Jupiter, FL
Jupiter wildfire risk explained
Out of every US place USFS scores, Jupiter lands at the 90th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 18,988 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Jupiter's burn probability — fire likelihood with no building count factored in — sits at the 90th percentile nationally.
What "at risk" means for the buildings here
Most of Jupiter's buildings (80.2% of 18,988) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure. At 18,988 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Where Jupiter ranks
Jupiter scores 90th nationally and 82nd within Florida — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Jupiter ranks 3,022 for wildfire risk (1 is highest) and 749 by building count (1 is largest). Within Florida alone, it ranks 171 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
What this risk score means for insurance
Jupiter's very high rating (90th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
Jupiter's 80.2% 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 Jupiter's figures come from
The methodology guide shows exactly how USFS turned 18,988 counted buildings into the percentiles shown above for Jupiter. The exposure-zones guide covers what Jupiter's dominant minimal exposure actually means, with real examples from across the dataset.