NOAA Ocean Forecast Models Optimized for Cloud Access

Reference files published by NOAA's National Ocean Service and IOOS enable lazy loading of multidimensional ocean forecast data. The Kerchunk process maps NOAA Operational Forecast System, Global Real-Time Ocean Forecast System, and National Water Model Short-Range Forecast outputs to the Zarr V2 specification. Cloud optimization workflows are supported by RPS Group, a Tetra Tech Company.

Use Cases

• Lazily load forecast data chunks based on the Zarr V2 specification mapping.
• Scale horizontal reads of ocean forecast data to optimize object storage performance.
• Access aggregated 'best forecast' or full model run data for NOAA operational models.

Strengths

• Data is optimized for cloud access using the Kerchunk process.
• Includes reference files for three specific NOAA forecast systems: OFS, Global RTOFS, and National Water Model.
• Provides virtual aggregations for entire forecast runs and continuously updated 'best' forecasts.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

NOAA's National Ocean Service, the Integrated Ocean Observing System (IOOS)

Collection Method

Data is published to the NOAA Open Data Dissemination Program and optimized via Kerchunk workflows run by RPS Group.