September 21, 2016

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Climate Study Finds Human Fingerprint in Northern Hemisphere

New analysis uses detection and attribution methods to establish multiyear trends of vegetation growth in northern-extratropical latitudes.

The Science

This study examines leaf area index (LAI; area of leaves per area of ground) during the growing season (April–October) over northern-extratropical latitudes (NEL; 30° to 75°N). Previous work assessing modeled and observed LAI focused on timing of seasonal growth, interannual variability, and multiyear trends. These earlier studies showed that spatiotemporal changes in LAI were related to variation in climate drivers (mainly temperature and precipitation). This new study adds to an increasing body of evidence that NEL vegetation activity has been enhanced, as reflected by increased trends in vegetation indices, aboveground vegetation biomass, and terrestrial carbon fluxes during the satellite era. However, this analysis goes beyond previous studies by using formal detection and attribution methods to establish that the trend of increased northern vegetation greening is clearly distinguishable from both internal climate variability and the response to natural forcings alone. This greening can be rigorously attributed, with high statistical confidence, to anthropogenic forcings, particularly to rising atmospheric concentrations of greenhouse gases.

The Impact

This work demonstrates the first clear evidence of a discernible human fingerprint on NEL physiological vegetation changes and points to new investigations that could use detection and attribution methods to study broad-scale terrestrial ecosystem dynamics.

Summary

Significant NEL land greening has been documented through satellite observations during the past three decades. This enhanced vegetation growth has broad implications for surface energy, water, and carbon budgets, as well as ecosystem services across multiple scales. Discernable human impacts on Earth’s climate system have been revealed by using statistical frameworks of detection and attribution. These impacts, however, were not previously identified on the NEL greening signal, due to the lack of long-term observational records, possible bias of satellite data, different algorithms used to calculate vegetation greenness, and lack of suitable simulations from coupled Earth system models (ESMs). Researchers, led by Oak Ridge National Laboratory, overcame these challenges to attribute recent changes in NEL vegetation activity. They used two 30 year–long, remote sensing–based LAI datasets, simulations from 19 coupled ESMs with interactive vegetation, and a formal detection and attribution algorithm. Their findings reveal that the observed greening record is consistent with an assumption of anthropogenic forcings, where greenhouse gases play a dominant role, but is not consistent with simulations that include only natural forcings and internal climate variability. This evidence of historical, human-induced greening in the northern extratropics has implications for both intended and unintended consequences of human interactions with terrestrial ecosystems and the climate system.

Principal Investigator

Jiafu Mao
Oak Ridge National Laboratory
maoj@ornl.gov

Program Manager

Daniel Stover
U.S. Department of Energy, Biological and Environmental Research (SC-33)
Environmental System Science
daniel.stover@science.doe.gov

Funding

J. Mao, X. Shi, P.E. Thornton, D.M. Ricciuto, and F.M. Hoffman are supported by the Office of Biological and Environmental Research, within the U.S. Department of Energy (DOE) Office of Science, including support from the following programs: Regional and Global Climate Modeling Program [Oak Ridge National Laboratory (ORNL) BGC-Feedbacks Scientific Focus Area (SFA)]; Terrestrial Ecosystem Science (TES) program (ORNL TES SFA); and Earth System Modeling (ACME project).

References

Mao, J., A. Ribes, B. Yan, and X. Shi, et al. "Human-induced greening of the northern extratropical land surface." Nature Climate Change 6 959–963  (2016). https://doi.org/10.1038/nclimate3056.