by Judith Curry
“You can say I don’t believe in gravity. But if you step off the cliff you are going down. So we can say I don’t believe climate is changing, but it is based on science.” – Katherine Hayhoe, co-author of the 4th National Climate Assessment Report.
So, should we have the same confidence in the findings of the recently published 4th (U.S.) National Climate Assessment (NCA4) as we do in gravity? How convincing is the NCA4?
The 4th National Climate Assessment (NCA4) is published in two volumes:
- Vol I: Climate Science Special Report
- Vol II: Impacts, Risks, and Adaptation in the United States
I’ve just completed rereading Vol I of the NCA4. There is so much here of concern that it is difficult to know where to start. I have been very critical of the IPCC in the past (but I will certainly admit that the AR5 was a substantial improvement over the AR4). While the NCA4 shares some common problems with the IPCC AR5, the NCA4 makes the IPCC AR5 look like a relative paragon of rationality.
Since the NCA4 is guiding the U.S. federal government in its decision making, not to mention local/state governments and businesses, it is important to point out the problems in the NCA4 Reports and the assessment process, with two objectives:
- provide a more rational assessment of the confidence that should be placed in these findings
- provide motivation and a framework for doing a better job on the next assessment report.
I’m envisioning a number of blog posts on aspects of the NCA4 over the course of the next few months (here’s to hoping that my day job allows for sufficient time to devote to this). A blog post last year Reviewing the Climate Science Special Report crowdsourced error detection on Vol. 1, with many of the comments making good points. What I plan for this series of blog posts is something different than error detection — a focus on framing and fundamental epistemic errors in approach used in the Report.
This first post addresses the issue of overconfidence in the NCA4. I have previously argued that overconfidence is a problem with the IPCC report (see examples from Overconfidence) and the consensus seeking process; however, the overconfidence problem with the NCA4 is much worse.
Example: overconfidence in NCA4
To illustrate the overconfidence problem with the NCA4 Report, consider the following Key Conclusion from Chapter 1 Our Globally Changing Climate:
“Longer-term climate records over past centuries and millennia indicate that average temperatures in recent decades over much of the world have been much higher, and have risen faster during this time period, than at any time in the past 1,700 years or more, the time period for which the global distribution of surface temperatures can be reconstructed. (High confidence)”
This statement really struck me, since it is at odds with the conclusion from the IPCC AR5 WG1 Chapter 5 on paleoclimate:
“For average annual NH temperatures, the period 1983–2012 was very likely the warmest 30-year period of the last 800 years (high confidence) and likely the warmest 30-year period of the last 1400 years (medium confidence).
While my knowledge of paleoclimate is relatively limited, I don’t find the AR5 conclusion to be unreasonable, but it seems rather overconfident with the conclusion regarding the last 1400 years. The NCA4 conclusion, which is stronger than the AR5 conclusion and with greater confidence, made me wonder whether there was some new research that I was unaware of, and whether the authors included young scientists with a new perspective.
Fortunately, the NCA includes a section at the end of each Chapter that provides a traceability analysis for each of the key conclusions:
“Traceable Accounts for each Key Finding: 1) document the process and rationale the authors used in reaching the conclusions in their Key Finding, 2) provide additional information to readers about the quality of the information used, 3) allow traceability to resources and data, and 4) describe the level of likelihood and confidence in the Key Finding. Thus, the Traceable Accounts represent a synthesis of the chapter author team’s judgment of the validity of findings, as determined through evaluation of evidence and agreement in the scientific literature.”
Here is text from the traceability account for the paleoclimate conclusion:
“Description of evidence base. The Key Finding and supporting text summarizes extensive evidence documented in the climate science literature and are similar to statements made in previous national (NCA3) and international assessments. There are many recent studies of the paleoclimate leading to this conclusion including those cited in the report (e.g., Mann et al. 2008; PAGES 2k Consortium 2013).”
“Major uncertainties: Despite the extensive increase in knowledge in the last few decades, there are still many uncertainties in understanding the hemispheric and global changes in climate over Earth’s history, including that of the last few millennia. Additional research efforts in this direction can help reduce those uncertainties.”
“Assessment of confidence based on evidence and agreement, including short description of nature of evidence and level of agreement : There is high confidence for current temperatures to be higher than they have been in at least 1,700 years and perhaps much longer.
I read all this with acute cognitive dissonance. Apart from Steve McIntyre’s takedown of Mann et al. 2008 and PAGES 2K Consortium (for the latest, see PAGES2K: North American Tree Ring Proxies), how can you ‘square’ high confidence with “there are still many uncertainties in understanding the hemispheric and global changes in climate over Earth’s history, including that of the last few millennia”?
