Human influence detected in changing seasons – “Powerful and novel evidence for a significant human effect on Earth’s climate”

Desdemona Despair

19 July 2018 (LLNL) – For the first time, scientists from Lawrence Livermore National Laboratory (LLNL) and five other organizations have shown that human influences significantly impact the size of the seasonal cycle of temperature in the lowest layer of the atmosphere.

To demonstrate this, they applied a so-called “fingerprint” technique. Fingerprinting seeks to separate human and natural influences on climate. It relies on patterns of climate change — typically patterns that are averaged over years or decades. But in the new research appearing in the 20 July 2018 edition of the journal Science, the team studied seasonal behavior, and found that human-caused warming has significantly affected the seasonal temperature cycle.

The researchers focused on the troposphere, which extends from the surface to roughly 16 kilometers in the atmosphere at the tropics and 13 kilometers at the poles. They considered changes over time in the size of the seasonal cycle of tropospheric temperature at different locations on the Earth’s surface. This pattern provides information on temperature contrasts between the warmest and coldest months of the year.

Away from the moderating effects of oceans, mid-latitude regions of Northern Hemisphere continents have a large seasonal cycle of atmospheric temperature, with frigid winters and hot summers. Satellite temperature data are consistent with models that project that this seasonal “heartbeat” is becoming stronger with human emissions of carbon dioxide.

Other features common to the observations and model simulations are small changes in the tropical seasonal temperature cycle, and a decrease in the size of the seasonal cycle in the Antarctic region.

“Our results suggest that attribution studies with the changing seasonal cycle provide powerful and novel evidence for a significant human effect on Earth’s climate,” said LLNL climate scientist and lead author Benjamin Santer.

Earth’s climate is simultaneously affected by different external and internal factors. Examples of external influences are natural changes in the sun’s energy output and human-caused increases in atmospheric concentrations of greenhouse gases. Internal influences include a wide range of natural cycles, such as the El Niño/Southern Oscillation and the Interdecadal Pacific Oscillation. Variations in these and many other internal and external factors have driven changes in historical climate.

Since the inception of climate fingerprint research in the late 1970s, scientists have used pattern recognition methods to detect unusually large changes in climate and to attribute these changes to different external influences. Initial studies concentrated on surface and atmospheric temperature. Later fingerprint research considered changes in a wide range of variables, including ocean heat content, the hydrological cycle, atmospheric circulation, sea ice extent and the behavior of extreme events.

In the new research, the team examined model simulations driven by historical changes in human factors. A prominent feature of these simulations is that at mid-latitudes, the size of the seasonal temperature cycle increases markedly. This increase results from larger warming in each hemisphere’s summer season. In turn, larger mid-latitude summer warming appears to be partly due to summer drying of the land surface.

Because of differences in the heat capacity of land and ocean, and because there is substantially more land in the Northern Hemisphere, mid-latitude increases in the seasonal temperature cycle are larger in the Northern than in the Southern Hemisphere. Similar large-scale patterns of seasonal cycle change occur in satellite tropospheric temperature data. The “pattern match” between the human influence fingerprint and the satellite patterns of seasonal cycle change was highly significant. The match was unlikely to be due to natural internal climate variability.

The satellite tropospheric temperature data used in the Science paper show global-mean annual average warming of roughly 1.25 degrees Farenheit from 1979 to 2016. The causes of this annual average warming signal have been the subject of many previous studies. But until the new research was conducted, no formal fingerprint study had been performed with the changing seasonal cycle of tropospheric temperature.

Other Livermore researchers include Stephen Po-Chedley, Mark Zelinka, Ivana Cvijanovic, Céline Bonfils, Paul Durack, Jeffrey Painter and Giuliana Pallotta. The paper was a collaboration with Qiang Fu at the University of Washington, Jeffrey Kiehl at UC Santa Cruz, Carl Mears and Frank Wentz at Remote Sensing Systems in Santa Rosa, Susan Solomon at the Massachusetts Institute of Technology and Cheng-Zhi Zou at the National Oceanic and Atmospheric Administration.

Contact

Anne M Stark, stark8@llnl.gov, 925-422-9799

Human influence detected in changing seasons

ABSTRACT: 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 T_AC, the geographical pattern of the amplitude of the annual cycle of tropospheric temperature. Information on how T_AC 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 T_AC. 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 T_AC 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.

Human influence on the seasonal cycle of tropospheric temperature