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    Author(s): R Barbero; J T Abatzoglou; E A Steel
    Date: 2014
    Source: Environmental Research Letters. 9(12): 124009.
    Publication Series: Scientific Journal (JRNL)
    Station: Pacific Northwest Research Station
    PDF: Download Publication  (1.87 MB)


    Very large-fires (VLFs) have widespread impacts on ecosystems, air quality, fire suppression resources, and in many regions account for a majority of total area burned. Empirical generalized linear models of the largest fires (>5000 ha) across the contiguous United States (US) were developed at ¡­60 km spatial and weekly temporal resolutions using solely atmospheric predictors. Climate−fire relationships on interannual timescales were evident, with wetter conditions than normal in the previous growing season enhancing VLFs probability in rangeland systems and with concurrent long-term drought enhancing VLFs probability in forested systems. Information at sub-seasonal timescales further refined these relationships, with short-term fire weather being a significant predictor in rangelands and fire danger indices linked to dead fuel moisture being a significant predictor in forested lands. Models demonstrated agreement in capturing the observed spatial and temporal variability including the interannual variability of VLF occurrences within most ecoregions. Furthermore the model captured the observed increase in VLF occurrences across parts of the southwestern and southeastern US from 1984 to 2010 suggesting that, irrespective of changes in fuels and land management, climatic factors have become more favorable for VLF occurrence over the past three decades in some regions. Our modeling framework provides a basis for simulations of future VLF occurrences from climate projections.

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    Barbero, R.; Abatzoglou, J.T.; Steel, E.A. 2014. Modeling very large-fire occurrences over the continental United States from weather and climate forcing. Environmental Research Letters. 9(12). doi:10.1088/1748-9326/9/12/124009


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    very large-fires, climate-fire, United States, timescales

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