Process-based modelling of fire extremes via large ensemble climate forcing

• Applicant: Dr. Andreia Filipa Silva Ribeiro
• Subject Area: Atmospheric Science
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 530175554

Fire is a major control of the Earth system, involving a complex interplay between vegetation, climate, and socioeconomic drivers, across multiple spatial-temporal scales and feedback chains. This complexity limits our ability to project future fire activity under climate change, particularly the more high-impact low-likelihood fire events. In spite of these limitations, adapting to unprecedent and very hard to predict wildfire outbreaks is becoming a reality worldwide, and of major concern is that increasing global warming is expected to increase extreme fire behavior. To tackle these critical challenges, this project proposes a novel use of a state-of-the-art fire-enabled dynamic global vegetation model (DGVM) via large ensemble climate-impact modelling, to explore a number of pressing research questions regarding extreme fires and climate change. To date, most of research have focused on modelling large ensemble fire-prone weather conditions only, and an impact-centric approach is proposed here. The key strategy of this project is to use output fire simulations from the LPJmL-SPITFIRE vegetation - fire model, forced using inputs from large ensemble climate simulations, which translates in large ensemble fire simulations. Firstly, building on the produced large ensemble fire simulations, this project aims to provide robust future projections of the most extreme fire events for different socioeconomic scenarios, in terms of burned area and fire emissions. Secondly, the proposed large ensemble climate-impact modelling will allow to identify the multiple climate drivers behind very long and extensive fires in a backward assessment. In particular, it is not clear yet if extreme fire seasons across distanced regions have common climate stressors, and the extent to which climate change could exacerbate these effects remains uncertain. The answer to these research questions is of outmost importance to better predict future fire extremes and take-action against its ultimate impacts. Via the proposed large ensemble fire modelling approach, this project aims to be a proof-of-concept application of novel uses of process-based fire modelling and climate narratives to contribute to better understand and constrain extreme wildfires today and to provide guidance for risk management strategies for the future.

• DFG Programme: WBP Position