New Auburn, WI
New Auburn wildfire risk explained
USFS scores New Auburn at the 23rd national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 387 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks New Auburn at the 22nd national percentile — 1 points below its risk-to-structures score, a gap driven by how much is actually built there.
New Auburn's building exposure, zone by zone
USFS puts 65.6% of New Auburn's 387 buildings in the Indirect exposure zone, versus 34.4% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.
How New Auburn compares
New Auburn's 43rd-percentile standing inside Wisconsin outpaces its 23rd national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, New Auburn ranks 24,223 for wildfire risk (1 is highest) and 19,480 by building count (1 is largest). Within Wisconsin alone, it ranks 464 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
What this risk score means for insurance
New Auburn's moderate wildfire rating (23rd 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.
Lowering exposure, not just insuring around it
Because 65.6% of New Auburn's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where New Auburn's figures come from
New Auburn's 23rd-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 New Auburn's dominant indirect exposure actually means, with real examples from across the dataset.