Ranier, MN
Ranier, MN's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Ranier at the 39th national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 687 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Ranier at the 36th national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
Most of Ranier's buildings (76.1%) 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.
Ranier against the rest of the country
Ranier scores 39th nationally and 52nd within Minnesota — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Ranier ranks 19,282 for wildfire risk (1 is highest) and 14,796 by building count (1 is largest). Within Minnesota alone, it ranks 438 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.
Shopping for coverage in Ranier
Ranier's moderate wildfire rating (39th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Hardening a home in Ranier
Ranier's 76.1% 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 Ranier's figures come from
Ranier's 39th-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 Ranier's dominant indirect exposure actually means, with real examples from across the dataset.