Further, Chapter 5 of the AR5 includes 1+ pages on uncertainties in temperature reconstructions for the past 200o years (section 5.3.5.2), a few choice quotes:
“Reconstructing NH, SH or global-mean temperature variations over the last 2000 years remains a challenge due to limitations of spatial sampling, uncertainties in individual proxy records and challenges associated with the statistical methods used to calibrate and integrate multi-proxy information”
“A key finding is that the methods used for many published reconstructions can underestimate the amplitude of the low-frequency variability”
“data are still sparse in the tropics, SH and over the oceans”
“Limitations in proxy data and reconstruction methods suggest that published uncertainties will underestimate the full range of uncertainties of large-scale temperature reconstructions.”
Heck, does all this even justify the AR5’s ‘medium’ confidence level?
I checked the relevant references in the NCA4 Chapter 1; only two (Mann et al., 2008; PAGES 2013), both of which were referenced by the AR5. The one figure from this section was from — you guessed it — Mann et al. (2008).
I next wondered: exactly who were the paleoclimate experts that came up with this stuff? Here is the author list for Chapter 1:
Wuebbles, D.J., D.R. Easterling, K. Hayhoe, T. Knutson, R.E. Kopp, J.P. Kossin, K.E. Kunkel, A.N. LeGrande, C. Mears, W.V. Sweet, P.C. Taylor, R.S. Vose, and M.F. Wehner
I am fairly familiar with half of these scientists (a few of them I have a great deal of respect for), somewhat familiar with another 25%, and unfamiliar with the rest. I looked these up to see which of them were the paleoclimate experts. There are only two authors (Kopp and LeGrande) that appear to have any expertise in paleoclimate, albeit on topics that don’t directly relate to the Key Finding. This is in contrast to an entire chapter in the IPCC AR5 being devoted to paleoclimate, with substantial expertise among the authors.
A pretty big lapse, not having an expert on your author team related to one of 6 key findings. This isn’t to say that a non-expert can’t do a good job of assessing this topic with a sufficient level of effort. However the level of effort here didn’t seem to extend to reading the IPCC AR5 Chapter 5, particularly section 5.3.5.2.
Why wasn’t this caught by the reviewers? The NCA4 advertises an extensive in house and external review process, including the National Academies.
I took some heat for my Report On Sea Level Rise and Climate Change, since it had only a single author and wasn’t peer reviewed. Well, the NCA provides a good example of how multiple authors and peer review is no panacea for providing a useful assessment report.
And finally, does this issue related to whether current temperatures were warmer than the medieval warm period really matter? Well yes, it is very important in context of detection and attribution arguments (which will be the subject of forthcoming posts).
This is but one example of overconfidence in the NCA4. What is going on here?
Confidence guidance in the NCA4
Exactly what does the NCA4 mean by ‘high confidence’? The confidence assessment used in the NCA4 is essentially the same as that used in the IPCC AR5. From the NCA4:
“Confidence in the validity of a finding based on the type, amount, quality, strength, and consistency of evidence (such as mechanistic understanding, theory, data, models, and expert judgment); the skill, range, and consistency of model projections; and the degree of agreement within the body of literature.”
“Assessments of confidence in the Key Findings are based on the expert judgment of the author team. Confidence should not be interpreted probabilistically, as it is distinct from statistical likelihood. “
These descriptions for each confidence category don’t make sense to me; the words ‘low’, ‘medium’ etc. seem at odds with the descriptions of the categories. Also, I thought I recalled a ‘very low’ confidence category from the IPCC AR5 (which is correct link). The AR5 uncertainty guidance doesn’t give verbal descriptions of the confidence categories, although it does include the following figure:
The concept of ‘robust evidence’ will be considered in a subsequent post; this is not at all straightforward to assess.
The uncertainty guidance for the AR4 provides some insight into what is actually meant by these different confidence categories, although this quantitative specification was dropped for the AR5:
Well this table is certainly counterintuitive to my understanding of confidence. If someone told me that their conclusion had 1 or 2 chances out of 10 of being correct, I would have no confidence in that conclusion, and wonder why we are even talking about ‘confidence’ in this situation. ‘Medium confidence’ implies a conclusion that is ‘as likely as not;’ why have any confidence in this category of conclusions, when an opposing conclusion is equally likely to be correct?
Given the somewhat flaky guidance from the IPCC regarding confidence, the NCA4 confidence descriptions are a step in the right direction regarding clarity, but the categories defy the words used to describe them. For example:
- ‘High confidence’ is described as ‘Moderate evidence, medium consensus.’ The words ‘moderate’ and ‘medium’ sound like ‘medium confidence’ to me.
- ‘Medium confidence’ is described as ‘Suggestive evidence (a few sources, limited consistency, models incomplete, methods emerging); competing schools of thought.’ Sounds like ‘low confidence’ to me.
- ‘Low confidence’ is described as inconclusive evidence, disagreement or lack of opinions among experts. Sounds like ‘no confidence’ to me.
- ‘Very high confidence’ should be reserved for evidence where there is very little chance of the conclusion being reversed or whittled down by future research; findings that have stood the test of time and a number of different challenges.
