How CivilSense Computes Climate-Adjusted Hazard Scores

Hazard scoring is the foundation of catastrophe modeling. Before you can estimate losses, you need to know what physical intensity a location will experience from a given peril. CivilSense computes Climate-Adjusted Hazard Scores on a 0–10 scale for six US perils: earthquake, hurricane, wildfire, flood, hail, and tornado.

Every score is fully decomposed. We show the components, the weights, and the source data. This is a deliberate choice.

Why Transparency Matters

The incumbent cat modeling platforms — AIR (Verisk), RMS (Moody's), and CoreLogic — treat their scoring methodologies as proprietary black boxes. This made sense in 1990 when data was scarce and modeling was a genuine competitive moat. It makes less sense in 2026 when the underlying data is freely available from federal agencies and the peer-reviewed literature is indexed and searchable.

More importantly, insurance professionals need to defend scores to their compliance teams, regulators, and reinsurers. A score that says "7.8 out of 10" without showing how it got there is useless in a regulatory filing. A score that says "7.8 based on: historical CAT3+ track frequency (3.1/3.5), NOAA SLOSH surge zone classification (2.8/3.0), and coastal proximity (2.3/3.5)" is defensible.

Scoring Architecture

Each peril score is the sum of weighted components. Components are derived from three data layers:

Historical frequency. How often has this peril affected this location in the observational record? For hurricanes, we use IBTrACS (1842–present, North Atlantic basin) to count CAT3+ tracks within 100km. For earthquakes, we use the USGS earthquake catalog with Gutenberg-Richter frequency analysis. For wildfires, NIFC perimeters (1984–present) provide fire frequency by region.

Hazard zone classification. Federal agencies publish authoritative hazard zone maps. FEMA flood zones (A, AE, V, X) classify flood risk. NOAA SLOSH model outputs classify storm surge exposure by hurricane category. USGS National Seismic Hazard Maps provide probabilistic ground motion estimates. These zones are the bedrock of hazard assessment — they represent decades of scientific work and billions of dollars in modeling investment.

Physical proximity and exposure. Distance to fault lines (USGS Quaternary Fault Database), distance to coastline (NOAA National Shoreline), distance to wildland-urban interface (USGS SILVIS Lab WUI data). These are geometric calculations against authoritative federal datasets.

Climate Adjustment

Historical frequency alone is insufficient because the climate is changing. Hurricane intensification rates in the Atlantic basin have increased measurably since 1980. Wildfire seasons in the western US are longer and more severe than the historical average. Flood return periods computed from 20th-century data underestimate 21st-century flood risk in many US watersheds.

CivilSense applies climate adjustment factors derived from peer-reviewed research. Each adjustment factor is stored in the model parameters database with a citation to the source paper. When a new paper is published that updates a climate trend estimate, the adjustment factor is versioned — the old value is superseded, not deleted. The full parameter history is preserved.

What Hazard Scores Are Not

Hazard scores are not risk scores. Risk requires exposure data — what is the replacement value of the structure at this location? What construction type? What year built? Until property-level exposure data is integrated (via ATTOM or comparable sources), CivilSense labels all scores as "Climate-Adjusted Hazard Scores" and includes a disclaimer: "Property exposure data not included. Not a substitute for professional actuarial assessment."

This distinction matters to actuaries. Conflating hazard and risk is a credibility-destroying mistake that we refuse to make.