Understanding Wildfire Interannual Variability using Large Ensembles

Annual wildfire occurrences are associated with a high degree of variability. As well as arising from the inherent randomness of wildfire events, this is also due to variability in the climate factors affecting wildfire risk, such as to summer precipitation. With climate change linked to the emergence of regionally catastrophic fire years, understanding the probabilistic distribution of wildfires and the extent these are linked to predictable modes of climate variability (such as El Niño Southern Oscillation, ENSO, or the Atlantic Multidecadal Oscillation, AMO) is of increasing importance. We use a large climate ensemble (KNMI-LENTIS) together with probabilistic fire occurrence model accounting for human, vegetation type, vegetation growth, and weather effects to predict 1600 simulated fire years over the contiguous US in the modern climate (2000-2009) and for +2°C global warming. There is significant spread in the distribution of fire years in the modern ensemble, with interannual variability higher in regions with a high mean rate of fire activity. Controlling for the effect of the average fire rate, the southwestern US, the Great Plains and southern Florida have proportionally highest variability. Wildfire occurrence is strongly influenced by climate modes in all three of these regions in the ensemble - with greater wildfire occurrence associated with La Niña, negative Indian Ocean Dipole (IOD), and positive Tropical North Atlantic (TNA) years. The AMO, Pacific Decadal Oscillation and Pacific/North American oscillation all exert a significant influence on US wildfire in the modern and modern +2°C climates. Climate warming results in a considerable increase in annual wildfire occurrences across the US, including in less fire-prone regions of the northern and interior US, as well as a strong effect on the likelihood of extreme fire years and long fire seasons in the southwest. There is a strengthening effect of key climate modes on annual wildfires, especially from the AMO, IOD, TNA and ENSO. This analysis, in addition to specific findings concerning US wildfire, highlights the utility of large climate ensembles in characterising the variability of the wildfire regime and projecting wildfire under future climate change.