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 owning 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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Are the prognostications of “Limits To Growth” and its “40 Year Update” helpful?
Does Claude Levi-Strauss’ greatest fear, “the Poisoning of the Planet,” have any consideration in the climate change debate?
LTG originally expected global population overshoot and collapse, from starvation caused by our failure to invent an effective detoxification response to our 90,000+ man-made chemicals accumulating in and poisoning our planet’s food chains to become obvious sometime between 2030 and 2050.
Its 40 Year Update expected it to happen NLT 2024!
I’ve presumed that the weakest amongst us will be the first to present evidence of that contamination. In our food chains there are I thousands of microbes required to grow, digest and excrete our food.
Are those microbes declining at a similar rate to that of insects?
Cooked, or Contaminated, as they disappear, why won’t we?
With regard to your comment that “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.” — it is not at all obvious to me that there would be “much future loss and damage from … the policies designed to prevent climate change.” Obviously that depends on the policies chosen, but it is at least possible to imagine a market-driven innovation strategy that would result in low costs and high non-climate benefits. Is this not a question for which you (and we) should show less confidence?
I’m not sure that it is possible to imagine a “market-driven innovation strategy” that results in low costs high climate benefits without artificial and certainly governmental constraint. Artificial constraint then in turn supplants “market-driven.” The easiest way to prove the point is to create/design such a product, Kickstart(er) it and sell it. I’m not being glib here. If it is in fact “easy to imagine” then it is easy to provide a plan/product/road map for doing so. I do doubt it though. Frankly, thinking that such a panacea is possible is the summit of overconfidence.
I can imagine a “low-cost and high benefit” strategy, unfortunately I don’t know any, and neither does Reid. Even more unfortunately, high-cost and low-benefit approaches are pushed down our throats. Ask the Yellow Vests.
JBM,
A valid free ‘market-driven innovation strategy’ is the opportunity for anyone to get rich quick by entering into the science of mineral exploration. Go out there, find the makings of a new mine, sell it for a profit. I worked with a modest team for decades in this environment, with success, a dozen new mines and sales to date of $65 billion.
The biggest impediment was unwanted and unsought government intervention. Mineral royalties, property rights, health and safety, aboriginal land rights, export licences, costs of services like electricity and water, etc. None of these was needed as a legislated intervention. We could have navigated with ease.
Society now suffers because these ‘frontier’ type activities are over-regulated to the point of being unattractive. It is easier to turn a quid now by subsidy mining, thus making economic activity a drain, when once it was a benefit.
We now have a mindset that says too often ‘This project could never happen because it would be too hard to write the regulations for it’. That is a social sickness of the mind, like saying that a vaccine is worse than the disease because it is so hard to regulate the vaccine inventors/makers/sellers.
With regret, I can but point out this problem while offering no solution that has a chance of success with current generations and they ways they think. I have a crisis of underconfidence. Geoff.
Low cost/high benefit strategies include things like promoting the use of cover crops by farmers, effective use of biodigesters (particularly for farming applications, where manure from growth operations is used on site to fuel barn heating and other local needs) and other low tech solutions, most of which aren’t “sexy” enough to attract the attention of advocates, who prefer high tech solutions like solar and modern wind power.
@Reid Detchon
I’m not sure if I picked you up correctly but I suspect you are implying that there are likely to be little consequences emerging from ‘policies designed to prevent climate change’.
120,000,000 people in developing countries are expected to die by 2050 (just 31 years away) because the scientific ‘consensus’ is over confident that them inhaling fumes from burning dung and twigs is a better option than the west supporting them to burn coal, gas and nuclear instead.
500,000 people a year are dying in developing countries from poor sanitation because they don’t have access to functional sewage processing, another problem solved by cheap, reliable electricity.
And whilst there is no empirically derived evidence that atmospheric CO2 causes the planet to warm, confidence is high that it causes the planet to warm……????
I’m no scientist but those just strikes me as wrong at any level of confidence when the science tells us sea levels aren’t rising unusually, weather events are not extraordinary and the planet is greening at a phenomenal rate thanks to increased atmospheric CO2.
Are the politics and economics of climate change alarmism doing humanity more harm than good? I would suggest, with increasing confidence that, yes, most emphatically they are.
There is already an identified crisis in one of the 5th richest countries in the world, the UK, with the ‘eat’ or ‘heat’ crisis affecting many on the breadline (nor will I refer to that as poverty because that’s a relative, emotive expression) where the poorest in the UK are faced with a problem created by wildly escalating energy prices thanks to the imposition of unstable renewable energy on a formerly stable grid.
Confidence, to me (a layman) is a question of reality Vs theory. Perceptibly, very little misery is being caused by climate change. Confidence is, however, growing that most ‘climate’ imposed misery is caused by political and economic measures designed to stop something that can’t be stopped even if humans are the cause.
Reid Detchon Re “much future loss and damage from … the policies designed to prevent climate change”
Consider the worst consequence of geoengineering by atmospheric aerosol reflection to cool earth. What if that was sufficient to trigger global cooling into the next glaciation? Demanding trillions of dollars for reducing global warming without quantifying the severe dangers of global cooling is an example of the supreme overconfidence.
The current interglacial is already 2 C below the previous 4 interglacials. Earth has been cooling on average since the Holocene Optimum.
“most interglacials typically last about 10,000 to 30,000 years”.
See Characterizing Interglacials.
We are already some 10,000 years into the present interglacial.
e.g McKitrick and Christy 2018 show that satellite and balloon temperature evidence invalidates global warming models.
A Test of the Tropical 200‐to 300‐hPa Warming Rate in Climate Models
There are at least huge Type B systematic errors between this data and conventional climate models OR between the satellite and balloon data vs surface temperature data that have NOT been identified.
The wild overconfidence of CO2 driven global warming climate models could be numbing us to tipping into long term global cooling as evidenced by the descent from the Holocene Optimum to the Little Ice Age.
The consequences of descending into glaciation could well be the loss of most agriculture with a resultant 5 to 6 billion dying of starvation. A mile thick glacier grinding thru Chicago would cause far greater devestation to Canadian and US agriculture and infrastrucutre than a foot or so of sealevel rise!
Until we have transitioned into cost effective abundant fusion and artificial agriculture we need to seriously consider such alternatives and consequences.
I consider glaciation caused starvation of most of earth a serious possible consequence of the extreme overconfidence identified by Judith Curry amplified by the very high TypeB errors between models and data. It has finite probability with major uncertainties that have not been quantified.
PS See the international standard Guide to the expression of Uncertainty in Measurement BIPM GUM JCGM 100:2008. The IPCC and us National Climate Assessment appear at least oblivious of the huge systemic TypeB errors in its models as evidenced by the obvious overconfidence highlighted here.
I believe we entered the new Ice Age aboout 18000 years ago. Since then the earth has been loosing more heat every day than it retains.This is shown in the Antarctic Ice core.
Weather is just nature removing heat stored in the ocean by freezing water and storing in at the poles. This is how nature keeps the average surface temperature constant, thus the radient hear sent to the black sky relatively constant.
There would not be much future loss and damage from … [pro-nuclear] policies designed to prevent climate change.
