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NVIDIA NIM for Earth-2 FourCastNet

Earth-2 FourCastNet NIM: containerised inference microservice for FourCastNet global AI weather forecasts at 6-hour timesteps with stability for over a year of simulated time.

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What's in it

Data offered docs-verified: global short-to-medium-range predictions · 6-hour time-step forecasts
Coverage docs-verified: Global
Resolution docs-verified: 6-hour time step; spatial resolution not stated
Formats docs-verified: container image (NIM microservice) with API
Access llm-inferred: NGC API key; licence: NVIDIA AI Enterprise / NIM terms; pricing not stated

Useful for

Use cases llm-inferred: Global short-to-medium-range forecast context for site-scale project planning · Weather-driven scenario generation for climate-resilience studies · Upstream forecast stage in a NIM pipeline feeding local downstream models
Audience llm-inferred: hydrologists · climate and resilience consultants · GIS analysts · data scientists

Limitations

Constraints llm-inferred: Described for short to medium-range forecasting only; not stated as suitable for seasonal or long-range use · Global model; no UK-specific resolution or validation stated in docs · Requires self-hosted NIM container deployment and an NGC API key · User is responsible for compliance with applicable laws

Licence: NVIDIA AI Enterprise / NIM terms
Authentication: NGC API key
GitHub stars: Unknown
Last commit: Unknown
Last successful page check: 14/10/2026
Page health: page reachable
Package: Not recorded
Verification: Not independently verified

Provenance & evidence

Verified 2026-10-15 via curl (HTTP 200).

Metadata observed 14/10/2026 · research sweep: manual-2026-10-15 (Chris sources (NVIDIA Earth-2))