Disciplines

🌦 Meteorological Intelligence (METOCINT)

🔍 Lookup

📊 Pre-built Queries · Meteorological Intelligence

📜 Playbook — Meteorological Intelligence collection

1. Direction — frame the requirement for Meteorological Intelligence: what decision does this support, by when?
2. Collection — collect from the 0 mapped sources (0 free) — filter the catalog by METOCINT; capture provenance and observe OPSEC.
3. Processing — normalize, de-duplicate and enrich the collected data.
4. Analysis — correlate against local holdings; apply ACH; assign confidence.
5. Dissemination — open a case, draft a report, share via STIX/MISP.
6. Feedback — set an alert rule / watchlist to monitor for change.

⚡ AI Skills & Automation

Automate unattended via the cron pipeline (collect → ingest → resolve → enrich → score → alert).

🗃 Data Management

🧩 Advanced Capabilities

✨ Enrichment pathways

🎯 Mission

Meteorological Intelligence delivers weather, ocean, and atmospheric forecasting to characterize conditions affecting operations, safety, and other collection disciplines. It answers what conditions to expect, how they impact assets and missions, and where severe weather threatens.

📡 Collection methods

• Numerical weather prediction ingestion from GFS and ECMWF open data
• Radar and satellite nowcasting for precipitation, cloud, and IR
• METAR/TAF aviation weather decoding for terminal and route conditions
• Ocean-state, wave, and SST collection from moored buoys
• Tropical cyclone track and intensity monitoring from official advisories
• Lightning and severe-storm index derivation
• ERA5 reanalysis for climatological baselines and anomaly detection

📚 Key sources & datasets

🎫 Data points produced

🔧 Tools & frameworks

• QGIS
• wgrib2
• MetPy
• Panoply
• Windy
• xarray

📜 Meteorological Intelligence Tradecraft

1. Collect: pull GFS/ECMWF grids, METAR/TAF, NDBC buoy obs, and GOES/radar feeds for the operational area
2. Process: decode GRIB and METAR, interpolate fields to the AOI, and QC against station observations
3. Analyze: derive forecasts, severe-weather indices, and route and asset impact windows
4. Attribute: correlate observed conditions with model runs to characterize forecast skill and hazard drivers
5. Disseminate: issue tailored forecasts, warnings, and go/no-go weather windows to operators
6. Act: trigger contingency plans and feed conditions into environmental, maritime, and air-tracking workflows

📊 Dashboard KPIs

🔍 Pre-built queries

🔗 Cross-discipline pivots

🗃 Data Management

🧩 Advanced Capabilities