As pointed out by Risbey and Kandlikar (2007), it is very difficult (and perhaps not very meaningful) to disentangle confidence from likelihood when the confidence level is medium or low.
Who exactly is the audience for these confidence levels? Well, other scientists, policy makers and the public. Such misleading terminology contributes to misleading overconfidence in the conclusions — apart from the issue of the actual judgments that go into assigning a confidence level to one of these categories.
Analyses of the overconfidence problem
While I have written previously on the topic of overconfidence, it is good to be reminded and there are some insightful new articles to consider.
Cassam (2017) Overconfidence is an epistemic vice. Excerpts (rearranged and edited without quote marks):
‘Overconfidence’ can be used to refer to positive illusions or to excessive certainty. The former is the tendency to have positive illusions about our merits relative to others. The latter describes the tendency we have to believe that our knowledge is more certain that it really is. Overconfidence can cause arrogance, and the reverse may also be true. Overconfidence and arrogance are in a symbiotic relationship even if they are distinct mental properties.
Cassam distinguishes four types of overconfidence:
- Personal explanations attribute error to the personal qualities of individuals or groups of individuals. Carelessness, gullibility, closed-mindedness, dogmatism, and prejudice and wishful thinking are examples of such qualities. These qualities are epistemic vices.
- Sub-personal explanations attribute error to the automatic, involuntary, and non-conscious operation of hard-wired cognitive mechanisms. These explanations are mechanistic in a way that personal explanations are not, and the mechanisms are universal rather than person-specific.
- Situational explanations attribute error to contingent situational factors such as time pressure, distraction, overwork or fatigue.
- Systemic explanations attribute error to organizational or systemic factors such as lack of resources, poor training, or professional culture.
To the extent that overconfidence is an epistemic vice that is encouraged by the professional culture, it might be described as a ‘professional vice’.
Apart from the epistemic vices of individual climate scientists (activism seems to the best predictor of such vices), my main concern is the systematic biases introduced by the IPCC and NCA assessment processes – systemic ‘professional vice’.
Thomas Kelly explains how such a systematic vice can work, which was summarized in my 2011 paper Reasoning about Climate Uncertainty:
Kelly (2008) argues that “a belief held at earlier times can skew the total evidence that is available at later times, via characteristic biasing mechanisms, in a direction that is favorable to itself.” Kelly (2008) also finds that “All else being equal, individuals tend to be significantly better at detecting fallacies when the fallacy occurs in an argument for a conclusion which they disbelieve, than when the same fallacy occurs in an argument for a conclusion which they believe.” Kelly (2005) provides insights into the consensus building process: “As more and more peers weigh in on a given issue, the proportion of the total evidence which consists of higher order psychological evidence [of what other people believe] increases, and the proportion of the total evidence which consists of first order evidence decreases . . . At some point, when the number of peers grows large enough, the higher order psychological evidence will swamp the first order evidence into virtual insignificance.” Kelly (2005) concludes: “Over time, this invisible hand process tends to bestow a certain competitive advantage to our prior beliefs with respect to confirmation and disconfirmation. . . In deciding what level of confidence is appropriate, we should taken into account the tendency of beliefs to serve as agents in their own confirmation. Kelly refers to this phenomenon as ‘upward epistemic push.’
The Key Finding regarding paleo temperatures described above is an example of upward epistemic push: the existence of a ‘consensus’ on this issue resulted in ignoring most of the relevant first order evidence (i.e. publications), combined with an apparent systemic desire to increase confidence relative to the NCA3 conclusion.
Walters et al. (2016) argues that overconfidence is driven by the neglect of unknowns. Overconfidence is also driven by biased processing of known evidence in favor of a focal hypothesis (similar to Kelly’s argument). Overconfidence is also attributed to motivated reasoning and protecting one’s self image from failure and regret (political agenda and careerism).
Kahneman (2011) refers to as the ‘What You See is All There Is’ (WYSIATI) principle, in context on focusing on known relative to unknown information.
I would say that all of the above are major contributors to systemic overconfidence related to climate change.
Solutions to overconfidence
I have written multiple blog posts previously on strategies for addressing overconfidence, including:
- Red Teams
- The method of multiple working hypotheses
- Cognitive bias – how petroleum scientists deal with it
- I know I’m right(?) – the best cure for overprecision is continual challenges of “How could I be wrong?”
- Certainly not! – on cultivating doubt and finding pleasure in mystery.
- Italian Flag – three-valued logic that explicitly includes unknowns.
From Kelly (2005):
“It is sometimes suggested that how confident a scientist is justified in being that a given hypothesis is true depends, not only on the character of relevant data to which she has been exposed, but also on the space of alternative hypotheses of which she is aware. According to this line of thought, how strongly a given collection of data supports a hypothesis is not wholly determined by the content of the data and the hypothesis. Rather, it also depends upon whether there are other plausible competing hypotheses in the field. It is because of this that the mere articulation of a plausible alternative hypothesis can dramatically reduce how likely the original hypothesis is on the available data.”
