The Effect of ENSO on United States Fire Weather

Fire Weather Index (FWI) is a numeric rating that assesses fire intensity based on meteorological conditions such as temperature, relative humidity, precipitation, and wind. Higher FWI values are well correlated to areas of higher burn probability across the United States. Global climate patterns, such as El Niño Southern Oscillation (ENSO), modify these FWI meteorological inputs across the United States. Being able to accurately evaluate how ENSO will modify FWI may provide enhanced fire season predictability at seasonal time horizons. Regressing the Niño 3.4 SST index with detrended FWI and burn area values across the United States reveals that as Niño 3.4 values increase, FWI values and burn area decrease. This negative relationship demonstrates that La Niña conditions are more favorable for increased fire weather conditions and burn area across the United States.

FWI values vary spatially and temporally across the United States, as do the impacts of ENSO. To understand the spatial distribution of the relationship between ENSO and detrended FWI, statistical relationships between FWI and the Niño 3.4 index were calculated over regions that share homogenous fire characteristics, called pyromes. Across the United States, negative relationships between ENSO and FWI are present, but the magnitude of these relationships varies from pyrome to pyrome. Pyromes located over the western United States have the largest correlation between ENSO and FWI. Analysis of how these relationships between ENSO and FWI change temporally identifies which months generate the most anomalous FWI values under certain ENSO phases, both nationally and regionally. Given the strong correlation between FWI and burn area, we find that the ENSO phase is also a strong predictor of burn area.

Improved ENSO forecasting in conjunction with a more holistic understanding of the connection between ENSO and fire behavior will help risk managers create seasonal fire forecasts on both the national and regional scales. Such findings may help the private and public sector better prepare for upcoming fire seasons with increased lead time.