AIMIP Phase 1 shows AI models simulate historical climate and El Niño responses as well as traditional models, though some underestimate trends and diverge in generalization tests, with a public dataset released for further checks.
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physics.ao-ph 2years
2026 2verdicts
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The paper presents a PMP-based evaluation framework to test deep-learning Earth system models on climatology and modes of variability using observational data.
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AIMIP Phase 1: systematic evaluations of AI weather and climate models
AIMIP Phase 1 shows AI models simulate historical climate and El Niño responses as well as traditional models, though some underestimate trends and diverge in generalization tests, with a public dataset released for further checks.
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A PMP-inspired Evaluation Framework for Assessing Deep-Learning Earth System Models
The paper presents a PMP-based evaluation framework to test deep-learning Earth system models on climatology and modes of variability using observational data.