From Walters (2016):
“Overconfidence can be reduced by prompting people to ‘consider the alternative’ or by designating a member of a decision-making team to advocate for the alternative (‘devil’s advocate technique’).”
“Our studies show that the evaluation of what evidence is unknown or missing is an important determinant of judged confidence. However, people tend to underappreciate what they don’t know. Thus, overconfidence is driven in part by insufficient consideration of unknown evidence.”
“We conceptualize known unknowns as evidence relevant to a probability assessment that a judge is aware that he or she is missing while making the assessment. We distinguish this from unknown unknowns, evidence that a judge is not aware he or she is missing. It is useful at this point to further distinguish two varieties of unknown unknowns. In some cases a judge may be unaware that he or she is missing evidence but could potentially recognize that this evidence is missing if prompted. We refer to these as retrievable unknowns. In other cases, a judge is unaware that he or she is missing evidence and furthermore would need to be educated about the relevance of that evidence in order to recognize it as missing. We refer to these as unretrievable unknowns.”
“Considering the unknowns may also be more effective than considering the alternative in judgment tasks where no obvious alternative exists. A hybrid strategy of considering both the unknowns and the alternative may be more effective than either strategy alone.”
JC reflections
Nearly everyone is overconfident. See these previous articles:
- The lure of incredible certitude
- We are all confident idiots.
- It pays to be overconfident, even if you have no idea what you are doing
The issue here is overconfidence of scientists and ‘systemic vice’ about policy-relevant science, where the overconfidence harms both the scientific and decision making processes.
I don’t regard myself as overconfident with regards to climate science; in fact some have accused me of being underconfident. My experience in owing a company that makes weather and climate predictions (whose skill is regularly evaluated) has been extremely humbling in this regard. Further, I study and read the literature from philosophy of science, risk management, social psychology and law regarding uncertainty, evidence, judgement, confidence, argumentation.
The most disturbing point here is that overconfidence seems to ‘pay’ in terms of influence of an individual in political debates about science. There doesn’t seem to be much downside for the individuals/groups to eventually being proven wrong. So scientific overconfidence seems to be a victimless crime, with the only ‘victim’ being science itself and then the public who has to live with inappropriate decisions based on this overconfident information
So what are the implications of all this for understanding overconfidence in the IPCC and particularly the NCA? Cognitive biases in the context of an institutionalized consensus building process have arguably resulted in the consensus becoming increasingly confirmed in a self-reinforcing way, with ever growing confidence. The ‘merchants of doubt’ meme has motivated activist scientists (as well as the institutions that support and assess climate science) to downplay uncertainty and overhype confidence in the interests of motivating action on mitigation.
There are numerous strategies that have been studied and employed to help avoid overconfidence in scientific judgments. However, the IPCC and particularly the NCA introduces systemic bias through the assessment process, including consensus seeking.
As a community, we need to do better — a LOT better. The IPCC actually reflects on these issues in terms of carefully considering uncertainty guidance and selection of a relatively diverse group of authors, although the core problems still remain. The NCA appears not to reflect on any of this, resulting in a document with poorly justified and overconfident conclusions.
Climate change is a very serious issue — depending on your perspective, there will be much future loss and damage from either climate change itself or from the policies designed to prevent climate change. Not only do we need to think harder and more carefully about this, but we need to think better, with better ways justifying our arguments and assessing uncertainty, confidence and ignorance.
Sub-personal biases are unavoidable, although as scientists we should work hard to be aware and try to overcome these biases. Multiple scientists with different perspectives can be a big help, but it doesn’t help if you assign a group of ‘pals’ to do the assessment. The issue of systemic bias introduced by institutional constraints and guidelines is of greatest concern.
The task of synthesis and assessment is an important one, and it requires some different skills than a researcher pursuing a narrow research problem. First and foremost, the assessors need to do their homework and read tons of papers, consider multiple perspectives, understand sources of and reasons for disagreement, play ‘devils advocate’, and ask ‘how could we be wrong?’
Instead, what we see in at least some of the sections of the NCA4 is bootstrapping on previous assessments and then inflating the confidence without justification.
More to come, stay tuned.
Moderation note: this is a technical thread, and I am requesting that comments focus on
- the general overconfidence issue
- additional examples (with documentation) of unjustified, overconfident conclusions (e.g. relative to the AR5)
I am focusing on Vol 1 here, since Vol 2 is contingent on the conclusions from Vol 1. General comments about the NCA4 can be made on the week in review or new year thread. Thanks in advance for your comments.
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With all the respect, I want ask the author of the report, what exactly you wanted to convey to the readers?
sjreddy
Irving Lagmuir coined the term Pathological Science in 1953 and defined it as:
(from Wikipedia)
I would suggest that the IPCC process ticks all the boxes.
Nice!!!
