Project: Improving PREdictability of circumboREAL forest fire activity and its ecological and socio-economic impacts through multi-proxy data comparisons

Duration 01/06/2016 - 31/05/2020
Project Topic The ability to predict forest fire activity at monthly, seasonal, and above-annual time scales is critical to mitigate its impacts, including fire-driven dynamics of ecosystem and socio-economic services. Fire is the primary driving factor of the ecosystemdynamics in the boreal forest, directly affecting global carbon balance and atmospheric concentrations of the trace gases including carbon dioxide. Resilience of ocean-atmosphere system provides potential for advanced detection of upcoming fire season intensity. There is a strong potential in using a large body of paleo-and dendrochronological reconstructions to improve predictability of weather extremes such periods of regionally increased fire activity. We propose that joint analyses of historical fire proxies (fire scars and charcoal in the lake sediments) with independently obtained proxies of climate variability and vegetation cover should contribute towards better knowledge of modern climate drivers of forest fires and predictability of fire activityat multiple temporal scales. In this project we will identify climatic drivers controlling boreal fire activity and its predictability at monthly, seasonal and annual timescales by relying on analyses of multiple proxies of modern and historic fire activity, and climate-ocean variability. We will also provide monthly to century-scale predictions of future fire activity and to translate these into impacts on ecosystem services and metrics of socio-economic performance. We argue that capitalizing on multi-proxy data comparisons should improve predictability of fire activity via (a) a large overlap between climate and fire proxies, which dramatically extends the period covered by instrumental observations and improves robustness of analyses, (b) a more realistic translation of fire hazard metrics into actual fire activity, and (c) a better separation of low vs. high frequency variability in the fire activity, an important aspect in the modeling of the future trends in fire activity.
Project Results
(after finalisation)
Website visit project website
Network JPI Climate
Call Call for Climate Services Collaborative Research action on Climate Predictability and Inter-regional Linkages

Project partner

Number Name Role Country
1 Swedish University of Agricultural Sciences Coordinator Sweden
2 University of Montpellier II Partner France
3 Université du Québec à Montréal Partner Canada
4 Norwegian Inst. for Nature Research Partner Norway
5 University of Science and Technology of China Partner China
6 Royal Netherlands Meteorological Institute Partner Netherlands