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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 We investigate changes in the vertical structure of the ocean temperature annual cycle amplitude (TEMP_AC) down to a depth of 300 m, providing important insights into the relative contributions of anthropogenic and natural influences. Using observations and phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we perform a detection and attribution analysis by applying a standard pattern-based “fingerprint” method to zonal-mean TEMP_ACanomalies for three major ocean basins. In all model historical simulations and observational datasets, TEMP_ACincreases significantly in the surface layer, except in the Southern Ocean, and weakens within the subsurface ocean. There is a decrease in TEMP_ACbelow the annual-mean mixed layer depth, mainly due to a deep-reaching winter warming signal. The temporal evolution of signal-to-noise (S/N) ratios in observations indicates an identifiable anthropogenic fingerprint in both surface and interior ocean annual temperature cycles. These findings are consistent across three different observational datasets, with variations in fingerprint detection time likely related to differences in dataset coverage, interpolation method, and accuracy. Analysis of CMIP6 single-forcing simulations reveals the dominant influence of greenhouse gases and anthropogenic aerosols on TEMP_ACchanges. Our identification of an anthropogenic TEMP_ACfingerprint is robust to the selection of different analysis periods. S/N ratios derived with model data only are consistently larger than ratios calculated with observational signals, primarily due to model versus observed TEMP_ACdifferences in the Atlantic. Human influence on the seasonality of surface and subsurface ocean temperature may have profound consequences for fisheries, marine ecosystems, and ocean chemistry. Significance StatementThe seasonal cycle is a fundamental aspect of our climate, and gaining insight into how anthropogenic forcing has impacted seasonality is of scientific, economic, and societal importance. Using observations and CMIP6 model simulations, this research applies a pattern-based detection and attribution method to ocean temperature annual cycle amplitude (TEMP_AC) down to 300 m across three major ocean basins. Key findings reveal significant increases in surface layer TEMP_ACexcept in the Southern Ocean and a weakening of TEMP_ACwithin the subsurface ocean. Importantly, the analysis confirms human influence on TEMP_AC. These findings underscore the profound influence of human-caused climate change on the world’s oceans and have important implications for marine ecosystems, fisheries, and ocean chemistry. 

The Antarctic ozone “hole” was discovered in 1985, and man-made ozone- depleting substances (ODS) are its primary cause. Following reductions of ODSs under the Montreal Protocol, signs of ozone recovery have been reported, based largely on observations and broad yet compelling model-data comparisons. While such approaches are highly valuable, they don't provide rigorous statistical detection of the temporal and spatial structure of Antarctic ozone recovery in the presence of internal climate variability. Here, we apply pattern-based detection and attribution methods as employed in climate change studies to separate anthropogenically forced ozone responses from internal variability, relying on trend pattern information as a function of month and height. The analysis uses satellite observations together with single-model and multi-model ensemble simulations to identify and quantify the month-height Antarctic ozone recovery “fingerprint”. We demonstrate that the data and simulations show remarkable agreement in the fingerprint pattern of the ozone response to decreasing ODSs since 2005. We also show that ODS forcing has enhanced ozone internal variability during the austral spring, influencing detection of forced responses and their time of emergence. Our results provide robust statistical and physical evidence that actions taken under the Montreal Protocol to reduce ODSs are indeed resulting in the beginning of Antarctic ozone recovery, defined as increases in ozone consistent with expected month-height patterns. 

We provide the first scientific evidence that a human-caused signal in the seasonal cycle of sea surface temperature (SST) has emerged from the background noise of natural variability. Geographical patterns of changes in SST seasonal cycle amplitude (SSTAC) reveal two distinctive features: an increase at mid-latitudes in the Northern Hemisphere related to mixed-layer depth changes, and a robust dipole pattern between 40˚S and 55˚S in the Southern Hemisphere which is mainly driven by surface wind changes. The model-predicted pattern of SSTAC change is identifiable with high statistical confidence in four observed SST products and in 51 individual model realizations of historical climate evolution. Simulations with individual forcing reveal that greenhouse gas increases drive most of the change in SSTAC, with smaller but distinct contributions from anthropogenic aerosol and ozone forcing. The robust human influence identified here on the seasonality of SST is likely to have wide-ranging impacts on marine ecosystems. 

In 1967, scientists used a simple climate model to predict that human-caused increases in atmospheric CO 2 should warm Earth’s troposphere and cool the stratosphere. This important signature of anthropogenic climate change has been documented in weather balloon and satellite temperature measurements extending from near-surface to the lower stratosphere. Stratospheric cooling has also been confirmed in the mid to upper stratosphere, a layer extending from roughly 25 to 50 km above the Earth’s surface (S 25 − 50 ). To date, however, S 25 − 50 temperatures have not been used in pattern-based attribution studies of anthropogenic climate change. Here, we perform such a “fingerprint” study with satellite-derived patterns of temperature change that extend from the lower troposphere to the upper stratosphere. Including S 25 − 50 information increases signal-to-noise ratios by a factor of five, markedly enhancing fingerprint detectability. Key features of this global-scale human fingerprint include stratospheric cooling and tropospheric warming at all latitudes, with stratospheric cooling amplifying with height. In contrast, the dominant modes of internal variability in S 25 − 50 have smaller-scale temperature changes and lack uniform sign. These pronounced spatial differences between S 25 − 50 signal and noise patterns are accompanied by large cooling of S 25 − 50 (1 to 2 ° C over 1986 to 2022) and low S 25 − 50 noise levels. Our results explain why extending “vertical fingerprinting” to the mid to upper stratosphere yields incontrovertible evidence of human effects on the thermal structure of Earth’s atmosphere.