How PeakScout Works
Complete transparency on every data source, scoring model, and update cycle — so you know exactly what you're getting and where it comes from.
The methodology section is for anyone who wants to understand PeakScout at a deeper level — what data powers each score, how fresh it is, and where the limits are. Whether you're a backcountry skier evaluating avalanche ratings, a hunter checking HuntScore methodology, or a guide verifying conditions before a trip, these pages give you the full picture.
PeakScout aggregates from government agencies, public APIs, and field networks — we don't own any of these sources. If something looks off, every page links to the authoritative agency so you can verify independently.
How It Works
The big picture — data pipeline, scoring overview, state coverage, and subscription tiers.
→ Start hereData Sources
Every external source we pull from — who it is, what it provides, how it updates, and reliability.
→ Start hereUpdate Frequency
What "real-time" actually means per signal — refresh intervals, caching, and stale data handling.
→Go Score
The 0–100 composite score for trail conditions: inputs, weighting, thresholds, and confidence.
→ ScoringForecast Models
Hazard Synthesis Engine, wind/lightning/flow/avalanche/cold components, and scoring floors.
→ ScoringAlpine Risk Score
Mountain-specific risk model: exposure, terrain traps, weather dependency, and decision framework.
→ ScoringSummit Window
How we identify high-confidence weather windows for peak attempts across the Mountain West.
→Trust Center
Legal, privacy policy, CCPA/GDPR, data attribution, and how to report an issue.
→ TrustWildfire Intelligence
How wildfire perimeters, smoke forecasts, and fire alerts are sourced, processed, and displayed.
→ TrustKnown Limitations
What PeakScout cannot do — coverage gaps by region, data freshness limits, edge cases, and verification guide.
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