Long Beach, WA
Long Beach, WA's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Long Beach lands at the 21st percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 1,510 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Long Beach at the 22nd percentile, close to its 21st-percentile risk score.
Long Beach's building exposure, zone by zone
91.5% of Long Beach's 1,510 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 8.5% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Long Beach compares
There's little gap between Long Beach's 21st national percentile and its 33rd percentile inside Washington, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Long Beach ranks 24,850 for wildfire risk (1 is highest) and 9,121 by building count (1 is largest). Within Washington alone, it ranks 423 of 628 places by risk. See the full county-by-county picture for Washington on its state page.
Long Beach and the insurance market
At the 21st national percentile, Long Beach rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
Lowering exposure, not just insuring around it
With ember exposure the dominant pattern in Long Beach (91.5% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Long Beach's figures come from
The methodology guide shows exactly how USFS turned 1,510 counted buildings into the percentiles shown above for Long Beach. The exposure-zones guide covers what Long Beach's dominant indirect exposure actually means, with real examples from across the dataset.