论文标题
短暂瞬态变暖模拟的平衡气候灵敏度的多元估计
Multivariate Estimations of Equilibrium Climate Sensitivity from Short Transient Warming Simulations
论文作者
论文摘要
衡量气候变化影响的最常用的指标之一是气候敏感性，定义为长期（平衡）温度升高，导致瞬时大气中的瞬时加倍。由于在实践中无法完全平衡全球气候模型，因此外推技术可用于估算瞬态变暖模拟的平衡状态。由于气候反馈的丰富性 - 跨越各种时间尺度 - 很难从短期序列中提取长期行为；主要使用的技术仅能够检测单个最主的本征模，从而妨碍了它们提供准确的长期估计的能力。在这里，我们通过将来自多个可观察结果的数据合并到多组分线性回归模型中，向这些方法提出扩展。这样，不仅捕获了气候系统的主要和次数征收算术，从而从短，未平衡的时间序列中获得了更好的长期估计。
One of the most used metrics to gauge the effects of climate change is the equilibrium climate sensitivity, defined as the long-term (equilibrium) temperature increase resulting from instantaneous doubling of atmospheric CO$_2$. Since global climate models cannot be fully equilibrated in practice, extrapolation techniques are used to estimate the equilibrium state from transient warming simulations. Because of the abundance of climate feedbacks - spanning a wide range of temporal scales - it is hard to extract long-term behaviour from short-time series; predominantly used techniques are only capable of detecting the single most dominant eigenmode, thus hampering their ability to give accurate long-term estimates. Here, we present an extension to those methods by incorporating data from multiple observables in a multi-component linear regression model. This way, not only the dominant but also the next-dominant eigenmodes of the climate system are captured, leading to better long-term estimates from short, non-equilibrated time series.
