'Tis the seasonal Anthropogenic climate change has become clearly observable through many metrics. These include an increase in global annual temperatures, growing heat content of the oceans, and sea level rise owing to the melting of the polar ice sheets and glaciers. Now, Santer et al. report that a human-caused signal in the seasonal cycle of tropospheric temperature can also be measured (see the Perspective by Randel). They use satellite data and the anthropogenic “fingerprint” predicted by climate models to show the extent of the effects and discuss how these changes have been caused. Science, this issue p. eaas8806; see also p. 227 Human activity is causing changes in the seasonal cycle of tropospheric temperature. INTRODUCTION Fingerprint studies use pattern information to separate human and natural influences on climate. Most fingerprint research relies on patterns of climate change that are averaged over years or decades. Few studies probe shorter time scales. We consider here whether human influences are identifiable in the changing seasonal cycle. We focus on Earth’s troposphere, which extends from the surface to roughly 16 km at the tropics and 13 km at the poles. Our interest is in TAC, the geographical pattern of the amplitude of the annual cycle of tropospheric temperature. Information on how TAC has changed over time is available from satellite retrievals and from large multimodel ensembles of simulations. RATIONALE At least three lines of evidence suggest that human activities have affected the seasonal cycle. First, there are seasonal signals in certain human-caused external forcings, such as stratospheric ozone depletion and particulate pollution. Second, there is seasonality in some of the climate feedbacks triggered by external forcings. Third, there are widespread signals of seasonal changes in the distributions and abundances of plant and animal species. These biological signals are in part mediated by seasonal climate changes arising from global warming. All three lines of evidence provide scientific justification for performing fingerprint studies with the seasonal cycle. RESULTS The simulated response of the seasonal cycle to historical changes in human and natural factors has prominent mid-latitude increases in the amplitude of TAC. These features arise from larger mid-latitude warming in the summer hemisphere, which appears to be partly attributable to continental drying. Because of land-ocean differences in heat capacity and hemispheric asymmetry in land fraction, mid-latitude increases in TAC are greater in the Northern Hemisphere than in the Southern Hemisphere. Qualitatively similar large-scale patterns of annual cycle change occur in satellite tropospheric temperature data. We applied a standard fingerprint method to determine (i) whether the pattern similarity between the model “human influence” fingerprint and satellite temperature data increases with time, and (ii) whether such an increase is significant relative to random changes in similarity between the fingerprint and patterns of natural internal variability. This method yields signal-to-noise (S/N) ratios as a function of increasing satellite record length. Fingerprint detection occurs when S/N exceeds and remains above the 1% significance threshold. We find that the model fingerprint of externally forced seasonal cycle changes is identifiable with high statistical confidence in five out of six satellite temperature datasets. In these five datasets, S/N ratios for the 38-year satellite record vary from 2.7 to 5.8. Our positive fingerprint detection results are unaffected by the removal of all global mean information and by the exclusion of sea ice regions. On time scales for which meaningful tests are possible (one to two decades), there is no evidence that S/N ratios are spuriously inflated by a systematic model underestimate of the amplitude of observed tropospheric temperature variability. CONCLUSION Our results suggest that attribution studies with the seasonal cycle of tropospheric temperature provide powerful and novel evidence for a statistically significant human effect on Earth’s climate. We hope that this finding will stimulate more detailed exploration of the seasonal signals caused by anthropogenic forcing. Trends in the amplitude of the annual cycle of tropospheric temperature. Trends are calculated over 1979 to 2016 and are averages from a large multimodel ensemble of historical simulations. The most prominent features are pronounced mid-latitude increases in annual cycle amplitude (shown in red) in both hemispheres. Similar mid-latitude increases occur in satellite temperature data. Trends are superimposed on NASA’s “blue marble” image. We provide scientific evidence that a human-caused signal in the seasonal cycle of tropospheric temperature has emerged from the background noise of natural variability. Satellite data and the anthropogenic “fingerprint” predicted by climate models show common large-scale changes in geographical patterns of seasonal cycle amplitude. These common features include increases in amplitude at mid-latitudes in both hemispheres, amplitude decreases at high latitudes in the Southern Hemisphere, and small changes in the tropics. Simple physical mechanisms explain these features. The model fingerprint of seasonal cycle changes is identifiable with high statistical confidence in five out of six satellite temperature datasets. Our results suggest that attribution studies with the changing seasonal cycle provide powerful evidence for a significant human effect on Earth’s climate.