“You can say I don’t believe in gravity. But if you step off the cliff you are going down.
≠=========
Climate change is equivalent to gravity changing. Unless we give up fossil fuels gravity will change causing disaster all over the world.
Science wants us to give something today of enormous proven benefit based on a risk that may or may not be real, many years in the future.
No allowance is given for human ingenuity to solve this problem using fossil fuels and the likelihood that we would be giving up the very thing we need to solve the problem.
Very good. For as long as we can tell, gravity has pulled us down and climate has varied but self corrects to within a fairly narrow range. Based on a hypothesis which offers no credible feedback mechanism to amplify a minor effect from CO2, we are supposed to ignore billions of years of evidence. AGW in fact requires us to believe that if we step off a cliff, we will fall up.
Jamal Munshi has recently offered this paper:
https://www.academia.edu/36025745/CIRCULAR_REASONING_IN_CLIMATE_CHANGE_RESEARCH
“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.
In biased research of this kind, researchers do not objectively seek the truth, whatever it may turn out to be, but rather 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.
Confirmation bias is thought to play a role in climate change particularly since climate science provides the rationale for environmental activism and the noble cause of saving humanity or perhaps the planet 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).”
In 1999, there was a series of seminars in Europe focusing on “Uncertainty in Climate Models”, known as the ECLAT series, “Representing Uncertainty in Climate Change Scenarios and Impact Studies” published by the Climatic Research Unit, University of East Anglia. Very many conclusions on uncertainty were drawn from the seminars. I quote from the introduction here:
“even with perfect models and unlimited computing power, for a given forcing scenario, a range of future climates will always be simulated. It is for this reason that the Intergovernmental Panel on Climate Change (IPCC) have always adopted the term ‘projection’.”
Here are a few more statements from the ECLAT series, (not my quote marks within the text):
“Projecting the future state(s) of the world with respect to demographic, economic, social, and technological developments at a time scale consistent with climate change projections is a daunting task, some even consider as straightforward impossible.
Over a century time scale, current states and trends simply cannot be extrapolated. The only certainty is that the future will not be just more of the same of today, but will entail numerous surprises, novelties and discontinuities.
“The probability of occurrence of long-term trends is inversely proportional to the ‘expert’ consensus.”
Excessive self-cite and “benchmarking” of modeling studies to existing scenarios creates the danger of artificially constructing “expert consensus”.
In the presence of multi-decadal climate variability a thirty-year mean may provide an incorrect estimate of the longer-term average climate.”
Uncertainty has now been transformed into “increasing scientific evidence tells us” without ever saying what that evidence is.
I have reviewed my confidence level in climate change.
I am 100% confident climate changes.
I am 97% confident not all journalists know this.
I am 100% confident research into “Mann” Changing historical Climate is justified.
I am 95% confidant snow fall in North America is causing people to question Gore-bull warming.
Happy New Year to all, might go skiing later…
The comparison between the theory of Gravity and the AGW muddle is a profoundly dishonnest one. It purpose is simple: you don’t doubt the knowledge about gravity, therefore you ought to accept ‘climate science’ as well. Implicitly it claims that the science of gravity ‘is settled’. That is rubbish, science is never settled, and that applies also to gravity. There are at least three research groups worldwide who do experiments on gravity at very small distances and atrophysicists have just started to explore the realm of gravitational waves. Why? Because they want to find out if there are aspects to gravity which we have not yet discovered. Science is never settled, and I would not bet against the possibility that two centuries from now there is a description of gravity even more profound than Einstein’s.
epistemology. Ivory tower.
Hölderlin.
literally priceless. Take care of you.
https://www.google.com/search?client=ms-android-samsung&ei=__MtXMnBJKiVmgXkqbOgBw&q=H%C3%B6lderlin+english+&oq=H%C3%B6lderlin+english+&gs_l=mobile-gws-wiz-serp.
“You can say I don’t believe in gravity. But if you step off the cliff you are going down. So we can say I don’t believe climate is changing, but it is based on science.” – Katherine Hayhoe,
__________________________________________________
science – or first steps in life?
https://www.google.com/search?q=children%27s+home+safety+equipment&oq=children+safety+home&aqs=chrome.
“‘High confidence’ is described as ‘Moderate evidence, medium consensus.’ The words ‘moderate’ and ‘medium’ sound like ‘medium confidence’ to me… Such misleading terminology contributes to misleading overconfidence in the conclusions'”
This is called hitting the nail on the head and burying it flat in a single blow. The PURPOSE of assigning a specific but misleading definition is to mislead the public, who will read the words quoted in an article and will assume they mean what they generally mean when they are used in conversation.
‘Overconfidence’ is the *only* word you need from this.
And where else do you see ‘overconfident’ folks if not in pubs, bars and drunken parties?
In part because they are in a large social gathering (The Consensus) but mainly because their brains are chemically depressed – their inhibitory system has been closed down.