I don’t find the label “Overconfidence” helpful. When used in general parlance, I’d take this to be a more benign term than the consequences it creates in this arena. I can’t think of an issue either present or historical in which “group think” so infected an objective pursuit as to render the bulk of an entire field at odds with reality.
I think the overconfidence bear should be poked and engaged with a bit more aggressive language. Otherwise, it is content to remain unconscious to what it perceives to be the fringe.
“Overconfidence” is actually more akin to hubris (pride that removes a correct perception of reality to the point of being destructive).
““Overconfidence” is actually more akin to hubris”
Hubris, it’s been said, tempts nemesis; let’s hope it (a cooling trend) happens soon, before developed countries go further down the renewables rathole.
Judith Curry raises valid concerns about the scientific process in use with regard to the confidence levels reported for current conclusions regarding climate change. Reading this article has increased my doubt about the methods used to determine the extent and potential results of climate change as it is studied and used for policy decisions today.
Consensus does not automatically mean that those who agree are correct in their assumptions. The current methods of communicating climate change information do not include verification of evidence, nor does it probe into the unknowns of climate change determinations, which are numerous and compelling.
If we create policy based on the current scientific process, we risk creating harm as great as that being predicted for an alleged changing climate.
Will the real scientists please stand up? Sheepishness, worry about your career, and the importance of being part of the group do not outweigh the potential for harm if the conclusions are incorrect.
“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)”
OK, so this is in reference to global no NH. “Recent decades” is not stated, at least not in the quote. Also, note that there is an “and” there that implies both the temp and the temp increase.
“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).”
It would be hard to compare the two anyway.
Recently came across an interesting article on this subject: Academics Should Not Be Activists.
AR5 “very low confidence” (less than 1 out of 10 chance) automatically implies “very high confidence” (more than 9 out of 10 chance) of whatever has very low confidence not being true. That strikes me as rather confusing: Having “very low confidence” in something being true is thus by definition identical to having “very high confidence” in the same thing not being true. But low confidence feels like thinking it still could be true but might be lacking sufficient evidence yet (= it is still open). High confidence feels like being pretty sure it is true. They don’t appear to add up, yet they should by definition per AR5. Consider this: “Globally, there is low confidence in attribution of changes in tropical cyclone activity to human influence.” compared to “Globally, there is high confidence in lack of detectable human influence on changes in tropical cyclone activity.” I would not think that the first conclusion is identical to the second (and is interchangeable), even though they are, according to IPCC AR5.
Thank you for the essay
For examples of overconfidence among experts, read the National Academies Press report “Strengthening Forensic Science in the United States: A Path Forward”; you can download it from http://nap.edu/12589.
To this list(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)
I would add cross-examination under oath with penalty of perjury. Thus Red team members would question Blue team members (about prior public statements and disputed or omitted lines of scientific research) and Blue team members would question Red team members. With Red and Blue teams, the Blue team members insult and pillory the Red team members and vice-versa, while ignoring conflicting evidence and speaking in paraphrases instead of direct quotes.
In reading your discussion about the list of paleoclimate experts which appears to include only 2 actual experts, my 2 thoughts were 1) what a shock and 2) if they expect to be above criticism, why lead with the chin.
I spend quite a bit of time explaining to others why I’m a skeptic. And then another reason just pops up, out of nowhere, justifying my position and making it easier to add to the extensive list of reasons.
Another eye rolling day. I keep waiting for the establishment to demonstrate they are worthy of the confidence they inherently expect. They just went backwards…..again.
Unfortunately these hyperbolic confidence levels are probably accurate measures for the authors in question. These folks may not be quite as certain about dangerous AGW as they are about gravity, but close enough. Every NCA exhibits this hyperbole, as do all the other USGCRP reports, at least since 2000 when the first NCA came out.
Thus criticism will achieve nothing as long as the zealots steer the ship. We need either a new crew or no ship.
They just keep lying to us. It is business as usual. Thank you for confirming my gut feeling.
They are not lying. They really believe it.
I don’t believe that they believe in their list of experts.
Absolutely.
Sorry George, but I have no idea what you mean by “they believe in their list of experts.” That list of authors (not experts) is probably correct.
See a comment by cerescokid at 2:04. Even better, read the post.
Curious George:
Their belief stems from emotive conviction, not reason, and so does not properly consider the level of appropriateness (or not) of their sources / experts. Strong emotive support of emergent cultural consensuses bypasses the objectivity necessary to perceive such things. We don’t think all those who are religious adherents (still a big majority in the world) are lying about their beliefs, or about the general validity of their priests or old religious writings; they are just emotively convinced. Same thing with belief in imminent global climate catastrophe. While this also means a fringe of folks more consciously bending the rules due to noble cause corruption, that stems from emotive belief too and the majority of adherents won’t be in this category anyhow. If it was as simple as all the adherents (whether grass roots or indeed elite) lying, the whole social phenomenon associated with a certainty of catastrophic climate change would never have made it out of the nursery. Conscious lying on this scale also implies a massive and massively co-ordinated conspiracy, but in reality no such are needed to explain events; cultural belief provides group co-ordination at instinctive / brain architecture level that bypasses reason and objectivity. Of course in any human enterprise that is large enough, just from statistics there’ll also be a few outright liars and scammers, and for sure the climate change domain has mushroomed in size. But that’s very different to being a main or causal component. Consider Hayhoe’s quote; do you really think this is an expression of bold and conscious lying, or merely deep conviction, an emotive belief?
“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”
However reasonably the formation of a consensus is initially approached, it is a social process, not a scientific one. In the context of perceived high stakes and genuine uncertainty (i.e. lower reality constraints), if the process goes on long enough it will revert to the deeply embedded group behaviours and purpose inherited from our evolutionary history regarding social consensus. Namely to create arbitrary (i.e. essentially myth) certainty in the face of unresolvable uncertainty (for group cohesion), and also label who is in-group (agrees with the arbitrary certainty) and who is out-group (doesn’t agree – hence must be ejected from the group). Perceived high stakes can also be amplified or even created by emergent and emotive consensus narratives. In short, this way of operating is almost certain to lead to the cognitive biases, or at least long-term this it is extremely difficult to protect against (given the group behaviours are governed right down at brain architecture level, they can undermine any safeguards based upon reason, plus indeed the consideration of further evidence within the domain – one reason why out-of-domain assistance is very helpful).
“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
If strictly referring to the report (and Trump’s rejection thereof), which was indeed the context of the CNN interview from which this quote came, the statement is an emotive (not reasoned) conviction that rejects any possibility of uncertainty in the report’s findings. Such convictions are an expectation for adherents of a group consensus emergent via the process above, and which leaves reality behind. However, highly selective memes may often feature plausible deniability; no-one is going to argue that the climate isn’t changing, and in this very different context the text is somewhat defensible.
It is not at all clear that the climate is changing, because that statement alone is too vague to be meaningful. In many ways the climate is completely unchanging. To take a long term example, there is a regular (that is, unchanging) oscillation between long ice ages and short interglacials. We see the same thing at many different shorter scales. My favorite climate joke goes like this:
Stranger: “Think it will rain?”
Farmer: “It always has.”
Or consider this. Is a sine wave constantly changing or unchanging? It depends on what you mean by changing.
