I argued last week that the way to combat confirmation bias—the tendency to behave like a defense attorney rather than a judge when assessing a theory in science—is to avoid monopoly. So long as there are competing scientific centers, some will prick the bubbles of theory reinforcement in which other scientists live.
For constructive critics, this is the problem with modern climate science. They don’t think it’s a conspiracy theory, but a monopoly that clings to one hypothesis (that carbon dioxide will cause dangerous global warming) and brooks less and less dissent. Again and again, climate skeptics are told they should respect the consensus, an admonition wholly against the tradition of science.
Last month saw two media announcements of preliminary new papers on climate. One, by a team led by physicist Richard Muller of the University of California, Berkeley, concluded “the carbon dioxide curve gives a better match than anything else we’ve tried” for the (modest) 0.8 Celsius-degree rise in global average temperatures over land during the past half-century—less, if ocean is included. He may be right, but such curve-fitting reasoning is an example of confirmation bias. The other, by a team led by the meteorologist Anthony Watts, a skeptical gadfly, confirmed its view that the Muller team’s numbers are too high—because “reported 1979-2008 U.S. temperature trends are spuriously doubled” by bad thermometer siting and unjustified “adjustments.”
Much published research on the impact of climate change consists of confirmation bias by if-then modeling, but critics also see an increasing confusion between model outputs and observations. For example, in estimating how much warming is expected, the most recent report of the Intergovernmental Panel on Climate Change uses three methods, two based entirely on model simulations.
The late novelist Michael Crichton, in his prescient 2003 lecture criticizing climate research, said: “To an outsider, the most significant innovation in the global-warming controversy is the overt reliance that is being placed on models…. No longer are models judged by how well they reproduce data from the real world—increasingly, models provide the data. As if they were themselves a reality.”
It isn’t just models, but the interpretation of real data, too. The rise and fall in both temperature and carbon dioxide, evident in Antarctic ice cores, was at first thought to be evidence of carbon dioxide driving climate change. Then it emerged that the temperature had begun rising centuries earlier than carbon dioxide. Rather than abandon the theory, scientists fell back on the notion that the data jibed with the possibility that rising carbon dioxide levels were reinforcing the warming trend in what’s called a positive feedback loop. Maybe—but there’s still no empirical evidence that this was a significant effect compared with a continuation of whatever first caused the warming.