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Solar Geoengineering, Learning, and Experimentation
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DOI：10.1086/729608.png)
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摘要
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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.
Keyword:
C61
C63
D81
D83
Q54
Q55
Q58
geoengineering
climate change
uncertainty
learning
integrated assessment
feedbacks
solar radiation management
abatement
DICE
期刊
J
IF:
3.2
论文数:
421
被引数:
1.9K
机构
引用论文
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