In an assessment of how Arctic sea ice cover could be remediated in a warming world, we simulated the injection of SO 2 into the Arctic stratosphere making annual adjustments to injection rates. We treated one climate model realization as a surrogate “real world” with imperfect “observations” and no rerunning or reference to control simulations. SO 2 injection rates were proposed using a novel model predictive control regime which incorporated a second simpler climate model to forecast “optimal” decision pathways. Commencing the simulation in 2018, Arctic sea ice cover was remediated by 2043 and maintained until solar geoengineering was terminated. We found quantifying climate side effects problematic because internal climate variability hampered detection of regional climate changes beyond the Arctic. Nevertheless, through decision maker learning and the accumulation of at least 10 years time series data exploited through an annual review cycle, uncertainties in observations and forcings were successfully managed.
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Jackson et al. (2015) studied this question.
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