中文翻译：

---

人类对对流层温度季节循环的影响

'这是通过许多指标可以清楚地观察到季节性人为气候变化。其中包括全球年气温升高、海洋热含量增加以及由于极地冰盖和冰川融化导致海平面上升。现在，桑特等人。报告还可以测量对流层温度季节性周期中的人为信号（参见 Randel 的观点）。他们使用卫星数据和气候模型预测的人为“指纹”来显示影响的程度并讨论这些变化是如何引起的。科学，这个问题 p。eaas8806; 另见第。227 人类活动正在引起对流层温度季节性周期的变化。简介 指纹研究使用模式信息来区分人类和自然对气候的影响。大多数指纹研究依赖于平均数年或数十年的气候变化模式。很少有研究探讨更短的时间尺度。我们在这里考虑在不断变化的季节性周期中是否可以识别人类的影响。我们关注地球的对流层，它从地表延伸到热带约 16 公里和两极约 13 公里。我们的兴趣在于 TAC，即对流层温度年循环幅度的地理模式。关于 TAC 如何随时间变化的信息可从卫星检索和大型多模型模拟集合中获得。基本原理 至少有三项证据表明人类活动影响了季节性周期。首先，某些人为外部强迫存在季节性信号，例如平流层臭氧消耗和颗粒物污染。其次，外部强迫引发的一些气候反馈具有季节性。第三，植物和动物物种的分布和丰度存在季节性变化的广泛信号。这些生物信号部分是由全球变暖引起的季节性气候变化介导的。所有三行证据都为使用季节性周期进行指纹研究提供了科学依据。结果季节周期对人类和自然因素历史变化的模拟响应在中纬度TAC幅度上有显着增加。这些特征源于夏季半球较大的中纬度变暖，这似乎部分归因于大陆干燥。由于陆地-海洋的热容量差异和半球陆地部分的不对称性，北半球中纬度地区的 TAC 增加幅度大于南半球。在卫星对流层温度数据中，年周期变化的大尺度模式在质量上相似。我们应用标准指纹方法来确定（i）模型“人类影响”指纹与卫星温度数据之间的模式相似性是否随时间增加，以及（ii）这种增加是否相对于指纹之间相似性的随机变化显着和自然内部变异的模式。这种方法产生信噪比 (S/N) 作为增加卫星记录长度的函数。当 S/N 超过并保持在 1% 显着性阈值以上时，就会发生指纹检测。我们发现，在六个卫星温度数据集中的五个数据集中，外部强迫季节性周期变化的模型指纹具有很高的统计置信度。在这五个数据集中，38 年卫星记录的信噪比从 2.7 到 5.8 不等。我们的正面指纹检测结果不受去除所有全局平均信息和排除海冰区域的影响。在可能进行有意义测试的时间尺度上（1 到 20 年），没有证据表明信噪比因系统模型低估了观测到的对流层温度变化幅度而被虚假夸大。结论 我们的结果表明，对流层温度季节性周期的归因研究为人类对地球气候具有统计学意义的影响提供了强有力的新证据。我们希望这一发现将激发对人为强迫引起的季节性信号的更详细的探索。对流层温度年循环幅度的趋势。趋势是从 1979 年到 2016 年计算的，并且是来自历史模拟的大型多模型集合的平均值。最突出的特征是在两个半球的年周期幅度（以红色显示）在中纬度显着增加。类似的中纬度增加出现在卫星温度数据中。趋势叠加在 NASA 的“蓝色大理石”图像上。我们提供了科学证据，表明对流层温度季节性周期中的人为信号已经从自然变化的背景噪声中出现。卫星数据和气候模型预测的人为“指纹”显示了季节性周期幅度地理模式的普遍大规模变化。这些共同特征包括两个半球中纬度的振幅增加，南半球高纬度的振幅减小，以及热带的小幅变化。简单的物理机制解释了这些特征。在六个卫星温度数据集中的五个数据集中，季节性周期变化的模型指纹具有很高的统计置信度。