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

<p>We will present approaches to modeling wildfire dynamics using the IIASA&#8217;s wild<strong>F</strong>ire c<strong>L</strong>imate impacts and&#160;<strong>A</strong>daptation&#160;<strong>M</strong>odel (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.&#160; 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 Ni&#241;o 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.</p>