In this study, gridded global sea surface temperatures (SST) are analyzed in relation to monthly North American wildland fire danger. Wildland fire danger is the sum of constant danger and variable danger factors affecting the inception, spread and resistance to control, and subsequent fire damage; often expressed as a relative number indicating the severity of wildland fire danger. Temperature, relative humidity and precipitation are integrated meteorological inputs for the computation of fire danger indices. While it is known that SSTs can influence anomaly patterns of these meteorological elements, it is of interest to examine patterns and variability of fire danger as related to SST anomalies. These results provide direct benefit to fire agencies by identifying key regions of potential predictability and areas most likely to be impacted by ocean influence using a decision-support tool (fire danger) common in fire management.

In this analysis, positive matrix factorization (PMF) is used to relate monthly global SST and fire danger computed from the 32 km North American Regional Reanalysis for the period 1980-2005. PMF is examined in part to determine its usefulness in geophysical applications, and in part because it has demonstrated more interpretable results in air quality studies. We also compare the PMF results to PCA.

The fire danger index used in the analysis is the energy release component (ERC), which is the computed total heat released per unit area within the flaming front at the head of an advancing fire, and is a heavily utilized index in fire management. While some studies have focused and found SST relationships to fire occurrence regionally, this analysis is unique in that 1) fire potential in the form of fire danger is examined; and 2) all of North America can be examined homogeneously across the continent. Analyses utilizing fire occurrence data can be problematic because of difficult to obtain or poor quality fire datasets; thus, a uniformly gridded dataset of fire danger is highly beneficial in this spatial analysis. Results of this study will be presented emphasizing geographic locations influenced by SSTs along with their primary climate modes (e.g., ENSO). PMF will also be discussed in the context of geophysical studies.