Strong claim files are evidence systems. In Colorado, that starts with weather data discipline.

Baseline Risk Context for Colorado

NOAA NCEI’s Colorado summary shows severe storms as the dominant billion-dollar disaster category affecting the state over the long term, with a marked increase in recent years.

That does not prove damage to your roof, but it does justify a structured storm-validation workflow.

Date-of-Loss: Build a Defensible Window

Use a two-source method:

  1. Macro validation (state/region context)
  • NOAA NCEI event timelines
  1. Local validation (metro/county context)
  • NWS local event summaries
  • NOAA Storm Events Database entries

Then tie your photo evidence and property observations to the best-supported window.

A Practical Data Stack for Homeowners

  • NOAA NCEI billion-dollar events (context)
  • NWS Denver/Boulder event summaries (local chronology)
  • Storm Events Database (event-type granularity)

Minimum file standards

  • Event links/PDFs saved to claim folder
  • UTC/local timestamp notes on all storm evidence
  • One-page chronology from storm date to inspection date

Why Adjusters Care About This

Claims teams evaluate causation and timing. A clear meteorological chain helps reduce ambiguity around:

  • Which storm is being claimed
  • Whether damage pattern aligns with event type
  • Why specific collateral indicators are expected

Hail Severity vs Damage Expectations

Not every hail report supports a full-roof replacement. Damage response depends on:

  • Hail size and density
  • Wind component and impact angle
  • Roof age and existing condition
  • Material class and installation quality

Use data to guide inspection depth, not to pre-judge final scope.

High-Value Output: The Storm Packet

Create a concise storm packet before adjuster inspection:

  • Candidate storm dates with source links
  • Property location and orientation map
  • Slope-by-slope photo index
  • Collateral evidence index
  • Short technical narrative of observed mechanisms

This improves meeting efficiency and reduces post-inspection email churn.

Common Data Mistakes

  • Pulling only social-media weather screenshots
  • No distinction between report date and loss date
  • Ignoring local NWS office summaries
  • Failing to archive source versions used in the claim

Sources

Educational guidance only. Final claim determinations depend on policy terms and property-specific evidence.