It is both intuitively right (the public know about ice ages but would not generally consider an oscillation to be ‘unchanging’, and in practice the detailed nature of the oscillation does change), plus also this…
‘…that statement alone is too vague to be meaningful…’
…indeed means that it can never as such be wrong 0:
The public per se does not generally consider anything. Another hopelessly vague concept. There are may such in the climate debate.
I started with ‘intuitive’, and should have stuck to that only.
“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.
You can say you don’t believe that the combination of increased CO2, increased temperature, and increased rainfall over the last 100+ years has increased net primary productivity, but if you reduce CO2 emissions you will likely only reduce net primary productivity. This is based on science.
You can say that you don’t believe that human CO2 has played a small role in the warming over the last 100+ years, but if you reduce CO2 emissions you will have a negligible effect on climate change. This is based on science.
I dare say I am less confident than Katherine Hayhoe, though I do “believe in” climate change. But I think the science now comes down on the side that human intentions to reduce human CO2 emissions are unlikely to have beneficial effects.
Hayhoe’s “we can say I don’t believe climate is changing” is an illogical strawman argument with implicit accusation of being illiterate of anti-scientific.
99.9% of geologists and engineers will say climate (as a 30 year average) has been changing for 3 billion years.
Hayhoe’s use of “climate change” is also an illogical equivocation – to mean “majority anthropogenic global warming” – again with implied accusation if you say no.
Nick, I am a P.Eng, mechanical ‘74 with post grad courses in heat transfer, with the same obligations to be correct.
The amount of heat being radiated from one surface to another is
q/a= [k/(1/ehot+1/ecold-1] x (Thot^4-Tcold^4).
The ground is at Thot due to being warmed by sunshine,
If the atmosphere was only N2 and O2, it would be completelely transparent to Infrared. The “surface” the ground would radiate to is outer space at -270 C. But CO2 and H2O readily absorb and reradiate IR. Because the H2O and CO2 are the same temperature in the atmosphere as the N2 and CO2, the “surface” the ground radiates to is “the sky”, and the “sky” is much warmer than outer space. You can take an IR thermometer and typically read the temperature of clouds at about freezing and blue sky down to -80, but $40 IR guns do not have proper emissivity settings for this job. Anyway my point is that the ground temp has to get warmer as it heats in the sunshine in order for Qout and Qin to be equal, when there are radiating gases between the ground and outer space.
Yes, it is foolish to assume a constant Albedo of .3 to come up with the often stated 33 C number, when Albedo is so dependent on clouds and clouds are made of water, but people who make this generalization are only trying to show how the radiative gas effect works,
Doug Affirm. For details see Line By Line (LBL) modeling with 11 greenhouse gases, 3459 spectral regions, and 150 atmospheric levels. e.g. by Ferenc Miskolczi using HARTCODE. https://www.researchgate.net/profile/Ferenc_Miskolczi/publication/268507883_The_Greenhouse_Effect_and_the_Infrared_Radiative_Structure_of_the_Earth%27s_Atmosphere/links/5a1c29d40f7e9be37f9d5b8e/The-Greenhouse-Effect-and-the-Infrared-Radiative-Structure-of-the-Earths-Atmosphere.pdf
PS At full sensitivity analysis, O2 also weakly absorbs/radiates.
Yup.
This.
JC asks for: examples (with documentation) of unjustified, overconfident conclusions
This is part of a paper rejection by an editor-in-chief of a scientific journal. I can forward the whole document with all details to JC if requested. It shows unjustified adherence to climate models on the basis that they are the best we have, in spite of (evidently) multiple instances of evidence that they have serious problems:
“Having done and presented this valuable analytical work, you then move to concluding that climate models are wrong because they do not reproduce these trends. In a sense, you are right as current models have many serious problems because of their poor resolution and their crude parameterisations of key processes. Every single piece of work that uses observational data sets could be used to criticise model performance. The conclusion that models are imperfect is, as a result, hardly new or illuminating. Models, nevertheless, encapsulate the best of our current understanding, however incomplete, and so their output need to be taken seriously (as the IPCC does) even with a pinch of salt.”
I would also note that there are many people who do not use any trace of salt at all. In other word, there is overconfidence among those who apply the model findings, as well as among those who produce and/or interpret the model findings.
Beautiful. Models have to be taken seriously. “Long-Term Capital Management (LTCM) was a large hedge fund led by Nobel Prize-winning economists and renowned Wall Street traders that nearly collapsed the global financial system in 1998.” They took their model really seriously.
It does seem there has been a driving down of the confidence assigned to the probability. Maybe this is a deliberate strategy as it hard to see it being anything else. Assigning the wording medium confidence to something that is 50% likely to be wrong (a coin toss) just makes a mockery of things. Imagine if it was just a weather forecast – People would rightly rubbish it as useless.
Why aren’t they called out on the deliberately loose terminology? It wouldn’t be tolerated in any other science.
Attribution is of moderate scientific interest – but inherently variable and unpredictable. Of much more interest is continued observation of Earth system processes in a complex dynamical system characterized by abrupt and more or less extreme change in energy trajectories, hydrology and biology. Is uncertainty your friend?
“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.
Hayhoe statement is just an “Appeal to Authority”. Just substituting putative “Scientists” for the more traditional “Priesthood”
An Ecologist’s Perspective on Pope Francis’s Encyclical Letter
Guest Contributor: Dan Botkin
Be that as it may, the greatest importance of the pope’s document is that it makes clear once and for all that this issue is fundamentally a religious and an ideological one, not a scientific one. As I make clear in several of my books and many of my articles, the fundamental irony of environmental science is that it is premised on mythology, on the myth of the great balance of nature, which is not scientific and not scientifically correct
https://wattsupwiththat.com/2015/07/04/an-ecologists-perspective-on-pope-franciss-encyclical-letter/
The Hayhoe “statement” is just a word salad.
The fundamental precept of ecology – environmental science is something different – is the richness and profusion of life occupying every available niche. But nature is red in tooth and claw and there are food webs with some sort of dynamic balance.
e.g. https://www.clatsopcc.edu/sites/default/files/file/rbeveridge/mth252/Sugihara_Fish_Modeling.pdf
Satellite data is the gold standard. One of the authors has some of that:
30-year trends, including the pause, and the biggest cooling in whatever:
https://i.imgur.com/8AVhxYn.png
https://i.imgur.com/naQF7wl.png
https://i.imgur.com/wmR3474.png
“Global-scale multidecadal variability missing in state-of-the-art climate models” – https://www.nature.com/articles/s41612-018-0044-6 – and in JCH’s intellectual microverse.
https://wol-prod-cdn.literatumonline.com/cms/attachment/51a17b52-58d5-4424-b569-2bfcdc8dafef/grl25658-fig-0001.png
“(top) Synchronization as measured by the root‐mean‐square correlation coefficient between all pairs of modes over a 7‐year running window. Note the reversed ordinate; synchronization increases downward in the plot. High synchronization at the p = 0.95 level is denoted by shading, tested by generation of surrogate data as described by Tsonis et al. [2007]. (middle) Coupling as measured by the fraction of consistently increasing or decreasing mode time series as described in the text. The shaded region denotes coupling at the p = 0.95 level as calculated from the surrogate data used for the confidence intervals in Figure 1 (top). (bottom) HadCRUT3g global mean temperature over the 20th century, with approximate breaks in temperature indicated. The cross‐hatched areas indicated time periods when synchronization is accompanied by increasing coupling.”
