data api · Global

NVIDIA NIM for Earth-2 CorrDiff

Earth-2 CorrDiff NIM: generative AI downscaling of coarse weather/climate fields to km-scale resolution, served as an inference microservice.

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What's in it

Data offered llm-inferred: downscaled surface and atmospheric variables · ensembled, downsampled forecasts
Coverage docs-verified: United States
Resolution llm-inferred: km-scale (per catalogue description; docs give no numeric resolution)
Access llm-inferred: NGC API key; licence: NVIDIA AI Enterprise / NIM terms (per catalogue metadata)

Useful for

Use cases llm-inferred: Km-scale meteorological input exploration for US project sites · Ensembled downscaled forecasts for US flood-risk screening · Comparing coarse and downscaled climate fields for US climate-allowance studies
Audience llm-inferred: hydrologists · climate scientists · GIS analysts

Limitations

Constraints llm-inferred: Docs describe US coverage only; catalogue metadata lists Global, which conflicts with the docs · No UK coverage evidenced; limited relevance to UK consultancy work · Requires NGC API key and NVIDIA AI Enterprise / NIM licence terms · No MCP tools listed

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))