I discuss this in the paper under the heading of ‘unknown risks’. I tend to deflate their significance because SAI has natural analogues—volcanoes, which haven’t set off said catastrophic spirals. The massive 1991 pinatubo eruption reduced global temperatures by 0.5 degreesish. There is also already an enormous amount of tropospheric cooling due to industrial emissions of sulphur and other particulates. The effects of this could be very substantial - (from memory) at most cancelling out up to half of the total warming effect of all CO2 ever emitted. Due to concerns about air pollution, we are now reducing emissions of these tropospheric aerosols. This could have a very substantial warming effect.
Concerns about model uncertainty cut in both directions and I think the preponderance of probabilities favours SAI (provided it can be governed safely). Estimates of the sensitivity of the climate to CO2 are also beset by model uncertainty. The main worry is the unprecedented warming effect from CO2 having unexpected runaway effects on the ecosystem. It is clear that SAI would allow us to reduce global temperatures and so would on average reduce the risk of heat-induced tipping points or runaway processes. Moreover, SAI is controllable on tight timescales—we get a response to our action within weeks—allowing us to respond if something weird starts happening as a result of GHGs or of SAI. The downside risk associated with model uncertainty about climate sensitivity to GHGs is much greater than that associated with the effects of SAI, in my opinion. SAI is insurance against this model uncertainty.
Concerns about model uncertainty cut in both directions and I think the preponderance of probabilities favours SAI (provided it can be governed safely)
Good point. Agreed. Had not considered this
I tend to deflate their significance because SAI has natural analogues… volcanoes … industrial emissions.
This seems like flawed thinking to me. Data from natural analogues should be built into predictive SAI models. Accepting that model uncertainty is a factor worth considering means questioning whether these analogues are actually good predictors of the full effects of SAI.
(Note: LHC also had natural analogues in atmospheric cosmic rays, I believe this was accounted for in FHI’s work on the matter)
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I think the main thing that model uncertainty suggests is that mitigation or less extreme forms of geoengineering should be prioritised much more.
SAI has advantages that other approaches don’t have, which is why it is insurance against model uncertainty about the sensitivity of the climate to GHGs. Carbon dioxide removal is much slower acting, will be incredibly expensive and has other costs. The other main proposed form of solar geoengineering involves tropospheric cooling by brightening clouds etc. Uncertainties about this are probably greater than for SAI.
I discuss this in the paper under the heading of ‘unknown risks’. I tend to deflate their significance because SAI has natural analogues—volcanoes, which haven’t set off said catastrophic spirals. The massive 1991 pinatubo eruption reduced global temperatures by 0.5 degreesish. There is also already an enormous amount of tropospheric cooling due to industrial emissions of sulphur and other particulates. The effects of this could be very substantial - (from memory) at most cancelling out up to half of the total warming effect of all CO2 ever emitted. Due to concerns about air pollution, we are now reducing emissions of these tropospheric aerosols. This could have a very substantial warming effect.
Concerns about model uncertainty cut in both directions and I think the preponderance of probabilities favours SAI (provided it can be governed safely). Estimates of the sensitivity of the climate to CO2 are also beset by model uncertainty. The main worry is the unprecedented warming effect from CO2 having unexpected runaway effects on the ecosystem. It is clear that SAI would allow us to reduce global temperatures and so would on average reduce the risk of heat-induced tipping points or runaway processes. Moreover, SAI is controllable on tight timescales—we get a response to our action within weeks—allowing us to respond if something weird starts happening as a result of GHGs or of SAI. The downside risk associated with model uncertainty about climate sensitivity to GHGs is much greater than that associated with the effects of SAI, in my opinion. SAI is insurance against this model uncertainty.
Good point. Agreed. Had not considered this
This seems like flawed thinking to me. Data from natural analogues should be built into predictive SAI models. Accepting that model uncertainty is a factor worth considering means questioning whether these analogues are actually good predictors of the full effects of SAI.
(Note: LHC also had natural analogues in atmospheric cosmic rays, I believe this was accounted for in FHI’s work on the matter)
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I think the main thing that model uncertainty suggests is that mitigation or less extreme forms of geoengineering should be prioritised much more.
I agree that mitigation should be prioritised.
SAI has advantages that other approaches don’t have, which is why it is insurance against model uncertainty about the sensitivity of the climate to GHGs. Carbon dioxide removal is much slower acting, will be incredibly expensive and has other costs. The other main proposed form of solar geoengineering involves tropospheric cooling by brightening clouds etc. Uncertainties about this are probably greater than for SAI.