Newcastle, WA
Newcastle, WA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Newcastle at the 32nd national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 3,839 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Newcastle's burn probability — fire likelihood with no building count factored in — sits at the 29th percentile nationally.
Where Newcastle's buildings actually sit
Most of Newcastle's buildings (63.7%) 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 Newcastle compares
Compare Newcastle's two percentiles: 51st within Washington, only 32nd nationally — a gap of 19 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Newcastle ranks 21,540 for wildfire risk (1 is highest) and 4,387 by building count (1 is largest). Within Washington alone, it ranks 309 of 628 places by risk. See the full county-by-county picture for Washington on its state page.
What this risk score means for insurance
Newcastle's moderate rating (32nd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Hardening a home in Newcastle
Newcastle's 63.7% 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 Newcastle's figures come from
Newcastle's 32nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Newcastle's dominant indirect exposure actually means, with real examples from across the dataset.