Multi-scale influence of vapor pressure deficit on fire ignition and spread in boreal forest ecosystems
Abstract. Climate-driven changes in the fire regime within boreal forest ecosystems are likely to have important effects on carbon cycling and species composition. In the context of improving fire management options and developing more realistic scenarios of future change, it is important to understand how meteorology regulates different aspects of fire dynamics, including ignition, daily fire spread, and cumulative annual burned area. Here we combined Moderate-Resolution Imaging Spectroradiometer (MODIS) active fires (MCD14ML), MODIS imagery (MOD13A1) and ancillary historic fire perimeter information to produce a data set of daily fire spread maps for Alaska during 2002–2011. This approach provided a spatial and temporally continuous representation of fire progression and a precise identification of ignition and extinction locations and dates for each wildfire. The fire-spread maps were analyzed with daily vapor pressure deficit (VPD) observations from the North American Regional Reanalysis (NARR) and lightning strikes from the Alaska Lightning Detection Network (ALDN). We found a significant relationship between daily VPD and likelihood that a lightning strike would develop into a fire ignition. In the first week after ignition, above average VPD increased the probability that fires would grow to large or very large sizes. Strong relationships also were identified between VPD and burned area at several levels of temporal and spatial aggregation. As a consequence of regional coherence in meteorology, ignition, daily fire spread, and fire extinction events were often synchronized across different fires in interior Alaska. At a regional scale, the sum of positive VPD anomalies during the fire season was positively correlated with annual burned area during the NARR era (1979–2011; R2 = 0.45). Some of the largest fires we mapped had slow initial growth, indicating opportunities may exist for suppression efforts to adaptively manage these forests for climate change. The results of our spatiotemporal analysis provide new information about temporal and spatial dynamics of wildfires and have implications for modeling the terrestrial carbon cycle.