Given the large sample size (1868) and the diversity in scientific backgrounds of our respondents, results were segregated according to fields of expertise and publication metrics, as indicated by the respondents in their respective answers to questions 6 and 7. The self-declared fields of expertise were categorized as WG1, 2, 3, or other fields of expertise, analogous to the tagged expertise fields (see SI ). Around 65% of those with self-declared WG1 fields of expertise also were tagged with WG1 fields of expertise. Respondents who were labeled as “unconvinced” indicated more often than other respondents that they had expertise in one or more of the WG1 fields and they indicated more expertise fields in general. For a subgroup of invitees, Google Scholar metrics regarding number of publications were also available as tagged information. For fields of expertise as well as publication metrics, aggregated results did not strongly depend on tagged or self-declared numbers. More details can be found in the SI

Figure 2. Percentages for the contribution of anthropogenic GHG to global warming since the mid-20th century (Q1). Responses are shown as a percentage of respondents ( N ) in each subgroup, segregated according to self-declared (SD) fields of expertise “WG1” (categorized as Working Group 1) and “attr or aer” (expertise in attribution or aerosols and clouds).

Four respondents tagged as AR4 WG1 authors chose the “26–50%” option and, as such, disagreed with AR4’s attribution statement. Those who were tagged as “unconvinced” ( N = 88, not shown) consisted of two main subgroups: one claiming only a minor effect of anthropogenic GHGs (GHG < 25%), and the other claiming the answer was “unknown due to lack of knowledge”. Six of the “unconvinced” respondents selected the option GHG > 50%, thus agreeing with AR4’s attribution statement.

AR4 WG1 authors (not shown) responded similarly to those with (self-declared) expertise in attribution or aerosols, also preferentially selecting “>100%”. As the self-declared number of publications increased, so did the proportion of respondents selecting “>100%”, although still below the answer option of “76–100%” (see SI ).

Their awareness of or judgment about the offsetting effect of aerosols appears important in how respondents answered Q1, as is discussed in more detail below. The proportion of respondents who chose GHG > 100% was higher among respondents with expertise in “attribution” or “aerosols and clouds” (see Figure 2 ).

Q1 also concerned the contribution of GHGs, but then as a percentage of observed warming since the mid-20th century. This enabled a direct comparison with the well-known AR4 statement on attribution, which states that this contribution is(probability >90%) to be more than 50%. Less well-known is the fact that IPCC in AR4 also states that GHG forcing alone was(probability >66%) to have resulted in greater than observed warming if there had not been an offsetting, cooling effect from aerosol and other forcings. In AR5 this was further clarified. The net cooling effect of aerosols means that the sum of all warming contributions exceeds 100%. (21-23) This is the reason for including the answer option “>100%”, which, even if counterintuitive, would be consistent with both AR4 and AR5 and with recent research. (21-23)

The responses to Q3, on the qualitative GHG contribution to global warming since preindustrial times, are shown in Figure 1 . Responses were segregated according to the self-declared number of climate-related peer-reviewed publications, in four ranges of approximately equal size. About half the respondents stated that they had authored or coauthored more than 10 peer-reviewed climate-related publications. Responses indicating a cooling influence of GHGs (11 responses or less than 1% of the total) were grouped under the category “insignificant”, for graphing purposes. The majority of respondents selected the highest score (“strong warming”) for the GHG contribution. This majority was even stronger for respondents with the highest number of self-declared publications. A similar, though less pronounced trend was found for respondents with increasingly relevant fields of expertise (see SI ). Furthermore, 82% of AR4 WG1 authors selected the “strong warming” option for this question (not shown).

Consensus

Responses to Q1 and Q3 were both condensed into three categories: (1) agreement; (2) disagreement; and (3) undetermined (“unknown”, “I do not know”, and “other”). Those who selected any of the options of GHG > 50% in answer to Q1 were included in the “agreement” category. The answer “no warming” was included in the “disagreement” category. For Q3, responses were interpreted as “agreement” if GHGs were accredited with strong warming or with moderate warming if none of the other natural or anthropogenic factors were deemed to have caused strong warming. So, according to these respondents, GHGs were either the strongest or tied for the strongest contributor to global warming.

