Ahwahnee, CA
Ahwahnee wildfire risk explained
USFS scores Ahwahnee at the 99th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 1,627 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Ahwahnee's burn probability — fire likelihood with no building count factored in — sits at the 99th percentile nationally.
Ahwahnee's building exposure, zone by zone
1,627 buildings are counted in Ahwahnee, and 98.6% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
How Ahwahnee compares
Ahwahnee's risk sits at a similar level relative to California (91st percentile statewide) as it does nationally (99th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Ahwahnee ranks 271 for wildfire risk (1 is highest) and 8,664 by building count (1 is largest). Within California alone, it ranks 146 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Shopping for coverage in Ahwahnee
Because Ahwahnee is in California, a wildfire-hazard disclosure is legally required before a sale closes here — unusual nationally, since only these two states mandate it. The state's FAIR Plan alone carried 668,609 policies by the end of 2025. Full detail in the disclosure-law guide.
Hardening a home in Ahwahnee
With 98.6% of Ahwahnee in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Ahwahnee's figures come from
Every one of the two percentiles behind Ahwahnee's 271-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Ahwahnee's dominant direct exposure actually means, with real examples from across the dataset.