AURORASIGNAL · PLATE
METHOD
Method & data governance
Data sources
- Kp (planetary K-index): NOAA SWPC 1-minute feed and 3-hour forecasts, fetched hourly
- Dst (storm-time ring current): Kyoto World Data Center, hourly; final→provisional→realtime by release status
- Solar flares: NOAA GOES X-ray flux, daily peak and class
- Schumann resonance: Tomsk State University spectrograms (frequency/amplitude/quality), archived hourly
Governance rules (mandatory)
- Missing = missing: Kyoto sentinel values (3999/9999) become null with a quality_flag at ingest — no interpolation, no forward-fill, API passes null through
- Range validation: Kp∈[0,9], Dst∈[-2500,2500]; violations fail the gate
- Freshness: Kp lag >6h or SR >26h fails the quality gate
- Provenance: every record carries a source field; Dst labeled final/provisional/realtime
- Immutable archive: JSONL is append-only
Derived quantities (public definitions)
- G-scale (G0-G5): mapped from 3-hourly Kp peaks per the NOAA scale (Kp5→G1 … Kp9→G4/G5)
- Active day: daily Kp_max ≥ 5 (the grouping used in diary correlation stats)
- dst_min_daily: daily minimum of hourly Dst
Personal correlation statistics
Each diary entry automatically carries that day's Kp/Dst snapshot. The Mirror view groups your metric means by "active vs quiet days" and shows sample sizes; any group with n<5 is explicitly labeled "insufficient to conclude". We compute correlation; we never claim causation.
Why so strict
This field is polluted from both ends: limitless mysticism on one side, "nothing ever happens" arrogance on the other. Data governance is the only way to pick a side — let the numbers speak, call missing missing, call unknown unknown.