Four hazard scores — each 0–100 — are combined into a single composite using a concentration-aware model. The baseline is a weighted average reflecting relative actuarial impact, but two additional layers prevent a single extreme hazard from being diluted by low scores elsewhere.

Layer 1 — Weighted Average

Baseline = (Flood × 0.40) + (Storm × 0.30) + (Heat × 0.20) + (Wildfire × 0.10)

Layer 2 — Concentration Penalty

If the peak hazard exceeds the average of the other three by more than 40 points, a concentration bonus is added. This catches properties where risk is dominated by a single hazard — coastal flood zones, WUI wildfire corridors, tornado alley cores — that a simple average would understate.

Bonus = max(0, (Peak − Others Avg − 40) × 0.3)

Layer 3 — Peak Hazard Floor

The composite can never fall more than one risk bucket below the highest individual hazard. A property with a 95 wildfire score cannot score "Low" overall regardless of what the other hazards read.

Composite = max(Baseline + Bonus, Floor)

This approach is supported by Painter (2020), who found that markets price concentrated climate exposure differently than diversified exposure for long-duration securities, and Smull et al. (2023), who showed that additive risk models systematically underprice concentrated climate exposure.

Each risk tier maps to a price discount anchored to peer-reviewed real estate transaction data — not proprietary models.

Commercial discounts vary by asset class (multifamily lowest, hospitality highest) and lease type (NNN passes ~60% of climate cost increases to tenants). Scenario parameters — insurance multipliers, cap rate additions, vacancy and opex adjustments — are calibrated against NCREIF, Swiss Re (2023), and Green Street Advisors research.

The studies below form the empirical foundation of Climassay's discount methodology and credibility framework.

Heat (2050) — IPCC AR6 CMIP6: Live property-level projections from the Open-Meteo Climate API, which provides IPCC Sixth Assessment Report (AR6) CMIP6 models downscaled to 10km resolution. Ensemble of MRI_AGCM3_2_S (Japan Meteorological Agency) and EC_Earth3P_HR (European Centre for Medium-Range Weather Forecasts) models. Reports projected days above 95°F per year under SSP2-4.5 (moderate emissions) and SSP5-8.5 (high emissions) scenarios as defined by the IPCC AR6 Working Group I. Falls back to NOAA CMIP6 state-level ensemble if the live API is unavailable.

Sea Level Rise (coastal only) — NOAA / IPCC AR6: Projections from NOAA CO-OPS tide stations under IPCC AR6 Low, Intermediate, and High scenarios, as published in the NOAA 2022 Interagency Sea Level Rise Technical Report — a joint product of NOAA, NASA, USACE, USGS, EPA, and the White House Council on Environmental Quality. Only shown for properties in the 23 coastal US states.

IPCC Sixth Assessment Report (AR6): Climassay's forward-looking heat and sea level rise projections are derived directly from CMIP6 climate models assessed in the IPCC AR6 (2021). The SSP2-4.5 and SSP5-8.5 scenarios used for 2050 projections are the IPCC's standard moderate and high emissions pathways. This makes Climassay's projections consistent with the same scientific foundation used by central banks, insurance regulators, and the SEC's climate disclosure framework.

UNDRR Sendai Framework for Disaster Risk Reduction (2015–2030): Climassay's four-hazard weighting structure — flood, storm, heat, wildfire — aligns with the UN Office for Disaster Risk Reduction's Sendai Framework, the international standard for disaster risk assessment adopted by 187 countries. FEMA's National Risk Index, which serves as Climassay's county-level fallback, was explicitly designed to align with Sendai Framework indicators.

World Bank Climate Change Knowledge Portal (CCKP): Climassay's hazard weighting rationale and scenario calibration draw on World Bank CCKP research, which integrates CMIP6 climate projections with socioeconomic vulnerability data under open data licensing.

CAL FIRE — Fire and Resource Assessment Program (FRAP): For California properties, Climassay queries the CAL FIRE FRAP ArcGIS REST API — the authoritative source for California wildfire perimeter history maintained by the California Department of Forestry and Fire Protection. Updated annually, it provides the most accurate property-level fire history available for any US state, covering all perimeters since 1990. This replaces the county-level FEMA NRI score for CA properties, providing a materially more accurate wildfire assessment for the state with the highest wildfire exposure in the country.

USDA Wildfire Risk to Communities: Updated in May 2024 under congressional direction, this USDA Forest Service dataset provides community-level wildfire risk data and is used to calibrate state-level wildfire fallback scores for western states.

1. Flood scores reflect the current FEMA FIRM designation and do not incorporate future sea level rise, climate model projections, or pending FIRM remapping.

2. Wildfire scores are county-level averages. They do not capture parcel-specific fuel load, defensible space, structure hardening, or proximity to WUI boundaries.

3. Heat scores are based on 1991–2020 climate normals. 2050 projections are shown separately via Open-Meteo CMIP6.

4. Storm scores are based on historical tornado tracks and do not account for projected changes in severe convective storm frequency or intensity.

5. Valuation adjustments are illustrative scenarios based on published actuarial research and should be independently verified by a licensed appraiser before transacting.

6. Climassay does not provide investment advice. Scores should be used alongside traditional underwriting, local market knowledge, and professional judgment.