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Theoretical and Applied Climatology

, Volume 131, Issue 1–2, pp 625–639 | Cite as

Climate change effects on wildland fire risk in the Northeastern and Great Lakes states predicted by a downscaled multi-model ensemble

  • Gaige Hunter Kerr
  • Arthur T. DeGaetano
  • Cathelijne R. Stoof
  • Daniel Ward
Original Paper

Abstract

This study is among the first to investigate wildland fire risk in the Northeastern and the Great Lakes states under a changing climate. We use a multi-model ensemble (MME) of regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) together with the Canadian Forest Fire Weather Index System (CFFWIS) to understand changes in wildland fire risk through differences between historical simulations and future projections. Our results are relatively homogeneous across the focus region and indicate modest increases in the magnitude of fire weather indices (FWIs) during northern hemisphere summer. The most pronounced changes occur in the date of the initialization of CFFWIS and peak of the wildland fire season, which in the future are trending earlier in the year, and in the significant increases in the length of high-risk episodes, defined by the number of consecutive days with FWIs above the current 95th percentile. Further analyses show that these changes are most closely linked to expected changes in the focus region’s temperature and precipitation. These findings relate to the current understanding of particulate matter vis-à-vis wildfires and have implications for human health and local and regional changes in radiative forcings. When considering current fire management strategies which could be challenged by increasing wildland fire risk, fire management agencies could adapt new strategies to improve awareness, prevention, and resilience to mitigate potential impacts to critical infrastructure and population.

Notes

Acknowledgments

We are grateful for Mike Flannigan (Department of Renewable Resources, University of Alberta), whose guidance helped with the implementation of CFFWIS in our focus region. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups (listed in Table 1 of this paper) for producing and making available their model output. CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison, provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

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Copyright information

© Springer-Verlag Wien 2016

Authors and Affiliations

  1. 1.Department of Earth & Planetary SciencesThe Johns Hopkins UniversityBaltimoreUSA
  2. 2.Department of Earth and Atmospheric SciencesCornell UniversityIthacaUSA
  3. 3.Soil Geography and Landscape GroupWageningen UniversityWageningenThe Netherlands
  4. 4.Department of Atmospheric and Oceanic SciencesPrinceton UniversityPrincetonUSA

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