Abstract. The response of the global climate–carbon-cycle system to anthropogenic perturbations happens differently at different timescales. The unravelling of the memory structure underlying this timescale dependence is a major challenge in climate research. Recently the widely applied α–β–γ framework proposed by Friedlingstein et al. (2003) to quantify climate–carbon-cycle feedbacks has been generalized to account also for such internal memory. By means of this generalized framework, we investigate the timescale dependence of the airborne fraction for a set of Earth system models that participated in CMIP5 (Coupled Model Intercomparison Project Phase 5). The analysis is based on published simulation data from C4MIP-type (Coupled Climate–Carbon Cycle Model Intercomparison) experiments with these models. Independently of the considered scenario, the proposed generalization describes at global scale the reaction of the climate–carbon system to sufficiently weak perturbations. One prediction from this theory is how the timescale-resolved airborne fraction depends on the underlying feedbacks between climate and the carbon cycle. These feedbacks are expressed as timescale-resolved functions depending solely on analogues of the α, β, and γ sensitivities, introduced in the generalized framework as linear response functions. In this way a feedback-dependent quantity (airborne fraction) is predicted from feedback-independent quantities (the sensitivities). This is the key relation underlying our study. As a preparatory step, we demonstrate the predictive power of the generalized framework exemplarily for simulations with the Max Planck Institute (MPI) Earth System Model. The whole approach turns out to be valid for perturbations of up to an about 100 ppm CO2 rise above the pre-industrial level; beyond this value the response becomes non-linear. By means of the generalized framework we then derive the timescale dependence of the airborne fraction from the underlying climate–carbon-cycle feedbacks for an ensemble of CMIP5 models. Our analysis reveals that for all studied CMIP5 models (1) the total climate–carbon-cycle feedback is negative at all investigated timescales, (2) the airborne fraction generally decreases for increasing timescales, and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all these timescales. Qualitatively similar results were previously found by employing the original α–β–γ framework to particular perturbation scenarios, but our study demonstrates that, although obtained from particular scenario simulations, they are characteristics of the coupled climate–carbon-cycle system as such, valid at all considered timescales. These more general conclusions are obtained by accounting for the internal memory of the system as encoded in the generalized sensitivities, which in contrast to the original α, β, and γ are scenario-independent.

中文翻译：

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CMIP5 模型中空气传播部分的时间尺度依赖性和弱扰动的潜在气候-碳循环反馈

摘要。全球气候-碳循环系统对人为扰动的反应在不同的时间尺度上发生不同的情况。揭示这种时间尺度依赖性背后的记忆结构是气候研究的一个重大挑战。最近，Friedlingstein 等人提出了广泛应用的 α-β-γ 框架。 （2003）量化气候-碳循环反馈的方法已被推广到也解释了这种内部记忆。通过这个广义框架，我们研究了参与 CMIP5（耦合模型比对项目第五阶段）的一组地球系统模型的空气部分的时间尺度依赖性。该分析基于已发布的 C4MIP 型（耦合气候-碳循环模型比较）实验的模拟数据。独立于所考虑的情景，所提出的概括描述了全球范围内气候-碳系统对足够弱的扰动的反应。该理论的一个预测是，时间尺度解析的空气传播部分如何取决于气候和碳循环之间的潜在反馈。这些反馈被表示为时间尺度解析函数，仅依赖于 α、β 和 γ 灵敏度的类似物，在广义框架中作为线性响应函数引入。通过这种方式，可以根据与反馈无关的量（灵敏度）来预测与反馈相关的量（空气传播分数）。这是我们研究的关键关系。作为准备步骤，我们以马克斯·普朗克研究所 (MPI) 地球系统模型为例，展示了通用框架的预测能力。事实证明，整个方法对于二氧化碳比工业化前水平上升约 100 ppm 的扰动是有效的；超过该值，响应将变得非线性。然后，通过广义框架，我们从 CMIP5 模型集合的基础气候-碳循环反馈中得出空气传播部分的时间尺度依赖性。我们的分析表明，对于所有研究的 CMIP5 模型（1）在所有研究的时间尺度上，总的气候-碳循环反馈都是负的，（2）空气传播部分通常随着时间尺度的增加而减少，（3）陆地生物地球化学反馈在模型中占主导地位在所有这些时间尺度上在空气中传播。之前通过将原始的α-β-γ框架应用于特定的扰动情景，发现了定性上相似的结果，但我们的研究表明，尽管是从特定情景模拟中获得的，但它们是耦合气候-碳循环系统本身的特征，有效在所有考虑的时间尺度上。这些更一般的结论是通过考虑编码在广义敏感度中的系统内部记忆而获得的，与原始的 α、β 和 γ 相比，它是与场景无关的。