Sunol, NE
Sunol, NE's wildfire risk, in USFS's own numbers
Sunol's 107 buildings earn a 73rd-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Sunol's burn probability — fire likelihood with no building count factored in — sits at the 72nd percentile nationally.
What "at risk" means for the buildings here
Most of Sunol's buildings (69.2%) 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 Sunol compares
There's little gap between Sunol's 73rd national percentile and its 74th percentile inside Nebraska, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Sunol ranks 8,571 for wildfire risk (1 is highest) and 28,742 by building count (1 is largest). Within Nebraska alone, it ranks 153 of 583 places by risk. See the full county-by-county picture for Nebraska on its state page.
Shopping for coverage in Sunol
Sunol's 73rd-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Sunol's 69.2% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Sunol's figures come from
The methodology guide shows exactly how USFS turned 107 counted buildings into the percentiles shown above for Sunol. The exposure-zones guide covers what Sunol's dominant indirect exposure actually means, with real examples from across the dataset.