I know I said that attribution was of minor scientific interest – but we are working on more than half of warming in the last 40 years.
“The global-mean temperature trends associated with GSW are as large as 0.3 °C per 40 years, and so are capable of doubling, nullifying or even reversing the forced global warming trends on that timescale.” op.cit. That’s Global Stadium Wave for the cultural agnotologists.
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Temperature anomalies don’t kill people, absolute temperatures kill people.
Sign my petition, to ban absolute temperatures !!!
We are better off, without them.
My latest article, shows just how evil absolute temperatures really are. They are not quite as evil as CO2, but CO2 has been quietly increasing absolute temperatures, while everybody has been busy looking at temperature anomalies.
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Global warming temperature distributions. (I know that this is a boring title, but the article is incredibly exciting !!!)
========================================
Where else can you see 10.0 and 15.0 degrees Celsius of global warming?
Using a single number to represent global warming, like 1.5 or 2.0 degrees Celsius of global warming, makes it hard to see how bad the problem really is. Is 2.0 degrees Celsius of global warming a major change from what we have now, or is it a minor change?
Using temperature anomalies to represent global warming, removes (or ignores) what is “normal” for temperatures. “Normal”, becomes a single temperature anomaly, 0.0 degrees Celsius. Does 0.0 degrees Celsius, really represent the “normal” temperature distribution of the Earth.
What is the solution to this problem? The answer is to look at temperature distributions, rather than single numbers. Temperature distributions make global warming multi-dimensional, rather than a one-dimensional number. Temperature distributions show how the temperature varies with latitude, elevation, proximity to the ocean, size of the landmass, UHI (urban heat island effect), and many other factors.
Comparing the “normal” temperature distribution, to a “global warming” temperature distribution, makes it easier to judge the size of the problem. Are “alarmists” trying to turn a molehill into a mountain? Or are “deniers” trying to turn a mountain into a molehill?
This article will show you the temperature distributions for a range of global warming “amounts”. People with weak hearts should not look at the more extreme amounts of global warming. Seeing 10.0 or 15.0 degrees Celsius of global warming on a graph, may be too much for those with a vivid imagination.
This article offers a choice of global warming simulations.
1) with NO polar amplification
2) WITH polar amplification
https://agree-to-disagree.com/gw-temperature-distributions-1
Excellent essay Judith. I see this kind of overconfidence all the time particularly with “assessment” reports. These assessments often reflect the consensus in the field as to what will help the field sell its point of view (and get more funding) and often neglect any negative results that might interfere with the message.
There is a strong herd instinct in most fields of computational science with individuals acutely aware of what will damage their reputation with their peers. That has a basis in the soft money culture where peers can be critical to continued funding, the awarding of perquisites, and professional society awards.
Contrary to the climate science warrior “meme” about retired scientists, they are relatively immune from peer pressure and in my view are more likely to be objective in their evaluations of the science.
One of the memes that dominates computational fields is that more physics (or as is more likely pseudo-physics) must be better. A corollary is that if we include all the physics on a fine enough grid, we will get the “right” answer. These memes are very damaging to scientific progress.
Will $4 billion of philanthropy address overconfidence?
Sciences, Publics, Politics: Climate Philanthropy and the Four Billion (Dollars, That Is)
By Matthew C. Nisbet bit.ly/2LNogD4
A crisis of epistemic overconfidence
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.”
–
Fixed the following
“Assessments of confidence in the Key Findings are based on the expert judgment of the author team. Confidence should not be interpreted literally, as it is distinct from statistical likelihood.“
–
The message being pushed is not the level of confidence but the need to have a level of confidence to persuade people to believe.
Yes, and to make sure there is no contradictory messaging that motivates people to actually think for themselves. The worst of all worlds, losing the narrative to the threat of critical thinking.
The IPCC position is stated in AR5 Chapter 6 (1) as:
The removal of human-emitted CO2 from the atmosphere by natural processes will take a few hundred thousand years (high confidence). Depending on the RCP scenario
considered, about 15 to 40% of emitted CO2 will remain in the atmosphere longer than 1,000 years. This very long time required by sinks to remove anthropogenic CO2 makes
climate change caused by elevated CO2 irreversible on human time scale. [original bold]
This high confidence statement has been falsified by Harde 2017. The IPCC also says that all of the recent rise in atmospheric CO2 content is caused by human activity. Harde and others have shown this to be erroneous.
As a degreed and registered mechanical engineer, I have a professional, legal and financial obligation to get it right.
1) 33 C warmer with atmosphere is rubbish. By reflecting 30% of the ISR the atmosphere cools the earth, i.e. it’s hotter without an atmosphere not colder. https://www.linkedin.com/feed/update/urn:li:activity:6473732020483743744
2) The 333 W/m^2 GHG energy loop is thermodynamic nonsense. Not because of the 2nd law regarding entropy, but because it appears out of nowhere violating the 1st law of energy conservation.
3) The surface upwelling 396 W/m^2 LWIR as a BB that powers the GHE is not possible. Because of the non-radiative heat transfer processes radiation’s share, 63/160 = 39.4%, presents an effective emissivity of 63/396 = 0.16 and demonstrated by experiment.
https://principia-scientific.org/debunking-the-greenhouse-gas-theory-with-a-boiling-water-pot/
1 + 2 + 3 = no GHE & no CO2 warming & no man caused climate change.
Bring science, prove me wrong.
Nick Schroeder, BSME CU ’78, CO PE 22774
https://www.linkedin.com/feed/update/urn:li:activity:6466699347852611584
Nick, I am a P.Eng, mechanical ‘74 with post grad courses in heat transfer, with the same obligations to be correct.
The amount of heat being radiated from one surface to another is
q/a= [k/(1/ehot+1/ecold-1] x (Thot^4-Tcold^4).
The ground is at Thot due to being warmed by sunshine,
If the atmosphere was only N2 and O2, it would be completelely transparent to Infrared. The “surface”, the ground would radiate to is outer space at -270 C. But CO2 and H2O readily absorb and reradiate IR. Because the H2O and CO2 are the same temperature in the atmosphere as the N2 and CO2, the “surface” the ground radiates to is “the sky”, and the “sky” is much warmer than outer space. You can take an IR thermometer and typically read the temperature of clouds at about freezing and blue sky down to -80, but $40 IR guns do not have proper emissivity settings for this job. Anyway my point is that the ground temp has to get warmer as it heats in the sunshine in order to radiate the same amount of heat it receives from the sun, when there are radiating gases between the ground and outer space.
Yes, it is foolish to assume a constant Albedo of .3 to come up with the often stated 33 C number, when Albedo is so dependent on clouds and clouds are made of water, but people who make this generalization are only trying to show how the radiative gas effect works.
0.04% GHGs do not have enough mass to absorb/re-emit squat. If they did absorb Trenberth’s 396 W/m^2 they would be so hot as to glow white!
I’m not confident that you have assessed the overconfidence in a robust repeatable way.
“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. ”
1. without the requisite knowledge it seems rather unreasonable to asses the claims or the confidence in those claims. What are we juding when we judge the stated confidence in the claim? I’ll return to this below
2. For NH temperatures over the past 1400 years, they only claim likely for where such an assessment is possible. You missed some critical text in the SPM.