N = 174) and four quartiles of approximately equal size (N = ∼400), based on their self-reported number of publications. Results are shown separately for the questions of qualitative (Q3) and quantitative (Q1) attribution. In Figure 3 the distribution of respondents over the categories “agreement”, “undetermined”, and “disagreement” is shown for all respondents and for five different subgroups: the group of AR4 WG1 authors (= 174) and four quartiles of approximately equal size (= ∼400), based on their self-reported number of publications. Results are shown separately for the questions of qualitative (Q3) and quantitative (Q1) attribution.

Undetermined responses (unknown, I do not know, other) were much more prevalent for Q1 (22%) than for Q3 (4%); presumably because the quantitative question (Q1) was considered more difficult to answer. This explanation was confirmed by the open comments under Q1 given by those with an undetermined answer: 100 out of 129 comments (78%) mentioned that this was a difficult question.

There are two ways of expressing the level of consensus, based on these data: as a fraction of the total number of respondents (including undetermined responses), or as a fraction of the number of respondents who gave a quantitative or qualitative judgment (excluding undetermined answers). The former estimate cannot exceed 78% based on Q1, since 22% of respondents gave an undetermined answer. A ratio expressed this way gives the appearance of a lower level of agreement. However, this is a consequence of the question being difficult to answer, due to the level of precision in the answer options, rather than it being a sign of less agreement.

As a fraction of the total, the level of agreement based on Q1 and Q3 was 66% and 83%, respectively, for all respondents, and 77% and 89%, respectively, for the quartile with the highest number of self-declared publications. As a fraction of those who expressed an opinion (i.e., excluding the undetermined answers), the level of agreement based on Q1 and Q3 was 84% and 86%, respectively, for all respondents, and 91% and 92%, respectively, for the quartile with the highest number of self-declared publications.

The similarity between the fractions as derived from Q1 and Q3 (excluding the undetermined responses) suggests that it is reasonable to interpret the answer option “moderate warming” (provided no other factor was deemed to have caused “strong warming”) as agreeing with the IPCC. The fraction of respondents that disagreed with a dominant human influence on climate was 12% and 14%, based on the answers to Q1 and Q3, respectively. This group becomes smaller, 8% in both cases, for the quartile with the highest number of publications. A table with consensus estimates for the different subgroups and expressed in the above-mentioned two different ways can be found in the SI (Table S3). Excluding undetermined answers, 90% of respondents, with more than 10 self-declared climate-related peer-reviewed publications, agreed with dominant anthropogenic causation for recent global warming. This amounts to just under half of all respondents.

Figure 3 Figure 3. Responses shown as percentages of agreement and disagreement about the dominant influence of GHGs on global warming, based on responses to Q3 (qualitative GHG contribution) and Q1 (quantitative GHG contribution). Also shown are the percentages of responses for the answer options “unknown”, “I do not know”, and “other”, combined and labeled as “undetermined”. These answer options were much more prevalent for the quantitative question (Q1). The level of agreement increases for respondents with increased self-declared number of peer-reviewed climate-related publications and is highest for AR4 WG1 authors.

Different surveys are not directly comparable, due to different groups of people being asked different questions. However, since climate science surveys typically drew from the same overall pool of climate-related scientists, Bray (18) suggests that these can be meaningfully compared, to study the net change in aggregate opinions. He concluded that the level of consensus has grown over time. This is consistent with the analysis of the peer-reviewed literature that shows a similar increase in consensus.

Our results for the level of consensus are similar to those found in other surveys. (3, 24-26) Doran and Kendall-Zimmermann (3) reported an 82% consensus among 3146 earth scientists, which rose to 88% for those who identified themselves as climatologists, which is very similar to our findings. However, Oreskes, (2) Anderegg et al., (4) and Cook et al. (5) reported a 97% agreement about human-induced warming, from the peer-reviewed literature and their sample of actively publishing climate scientists, as did Doran and Kendall-Zimmermann (3) for the most published climatologists. Literature surveys, generally, find a stronger consensus than opinion surveys. This is related to the stronger consensus among often-published–and arguably the most expert–climate scientists. The strength of literature surveys lies in the fact that they sample the primary fora where the evidence is laid out, whereas the strength of opinion surveys such as ours relates to the fact that much more detail can be achieved about the exact opinions of scientists. As such, these two methods for describing scientific consensus are complementary. Different surveys typically use slightly different criteria to determine their survey sample and to define the consensus position, hampering a direct comparison. It is possible that our definition of “agreement” sets a higher standard than, for example, Anderegg’s definition (e.g., AR4 WG1 author or having signed a public declaration) and Doran and Kendall-Zimmermann’s survey question about whether human activity is “a significant contributing factor”.