CIRCULAR REASONING IN CLIMATE SCIENCE
Posted on: October 2, 2021
LINK TO SOURCE: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3130131
LINK TO RELATED POST: EXAMPLE OF CIRCULAR REASONING IN CLIMATE SCIENCE: https://tambonthongchai.com/2018/05/31/the-carbon-cycle-measurement-problem/
A literature review shows that the circular reasoning fallacy is common in research. It is facilitated by confirmation bias and by statistical and methodological errors such that the prior conviction of researchers is subsumed into the analysis. Example research papers in climate science on the impact of fossil fuel emissions on tropical cyclones, on sea level rise, and on atmospheric CO2 concentration demonstrate that circular reasoning plays a significant role in climate science. The validity of the anthropogenic nature of global warming and climate change and that of the effectiveness of proposed measures for climate action may therefore be questioned solely on this basis.
DETAILS
ITEM#1: Circular reasoning is a logical fallacy in which research design and methodology as well as the
interpretation of the data subsume the finding. This fallacy can be found in published research and it
is more common in research areas such as archaeology, finance, economics, and climate change
where the data are mostly time series of historical field data with no possibility for experimental
verification of causation.
ITEM#2: In biased research of this kind, researchers do not objectively seek the truth, whatever it may turn out to be, but rather they seek to prove the truth of what they already know to be true or what needs to be true to support activism for a noble cause (Nickerson, 1998). Such confirmation bias or “yearning” (Finkelstein, 2011) is found in research areas related to religion or to activism.
ITEM#3: Confirmation bias is thought to play a role in climate change because climate
science provides the rationale for environmental activism against fossil fuels and the noble cause of saving humanity or perhaps the planet itself from climate cataclysm (Kaptchuk, 2003) (Nicholls, 1999). This hidden hand of activism plays a role in the way climate research is carried out and in the way findings are interpreted and disseminated (Cooper, 2006) (Britt, 2001) (Bless, 2006) (Juhl, 2007) (Watkins, 2007) (VonStorch, 1995) (Enright, 1989) (Britt, 2001) (Hodges, 1992) (Curry, 2006).
ITEM#4: A famous example of confirmation bias in research is Biblical Archaeology. William Albright, and fellow Biblical Archaeologists, convinced of the historicity of Biblical accounts, carried out extensive
archaeological digs in the holy lands looking for evidence that they were sure would prove their
case. In their many publications, they proved the historicity of Biblical stories about the patriarchs,
the move to Egypt, the exodus, the wandering in the desert, the conquest of the Canaan, the period
of the Judges, and finally of the grand United Monarchy of David and Solomon (Albright, 1973)
(Albright2, 1973) (Dever, 2003) (Cross, 1973). These findings stood as scientific truth for 30 years.
ITEM#5: Albright’s findings were successfully challenged only recently by Israel Finkelstein of Tel Aviv University (Finkelstein, 2002) (Finkelstein, 1996) (Finkelstein,1998) who became known and villified as the Albright Denier.
ITEM#6: Finkelstein points out that Biblical chronology places the period of the patriarchs at 2100 BCE
but in the quest to find archaeological evidence for the historicity of the patriarchs other dates were
accepted as evidence if the material culture of the stratum could be compared with the Biblical
description of the material culture of the patriarchs. The theory about the age of the patriarchs
changed according to the archaeological discoveries. Any age from 1100BCE to 2100BCE was taken
as evidence of the historicity of the patriarchs. It was with this circular reasoning that the historicity
of the patriarchs was “proven” to the satisfaction of Biblical Archaeologists.
ITEM#7: Finkelstein offers a similar account of circular reasoning in the effort by Biblical Archaeologists to establish the historicity of the story of David and Solomon and their grand united monarchy. In the case of David’s conquests and also for the lavish kingdom of Solomon, the archaeological data are interpreted and dated in terms of the Biblical accounts of these events – and then used as evidence to support the historicity of the same Biblical accounts. The use of circular reasoning in these cases was completely missed by researchers and peer reviewed journals and the claimed archaeological evidence for the historicity of David and Solomon’s grand united monarchy stood as textbook truth for decades Finkelstein, 2002). These accounts show that the use of circular reasoning in research and the general acceptance of the findings of circular reasoning research by the public and the research community are not unusual.
THE APPLICATION OF THESE PRINCIPLES TO CLIMATE CHANGE SCIENCE
Here we show that this kind of pattern is also found in climate science. A unique circular reasoning issue in climate change research is that the use of climate models in empirical test of theory (Rahmstorf, 2007) (Rowlands, 2012) compromises the independence of the empirical test of theory from the theory itself. Climate models are an expression of theory. They execute the mathematics to spell out what results we might expect to see if the theory is correct. Therefore, the practice of utilizing climate models in empirical tests of theory is a form of circular reasoning because the empirical test is no longer independent of the theory that is being tested (VonStorch, 1995) (Hodges, 1992) (McDonald, 2013.) (Harper, 2008) (Enright, 1989) (Mehta, 2004) (Krueger, 2001) (Freedman, 1991) (Vul, 2010).
A recurring pattern of circular reasoning in climate science involves the discovery from the data that the hypothesis to be tested is true only under certain conditions that are not found in the hypothesis or that it can be found to be true only in a portion of the time span of the data time series being used for the test. The hypothesis is then adjusted to meet these conditions and the hypothesis test of the adjusted hypothesis is then found to be true. The finding is then published as empirical evidence in support of the theory with the added “discovery” of the time span or the conditions where the effect is most evident (Huber, 2011). These research findings contain circular reasoning because in the end the hypothesis is proven with data from which the hypothesis was derived. A hypothesis derived from the data cannot be tested with the same data.
And yet, in all such cases the research findings are readily accepted by the researcher and by the research community by way of confirmation bias because the results are reasonable in the context of the AGW theory that serves as the foundational basis for the research and that has gained widespread acceptance as “settled science” or “consensus science“.
EXAMPLES OF CIRCULAR REASONING IN CLIMATE SCIENCE
ITEM#1: THE RESPONSIVENESS OF ATMOSPHERIC CO2 CONCENTRATION TO FOSSIL FUEL EMISSIONS.
This relationship is at the very foundation of climate change science because without this relationship nothing remains of the needed rationale for the underlying activism against fossil fuels and for the promotion of renewable energy that serve as the foundational motivations for the climate change movement. And yet this foundational relationship in climate science between fossil fuel emissions and rising atmospheric CO2 concentration has been established with circular reasoning as follows.
First, the theory that fossil fuel emissions end up in the atmosphere and cause atmospheric CO2 to rise is found to be inconsistent with the measured and required rate of fossil fuel emissions for these changes because changes in atmospheric CO2 are too slow to be driven by fossil fuel emissions. A study of the data showed that atmospheric CO2 needs to rise twice as fast as what is found in the data if it is driven by fossil fuel emissions and based on that the theory was modified to posit that only half of the CO2 in fossil fuel emissions cause atmospheric CO2 to rise and the other half must therefore go somewhere else and perhaps it is absorbed by the carbon cycle.
But how is this new modified theory to be tested? A theory derived from the data cannot be tested with the same data because that would be circular reasoning. And yet this is exactly what we find in climate science. The most fundamental relationship in climate science that serves as the foundation for the call to a climate action to cease the production and combustion of fossil fuels, is a creation of circular reasoning.
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