Stabilizing global mean surface temperature: A feedback control perspective |
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| Authors: | Andrew Jarvis David Leedal C. James Taylor Peter Young |
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| Affiliation: | 1. Department of Electronics Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China;2. Department of Communication Engineering, Xiamen University, Xiamen 361005, China;3. Department of Imaging Sciences, University of Rochester, Rochester, NY 14642, USA;1. Department of Biomedical Engineering, Tsinghua University, Beijing, China;2. Key Laboratory of Particle and Radiation Imaging, Ministry of Education, Medical Physics and Engineering Institute, Department of Engineering Physics, Tsinghua University, Beijing, China;3. Department of Orthopedics, First Affiliated Hospital of PLA General Hospital, Beijing, China |
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| Abstract: | In this paper, we develop a discrete time, state variable feedback control regime to analyze the closed-loop properties associated with stabilizing the global mean surface temperature anomaly at 2 °C within a sequential decision making framework made up of 20 year review periods beginning in 2020. The design of the feedback control uses an optimal control approach that minimizes the peak deceleration of anthropogenic CO2 emissions whilst avoiding overshooting the 2 °C target. The peak value for emissions deceleration that satisfies the closed-loop optimization was found to be linearly related to climate sensitivity and a climate sensitivity of 3.5 °C gave a deceleration of ?1.9 GtC/a/20 years2. In addition to accounting for the predicted climate dynamics, the control system design includes a facility to emulate a robust corrective action in the face of uncertainty. The behavior of the overall control action is evaluated using an uncertainty scenario for climate model equilibrium sensitivity. |
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