The statistical method used to predict AMOC collapse timing from historical sea-surface temperatures is highly sensitive to unaccounted uncertainties and does not reliably constrain the collapse time.
Observed fingerprint of a weakening Atlantic Ocean overturning circulation
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Case study demonstrates that a Gemini AI integrated into a climate science workflow produced most of a 79-paper synthesis on AMOC stability in 46 person-hours, with experts retaining the majority of AI output while adding critical content and oversight.
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Extrapolation from historical data cannot reliably predict the time of a potential AMOC collapse
The statistical method used to predict AMOC collapse timing from historical sea-surface temperatures is highly sensitive to unaccounted uncertainties and does not reliably constrain the collapse time.
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AI-Assisted Scientific Assessment: A Case Study on Climate Change
Case study demonstrates that a Gemini AI integrated into a climate science workflow produced most of a 79-paper synthesis on AMOC stability in 46 person-hours, with experts retaining the majority of AI output while adding critical content and oversight.