Long lead statistical forecasts of area burned in western U.S. wildfires by ecosystem province
By: A.L. Westerling, A. Gershunov, D.R. Cayan, and T.P. Barnett
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Abstract
A statistical forecast methodology exploits large-scale patterns in monthly U.S. Climatological Division Palmer Drought Severity Index (PDSI) values over a wide region and several seasons to predict area burned in western U.S. wildfires by ecosystem province a season in advance. The forecast model, which is based on canonical correlations, indicates that a few characteristic patterns determine predicted wildfire season area burned. Strong negative associations between anomalous soil moisture (inferred from PDSI) immediately prior to the fire season and area burned dominate in most higher elevation forested provinces, while strong positive associations between anomalous soil moisture a year prior to the fire season and area burned dominate in desert and shrub and grassland provinces. In much of the western U.S., above- and below-normal fire season forecasts were successful 57% of the time or better, as compared with a 33% skill for a random guess, and with a low probability of being surprised by a fire season at the opposite extreme of that forecast.
| Publication type | Conference Paper |
|---|---|
| Publication Subtype | Conference Paper |
| Title | Long lead statistical forecasts of area burned in western U.S. wildfires by ecosystem province |
| Volume | 11 |
| Issue | 3-4 |
| Year Published | 2002 |
| Language | English |
| Larger Work Title | International Journal of Wildland Fire |
| First page | 257 |
| Last page | 266 |
| Google Analytic Metrics | Metrics page |