Solar Geoengineering, Learning, and Experimentation

doi:10.1086/729608

Solar Geoengineering, Learning, and Experimentation

2024-11-02

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DOI：10.1086/729608

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Solar geoengineering (SGE) can offset climate change by directly reducing temperatures. Both SGE and climate change itself are surrounded by great uncertainties. Implementing SGE affects learning about these uncertainties. We model endogenous learning over two uncertainties: the sensitivity of temperatures to carbon concentrations (the climate sensitivity) and the effectiveness of SGE in lowering temperatures. We present both theoretical and simulation results from an integrated assessment model, focusing on the informational value of SGE experimentation. Surprisingly, under current calibrated conditions, SGE deployment slows learning, causing a less informed decision. For any reasonably sized experimental SGE deployment, the temperature change becomes closer to zero and thus more obscured by noisy weather shocks. Still, some SGE use is optimal despite, not because of, its informational value. The optimal amount of SGE is very sensitive to beliefs about both uncertainties.

Keywords:

C61

C63

D81

D83

Q54

Q55

Q58

geoengineering

climate change

uncertainty

learning

integrated assessment

feedbacks

solar radiation management

abatement

DICE

Solar Geoengineering, Learning, and Experimentation

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