The paper that Patrick Michaels contributed to Climate Science: The Facts 2017 contains scientific analysis and a penetrating appraisal of “normal science” and the political economy of research. This is a very important and incisive contribution at several levels of analysis.
At the technical level he explains how the computer models and cherry-picking of data have been used to exaggerate the amount of warming that we can expect.
He notes that the pathology of science that Thomas Kuhn described as “normal science” has become distressingly common.
He provides a thumbnail sketch of the social/institutional pressures related to publication, government funding and career advancement that perpetuate bad science.
Patrick Michaels is the Director of the Centre for the Study of Science at the Cato Institute in Washington. We met briefly after I lunched with Dan Mitchell (our man in DC) when he was working at Cato. Pat advocates the “lukewarming” scenario: the surface temperature is about 0.8C above the level at the turn of the twentieth century with a small human contribution from CO2 emissions. He is not alarmed about this. Bjorn Lomborg in contrast can be described as a “lukewarm alarmist” because he considers that warming will cause problems in the somewhat distant future.
Michaels made his case in Lukewarming: The New Climate Science That Changes Everything and a summary of some key points can be found in his contribution to Climate Science.
Defending the paradigm
The climate community, which is defined by models and modellers, is engaged in the kind of behaviour predicted by Thomas Kuhn in his classic book The Structure of Scientific Revolutions. This community generates data in support of a paradigm that may violate basic physics, blatantly cherrypicking to support to policy science. The incentive structure in modern science requires that practitioners largely support the high-CO2 sensitivity model-based paradigm in warming to remain employed and to advance in their careers. The result is a polluted canon of knowledge. This disorder is systemic across most areas of science that are difficult to replicate, climate science being a prime example.
The following are some of the examples that are sketched in the paper:
Ignoring studies that show the sensitivity of warming to increasing CO2 is much less than 3 degrees for doubling CO2 that is used by the IPCC.
Ignoring the serious and growing mismatch between projections and the measured numbers for the global temperature.
Cherrypicking start and end dates for data series.
Adjusting away the pause in warming by correction and “homogenization” of raw data.
The political economy of research and publication
The paper does not stop with the science but goes deeper to provide some insights into the social-political-institutional features of postwar Big Science driven by government funding. He points out that the academic reward structure demands a body of individual research starting in graduate school and achieving a “tenure track” position as an assistant professor. In climate science this demands a massive amount of research funding in the order of US$5 million for a scientist to publish enough papers to make the grade to tenure track in a tier-one research school.
The government provides the money and the funding is driven by the politics of the time as described by Butos and McQuade. They wrote during the Obama administration and it will take a long time to drain the swamp and correct the situation.