Morris Jennifer, Sokolov Andrei, Reilly John, Libardoni Alex, Forest Chris, Paltsev Sergey, Schlosser C Adam, Prinn Ronald, Jacoby Henry
MIT Center for Sustainability Science and Strategy, Massachusetts Institute of Technology, Cambridge, MA, USA.
Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, USA.
Nat Commun. 2025 Mar 19;16(1):2703. doi: 10.1038/s41467-025-57897-1.
Information about the likelihood of various outcomes is needed to inform discussions about climate mitigation and adaptation. Here we provide integrated, probabilistic socio-economic and climate projections, using estimates of probability distributions for key parameters in both human and Earth system components of a coupled model. We find that policy lowers the upper tail of temperature change more than the median. We also find that while human system uncertainties dominate uncertainty of radiative forcing, Earth system uncertainties contribute more than twice as much to temperature uncertainty in scenarios without fixed emissions paths, reflecting the uncertainty of translating radiative forcing into temperature. The combination of human and Earth system uncertainty is less than additive, illustrating the value of integrated modeling. Further, we find that policy costs are more uncertain in low- and middle-income economies, and that renewables are robust investments across a wide range of policies and socio-economic uncertainties.
为了为有关气候缓解和适应的讨论提供信息，需要了解各种结果的可能性。在此，我们使用耦合模型中人类和地球系统组件关键参数的概率分布估计，提供综合的、概率性的社会经济和气候预测。我们发现，政策对温度变化上尾的降低幅度大于中位数。我们还发现，虽然人类系统的不确定性主导了辐射强迫的不确定性，但在没有固定排放路径的情景中，地球系统的不确定性对温度不确定性的贡献是其两倍多，这反映了将辐射强迫转化为温度的不确定性。人类和地球系统不确定性的组合小于两者相加的结果，这说明了综合建模的价值。此外，我们发现低收入和中等收入经济体的政策成本更具不确定性，并且可再生能源在广泛的政策和社会经济不确定性范围内都是稳健的投资。
