Fire Probability for Carbon Accounting
The Fire and Resource Assessment Program (FRAP) at CAL FIRE is investigating methods for estimating the likelihood of wildfire occurrence across the State of California in the coming decades. As part of this effort, FRAP has worked with researchers from the University of California and The George Washington University to develop a map of annual wildfire probability for the period 2021-2050. This map is provided here for use in the quantification of GHG benefits of fuel reduction activities funded under CAL FIRE-California Climate Investments (CCI) Forest Health Grants Program.
A web-based tool is provided below to explore the data, and summarize for specific project areas. The full dataset (GDB) and map (PDF) are provided below for download.
Data Access Web Tool
This web-based tool will allow you to select, draw, or upload a project area polygon and summarize the fire probability information from this dataset. Click here to open the tool in a web browser.
Data Download [forthcoming]
- PDF statewide map
- Zipped geodatabase with metadata
California Annual Probability of Wildfire Occurrence 2026-2050
This data represents mean projected annual probability (%) of wildfire occurrence for the period 2021-2050. It is intended for use in the quantification of GHG benefits of fuel reduction activities funded under the CAL FIRE-CCI Forest Health Program.
This data represents mean projected annual probability (%) of wildfire occurrence for the period 2021-2050, developed by researchers at the University of California and The George Washington University with support from CAL FIRE and California Climate Investments (CAL FIRE contract #8CA06938). Probability was projected annually through 2099 using each of four climate models (CanESM2, HadGEM2-ES, CNRM-CM5, and MIROC5) under the RCP 8.5 emissions scenario at 1 km resolution. Predictive models were trained using a GAM framework on a spatially randomized subset of data from 1980-2019, and incorporate predictions of actual evapotranspiration, climatic water deficit, and local housing density, as well as distance to roads and electrical infrastructure, area of cultivated land, and historical fire perimeters. Mean annual probability of wildfire was derived from annual projections over the thirty-year period 2021 - 2050 and across all four climate models. 1 km grid cells with >=50% cultivated land, urban cover, water, or barren/rock were excluded in the model or ex post facto for purposes of this dataset.
Source Data References:
Park, I., Mann M., Flint, L.E., Flint, A.L., and Moritz M.A., 2021. Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California. In Review.
Mann, M.L., Batllori, E., Moritz, M.A., Waller, E.K., Berck, P., Flint, A.L., Flint, L.E. and Dolfi, E., 2016. Incorporating anthropogenic influences into fire probability models: effects of human activity and climate change on fire activity in California. PloS one, 11(4), p.e0153589. Available at: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0153589
Isaac Park, Ph.D. (UC Santa Barbara), Michael L. Mann, Ph.D. (The George Washington University), Max A. Moritz, Ph.D. (UC Berkeley) and others developed the model and made projections for California with support from CAL FIRE and California Climate Investments (CAL FIRE contract #8CA06938). Tadashi J. Moody (Fire and Resource Assessment Program, CAL FIRE) performed data conversion (%), masking and other preparation for use in the CAL FIRE-CCI Forest Health Program.
Access and Use Constraints:
Provided for public use as part of the CAL FIRE-CCI Forest Health Program. For all other uses, please contact Tadashi Moody, CAL FIRE - FRAP, (916) 445-5342, email@example.com.
More Information Contact FRAP staff: firstname.lastname@example.org