Effective climate policy requires information from various scientific disciplines. Here, we construct a metamodel from climate and integrated assessment models that assesses the emissions budget, costs and uncertainty sources of achieving temperature targets. By calibrating to the model-based literature range, the metamodel goes beyond the parametric uncertainty of individual models. The resulting median estimates for the cumulative abatement costs (at 5% discount rate) for 2 °C and 1.5 °C targets are around US$15 trillion and US$30 trillion, but estimates vary over a wide range (US$10–100 trillion for the 1.5 °C target). The sources determining this uncertainty depend on the climate target stringency. Climate system uncertainty dominates at high warming levels, but uncertainty in emissions reductions costs dominates for the Paris Agreement targets. In fact, costs differences between different socio-economic development paths can be larger than the difference in median estimates for the 2 °C and 1.5 °C targets. This simple metamodel helps to explore implications of scenario uncertainty and identify research priorities.

有效的气候政策需要来自各种科学学科的信息。在这里，我们从气候和综合评估模型构建了一个元模型，用于评估排放预算，成本和实现温度目标的不确定性来源。通过校准基于模型的文献范围，元模型超越了单个模型的参数不确定性。由此得出的2°C和1.5°C目标的累计减排成本（按5％的折现率）的中位数估算值约为15万亿美元和30万亿美元，但估算值的变化范围很广（10-20万亿美元）。 1.5°C目标）。确定这种不确定性的来源取决于气候目标的严格程度。气候系统的不确定性在高变暖水平上占主导地位，但是减排成本的不确定性在《巴黎协定》的目标中占主导地位。实际上，不同社会经济发展路径之间的成本差异可能会大于2°C和1.5°C目标的中位数估算值之间的差异。这个简单的元模型有助于探索情景不确定性的含义并确定研究重点。