“Each of the last three decades has been successively warmer at the Earth’s surface than any preceding decade since 1850. The period from 1983 to 2012 was likely the warmest 30-year period of the last 1400 years in the Northern Hemisphere, where such assessment is possible (medium confidence).”
It is likely (medium confidence) that you didnt read the whole IPCC text.
The IPCC statement doesnt seem–highly likely–the least bit overconfident . And I am highly confident of that.
A group of experts considered the publications about the past 1400 years in the NH. They conclude that publications show its likely (66% +) that the NH was warmer in the 1983-2012 time period. And they only have medium confidence in this assesment. To tell if this is OVER confident I have to at least do the same work they have. I have to at least read everything they read. And then I have to give reasons why I think Medium confidence is over confident. If I dont do this I cant be confident in my assesment of their confidence. Their confidence results from engaging in a behavior: reviewing all the relevent science. I kinda have to walk a mile in their shoes. You for example have some confidence after working with ECMWF. That confidence is the result of your experience. If I wanted to seriously question your confidence, at a bare minimum I would have to share some of your experience and see if I came to the same conclusion
And it would help ( for traceability) for people to explain WHY their confidence is Medium. Few studies? Studies with shakey assumptions?
new methods? untested methods? Why medium confidence?
If you dont know why Medium confidence, then its very hard to say why medium is too high. If you don’t have knowledge in a field and they dont explain why they have medium confidence, then its over confident to claim that that they are over confident. The simple truth is you may just not know why they say medium confidence and may not know whether that is too much or too little confidence
I have a simpler way of approaching it. An assessors confidence level should be justified by the evidence they use (and cite), and be consistent with the language the use to describe their evidence and the uncertainties and ambiguities associated with their evidence.
Uncertainties and ambiguities were classically handled by the use of statistics on measurements resulting in error analysis and mathematical bounds to express uncertainty.
Sadly, few recent climate papers show any comprehension of the formal treatment of errors, despite established methodologies such as those written by the Bureau of Weights and Measures.
Some might argue that climate research is different, because of the common impossibility of replicating a climate event to measure, for example, a bias so derived conventionally. That might be so, but it does not excuse the lack of formal error analysis in a multitude of other more ordinary endeavours, like finding the temperature of a portion of the atmosphere from time to time adequate to make quantitative descriptions of it and its variations.
The classic, formal approach to uncertainty has no place for subjective assessments or expert opinion. Nor should it have.
Disrespect for such formality about errors and uncertainties is one of the prime reasons why I personally have so little trust of the climate field. Much of it is at a child-like level of intellect, is known to be so, yet is allowed to continue and to grow, with horrible, predictable outcomes. Geoff.
Actually, the errors and uncertainty are so large that they are mostly unquantifiable. Putting ‘medium’ or ‘high’ confidence on errors/uncertainty that you can’t objectively quantify seems rather ridiculous.
Mosh
The Met Office, The Dutch Met Office and various other scientists have concluded that CET is a reasonable, if not perfect proxy for the Northern Hemisphere.
From the instrumental record we can reasonably conclude that there was a remarkable temperature rise from around 1695 and that, according to Lamb and Jones, the 1730’s were the warmest decade until the 1990’s.
From the extended record (my own) to 1535 plus the observations from a variety of scientists and historians it would appear that the few years centred on 1540 were probably the warmest and driest in our history, from any reasonable record until the Domesday book. I have not examined the early part of the 1500’s so can not comment how long lasting the extreme heat and drought lasted in the English record.
I have examined the 1200’s and whilst there were periods of extreme warmth they were relatively short lived so I doubt if there were a very warm 30 year consecutive period as most of this century was rather cool.
There were certainly some extended warm periods in the 1300’s which was quite a turbulent century but as yet I have not examined it in detail, nor the 1400’s.
The medieval warm period is well represented in English literature and records for both architecture,(churches and castles) sea levels (high) altitude of tilled fields and habitation. I would say that any claim of the warmest in the past 1400 years would need to ignore the works of Lamb Groves and many many others.
The high point of the MWP -generally warm and settled with less wind-was around the 750 to around the 1050 period, with a century either side being generally fairly characteristic of the warm period but with undoubtedly some extremely cold periods mixed in.
So we need to explain the 1730’s warm decade, various other decades or longer periods in a variety of centuries and certainly the MWP with its history of exploration, extension of settlements to heights not currently possible, abundance of crops etc which would seriously challenge the IPCC claim of the warmest 30 year period since around the 6th Century.
At that point of course we have abundant evidence of the Roman warm period but the period from around 450 to around 650 or later seemed cold but not as cold as the intermittent little ice age.
The last couple of hundred years illustrate a continual increase of warmth with the starting point being around 1700 rather than 1850. Manley noted the general retreat of the glaciers from around 1750 and Ladurie noted in great detail their sporadic retreat and advance back to the 11th century.
So, the 30 year claim is unproven as yet
tonyb
Thank you tony b
Based on CET, this is flat out false.
The trend from 1700 to 1900 is negative (although not significantly different to zero).
The trend from 1900 to now is, by contrast, nearly two degrees per century.
CET shows a hockey stick.
Mosh
Taking my comment to its logical conclusion we can query the 30 year period used-why 1983?. The 1990’s were the warmest decade in CET since the 1730’s. From the year 2000 there has been a small overall decline in CET
https://wattsupwiththat.com/2018/03/04/the-rise-and-fall-of-central-england-temperatures-help-needed-to-find-missing-data/
What is noticeable is that though we can observe this decline in CET it remains on an overall high plateau. The year just passed was one of the warmest years on record in CET but not the warmest, despite a very hot summer-but not as warm as 1976.
The 1730’s were not noted for their warm summers, but a general overall warmth, with especially mild winter and Autumn.
So the warmest 30 year consecutive period? I would want to check that out, with a start at a year of my choice rather than from the start of the decade, as is more normal, but not it seems with the work under reference-1983?
tonyb
A very happy new year to you very tall guy. I look forward to your article on CET in due course.
tonyb
Tony,
Happy new year to you too!
Here’s my article on CET for you:
CET is only reported daily from 1772, but earlier data is available, should one wish to trust it. Using this earlier data, the trend from 1700 to 1900 is negative (although not significantly different to zero).
The trend from 1900 to now is, by contrast, nearly two degrees per century.
CET shows a hockey stick.
https://www.metoffice.gov.uk/hadobs/hadcet/graphs/HadCET_graph_ylybars_uptodate.gif
ref https://www.metoffice.gov.uk/hadobs/hadcet/index.html
http://climexp.knmi.nl/plotseries.cgi?id=someone@somewhere&TYPE=t&WMO=cet_1900:2018&STATION=Central_England_Temperature&NAME=temperature&KIND=season
CET show no significant warming from 1989 on.
CET winter temperatures show now significant warming for the last century.
The Met Office, The Dutch Met Office and various other scientists have concluded that CET is a reasonable, if not perfect proxy for the Northern Hemisphere.
This is silly.
JCH
Section 6
https://judithcurry.com/2011/12/01/the-long-slow-thaw/
Lamb of Cru, the Met Office, the KNMI, Hulme, Barrow, Lockwood of The University Of Reading, amongst many others, believed CET had a useful place as a proxy for the temperature of the Northern Hemisphere.
