Climate-fire analog mapping to inform adaptive management strategies for wildland fire in protected areas of the conterminous U.S.

Managing and adapting to changing wildland fire regimes due to human-caused global warming can be facilitated through the use of analog mapping of potential climate-influenced outcomes. This dataset contains results from a simple process-based model, PC2FM, to derive projected analog fire regimes with respect to the potential fire probability concept. This concept is based on the potential energy and fuels available in the background environmental state under pre-industrial conditions for the coterminous US. To map climate-fire analog futures, three key relevant variables are used in addition to fire probability derived from PC2FM: annual temperature, annual precipitation, and precipitation seasonality. Projections of the climate-fire analogs are provided for 20 downscaled climate models under two climate forcing scenarios, Representative Concentration Pathways (RCP 4.5 and 8.5) for two time periods (2040-2069 and 2070-2099) and 655 protected areas in the conterminous U.S.