The process starts at with breakfast (cereals, toast, jam, jelly, sugar) and when that barrage of junkfood wears off, is re-reinforced with mid-morning snacks of Mars Bars, doughnuts, biscuits, sweetened tea/coffee.
That wears off by lunchtime so another bellyful of junk is taken aboard (what do you have for lunch)
This is a much bigger bellyful than normal so by 15:00 in the afternoon, almost everyone is effectively asleep.
What sort of science are they gonna be doing?
They wake at 15:30 into a dehydration-induced hangover and their heads are full of ‘Oh God I can’t wait to get home’
For what?
Another epic belly full of nutrient free mush washed down with beer, wine and whiskey and in the resulting half-asleep state, they proceed to watch hordes of dysfunctional characters acting out bizarre & surreal situations on Trash TV
Doing what? Slagging each other off. Throwing around wild & exaggerated accusations. Being world-saving Super Heroes.
(Some folks have realised all this and come up with the term ‘Unreasonable Behaviour’. You may have married one of them. And all that ‘food’ is going into a machine that can happily exist, evolved to exist in fact, on a single meal every 24 or 48 hours. Utterly crazy. All the stuff we now eat has stopped being ‘food’. It is a drug.)
Do ANY of those things seem familiar to what Warmists do or wish upon others?
Lets play the game here too – Skeptics also.
The chemically disabled brain loses track of what is real and what is not – it creates fake memories, false beliefs and dysfunctional neural pathways.
It is also lazy, it panics easily, is belligerent and readily gets angry.
It cannot ‘think’ its way out of everyday humdrum problems, let alone huge things like Climate and once it has set its path, it will defend that with great vigour.
Thinking is hard work.
Hence we see endless appeals to the authority of The Computer.
The barrage of depressant chemicals taken aboard throughout the day results in their consumer falling unconscious when they ‘hit the sack’.
NOT asleep. Effectively dead.
Hence why and when aroused 7, 8 or 9 hours later, the chemically deranged brain reaches for 2 things.
Coffee – to wake itself up. (If that’s not bizarre enough after so much ‘sleep’)
And sugar. Exactly similar to the good-old-days, when it reached for a cigarette.
Both do the same thing -creation of a (false) state of happiness and well being and so the new day follows the same path as the previous one – a constant state of semi-sleep, belligerence, (dehydration induced) grumpiness and heightened startle response.
All sensible work ceases as the brain endlessly worries about when its next dose of Dopamine is coming from.
THAT is the real problem.
All the blog posts in the world, all the best reasoned thinking, all the best appeasement and niceness is NOT going to change the mind or behaviour of the chronically chemically depressed brain.
If it does have any effect, it will only reinforce the thinking of the chemically damaged mind and if you persistently push the point, will result in a fight.
A proper fight where folks get hurt.
I’m actually in front of a TV showing ‘news’ and The Main Story this morning is exactly what I’m raving about here:
The Obesity Crisis – the significant side effect of all that drug taking, the sugar-induced dehydration and the trashed sleep. Bizarrely, it was actually predicted to happen. (50 years ago??)
Not HOW it was going to happen, but that it WOULD happen. Note the difference.
No matter, A New Tax will solve it I’m sure.
Oooh, there’s some refugees climbing out of an inflatable boat on the telly now – wonder what THAT is all about? Come to visit the Land of Milk and Honey I expect.
Apart from the GHGE, how wrong is it possible to be?
The NCA4 is largely BS (High confidence).
There is a fifth type of overconfidence:
Does this need to be argued in as much detail? Real sceptical scientists are not the problem or the audience here. They can test this carefully constructed deceit and understand what is fact and what is guessed, what is deceitful assertion and what is honest science in the probablistic sense Feynman sense. No policy maker would ever read such a level of detail, never mind filter the implications, and a lot of statistical climate “scientists” would get (more) lost. They can only follow the simplest truths, that they knew when designing the models to test them. So are there any simple measurable facts to to nail conclusions to and test IPCC assertions against?
1. Seems from your scrutiny that the IPCC base their history of the holocene on the one set of much manipulated, extreme and ultimately unprovable assumptions of Mann et als tree and consequential smoke rings. MOre interesting, although they claim support from other temperature series they don’t actually produce or refer to. So they are relying on an outlier and he mean/median. There ARE others papers with series that show different temperature profiles from different proxy data. The IPCC picked an outlier study, and implied support that doesn’t exist. That is deceitful. The facts support the actual deceit. See graph.
2. FACT: The predictions of doom do not reflect measured reality, so the models are wrong. Probably because the models programme a weak, diminishing logarthmically in power, and ultimately unlikely cause to be dominant, rather than seek the answer. The results can offer no scientific proof, show little measured correlation, are are based on various unprovable guesses input by the modellers, not facts. The most extreme and disparate model outputs versus actual measurements are used as the basis for demanding a response to an unproven in fact cause. Why? Could it be the money?
