Newman, CA
Newman, CA's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Newman lands at the 78th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 3,872 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Newman's burn probability — fire likelihood with no building count factored in — sits at the 78th percentile nationally.
Newman's building exposure, zone by zone
Indirect exposure is dominant in Newman (64.6% of 3,872 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 5.5% sit in the Direct zone.
Where Newman ranks
Newman's 78th national percentile looks worse in isolation than its 37th ranking inside California does — this place is on the milder end for its own state, by 41 points. Among the 31,521 US communities USFS scores, Newman ranks 7,081 for wildfire risk (1 is highest) and 4,365 by building count (1 is largest). Within California alone, it ranks 994 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Newman and the insurance market
Newman sits in California, one of two states that legally require a wildfire-risk disclosure at sale. California's FAIR Plan, the state's insurer of last resort, ended 2025 with 668,609 residential policies after adding 21,859 in Q4 alone — the kind of market shift a 78th-percentile score like Newman's can end up mattering for. More on the disclosure law.
What would actually reduce this score
With ember exposure the dominant pattern in Newman (64.6% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Newman's figures come from
The methodology guide shows exactly how USFS turned 3,872 counted buildings into the percentiles shown above for Newman. The exposure-zones guide covers what Newman's dominant indirect exposure actually means, with real examples from across the dataset.