Optimizing training data via a differentiable SCM yields climate emulators that outperform those trained on six standard ScenarioMIP pathways while using less data and isolating distinct forcing responses.
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physics.ao-ph 2years
2026 2verdicts
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Presents integral dynamic emergent constraints from linear response theory as a generalization of traditional ones, tested on MPI-ESM global warming simulations.
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Optimal scenario design for climate emulation
Optimizing training data via a differentiable SCM yields climate emulators that outperform those trained on six standard ScenarioMIP pathways while using less data and isolating distinct forcing responses.
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A mathematical framework for dynamic emergent constraints in climate science
Presents integral dynamic emergent constraints from linear response theory as a generalization of traditional ones, tested on MPI-ESM global warming simulations.