Why don’t politicians compare the IPCC forecasts with measured reality from real satellite data? Perhaps no one cares to show them? Could it be the money, those skimmimg the cash flow of snake oil cures don’t want to know?
3. Why are the IPCC forecasts NOT validated by the actual data? Which should we believe?The observations or the guesses for reward?
4. Statistical models do not require or prove any physical laws. Climate models are made up for reward by University’s VR “climate scientist” computer theorists to support the client’s particular assumption about CO2 – and simply show statistical correlation by number wrangling. Here is how that work matches reality on the climate facts that anyone can plot for themselves:
Clearly the models are wrong.
5. Why the over forecast? Could this IPCC statement regarding its models be a reason?
“The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.” IPCC: https://www.ipcc.ch/ipccreports/tar/wg1/501.htm
QED?
More Technical bit:
A1 Simple fact of modelling: If you guess a larger sensitivity due to CO2 in history to create a model that correlates with reality in “real times”, and also artificially limit the variables you consider and the sensitivities applied to other variables to get that result, then extrapolating such a model into the future will amplify those errors, e.g. it will be wrong, doesn’t matter who designed it. Obs. I suggest that is as complicated as an non modeller needs to go.
A2 The climate scientist’s deceit is overt, as illustrated above and elsewhere, and hence undeniable (honestly). The real science denial for a fast buck academic statistical modelling industry that the UN created to drive this multi $Trillion deceit is easy to expose, but their pseudo science, as with any pseudo science, is always unprovable either way. That’s why they use it.
A3 Follow the money. The much larger subsidy fraud that depends on belief in “climate change caused by CO2” is wholly provable, and the absolute deceit regarding the deliverability of adeqaute , sustainable, affordable renewable energy (subsidy) industry that can replace fossil enregy (that isn’t renewable nuclear energy) is easy to demonstrate.
But who needs numbers, when you can make Trillions from averting a non-problem – if you can sell this bullshit to fearful citizens as a religion? Never mind the climate, follow the money. Unless you are a major manufacturer and not a populist regime, then you create the energy you need by the methods that work, as in SE Asia, China, India. Because nothing else works.
So this scam is really only working where we have exported the manufacture of our stuff to those who need to emit CO2 or build nuclear to make the energy to make our stuff, and no one left in the de indusrialised world understands how things work, except making a fast buck.
That’s what I think. And can also prove.
Some commentary on the overconfidence issue:
I think, to a point, the confidence scale that is used above and has worked it’s way into reports is indicative of what I call “Societal Inflation”. We do everything bigger etc. as compared to our past. Examples include drink, pizza, fries etc. It used to be, when I was a small lad, that you had small and large. Then medium was added. Over time that criteria has been replaced with medium, large, extra-large, super sized. Small is gone from our sizing criteria. Pinball scoring (This is where I first observed this phenomenon), used to be in the hundreds, then to thousands and now into the millions. So the elevation of the confidence levels is reflective of that.
As an engineer, I will verify what several of the engineers stated above. We would loose out jobs if we did this type of analysis.
Notice that almost none of the predictions stated by the alarmists have any confidence level associated with them. And most of the predictions have a confidence level of almost zero. They are just boldly stated and we move on. The prediction does not occur and we yawn and continue our lives.
The original hockey stick graph showed runaway temperatures in the early 2000s. Media source after media source copied the graph and presented it without reference to sources, confidence level etc. The confidence level for that graph had to be low, but is was not stated or inferred that it was. It looked good to start a movement.
I think another thing that enters into the confidence ratings is the current mentality of so many people, especially young people. They know because they are _____________. Therefore it must be true. Fill in the blank with special, smart, virtuous, etc. It is emotionalism at work. It replaces wisdom, life experiences, facts, technical analyses, and debate.
By having our guiding hand on a colourless odourless trace gas in the atmosphere that feeds plants we have our hand on the thermostat dial that controls the temperature of the globe. That’s not overconfidence but hubris and a whole new category again.
One thing about NCA4 having higher confidence than AR5 that the past few decades were the warmest in the past 1700 years: The AR5 statement is about 1983-2012. If one considers a start year a few years after 1983 and an end year a few years after 2012, one finds global temperature significantly warmer than it was over 1983-2012.
Well, it’s all just a big confidence game, innit. The Climate Hucksters look on people as stupid sheeple, ready to be fleeced.
What truly needs to be conducted and published is an assessment of each piece of evidence. The “confidence measure” should not rise above the confidence associated with each piece of evidence. For example, Mann 2008 needs to include all the opposing material associated with it, and a final conclusion made regarding the confidence in the individual paper as judged by uninterested parties. If both Mann and the other paper bring with them medium confidence, then the overall confidence in the finding should not rise above medium confidence. …. JMO.
“Inconclusive evidence (limited sources, extrapolations, inconsistent findings, poor documentation and/or methods not tested, etc.) disagreement or lack of opinions among experts”
Sounds like a perfect description of what is laughingly called “climate science” to me. So the whole “field” of so-called “climate science” gets a “Low Confidence” rating by their own definition.
