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The physics of the heat-trapping properties of CO ${}_2$were established in the mid-19th century, as fossil fuel burning rapidly increased atmospheric CO ${}_2$levels. To date, however, research has not probed when climate change could have been detected if scientists in the 19th century had the current models and observing network. We consider this question in a thought experiment with state-of-the-art climate models. We assume that the capability to make accurate measurements of atmospheric temperature changes existed in 1860, and then apply a standard “fingerprint” method to determine the time at which a human-caused climate change signal was first detectable. Pronounced cooling of the mid- to upper stratosphere, mainly driven by anthropogenic increases in carbon dioxide, would have been identifiable with high confidence by approximately 1885, before the advent of gas-powered cars. These results arise from the favorable signal-to-noise characteristics of the mid- to upper stratosphere, where the signal of human-caused cooling is large and the pattern of this cooling differs markedly from patterns of intrinsic variability. Even if our monitoring capability in 1860 had not been global, and high-quality stratospheric temperature measurements existed for Northern Hemisphere mid-latitudes only, it still would have been feasible to detect human-caused stratospheric cooling by 1894, only 34 y after the assumed start of climate monitoring. Our study provides strong evidence that a discernible human influence on atmospheric temperature has likely existed for over 130 y. 

Abstract The patterns associated with the top-of-the-atmosphere radiative responseRto surface temperatureTare typically explored through two relationships: 1) the spatially varying radiative response to spatially varying changes in temperature (ΔR_i/ΔT_i) and 2) the spatially varying radiative response to global-mean changes in temperature (ΔR_i/ΔT). Here, we explore the insights provided by an alternative parameter: the global-mean radiative response to changes in spatially varying temperature (ΔR/ΔT_i). The pattern ΔR/ΔT_iindicates regions where surface temperature covaries withRand thus provides a statistical analog to the causal response functions derived from atmospheric Green’s function experiments. The pattern can be transformed so that it can be globally averaged and thus indicates the local contribution to the global feedback parameter. The transformed version of ΔR/ΔT_icorresponds to the pattern in surface temperature whose expansion coefficient time series explains the maximum fraction of the covariance betweenRandT_i. It explains roughly the same fraction of internal variability inRas that explained by the Green’s function approach. We focus on the physical insights provided by ΔR/ΔT_iwhen it is estimated from regression analyses of monthly mean observations. Consistent with the results of Green’s function experiments, the observational analyses indicate negative contributions to the global internal feedback parameter over the western Pacific and positive contributions over the southeastern tropical Pacific. Unlike the results of such experiments, the analyses indicate notable negative contributions to the global feedback parameter over land areas. When estimated from observations, temperature variability over the land areas accounts for ∼70% of the negative global internal feedback, whereas variability over the southeastern tropical Pacific reduces the global-mean negative internal feedback by ∼10%. 

Abstract We compare insights provided by local and large‐scale perspectives of extreme heat events in ERA5 near‐surface temperature data. Heat waves where temperatures exceed four standard deviations about the climatological‐mean are expected less than once a century locally but occur roughly once every 10 days somewhere in the Northern Hemisphere midlatitudes. The high frequency of occurrence indicated by the hemispheric perspective is not well represented by normal statistics because it strongly depends on the shapes of the local temperature distributions. The large effective sample size afforded by the hemispheric perspective provides robust evidence of trends in the frequency of occurrence of extreme heat events integrated over the Northern Hemisphere. It also confirms that trends in heat events summed over the hemisphere can be explained by changes in mean temperature alone.