Precision weather monitoring instruments in a field

Trigger Reference

The index is the policy.

A reference catalog of parametric trigger metrics available in Riskwright policies — with source agency, threshold ranges, and typical use case. Every metric references publicly archived data that both parties can independently verify at NOAA Climate Data Online or equivalent sources.

10
Trigger metrics available
4
Hazard categories
100%
Public data sources

Full trigger metric reference.

Metric Category Source Threshold Range Typical Use
SPI-3 Drought NOAA Co-op ≤ -1.0 to -2.0 Agricultural drought, row crops, forage
PDSI Drought NOAA / NCEI ≤ -2.0 to -4.0 Multi-month drought, soil moisture depletion
USDM Category Drought USDA / NDMC D2–D4 designation Livestock/forage ops, broad drought exposure
GDD Deficit % Heat Stress PRISM 15–25% below normal Corn, soybean, specialty vegetable phenology
Precip Deficit % Drought PRISM / NOAA 25–50% below 30-yr normal Pasture forage, direct precipitation-dependent crops
Max Sustained Wind Wind NOAA ASOS 45–74 mph (Bft 9–12) Transmission infrastructure, above-ground assets
3-Sec Gust Wind NOAA ASOS 65–90 mph Solar arrays, light structural elements, towers
Cooling Degree Days Heat NOAA Co-op 20–35% above normal CDD Power generation, utility grid stress
Flash Flood Guidance Flood NWS / AHPS 1-hr or 3-hr FFG exceedance Stormwater infra, road networks, underground assets
Ice Accumulation Winter NOAA Co-op ≥ 0.25 in. – 0.75 in. Transmission lines, tree-canopy adjacent assets

Threshold calibration methodology.

Setting the right trigger threshold is the central technical challenge in parametric insurance underwriting. A threshold that's too sensitive triggers frequently but at low damage levels — generating payouts for events that didn't cause meaningful loss. A threshold that's too conservative misses genuine loss events — defeating the purpose of the coverage.

Riskwright's calibration process uses three analytical steps to find the historically optimal threshold for each client's location and exposure:

Historical percentile analysis — we compute the nth-percentile value of the index at the reference station(s) over a 30–50 year record. The SPI-3 value of -1.5 represents roughly the 10th percentile of 3-month precipitation anomaly for most Southeast US stations.
Correlation with loss data — where client or industry loss data is available, we compute the Pearson correlation between index values and observed damage or yield loss. Higher correlation = lower basis risk = tighter trigger calibration.
Client-specific backtesting — we simulate how the proposed trigger would have performed against historical data. This generates a trigger frequency (expected events per decade), historical payout rate, and basis risk assessment — all disclosed to the client before binding.

Threshold Selection — Frequency vs. Correlation Tradeoff

Optimal zone Sensitive Conservative Trigger freq. Loss correlation

Data source reference.

Source Data Type Update Frequency Coverage Area Access
NOAA Climate Data Online Daily precipitation, temperature, wind; station records Daily (24-48hr lag) Continental US, 8,700+ stations ncei.noaa.gov/cdo-web/
PRISM Climate Group Gridded temperature, precipitation (800m resolution) Daily provisional; monthly stable Continental US grid prism.oregonstate.edu
USDA Risk Management Agency USDM drought category designations, crop loss data Weekly (USDM) Continental US county-level rma.usda.gov
NWS / NOAA AHPS Flash Flood Guidance, river stage, precipitation rate Sub-hourly Continental US basins water.noaa.gov

Design a trigger for your exposure.

Tell us your location, asset type, and the weather risk you face. We'll identify the right index, calibrate the threshold, and present a coverage proposal.

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