Human and natural influences on the changing thermal structure of the atmosphere.

Since the late 1970s, satellite-based instruments have monitored global changes in atmospheric temperature. These measurements reveal multidecadal tropospheric warming and stratospheric cooling, punctuated by short-term volcanic signals of reverse sign. Similar long- and short-term temperature signals occur in model simulations driven by human-caused changes in atmospheric composition and natural variations in volcanic aerosols. Most previous comparisons of modeled and observed atmospheric temperature changes have used results from individual models and individual observational records. In contrast, we rely on a large multimodel archive and multiple observational datasets. We show that a human-caused latitude/altitude pattern of atmospheric temperature change can be identified with high statistical confidence in satellite data. Results are robust to current uncertainties in models and observations. Virtually all previous research in this area has attempted to discriminate an anthropogenic signal from internal variability. Here, we present evidence that a human-caused signal can also be identified relative to the larger "total" natural variability arising from sources internal to the climate system, solar irradiance changes, and volcanic forcing. Consistent signal identification occurs because both internal and total natural variability (as simulated by state-of-the-art models) cannot produce sustained global-scale tropospheric warming and stratospheric cooling. Our results provide clear evidence for a discernible human influence on the thermal structure of the atmosphere.

Identifying human influences on atmospheric temperature.

We perform a multimodel detection and attribution study with climate model simulation output and satellite-based measurements of tropospheric and stratospheric temperature change. We use simulation output from 20 climate models participating in phase 5 of the Coupled Model Intercomparison Project. This multimodel archive provides estimates of the signal pattern in response to combined anthropogenic and natural external forcing (the fingerprint) and the noise of internally generated variability. Using these estimates, we calculate signal-to-noise (S/N) ratios to quantify the strength of the fingerprint in the observations relative to fingerprint strength in natural climate noise. For changes in lower stratospheric temperature between 1979 and 2011, S/N ratios vary from 26 to 36, depending on the choice of observational dataset. In the lower troposphere, the fingerprint strength in observations is smaller, but S/N ratios are still significant at the 1% level or better, and range from three to eight. We find no evidence that these ratios are spuriously inflated by model variability errors. After removing all global mean signals, model fingerprints remain identifiable in 70% of the tests involving tropospheric temperature changes. Despite such agreement in the large-scale features of model and observed geographical patterns of atmospheric temperature change, most models do not replicate the size of the observed changes. On average, the models analyzed underestimate the observed cooling of the lower stratosphere and overestimate the warming of the troposphere. Although the precise causes of such differences are unclear, model biases in lower stratospheric temperature trends are likely to be reduced by more realistic treatment of stratospheric ozone depletion and volcanic aerosol forcing.

Arctic tropospheric warming amplification?

Relative rates of temperature change between the troposphere and surface, and the mechanisms that produce these changes, have long been a contentious issue. Graversen et al., predicated upon the ERA-40 reanalysis, report polar tropospheric amplification of surface warming and attempt to explain this finding dynamically. Here we show (1) that data from satellites and weather balloons indicate that the ERA-40 trends are increasingly unrealistic polewards of 62 degrees N; (2) that the two other reanalyses considered exhibit very different polar trends; and (3) that the vertical profile of polar trends in ERA-40 is unrealistic, particularly above the troposphere. These quasi-independent strands of evidence imply that the pattern of warming in the Arctic troposphere is highly unlikely to be as given in ERA-40 and as reported by Graversen et al..

Attribution of observed surface humidity changes to human influence.

Water vapour is the most important contributor to the natural greenhouse effect, and the amount of water vapour in the atmosphere is expected to increase under conditions of greenhouse-gas-induced warming, leading to a significant feedback on anthropogenic climate change. Theoretical and modelling studies predict that relative humidity will remain approximately constant at the global scale as the climate warms, leading to an increase in specific humidity. Although significant increases in surface specific humidity have been identified in several regions, and on the global scale in non-homogenized data, it has not been shown whether these changes are due to natural or human influences on climate. Here we use a new quality-controlled and homogenized gridded observational data set of surface humidity, with output from a coupled climate model, to identify and explore the causes of changes in surface specific humidity over the late twentieth century. We identify a significant global-scale increase in surface specific humidity that is attributable mainly to human influence. Specific humidity is found to have increased in response to rising temperatures, with relative humidity remaining approximately constant. These changes may have important implications, because atmospheric humidity is a key variable in determining the geographical distribution and maximum intensity of precipitation, the potential maximum intensity of tropical cyclones, and human heat stress, and has important effects on the biosphere and surface hydrology.