The paper is on-line here (free registration required). Update Alternate link at Bray’s site (near the top).
The authors started with 5,947 (reasonably discovered, mostly senior folks from USA, Germany, and UK) email addresses (culled from earlier surveys), but had to toss 1,456 for invalidity. Only 286 people turned in a survey. I was one. This makes for a very dismal 7% response rate. Any conclusions drawn from this study should therefore be viewed with fish eyes, because 93% had noting to say, did not to participate, who knows why.
What follows is a summary. Most questions were on a 7-point scale, higher more confident, increased significantly, that sort of thing. I dichotomize these, with 4 (neutral) and above or 3 and lower.
Main: No Consensus
Only 8% (of the 7%) said their “confidence in the findings of climate science” decreased. Which is to say—and not for the last time—there is no consensus. Of the other 93% who didn’t turn in a survey, nobody knows. But there are at least some who aren’t so happy with the state of affairs in climatology (I’m one).
On a bright note (to me), about 36% did not agree that “climate science has remained a value-neutral science.” But no consensus.
Around 11% felt “less confident concerning the IPCC’s attribution of warming to GHS”. No consensus in the 7%.
Model Modules: No Consensus
Some 20% did not agree that “Climate models accurately simulate the climatic conditions for which they are calibrated.” No C. Same number of folks disagreed that atmospheric models deal well with hydrodynamics. Only 10% were skeptical of modeling radiation. But 26% worried about simulate vapour in the atmosphere.
And a whole 60% admitted that climate models don’t do well with “the influence of clouds.” About half had the same negative view of precipitation, and between 50-60% frowned on atmospheric convection. Gee, No C.
The same pattern repeated itself for ocean modeling, so I won’t repeat it, except to note that 24% did not think models had the “ability to couple atmospheric and ocean models.” No C again.
What about turbulence in climate models? Just under half said no confidence; 28% said nope to land surface processes; about the same were dim on sea ice. Least negative were views on surface albedo and “green house gases emitted from anthropogenic sources”; about 14% were negative on each. No C.
Model Mimicking: No Consensus
About 9% were skeptical that models were able to reproduce both “mean values for the last 50 years” and “trends for the last 50 years”. More than double that (around 21%) were skeptical about reproducing “variability for the last 50 years.” Some 24% didn’t think models did well with precipitation over the last 50 years.
Even more—37%—said the models could not reproduce “trends for the last 50 years.” And even more still (52%!) thought models blew it on “variability for the last 50 years”. Talk about no consensus! (Of the 7%.)
Model Predictions: No Consensus
Despite that half thought models stank at reproducing variability, only 25% (why not the same 50%?) or so thought models would not well predict “mean values for the next 10 years” nor would they well predict “trends for the next 10 years.” And even more, around 38%, didn’t think models will do well with “variability for the next 10 years.” No C again.
It was the same story for predicting 50 years ahead, with even more folks skeptical of models making such long-range predictions.
Predicted precipitation? 42% said no to “mean values for the next 10 years”; 54% or so said no to “trends for the next 10 years”; and around 68% said no to “variability for the next 10 years.” Out 50 years, and skepticism only grows (as it should). No C.
Sea-level rise? Around 19% said no to good predictions of “mean values for the next 10 years”. About 23% said no to “trends for the next 10 years”, and about 31% said no to “variability for the next 10 years.” As before, out 50 years and only a handful believe. No C.
Extreme events? Over half (52%) didn’t think models would do well predicting “mean values for the next 10 years.” Around 60% said no to “trends for the next 10 years” and some 66% said no to “variability for the next 10 years.” Once more, looking out 50 years produces very little confidence. No C.
The authors also asked a series of questions on regional models, which produced less agreement than the global models; indeed, the majority were skeptical on many questions. No Consensus discovered. (Of the few who bothered to answer.)
Impact!: No Consensus
Around 28% didn’t think they had much to say about “the detrimental effects that climate change will have on society”.
Pay attention: The closest to a Consensus was to the question “How convinced are you that climate change, whether natural or anthropogenic, is occurring now?” Only 2% disagreed. Now, if even this banal, harmless question (“natural or anthropogenic“) cannot produce a Consensus, then what can?
About 11% were not convinced “that most of recent or near future climate change is, or will be, a result of anthropogenic causes”; about 14% were not convinced “that climate change poses a very serious and dangerous threat to humanity”. Note the words very serious.
