Energy budget constraints on historical radiative forcing
Energy budget constraints on historical radiative forcing
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DOI：
10.1038/s41558-020-0696-1
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发表时间：
2020-02-10
影响因子：
30.7
通讯作者：
Forster, Piers M.
中科院分区：
文献类型：
--
作者：
Andrews, Timothy;Forster, Piers M.
人类和自然驱动因素（有效辐射强迫）造成的地球能量失衡很难受到约束，从而加剧了长期气候变化的不确定性。自上而下的观测约束使IPCC AR 5评估的不确定性降低了近40%，并表明模型偏低。辐射强迫是理解过去和未来气候变化的人为和自然驱动因素的基本量（1），但在我们对辐射强迫及其模型表示的量化中仍然存在显著的不确定性（2-4）。在这里，我们使用的历史全球平均表面温度变化和地球的总热量吸收的仪器测量，以及地球的辐射响应的估计，提供一个自上而下的能量预算约束的历史（1861-1880年到近现在）的有效辐射强迫为2.3 W m（-2）（1.7- 3.0 W m（-2）; 5-95%的置信区间）。这意味着IPCC第五次评估报告（2）评估的5-95%不确定性范围减少了近40%。虽然在模式中有效辐射强迫的精确估计并不广泛存在，我们的研究结果表明，有效辐射强迫可能太小，在耦合模式相互比较项目的第五阶段多达三分之一的气候模式。改进辐射强迫的模型表现应该是模拟中心的一个优先事项。这将减少持续了几十年的气候预测的不确定性（4，5）。
Earth's energy imbalance from human and natural drivers-effective radiative forcing-is difficult to constrain, contributing to uncertainty in long-term climate change. A top-down observational constraint reduces IPCC AR5 assessed uncertainty by nearly 40% and suggests models are biased low.Radiative forcing is a fundamental quantity for understanding anthropogenic and natural drivers of past and future climate change(1), yet significant uncertainty remains in our quantification of radiative forcing and its model representation(2-4). Here we use instrumental measurements of historical global mean surface temperature change and Earth's total heat uptake, alongside estimates of the Earth's radiative response, to provide a top-down energy budget constraint on historical (1861-1880 to near-present) effective radiative forcing of 2.3 W m(-2) (1.7-3.0W m(-2); 5-95% confidence interval). This represents a near 40% reduction in the 5-95% uncertainty range assessed by the IPCC Fifth Assessment Report(2). Although precise estimates of effective radiative forcing in models do not widely exist, our results suggest that the effective radiative forcing may be too small in as many as one-third of climate models in the fifth phase of the Coupled Model Intercomparison Project. Improving model representation of radiative forcing should be a priority for modelling centres. This will reduce uncertainties in climate projections that have persisted for decades(4,5).