Radiative Feedbacks From Stochastic Variability in Surface Temperature and Radiative Imbalance
Radiative Feedbacks From Stochastic Variability in Surface Temperature and Radiative Imbalance
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表面温度随机变化和辐射不平衡的辐射反馈
DOI：
10.1029/2018gl077678
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发表时间：
2018
影响因子：
5.2
通讯作者：
Bitz, Cecilia M.
中科院分区：
文献类型：
--
作者：
Proistosescu, Cristian;Donohoe, Aaron;Armour, Kyle C.;Roe, Gerard H.;Stuecker, Malte F.;Bitz, Cecilia M.
通过回归大气层顶（TOA）能量不平衡和地表温度波动获得的辐射反馈估计值严重依赖于采样间隔和关于驱动内部变率的随机强迫性质的假设。在这里，我们开发了一个能量平衡框架，使我们能够模拟随机大气和海洋强迫反馈估计的不同影响。不同强迫分量的贡献基于其对近地面气温和TOA能量通量协方差结构的影响进行解析，该框架在跨越一系列海洋配置的气候模式模拟中得到验证，并再现了观测中看到的关键特征。我们发现，至少有三个不同的强迫源，反馈和时间尺度需要解释完整的协方差结构。大气和海洋强迫驱动的变化模式与温度和TOA辐射之间的独特关系，导致类似于回归稀释的效果。基于净回归的反馈估计被发现是与每个模式相关联的不同反馈的加权平均值。此外，估计的反馈取决于是否表面温度和TOA能量通量的采样在每月或每年的时间尺度。结果表明，基于回归的反馈估计反映了随机强迫组合的贡献，不应被解释为提供控制气候对温室气体强迫响应的辐射反馈的估计。
Estimates of radiative feedbacks obtained by regressing fluctuations in top‐of‐atmosphere (TOA) energy imbalance and surface temperature depend critically on the sampling interval and on assumptions about the nature of the stochastic forcing driving internal variability. Here we develop an energy balance framework that allows us to model the different impacts of stochastic atmospheric and oceanic forcing on feedback estimates. The contribution of different forcing components is parsed based on their impacts on the covariance structure of near‐surface air temperature and TOA energy fluxes, and the framework is validated in a hierarchy of climate model simulations that span a range of oceanic configurations and reproduce the key features seen in observations. We find that at least three distinct forcing sources, feedbacks, and time scales are needed to explain the full covariance structure. Atmospheric and oceanic forcings drive modes of variability with distinct relationships between temperature and TOA radiation, leading to an effect akin to regression dilution. The net regression‐based feedback estimate is found to be a weighted average of the distinct feedbacks associated with each mode. Moreover, the estimated feedback depends on whether surface temperature and TOA energy fluxes are sampled at monthly or annual time scales. The results suggest that regression‐based feedback estimates reflect contributions from a combination of stochastic forcings and should not be interpreted as providing an estimate of the radiative feedback governing the climate response to greenhouse gas forcing.
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