Some 9% didn’t think we were feeling effects of a changed climate yet. But 38% said we could not “ttribute recent climate related disasters to climate change (anthropogenic or otherwise)”. Note that “anthropogenic or otherwise”.
The hardest question to summarize was this: “Since 1850, it is estimated that the world has warmed by 0.7 degrees C. Approximately what percent would you attribute to human causes?” About 10% said thirty-percent attribution or less. The peak was 26% at eighty-percent attribution. But, no consensus.
View: No Consensus
There then followed a series of questions on what interactions climate scientists had with the public. But about 60% of scientists said that adaptation is better than mitigation when dealing with climate change problems. Whoa!
Again, around 60% disagreed with the practice which some scientists employ; those who “present extreme accounts of catastrophic impacts related to climate change in a popular format with the claim that it is their task to alert the public.” (Bad news, right, Gav?) But still no consensus.
Even 33% said it was not the job of climate scientists to “be directly involved in alerting the general public about the possible socio-economic consequences to humans (health, policies, damages, economic loss, etc.) resulting from changes in the climate”
There then followed a few more questions along the same lines, all pointing to mixed views on the proper role of scientists and public policy.
Indulge Me: You can skip this section
The last few questions were of interest to statisticians. To “A description of the most probable outcome best defines” 28% said “a projection”, 64% said “a prediction”, and the rest “other.”
To “A description of a possible outcome best defines” 62% said “a projection”, 16% said “a prediction”, and the rest “other.”
To “From a scenario simulation prepared with climate models, scientists are more inclined to make” 76% said “a projection” and 18% “a prediction” and the rest “other.”
Now, since according to logic, all predictions are conditional (as all probability is condition), there is no difference in “a projection” or “a prediction.” Though I have the idea more people would like to hide behind the former, as it sounds weaker. More on this another day.
Overall Conclusion
I’m struggling to tie a theme together. Maybe readers can help me?
Theme: How about reading this report is more effective than counting sheep? I also think that in judging paper survey reports, which are the bane of legitimate research, a suitable control should be administered that tests for simple literacy. Questions like “to sustain life potable water is required on a daily basis” should be peppered throughout the survey. Any survey that doesn’t get 100% agreement on these questions should be tossed.
If this were any other type of study, I would say it never should have seen the light of day. It is barely, indiscernibly, better than “a survey of 13 college students paid to participate.” Better I guess than the birds in Australia who did one extrapolating results of just one or two responses.
They should have done something to get a large enough number of “random” respondents to actually have a finding.
It is embarrassing.
Just my two cents on your future article. They are all predictions. If you mention the future, it’s a prediction. Of course though, there are different types of predictions.
A projection is a type of prediction of the future which is based on current (and historic) trends. The stock market is a classic example of making projections. What happens to orange futures when there is a wet spring? Look at the past.
So what is a weather forecast? A climate model output? I don’t know, I’ll wait for your article.
Michael Craig,
It would seem to me that all predictions (other than WAGs and signs from the gods) are based on past performance — even those based on physical models. Effectively, those models say: (nearly) every time I have had X=x I got Y=y. The “nearly” is always present but often swept under the rug calling it things like “experimental error”.
Projections are predictions made from the most recent extended trend line. Essentially, the condition is “if this goes on”.
Those are my definitions anyway. I came across one site that had them reversed.
I would think a forecast is any prediction into the future but the way some people use the word it’s not clear.
Michael Craig,
Completely OT: one of my sisters has two sons named, in order of birth, Michael and Craig. Ain’t life sumthin?
I think Al Gore might have some ideas on how it ties together.
FIRST THIS: “Any conclusions drawn from this study should therefore be viewed with fish eyes, because 93% had noting to say, did not to participate, who knows why.”
THEN THIS!?!?!?!?: “I’m struggling to tie a theme together. Maybe readers can help me?”
Presumably the question immediately above is not limited to the dubious study described…because if it is, it is logically inconsistent from the obvious observation made initially (i.e. it is illogical to try & extract a meaningful ‘anything’ from a study one recognizes is dubious or worse).
Seems like the sensible thing to do is find a credible study [or studies] from which to develop a credible theme. Toss this one away.
This appears to be the fourth study in a series. Maybe the first three can help tie things together:
http://klimazwiebel.blogspot.com/search/label/CliSci%20Survey
Dr. Briggs, out of curiosity, what is the background in your career, studies, etc. that would allow you to opine on such questions as “turbulence in climate models” or “climate models don’t do well with clouds?” Generally, in what way do you consider yourself to be a climate scientist? What portion of the surveyed population actually consisted of those who actually study climate?
