Assessing the controllability of Arctic sea ice extent by sulfate aerosol geoengineering

By L. Jackson, J. Crook, A. Jarvis, D. Leedal, A. Ridgwell, N. Vaughan, Piers M. Forster. 2015

In an assessment of how Arctic sea ice cover could be remediated in a warming world, we simulated the injection of SO2 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. SO2 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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Citations in the corpus

• Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem (2019, background): “ control within the climate community is currently constrained to low-dimensional injection pattern parametrisations (Ban-Weiss & Caldeira,2010) or manual grid search over edge cases of interest (Jackson, 2015). Even in simple settings, it has been shown that regional climate response is sensiti”