Feedback control algorithms are important tools in climate intervention simulation design because they facilitate “top-down” design, in which climate goals (often temperatures) are prescribed and a strategy chosen to meet the target. This approach is commonly used in simulations of stratospheric aerosol injection (SAI) interventions, but have never been used with marine cloud brightening (MCB) interventions. Using data from previously published MCB simulations, we use the Community Earth System Model (CESM2) to simulate MCB deployments over regions which expand with time to limit global warming to 1.5°C in the SSP2-4.5 scenario, and we design a feedback control algorithm to determine the scope of intervention each year. Our methodology is able to control global mean temperature in this way, but controlling global mean temperature does not by itself mitigate regional impacts common to tropical MCB; additionally, the algorithm takes longer than intended to converge, indicating room for future improvement.

中文翻译：

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反馈算法调控海洋云增亮的首次模拟


反馈控制算法是气候干预模拟设计中的重要工具，因为它们促进了“自上而下”的设计，其中规定了气候目标（通常是温度）并选择了满足目标的策略。这种方法通常用于平流层气溶胶喷射 （SAI） 干预的模拟，但从未与海洋云增亮 （MCB） 干预一起使用。使用来自先前发布的 MCB 模拟的数据，我们使用社区地球系统模型 （CESM2） 来模拟 MCB 部署在随时间扩展的区域，以在 SSP2-4.5 情景中将全球变暖限制在 1.5°C，并且我们设计了一种反馈控制算法来确定每年的干预范围。我们的方法能够以这种方式控制全球平均温度，但控制全球平均温度本身并不能减轻热带 MCB 常见的区域影响;此外，该算法收敛的时间比预期的要长，这表明未来还有改进的空间。