Sundown, MO
Sundown wildfire risk explained
Sundown sits at the 78th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 113 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Sundown at the 80th percentile, close to its 78th-percentile risk score.
What "at risk" means for the buildings here
113 buildings are counted in Sundown, and 100% 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.
Sundown against the rest of the country
Compare Sundown's two percentiles: 94th within Missouri, only 78th nationally — a gap of 17 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Sundown ranks 7,090 for wildfire risk (1 is highest) and 28,508 by building count (1 is largest). Within Missouri alone, it ranks 61 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
What this risk score means for insurance
Sundown's 78th-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.
Hardening a home in Sundown
Sundown's 100% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Sundown's figures come from
Sundown's 78th-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 Sundown's dominant direct exposure actually means, with real examples from across the dataset.