WildfireRiskFinder

Welcome, MN

Welcome wildfire risk explained

Low
11thpercentile nationally

USFS's Wildfire Risk to Communities model puts Welcome at the 11th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 539 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Welcome's burn probability — fire likelihood with no building count factored in — sits at the 7th percentile nationally.

Where Welcome's buildings actually sit

539Total buildings
20%Direct exposure
0%Indirect exposure
80%Minimal exposure

USFS classifies 80% of Welcome's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 20% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.

How Welcome compares

Welcome's risk sits at a similar level relative to Minnesota (15th percentile statewide) as it does nationally (11th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Welcome ranks 28,055 for wildfire risk (1 is highest) and 16,732 by building count (1 is largest). Within Minnesota alone, it ranks 779 of 914 places by risk. See the full county-by-county picture for Minnesota on its state page.

Shopping for coverage in Welcome

At the 11th national percentile, Welcome rates low 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

Welcome's 80% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.

Where Welcome's figures come from

The methodology guide shows exactly how USFS turned 539 counted buildings into the percentiles shown above for Welcome. The exposure-zones guide covers what Welcome's dominant minimal exposure actually means, with real examples from across the dataset.