EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Modeling wildfire dynamics and future projections under climate change scenarios: the FLAM approach 

Andrey Krasovskiy1, Shelby Corning1, Esther Boere1, Nikolay Khabarov1, Reinis Cimdins2, and Florian Kraxner1
Andrey Krasovskiy et al.
  • 1International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria (
  • 2University of Eastern Finland, Joensuu, Finland (

We will present approaches to modeling wildfire dynamics using the IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM). FLAM operates with a daily time step and uses mechanistic algorithms to parametrize the impacts of climate, human activities, and fuel availability on wildfire probabilities, frequencies, and burned areas. Validation on historical data and future projections under climate change scenarios will be discussed at various scales and resolutions.  We will present results for the following case-studies: (i) projections of global burned areas driven by climate change scenarios until 2100; (ii) modeling burned areas and adaptation options in Europe; (iii) modeling burned areas and their feedback to land-use change in Indonesia with a particular emphasis on extreme fires due the impacts of El Niño southern oscillation using historical data and the delta approach for future scenarios; (iv) regional variability and driving forces behind forest fires in Sweden. Our results support international analyses that, irrespective of changes in management, it is evident that climate change is very likely to increase the frequency and impact of wildland fires in the coming decades.

How to cite: Krasovskiy, A., Corning, S., Boere, E., Khabarov, N., Cimdins, R., and Kraxner, F.: Modeling wildfire dynamics and future projections under climate change scenarios: the FLAM approach , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16190,, 2023.