Also, you say “Only 8% (of the 7%) said their confidence in the findings of climate science’ decreased.” Doesn’t this mean that 92% (of the 7%) did NOT have their confidence in the findings of climate science decrease?
Lastly, your link to the paper appears to be broken.
Rob Ryan: I had the same problem with the link. If you just google the authors and do a bit of looking, you can get to academia.edu piece. You do have to sign up to download the article.
Rob Ryan,
Well, first I have a Bachelor’s in Meteorology, then a Masters in Atmospheric Physics (where I began my transition from dynamics to probability), then a PhD in Mathematical Statistics where I studied model goodness and skill. Then I was for a long time Associate Editor of Monthly Weather Review, and served on the American Meteorological Society’s Probability & Statistics Committee. Then I published several articles in Journal of Climate and other atmospheric entities (including solar weather!). Then I spent years doing work in the field.
Now, what are you qualifications to judge the claims of climatology?
I do not ask to be glib, but (and I know you’re not in this camp) I always wonder that people who know much less than I are so much more concerned about the state of the atmosphere.
I notice you worded your response as “who know much less than I”, not who posses higher or “better” degrees.
From experience on other blogs, I find it best not to say “what are your qualifications” or “how do you know so much”. Very often, the blogger or commenter has very high qualifications. Not so much a problem here, but I have seen that question blossom to a heated argument over whether or not everyone had qualifications worthy of the asker’s consideration, rather than the argument or data at hand.
So 92%(of 7%) have maintained or increased their confidence in the findings of climate science. 98% do believe that climate change is happening and 89% do think that it is mostly anthropogenic. And 2/3 of them think that it IS the job of climate science to “be *directly* involved in alerting the general public”. Perhaps your ideal of consensus is only really ever likely with a sample size of one.
With regard to your requested indulgence:
1. I think a “prediction” refers to the assertion that something *will* happen. I believe that the attachment of “probabilities” to outcomes only makes sense in a very restricted class of situations, but that any statement about the probability of outcomes in a repeatable experiment or game can be interpreted as a “prediction” about ultimate limiting frequencies (albeit one that can never in finite time be truly tested). In that sense, I suppose identifying the mode of a distribution counts as a prediction, but one that is not very interesting without some more information about the nature of that distribution. Similarly, in the repeatable context, the assertion that some outcome has nonzero probability (ie is “possible”) can be seen as a prediction, but I wouldn’t interpret it that way in a single trial.(Though perhaps oddly, I would interpret the assertion of zero probability as a prediction that the event will not happen.)
2. To me the word “projection” implies something like extrapolation from a model which may or may not be a good fit to the future data and so doesn’t necessarily say anything about either the probability or the possibility of an outcome. If one believes the model to be accurate then I suppose one might use the projection to make a prediction, but the projection and the prediction aren’t really the same thing.
>>”I always wonder that people who know much less than I are so much more concerned about the state of the atmosphere.â€
The REAL climate scientists wonder the same thing too.
Everybody missed the point. Which is: there is no consensus among qualified experts regarding climate models or their predictions.
No consensus. The “Consensus Argument” is thus disproved.
Argue about that!
Tom,
Are you one of these “REAL climate scientists”?
It does not matter what your background is. All that matters is someone questioning if you have any skills to make your skills questionable.
Try and talk about the facts or the theory behind the concepts of temperature, modeling, enthalpy, thermodynamics, fluid dynamics, boundary layers, and the challenges of all of them and you run smack dab into the “Who are you to question ‘REAL’ authorities?”
http://neurotheory.columbia.edu/~ken/cargo_cult.html
I am a guy who admires what Feynman said and am constantly asking myself how am I wrong?
When our hosts writes, I see a constant undertone of this. This entire article keeps reiterating it over and over… The uncertainty of the data is huge.
Feynman, Briggs, Brignell, Milloy, Bishop Hill, and the entire underground cabal that is the “Global Warming Skeptic” movement, keeps trying to point to “How is this wrong?” The challenge is that there is nothing there. Pointing at nothing inspires no one except for nuts like me who fixate on the importance of the nothingness. Pointing at scary pictures of hurricanes and tornadoes though, that gets butts in the seats.