Why are they ‘silly’?
tonyb
VTG
In section 3 of this article I described how CET was put together
https://judithcurry.com/2011/12/01/the-long-slow-thaw/
I have also seen in the archives, material from Manley and Lamb that supported the older record which you dismiss as ‘CET is only reported daily from 1772, but earlier data is available, should one wish to trust it.’
I met with David Parker at the Met Office whose name you will note on the bottom right of the chart you link to.
He was perfectly happy with the extended record to 1659. As it is a monthly rather than daily record it tends to be less useful in their research and is limited in its use these days. As you will note, various other innovations have been introduced over the years as regards for example max/min temperatures and in particular the use of a factor to take into account the Urban heat island effect.
Arguably the amount used is not sufficient. Britain is small and is rapidly urbanising as its population soars . It has increased by some 25% since 1974
This and the use of Ringwood as a temperature record, next to a rapidly developing international airport call into question the characteristic modern hump we can observe. I know the Met office were looking at the UHI factor for the period since 2002. I think they are happy that Ringwood has not corrupted the record so this aspect can be set aside.
I am doing an update of CET in the next few weeks so I hope you can contain your excitement
tonyb
TonyB writes “As you will note, various other innovations have been introduced over the years as regards for example max/min temperatures and in particular the use of a factor to take into account the Urban heat island effect.”
The UHI effect badly needs more study. I tried an informal review of it last month
http://www.geoffstuff.com/uhi2018.docx
The more I dug, the longer it got and the more evident the deficiencies became. UHI is an unholy, incomplete mess with capacity to lower the value of the important CET study.
Can I suggest that comparisons of CET with recent times might be better done without instrumental data that might be affected by UHI?
(For now, without formal explanation for this, my private conclusion is that UHI is as big a factor as GHG and natural variation in the last 50 years or so). Geoff.
“….as big a factor as GHG…”
Even without any empirical evidence I tend to agree with you. I would love to see an analysis of how many millions of acres were rural farmland or forests in 1850 and are now heavily developed. In my area the change in only 40 years is tremendous. I can only imagine what the changes have been over 170 years in the US and many other countries.
Geoff and Ceresco kid
You may be interested in this link that illustrates the population of England.
https://en.wikipedia.org/wiki/Demography_of_England
There is a very useful map on the right hand size.
At the start of the CET there were 5.5 million people. Today there are some 55 million. As can be seen England is crowded and the CET area-a triangle north of London to south of Manchester and to the east- takes in a lot of inhabited area.
In the 1600’s there were few made up roads, The most solid ones were made of stone and had been laid by the romans. Since then black tarmac has been laid on tens of thousands of miles of roads, car parks, pavements, driveways and there are much larger urban and industrial areas. To allow this to happen, millions of acres of farmland have been built over.
England is much the size of New York State. It is difficult to imagine all this building has not had an effect.
The Met Office acknowledges this and is currently studying the effect. As I say above, I doubt if the current allowance is enough so I shall await their report with interest.
My ‘man of 70’ graphic shows that the average person has seen a rise of 1 degree c over the lifetime of CET. With a population increase of 5 million to 55 million over the timescale of the graphic how much is natural variation, GHG, uhi and how much are changes in how land is used, would need teasing out, but it is difficult to believe that GHG are responsible for all the increases.
tonyb
VTG
It’s pretty obvious Tony is correct and even more obvious you are incorrect. Apparently you are ignoring the temperatures around 1700.
ceresco
I can only suggest you look at trends starting a couple of decades either side of 1700.
(spoiler: it unsurprisingly makes little difference. The reality is there is no long term trend in CET until the 20th century warming is included. Claims of “continual warming” have no basis in fact)
A perfect proxy for the NH to a useful proxy to a useless proxy.
VTG and TB, this discussion is going nowhere. If either of you has something new to say on this please say it. I will be deleting the repetitive posts for the sake of the other readers. Thanks.
Judith
I agree. This is going nowhere.
tonyb
Mosher, Judith in this regard cites Steve McIntyre who has many hundreds of posts on paleoclimate and is one of the world’s leading experts. Any assessment that omits his work is in my view not worth much. I would liken paleoclimatology to nutrition science. Both are fields where poor statistical methods and poor quality data give a large scope for bias. Both fields have a poor track record.
Exactly, I cited SMI also in my evaluation. SMI is probably the best single person to do a first-order assessment on this topic. I am doing a second order assessment, in terms of assessing whether the assessment appears justified. IPCC AR5 did a first order assessment, whereas NCA4 did a second-order assessment.
I know that. Doesn’t change my position.
She cant assess their confidence.
Full stop.
Two ways she can do this.either do all the work they did.. which she has not.
Or
Evaluate their rational for their confidence, which they don’t supply.
Punting to McIntyre my good friend makes her assessment of their confidence less reliable.
I don’t think she understands what he writes and has never demonstrated that she does.
Best she can do is suspend judgement.
Mosher, I’d be careful with the mind reading of our host if I were you. She has an opinion that I happen to agree with and for which she supplied some good reasons. You disagree. Why can’t you just leave it at that?
If a field of science is generally sloppy and infested with poor work, that by itself justifies low confidence in the results drawn from that field. It’s not a punt.
The accusation is so broad it’s not even a punt. It’s nothing. But nutrition.
The variance of observations from means can be simply calculated. But all methods have limitations that have difficult to quantify departures from reality. Large in paleoclimatology – the ones listed by Judith in the post. Although I have been impressed by the attention to detail and quality control in PAGES2K 2017 especially.
https://media.nature.com/m685/nature-assets/sdata/2017/sdata201788/images_hires/sdata201788-f8.jpg
What I comfortably take from this is that there was a global little ice age before the modern era.
This from PAGES2K 2013 has some interesting features.
https://watertechbyrie.files.wordpress.com/2018/09/pages.png
The hint of leads and lags in a Global Stadium Wave (GSW) and the apparent anti-phase polar warming identified by Rial et al 2014 as synchronous chaos at the millennial scale.
The GSW is a metaphor for perturbation initiated shifts in quasi standing waves in a spinning Earth’s flow field. It is akin to catastrophe theory where small changes in control variables lead to large and abrupt shifts in the system state (e.g. NAS 2002, Broecker 1995) – including in TOA energy flux (Loeb et al 2012, Loeb et al 2018).
But as the IPCC and NCA continue to miss internal variability at decadal scales – e.g. https://www.nature.com/articles/s41612-018-0044-6 – whatever they have to say about recent decades on the basis of paleoclimatology is of no significance.
Hayhoe is one of the most irrational ideologues in climate science. The fact that they have given her the megaphone is reason enough to ignore the assessment as political theater.
The epistemological problem is we don’t even know what we don’t know about CO2 and climate. The only crisis is the deflation of the 16′ blow up mickey mice posturing as scientific savants. They lie on the lawns like morning deflated Santas., even as their workshops continue to crank out toys no one will ever bother to look at.
There never was any basis for confidence that we understand the climatic effect of CO2. The proxies are unequivocal. In deep time CO2 shows no relation, except possibly to follow temperature into the Ordovician glaciation. In ice core time, CO2 follows temperature like a poodle on a leash.
These are proxies, with all the attendant uncertainty.
