Solar Geoengineering, Learning, and Experimentation

[Andrew Lockley]

Solar Geoengineering, Learning, and Experimentation

David L. Kelly, Garth Heutel, Juan B. Moreno-Cruz, and Soheil Shayegh

NBER Working Paper No. 28442

February 2021

JEL No. D83,Q54

ABSTRACT

Solar geoengineering (SGE) can combat climate change by directly reducing temperatures. Both

SGE and the climate 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.

[Renaud de RICHTER]

Does the author's conclusions apply to "cool roofs", "bright water - hydrosols", and "marine cloud brightening"?

The title, abstract and conclusions are unclear.

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