When a Warmunist asks me, “Do you believe in gravity?” I reply, “Of course, but I also believe gravity has not gotten any stronger in the last 100 years nor will it turn my children and grandchildren into pancake people.”
I am rather surprised by this statement
It is an ex cathedra statement, nothing more. It presents no evidence for confidence, and I think nothing more demonstrates overconfidence than ex cathedra argumentation.
By the way, Dr. Curry again speaks of a “red team” as a way to inject more rationality into this process. However, won’t members of a red team have many of the same limitations of the “green” team (or whatever the other color is)? Since the skeptical bench is a bit thin and not very deep, won’t some of the red team be unenthusiastic greens? How can we have confidence of a reasonably, or better yet competent, adversarial debate?
The other color is blue.
https://whatis.techtarget.com/definition/red-team-blue-team
Thank you Judith, for the excellent analysis of how they label NCA4 findings with confidence levels. The NCA4 seems to miss some of the qualities found in the AR reports. I think IPCC does a superb job in the scientific AR reports though.
Personally, I think the most interesting part in the NCA4 is the estimates of direct economic damage described in figure 29.3. The economic damage reflects most of the other problems and is therefore usually the single most important metric.
The figure says that the damage in the higher scenario (i.e. the worst case) will amount to between 2% and 11% if GDP in 2090.
My take on this is that it seems to be a rather small problem that the economy become between 2 and 11 percent smaller than it could have become in 71 years. In that time the GDP will probably have grown several hundred percent, and nobody will notice that it has not grown as much as it could.
https://nca2018.globalchange.gov/chapter/29/#key-message-2
/Jan
This is not “epistemic overconfidence”, this is the manifestation of woke progressive-ism on a grand scale. Ideology determines truth, truth become a tool to move the ideological agenda, the agenda is to advance the ideology. The meaning of words, Truth and thus the scientific method are all subverted to become malleable and plastic. All policy advocacy converges far more towards creating the perfect society and by those means to create the Perfect Socialist Man than any other factor.
Marx, in Das Kapital, originally looked to economic reordering to reshape human nature. When his ideology caused the deaths of 100 million people, post-modern Marxists redesigned the vision to use “social justice” and “diversity” as their transformative mechanism. Environmentalism and “climate change” are closely related. But the end goal is the same. When anyone refuses to go along, or refutes it in any way, they must be destroyed by any means necessary because they are holding up humanity’s transformation and Utopia itself.
“You can say I don’t believe in gravity. But if you step off the cliff you are going down. So we can say I don’t believe climate is changing, but it is based on science.” – Katherine Hayhoe, co-author of the 4th National Climate Assessment Report.
false equivalence.
First off, no one doesn’t believe climate is changing. Climate has been changing ever since there’s been a climate (long before man every came along) and will continue change (even long after man is long gone from the scene). so that’s a strawman to go with the false equivalence.
Secondly, the science of gravity is scientific. Science, you see, is predictive. You can predict how fast an object will fall off that cliff and when it will hit the ground (heck when I was a student in High school we performed such calculations as one of our class projects). AGW aka CAGW aka man-made climate change is not predictive (or rather it’s failed in every testable prediction it’s tried to make) therefore it’s not scientific. The arctic is not ice free (despite the prediction of “climate change” proponents), Hurricanes have not increased in number and severity (despite the prediction of “climate change” proponents), the West Side Highway is not underwater (despite the prediction of “climate change” proponents), etc. There isn’t one testable prediction they’ve gotten “right” so far.
Thank you for the always attempting to translate difficult science, philosophy, logic, quality of evidence, et al for the interested, somewhat capable public.
As a former electric utility engineer and lifetime science fan, I offer some additional perspectives: 1. Just as confidence in science is not generally understood, the offered solutions for climate change are also highly questionable from a both effects and economic costs (vs effects of warming and damage). 2. Science in general is highly respected and perhaps too easily and quickly trusted by the general public. Scientific claims and sources are trusted almost religiously-even within the “capable of understanding” science and related communities. 3. The general public and associated folks who could follow along and support or change their beliefs are too busy with life to spend time on issues from even “trusted” sources. Policy is made by the unelected regulators or politicians, both seeking power and hoping to gain at every issue by claiming they’re only interested in the earth, poor, frail, old, young-every subset of humanity as well as the exploitable flora and fauna ..ad infinitum, ad nauseam.
If only there was a scorecard of issues with consistent descriptions of : problem statements, quality of data, evidence, omissions, possibilities, probabilities, full transparency of analysis, assumptions, methods, costs, benefits, choices of action/no action/solutions and resulting personal/ public /national/ global priorities…all forced ranked by magnitudes and confidence in an accessible database.
You are on the right track. As hard as science is, selling it to the general public (and their political sycophants ) is even harder!