Methodology
- The percentage of acceptance of AGW based on the peer-reviewed literature has been shown to be more reliable than that from opinion surveys. See here.
- The only practical way to assemble a database of relevant articles is to use the Web of Science, which categorizes each peer-reviewed article. I chose the topics " climate change" and "global warming." Some of the articles thus found do not appear on the surface to be about either topic. But the Web of Science says they are. Better to assume that the Web of Science is correct than to exclude those articles.
- Publishing scientists rarely directly endorse the leading theory of their discipline. They take it as a given and work from there. As reported here, I read hundreds of articles on plate tectonics, evolution, and meteorite impact cratering without finding a single endorsement. Cook et al. (2013) reviewed 11,944 peer-reviewed articles on AGW and found only 0.5% that directly endorsed the theory. Many of those were specifically about whether human activities are causing observed global warming, so it was natural that they made an affirming statement. These were not endorsements but research findings.
- Scientists who have solid evidence against a prevailing theory will be sure to publish it. If there were such evidence against AGW, we would not have to search for it: the news would have made headlines and the discoverer would go down in history.
- Putting all this together, to judge the extent of a consensus among scientists, look for peer-reviewed articles that reject the theory. If there are none, then as far as we can tell, scientists are unanimous AND there is no evidence against the theory that can pass peer review.
- To classify an article as a rejection, I looked for a clear statement that AGW is false or that some other process better explains the rise in global temperature. I did not count articles that report some discrepancy but did not use that discrepancy as the basis for claiming that AGW is false. Any theory has discrepancies, observations that the theory cannot yet explain. They provide the next set of research problems.