Our historic measurements are fraught with uncertainty. Dismal coverage, questionable dedication, and poor quality instruments.
In the sober early days of the new year, we should resolve to better understand why temperature still controls the variation around the trend of increasing atmospheric CO2; but CO2 does not control the variation around the trend in increasing temperature.
Figure 2 from NCA4 Executive Summary is an excellent example of graphical overconfidence:
https://science2017.globalchange.gov/img/figure/es-2.png
“Global annual average radiative forcing change from 1750 to 2011 due to human activities, changes in total solar irradiance, and volcanic emissions. Black bars indicate the uncertainty in each. Radiative forcing is a measure of the influence a factor (such as greenhouse gas emissions) has in changing the global balance of incoming and outgoing energy. Radiative forcings greater than zero (positive forcings) produce climate warming; forcings less than zero (negative forcings) produce climate cooling. Over this time period, solar forcing has oscillated on approximately an 11-year cycle between −0.11 and +0.19 W/m2. Radiative forcing due to volcanic emissions is always negative (cooling) and can be very large immediately following significant eruptions but is short-lived. Over the industrial era, the largest volcanic forcing followed the eruption of Mt. Tambora in 1815 (−11.6 W/m2). This forcing declined to −4.5 W/m2 in 1816, and to near-zero by 1820. Forcing due to human activities, in contrast, has becoming increasingly positive (warming) since about 1870, and has grown at an accelerated rate since about 1970. There are also natural variations in temperature and other climate variables which operate on annual to decadal time-scales. This natural variability contributes very little to climate trends over decades and longer.”
All they did was to take figure 8.18 from Chapter 8 AR5 and add all the radiative forcings since 1750. According to that best knowledge there hasn’t been any significant natural contribution to climate change since 1750. The error bars do not permit any other conclusion except that for the last 270 years nearly all climate change has been anthropogenic. If we ask climatologists how many believe this is true, we know based on past polls that a majority of them would respond that they believe natural climate change has played a significant role since 1750. After all they have answered they believe it has done so since 1950.
https://i.imgur.com/6IUuIht.jpg
This is from a poll published by Verheggen et al., 2014, where only 17% spoused the IPCC belief that GHG had caused more than 100% of the observed warming (compensated by aerosol cooling). 50% believed it had caused more than 75%, and 66% believed it had caused more than 50%. If instead of recent warming you would ask them about since 1750, do we think a majority of them would be more convinced that human contribution is likely to be >95%?
At the basis of this figure is the root of the problem. The IPCC has decided that climate change can only be defined and quantified in terms of radiative balance, and any climate factor that has a small impact on radiative balance cannot play a significant role. This essentially rules out anything but GHGs from affecting climate. By accepting that paradigm, the IPCC crowd, that makes a great majority of climate scientists, has painted itself into a corner where it is impossible to understand climate change. Surprises are guaranteed. Until the paradigm is rejected climate science cannot advance.
You don’t have to worry about going off the cliff, because the water level has risen so much with global warming – oh, wait!
Reflections – “My experience in owing a company that makes weather and climate predictions …” “Owning,” I think!
!!! fixed
overconfidence is a problem in most areas of science.
https://www.bbc.com/news/science-environment-39054778
And then you have sociologists and anthropologists happily demonstrating that politicization of research is a thing. And you have an aging, well read population that remembers this whole thing isn’t really partisan. The left abhors scientists and thinks the whole thing is corrupt when it suits their purpose- nuclear, forensics, any geologist who works in the private sector are all horribly, dishonestly wrong about everything!
Excellent post, and (for me) a new perspective.
I did an analysis of every AGW example used in Chapter 1 of NCA3 (2013). Each was either simply false, or false in a broader context (i.e. cherrypicked), or definitionally exaggerated. Concluded the chapter showed deliberate (intentional) NCA bias. Illustrated each example in essay Credibility Conundrums in ebook Blowing Smoke.
Dr Curry,
I am not surprised that you have misgivings regarding the IPCC’s treatment of confidence levels. When reading “IPCC AR5 guidance note on consistent treatment of uncertainties: a common approach across the working groups”, I was struck by a number of serious flaws. In particular, I found the following:
a) Failure to define its terms
There are plenty of references to variables such as ‘confidence’, ‘risk’, ‘likelihood’ and ‘uncertainty’ but nowhere are these terms defined – even though the guidance note has the sole purpose of standardising upon how levels of said variables are to be described.
b) The use of semantically vague terminology
Any adjective that can take the modifiers ‘high’, ‘medium’ and ‘low’ is, by definition, a ‘degree adjective’ suffering all of the problems associated with the philosophy of vagueness. In particular, there will be boundary-related paradoxes and ambiguities resulting from shifting context.
c) Skewed framing
Using the term ‘confidence’ as the measurand communicates a built-in bias towards certitude. A commonly understood definition for ‘confidence’ is ‘full trust’. That being the case, ‘medium confidence’ is no longer a neutral position. If instead of ‘confidence’, one had used ‘uncertainty’ as the measurand, the subject matter would take on an entirely different framing.
d) Treating consensus as an independent factor contributing towards confidence
By treating ‘degree of agreement’ as one of two dimensions in the calculation of confidence levels (the other being evidential weight), figure 1 of the guidance note represents a seriously flawed approach to the metrication of confidence levels:
i) In reality, the level of agreement is not an orthogonal variable that can be treated separately from the robustness of evidence. For example, if the evidence is robust then disagreement should be low, or something very odd is happening. Moreover, it is only when the data is sparse, and expert opinion starts to serve as a substitute, that level of agreement between experts even becomes relevant. That said, when the experts do agree, this agreement is factored into the assessment of evidential weight – it still can’t be treated as a second dimension in the assessment of uncertainty.
ii) In treating levels of dispute as a legitimate measure of uncertainty, the assessment invites the involvement of factors that have much more to do with politics, sociology and cultural bias than they do the objective evaluation of data. The methods adopted by the IPCC represent a professionally immature approach towards uncertainty analysis, in which there is too much focus upon social cohesion within the scientific community and not enough focus upon the evidence.
e) Conflation of uncertainty and risk
It is not always clear whether ‘likelihood’ refers to the probability of occurrence of an event or the prospects for a hypothesis proving incorrect. The former would be a factor in the calculation of risk; the latter is germane when calculating levels of epistemic uncertainty. In this respect I found the advice to be conceptually confusing and too open to misinterpretation.
These, and other deficiencies, will be very apparent to anyone who has any background in the application of uncertainty analysis when making risk-based decisions. There are plenty of professions that fall within that category (e.g. safety-critical systems engineering) and I find it disappointing that greater effort has not been made by the climate science community to engage such expertise.
On a wider matter, I have always found IPCC judgements to be over-reliant upon the use of probabilistic methodologies that pay insufficient regard to the capture and propagation of systemic uncertainty. Once again, one cannot help but feel that a bit of cross-professional liaison would have been of benefit here.
An example of no downside for being overconfident and wrong: Paul Krugman asserted when Trump won that the stock markets would recover and he said never (NYT nov 9 2016). He lost no prestige of work due to being absurdly wrong. Same with climate scientists (the Pause, tropical troposphere hot spot, arctic sea ice, sea level rise, more droughts–all wild forecasts that did not happen).
