Paauilo, HI
Paauilo, HI's wildfire risk, in USFS's own numbers
Paauilo sits at the 84th percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 259 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Paauilo's burn probability — fire likelihood with no building count factored in — sits at the 79th percentile nationally.
Paauilo's building exposure, zone by zone
Most of Paauilo's buildings (65.3%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
How Paauilo compares
Paauilo's 84th national percentile looks worse in isolation than its 14th ranking inside Hawaii does — this place is on the milder end for its own state, by 71 points. Among the 31,521 US communities USFS scores, Paauilo ranks 4,977 for wildfire risk (1 is highest) and 22,849 by building count (1 is largest). Within Hawaii alone, it ranks 141 of 163 places by risk. See the full county-by-county picture for Hawaii on its state page.
Shopping for coverage in Paauilo
Paauilo's very high rating (84th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
Because 65.3% of Paauilo's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Paauilo's figures come from
The methodology guide shows exactly how USFS turned 259 counted buildings into the percentiles shown above for Paauilo. The exposure-zones guide covers what Paauilo's dominant indirect exposure actually means, with real examples from across the dataset.