Finding the human fingerprint in Northern Hemisphere greening

Jun 28, 2016

Using newer data and strict statistical methods, a multinational team led by the Oak Ridge National Laboratory Climate Change Science Institute’s (CCSI’s) Jiafu Mao has found the first positive correlation between human activities and enhanced vegetation growth in the northern extratropical latitudes (NELs; roughly between 30°N and 75°N).

“This is the first clear evidence of a discernible human fingerprint on physiological vegetation changes at the continental scale,” Mao says.

Earth system models simulate Northern Hemisphere greening. Figure shows the spatial distribution of the linear trends in the growing season (April–October) leaf area index (m2/m2/30yr) during the period 1982–2011 in the mean of satellite observations (LAI3g and GEOLAND2) (upper figure), Earth system model (ESM) simulations with natural forcings alone (lower left figure), and ESM simulations with anthropogenic and natural forcings (lower right figure).

Among the reasons the human “touch” had not been positively identified previously were the lack of long-term observational records and the lack of suitable Earth system model (ESM) simulations. The team used two recently available, 30-year-long, leaf area index (LAI) data sets (LAI3g and GEOLAND2); simulations from 19 ESMs; and a formal detection and attribution (D&A) algorithm, developed for this project. These tools positively attribute changes in vegetation activity in the NELs to human sources, particularly well-mixed greenhouse gas (GHG) emissions.

LAI, the ratio of leaf surface area to ground area, is an indicator of vegetation growth and productivity measurable by satellite. What the two LAI datasets and ESM simulations showed for the years 1982–2011 was a significant “greening” trend over the NEL vegetated area, indicating increased vegetation. When Mao and his colleagues accounted for internal climate variability (e.g., the El-Niño Southern Oscillation) and responses to natural forcings (that is, things that impact Earth’s energy balance such as volcanic eruptions and changes in incoming solar radiation), it was clear that the greening could only be explained by human activities such as those associated with GHG emissions (mainly elevated CO2 concentrations) and was not consistent with simulations that included only natural forcings and internal climate system variability (figure).

These results are important for a number of reasons. For example, changes in vegetation growth like those demonstrated here can impact energy exchanges, water use, and carbon budgets, accelerating or slowing climate change. Accurate D&A of changes in terrestrial vegetation growth patterns is essential for ecosystem management, agricultural applications, and sustainable management and development—in short, strategic decision making.

The D&A statistical technique typically is applied to physical climate data in studies of extreme events or variations in temperature or precipitation; this is the first time it has been applied to terrestrial ecosystem changes such as trends in LAI.

As more long-term regional- and global-scale observational data on terrestrial ecosystem variables become available, Mao would like to see these data used in similar studies. Mao says the D&A method could also be applied to study broad-scale terrestrial ecosystem dynamics, and the framework developed for this study could be used to identify potential errors in ESMs, contributing to more accurate next-generation ESMs.

The study and its results are reported in the article “Human-induced greening of the northern extratropical land surface” in Nature Climate Change. Other ORNL participants and coauthors were CCSI’s Xiaoying Shi, Peter Thornton, Dan Ricciuto, and Forrest Hoffman.

The work of Mao and his CCSI coauthors for this paper was supported by the DOE Office of Science, Office of Biological and Environmental Research.

by VJ Ewing