New statistical analysis confirms human role in climate change
Aug 2, 2007 4 comments
The idea that global warming is caused by changes in solar output rather than human activity has been dealt a further blow by a new analysis of temperature, volcanic and solar-radiation data by a physicist in Germany. The research, carried out by Pablo Verdes from the Heidelberg Academy of Sciences in Germany, does not rely on climate models, which cannot account for all global-warming mechanisms. Instead, the work reveals a strong statistical link between rising temperatures and greenhouse gas emissions (Phys. Rev. Lett. 99 048501).
Most of the evidence for human-induced or “anthropogenic” climate change has come from climate models, which simulate the dynamics of the atmosphere using complex fluid-flow equations. Given inputs of temperature and other climate data from instruments and older proxy records, such as tree rings, these equations are solved numerically using short time increments.
Although all climate models indicate that the Earth’s temperature will continue to rise, some climate-change sceptics have suggested that the anthropogenic influences are exaggerated. For example, because the simulations divide the atmosphere into a 3D lattice with a coarse resolution, they cannot take into account the effects of clouds, which can both reduce or enhance warming.
Rather than trying to simulate the atmosphere as climate models do, Verdes has used statistics to assess man’s role in climate change.
Verdes started with data records of the past 150 years of the three main natural components thought to be involved in global warming: temperature anomalies, volcanic activity and the energy received from the Sun. To see if these were the only significant components, he looked for trends between the data - that is, if changes in volcanic activity and solar output could account for the changes in temperature. Verdes then checked whether the addition of an external driving force, such as human activity, resulted in a better description of the data.
To do this Verdes used a theory known as nonlinear time-series analysis, whereby the existence of a slowly-varying driving force can be deduced without any knowledge of internal dynamics. First, he assumed the driving force was zero and chose a generic function to fit the data computationally. He then introduced a non-zero driving force and estimated different profiles that would improve the accuracy of the fit.
Verdes found that the driving-force profile that produced the best fit almost exactly matched records of greenhouse gas and aerosol emissions (see Driving force). In other words, fitting the data using the natural components alone left a hole that could be filled by our anthropogenic components. “The coincidence is remarkable,” he said.
The results add weight to the consensus of the Intergovernmental Panel on Climate Change, which came to the conclusion earlier this year that humans are to blame for rising temperatures.
Verdes thinks that his statistical approach should “enrich the continuing debate on the future of our climate.”
About the author
Jon Cartwright is a reporter for physicsworld.com