> 99% of experts

Ah, the fabled /9[789]%(.9)?/ argument raises its ugly head again. This claim has several sources, let's have a look at them.

In 2009, the University of Illinois sent a survey [1] online to about 10200 scientists (of many disciplines) with the following two questions:

1: Do you agree that global temperatures have generally risen since the pre-1800s?

2: Do you think that human activity is a significant contributing factor?

3146 responses were received of ~10,200, and of that 31%, 90% said yes to the first question while 82% said yes to the second question. When narrowed down to actual experts in the field (mostly meteorologists) 64% answered 'yes' to the second question. Of the 3146 responses 77 were selected which came from self-professed 'climate experts'. Of these 77 individuals 75 answered 'yes' to the second question. 75/77 = 0.97 -> 97% of experts agree

In reality a self-professed "expert" group of 2.4% of the answerers were selected who in turn formed 0.8% of those who received the survey. The well-known saying about statistics - there's lies, damned lies and statistics [2] - comes to mind here.

Then there was the '2013 Cook study' [3] entitled 'Quantifying the consensus on anthropogenic global warming in the scientific literature' which is often cited as another source for the '97%'. Cook and his team searched the Web of Science for the phrases "global warming" and "global climate change", then categorised the results to what they considered to be their level of endorsement of anthropogenic global warming. While Cook's conclusion - “Cook et al. (2013) found that over 97 percent [of papers he surveyed] endorsed the view that the Earth is warming up and human emissions of greenhouse gases are the main cause.” - was taken for gospel by those who were looking for more endorsement of the earlier '97%' study. What is it based on? Cook created a category called “explicit endorsement without quantification” (papers in which the author did not say whether 1 percent or 50 percent or 100 percent of the warming was caused by man). He had also created a category called “implicit endorsement” for papers that imply (but don’t say) that there is some man-made global warming without quantification of the effect. These were the categories used to calculate the '97%'. Many scientists whose papers were classified in these categories protested to Cook [4] for being selective in which papers were cited and misrepresentation of their positions on the subject of anthropogenic climate change.

Cook's data is available in the study [3], the positions on anthropogenic global warming look like this:

Explicitly endorse AGW 50+% = 0.54%
Explicitly endorse – does not quantify = 7.72%
Explicitly endorse AGW without minimizing it = 24.36%
No Position = 66.73%
Implicit minimizes/rejects AGW = 0.45%
Explicit minimizes/rejects AGW = 0.13%
Explicitly minimizes/rejects AGW as <50% = .08%

These 7 groups are summarised in 4 categories by Cook:

Endorse AGW 32.6%
No AGW Position 66.4%
Reject AGW .7%
Uncertain on AGW .3%

The study arrives at the '97% endorsement' by leaving out the 66% who do not have a position which leaves the 32.6% who endorse some form of AGW against the 0.7% who reject it. Apart from the mentioned problems with the categorisation this is another example of lies, damned lies and statistics [2].

In short, don't use the /9[789]%(.9)?/ argument in an attempt to appeal to authority, especially not in the context of a discussion around the viability of global climate models as evidence for future climate change. First because of the mentioned reasons but also because the '97%' argument has no bearing on the validity of climate models since it just - rightly or wrongly - claims that '97% of experts agree that anthropogenic climate change is a fact'.

[1] https://www.sciencedaily.com/releases/2009/01/090119210532.h...

[2] https://en.wikipedia.org/wiki/Lies,_damned_lies,_and_statist...

[3] https://iopscience.iop.org/article/10.1088/1748-9326/8/2/024...

[4] http://www.populartechnology.net/2013/05/97-study-falsely-cl...