ThousandWorlds: A benchmark for climate emulation of potentially habitable exoplanets
The search for life beyond Earth will depend on detecting faint signatures in the atmospheres of potentially habitable exoplanets. Interpreting those signatures requires understanding the host planet's climate: the same molecule may signal life on one planet and abiotic chemistry on another. Global climate models (GCMs) provide this understanding, but individual runs can require up to millions of core-hours and substantial domain expert time. Machine-learning emulators could remove this bottleneck, but progress has been limited by the absence of a curated, multi-model exoclimate dataset. We introduce ThousandWorlds, an ML-ready benchmark for exoclimate emulation and for the broader regime...
| Authors | Edward T. Stevenson, Mei Ting Mak, Eric Wolf et al. |
|---|---|
| Primary category | cs.LG |
| Published | 16 June 2026 |
| Last updated at source | 25 September 2026 |
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- AstroAutomata/ThousandWorldsDataset · cited by
- es833/ThousandWorldsDataset · cited by
Models and datasets referencing this paper
- es833/ThousandWorldsDataset
- AstroAutomata/ThousandWorldsDataset
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