HiRO-ACEv2 v2

Allen Institute for AI (Ai2) · released Oct 14, 2026

UnknownUSgeospatial data

Openness taxonomy

access, licence, and disclosure — never a single open/closed binary

Weights availability: unknown
Licence: unknown
Licence category: unknown
Commercial use allowed: unknown
Derivatives allowed: unknown
Redistribution allowed: unknown
Field-of-use restrictions: unknown
Training code availability: unknown
Inference code availability: unknown
Architecture disclosure: Two-part system: ACE at 100 km resolution and HiROv2 downscaling to 3 km
Training data disclosure: HiROv2 was trained using X-SHiELD data; system currently works with ACE tuned to match X-SHiELD

openness confidence

Deployability

raw values as extracted — free text, never inferred from branding

Self-hosting: unknown
On-premise: unknown
Edge deployability: unknown
API availability: unknown
Regions available: unknown

Benchmarks

as reported — vendor-supplied unless otherwise noted

High-resolution statistics compared with X-SHiELD for rare events Within 3% for events occurring once per million data pointsGlobal 3 km climate data generation cost compared with X-SHiELD About 1/300th the costRegional high-resolution data generation cost compared with X-SHiELD More than 100 times less, depending on area size

National-security pathway & evidence

from the assessed source item, when one is linked

Impact: lowConfidence: mediumNat-sec: indirectprimary

Domains: cni

Pathway: More affordable high-resolution extreme-weather simulations could support climate-risk analysis for critical infrastructure, although the source does not describe operational security adoption.

Evidence limitations: Performance and cost figures are presented by Ai2; no independent evaluation is cited in the supplied text.

HiRO-ACEv2: Simulating extreme weather at 3 km resolution for a fraction of the cost

Linked research papers

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No linked research papers yet.