Well, my qualifications are irrelevant since I didn’t participate in the survey. I agree that, when discussing facts and evidence, degrees and such are generally not relevant (nor, for the matter of that, is whose name is at the bottom of checks written to the propounder). This isn’t that. This is a discussion of people’s opinions on other people’s claims. As such, the background on those who opine IS relevant, particularly when the issue at hand is a bunch of head counts.
As it happens, I have no background in climatology, I have a BS in mathematics and am pursuing an MS in applied mathematics. I run an engineering firm. My opinion on the various questions raised in the survey is (and can only be) based on choosing the people to whom to give credence, certainly not on evaluation of the primary literature or on fundamental geophysics.
In many areas, this is how one must choose. If I’m deciding my view on whether string theory or loop quantum gravity is a more accurate description of fundamental physics, I’m not likely to learn the background in sufficient depth to base my opinion on evaluation of the primary literature and the papers of the proponents (assuming, generously, that I even had the intelligence to do so). Similarly with many medical decisions. If I’m to have an opinion, it will, of necessity, be based on choosing who “seems” more credible. I’ve blogged a couple of times on this dilemma.
Dr. Briggs, thanks for answering the question. But many who know as much or more than you are very concerned. As a non-expert taxpayer, economic participant, and voter I have to decide in whose opinion to place the most credence.
I am not a scientist and on a good day can occasionally remember how to solve a moderately complex differential equation (with a slide rule). When I read of IPPC conclaves, my mind sees politicians, scientists, and celebrities all screaming in a multitude of languages that (i) they know with precision the problem, and (ii) know with more precision the solution. These gatherings are rock concerts featuring songs that everyone knows chorus lyrics but is struggling to write the verse and refrain. My meager BSCE and MBA qualifications only enable me to only opine that IPPC science is not.
As an aside, along with computers on nearly all operating systems, Maple, Mathcad, Mathematica, Matlab, Derive, Sage, and Python, I also have (and use) a slide rule and have (but don’t use except to keep in practice) an abacus. You know, in case the balloon goes up…
One does not need to be able to do differential calculus to be able to determine whether or not climatologists preaching climate change have flawed arguments. A great deal of information given out by these individuals has little or no math and a great number of fallacious arguments and ad hominem attacks. Their “scientific method” is anything but scientific.
Deferring to experts is a difficult task when the experts are in total disagreement with each other. Do you go with the ones that get the most press? Do you go with the ones who are the most charming? The ones that are the most frightening? How do you know who to listen to? I would say that’s where understanding of the scientific method and of logical fallacies comes in. If an expert is unwilling to share how he reached his conclusion or to share the data and methods used (except in proprietary sciences), you should be suspicious. If the scientist merely insults you and tells you never to question their authority, that would be a clue. Briggs is generally open to explaining where the data came from and how he arrived at his conclusions here. I have read at least one of his papers on climate done with Willie Soon and it’s quite straightforward. I would suppose if I had questions, he would try to answer. Questions on the methods and data and if I am at least mostly understanding him, that is, not where he got his degree. ( I would note that you do not have to be a scientist to publish peer-reviewed papers, or at least that is what I am told, which really made me question this “expert” stuff.)
Yes, complex mathematics and statistics in science make it difficult for people to understand, but I consider it part of the job of science to attempt to clearly explain at least the methods used, why they were used and to allow questioning. Science is about learning, at whatever level possible. Not name-calling and politics.
There are some very patient climatologists out there that will answer questions all day long if asked politely–I consider these people to be true scientists.
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Uncle Mike, in what way have I “missed the point”?
It seems to me that Briggs is saying that having about 90% of a group in agreement with a proposition (in this case that we are experiencing a period of primarily human caused global warming) does not qualify as having a “consensus”.
While that is true according to one interpretation of the word, most dictionaries do include both unanimous and just widespread opinions as acceptable interpretations of “consensus” – and I would be inclined to characterize 90% agreement as pretty much a consensus, and since 90% indicated an increasing trust in that majority I might even call it a “growing consensus”.
Dear Alan,
Backpeddling are we? Scrambling to find your shoes? Sorry, but redefining commmon words will not save you.
“Consensus” means unanimity. Always has, always will. That’s the meaning intended when the climate hysterics use it. They don’t mean “most” or “a majority” or even “a plurality”. They mean all members of the set agree with whatever the proposition is.
Clearly, they don’t. Nuff said.
Well Uncle Mike, I did check the dictionaries before posting that. So, unlike you, I wasn’t just blowing hot air.