Grantham Institute, Imperial College London, London SW7 2AZ, United Kingdom;
Department of Physics, Imperial College London, London SW7 2AZ, United Kingdom.
Proc Natl Acad Sci U S A. 2021 Jul 27;118(30). doi: 10.1073/pnas.2026290118.
Global warming drives changes in Earth's cloud cover, which, in turn, may amplify or dampen climate change. This "cloud feedback" is the single most important cause of uncertainty in Equilibrium Climate Sensitivity (ECS)-the equilibrium global warming following a doubling of atmospheric carbon dioxide. Using data from Earth observations and climate model simulations, we here develop a statistical learning analysis of how clouds respond to changes in the environment. We show that global cloud feedback is dominated by the sensitivity of clouds to surface temperature and tropospheric stability. Considering changes in just these two factors, we are able to constrain global cloud feedback to 0.43 ± 0.35 W⋅m⋅K (90% confidence), implying a robustly amplifying effect of clouds on global warming and only a 0.5% chance of ECS below 2 K. We thus anticipate that our approach will enable tighter constraints on climate change projections, including its manifold socioeconomic and ecological impacts.
全球变暖导致地球云覆盖的变化,而这反过来又可能放大或减缓气候变化。这种“云反馈”是气候敏感度(Equilibrium Climate Sensitivity,简称 ECS)——大气二氧化碳倍增后的全球变暖平衡——中不确定性的唯一最重要原因。我们使用地球观测数据和气候模型模拟,对云如何响应环境变化进行了统计学习分析。我们表明,全球云反馈主要由云对地表温度和对流层稳定性的敏感性决定。仅考虑这两个因素的变化,我们就能够将全球云反馈限制在 0.43 ± 0.35 W⋅m⋅K(90%置信区间),这意味着云对全球变暖具有稳健的放大效应,而 ECS 低于 2 K 的可能性仅为 0.5%。因此,我们预计我们的方法将能够更严格地限制气候变化预测,包括其多方面的社会经济和生态影响。