 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 during the day of large wildfires were on average 2–3 times higher than normal with respect to the mean seasonal cycle. The model has wide applications, including improving our understanding of the drivers of large wildfires over the historical period and providing a basis to estimate future changes to large wildfire from climate scenarios.

Renaud Barbero et al.
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Renaud Barbero et al.
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We developed statistical models simulating the probability of large wildfires in France from the climate forcing. The models were able to reproduce both spatial and temporal variability in large wildfires across different environmental regions. The models have wide applications, including improving our understanding of the drivers of large wildfires over the historical period and providing a basis for simulations of future large wildfires from climate projections.
We developed statistical models simulating the probability of large wildfires in France from the...
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