Nor does krugman suffer any loss of prestige when he claims changes in the minimum wage will not affect the supply and demand curve. He embraces the krueger NJ study in spite of the obvious flaws.
Krugman, who was once a brilliant economist who made a major theoretic contribution, notably on international trade, long ago lost credibility with serious economists. He wrote a book to explain economics simply to the non-cognescenti; that was fine, but it led to his columns in the NYT and swallowing the Green-Left Kool-aid. Best to ignore him.
As an analytic philosopher, I collect semantic tricks in the climate debate, “carbon pollution” being the best. But your take on the NCA4 certainty levels is certainly going on the list. Their high should be medium, their medium should be low and their low should be no. Elegant!
On the education front, please consider my reopened campaign to build a Skeptical Video Center:
https://www.gofundme.com/climate-change-debate-education
There are at least 1000 skeptical videos on YouTube. I want to make them searchable.
Tweet by Scott Adams about overconfidence:
“Four out of the five top comic industry experts said ‘Dilbert” had no commercial potential. Five out of six doctors and specialists told me my voice problem was incurable. And every expert was wrong on nutrition for decades.”
https://twitter.com/ScottAdamsSays/status/1080928424980430848
And then there is the experience of J.K. Rowling. Those publishers that turned her down probably spent years imagining what could have been.
Yes Larry, most smart people know that there is a crisis of confidence in experts for many valid reasons. It continues to amaze me that anyone would take the advice of an MD without doing some research themselves. There is just so much rubbish out there masquerading as science.
DPY,
“most smart people know that there is a crisis of confidence in experts”
Perhaps so. On the other hand, I have seen polls that (from memory) show that trust in scientists has been roughly stable for a long time.
In one of the fields I follow closely, American’s are blindingly trusting, “smart” or not. See The Big List of Lies By Government Officials. All were widely believed at the time. Many still are widely believed, despite being proven falsehoods.
https://fabiusmaximus.com/2015/08/02/big-list-government-lies-87863/
This isn’t the same as trust in experts, of course.
How to NOT find a slowdown.
===========================
The slowdown/pause/hiatus, would probably be only a dim memory, if Alarmists didn’t keep digging up the imaginary corpse, in order to show that it really is dead.
The website called “The Conversation”, recently featured an article called “Global warming ‘hiatus’ is the climate change myth that refuses to die”, by Stephan Lewandowsky and Kevin Cowtan.
It was dated “December 20, 2018”, and the web address is:
https://theconversation.com/global-warming-hiatus-is-the-climate-change-myth-that-refuses-to-die-108524
Both of the authors have also recently co-authored 2 scientific papers, with a large number of other well-known Alarmists (they now write scientific papers in “gangs”, to show how tough they are). The 2 scientific papers claim to “demonstrate convincingly that the slowdown/pause/hiatus wasn’t a real phenomenon”.
It is rare to find a “scientific” article, which features so much “woolly-headed” thinking. And so much misdirection.
It starts badly. Just reading the first 2 paragraphs made me annoyed. They used the word “denier” in the first sentence, and the phrase “science-denying” in the second paragraph.
When did the word “denier”, become a scientific term? What do these arrogant Alarmist jerks, think they are doing. I took a deep breath, and continued reading the article.
The third paragraph really made me sit up, and take notice.
They repeated a common Alarmist lie, about the slowdown, which I talked about in a recent article.
They said, “But, more importantly, these claims use the same kind of misdirection as was used a few years ago about a supposed “pause” in warming lasting from roughly 1998 to 2013.”
They talk about “deniers using misdirection”, and then THEY misdirect people to a false weak slowdown (1998 to 2013). This is part of an Alarmist myth, which claims that the recent slowdown only exists because of the 1998 super El Nino.
In my article, I said:
– The strongest slowdown (the one with the lowest warming rate), went from 2002 to 2012. It had a warming rate of +0.14 degrees Celsius per century. Because it went from 2002 to 2012, it had nothing to do with the 1998 super El Nino.
– The average warming rate from 1970 to 2018, is about +1.8 degrees Celsius per century. So the slowdown from 2002 to 2012, had a warming rate that was less than 8% of the average warming rate.
– If the average warming rate was a car travelling at 100 km/h, then the slowdown was a car that was travelling at less the 8 km/h. Doesn’t that sound like a slowdown?
– The strongest slowdown WHICH INCLUDED THE YEAR 1998 (the one with the lowest warming rate), went from 1998 to 2013. It had a warming rate of +0.96 degrees Celsius per century.
[this is the slowdown interval that Lewandowsky and Cowtan used]
– So the false Alarmist slowdown (1998 to 2013), had a warming rate which was 6.9 times greater than the warming rate of the real slowdown (2002 to 2012).
-If the real slowdown (2002 to 2012) was a car that was traveling at 100 km/h, then the false Alarmist slowdown (1998 to 2013), would be a car that was traveling at 690 km/h.
Perhaps this is one of the reasons why Alarmists don’t believe that there was a slowdown. They are not even looking at the real slowdown.
====================
Lewandowsky and Cowtan seem to be under the impression that, because “the past two years were two of the three hottest on record”, that there could NOT have been a slowdown. Have they never noticed, that when a person takes their foot off the accelerator in a car, the car keeps moving forward (but at a slower rate, i.e. a slowdown)? So the car is still setting records, becoming further from where it started, even though it has slowed down.
This “everyday” observation (about a person taking their foot off the accelerator of a car), appears to be too complicated for them to grasp. Perhaps they are chauffeur driven, everywhere.
====================
Lewandowsky and Cowtan say, “In a nutshell, if you select data based on them being unusual in the first place, then any statistical tests that seemingly confirm their unusual nature give the wrong answer.”
There is a well-known saying, “If it looks like a duck, and walks like a duck, and quacks like a duck, then it probably IS a duck”.
We could rephrase that as, “If it looks like a slowdown, and the warming rate is lower than normal, and the statistical test says that it COULD be a slowdown, then it probably IS a slowdown”.
But Lewandowsky and Cowtan want you to believe that, “If it looks like a slowdown, and the warming rate is lower than normal, and the statistical test says that it COULD be a slowdown, then it DEFINITELY IS NOT A SLOWDOWN”.
Lewandowsky and Cowtan don’t want skeptics to look for slowdowns in places that look like slowdowns. They want skeptics to only look for slowdowns in places that DON’T look like slowdowns.
I would like to suggest that skeptics start looking for slowdowns, on the moon. There isn’t much chance of finding one, but if you do find one, it is almost certainly real.
====================
I am amazed at how Lewandowsky and Cowtan don’t seem to be able to understand simple logic. They give an example, “If someone claims the world hasn’t warmed since 1998 or 2016, ask them why those specific years – why not 1997 or 2014?”
If somebody got run over by a truck in 1998, would you ask them, “Why 1998, why didn’t you get run over by a truck in 1997 or 1999”? If something happens in a particular year, or over a particular interval, then that is a fact. There is little point in questioning why it didn’t happen at a different time.
The reason that Lewandowsky and Cowtan ask, “Why those specific years – why not 1997 or 2014?”, is because they CAN’T PROVE that there wasn’t a slowdown since 1998, and they want to misdirect people, with a stupid question.
====================
Lewandowsky and Cowtan are concerned that skeptics will cherry-pick intervals which “look like” a slowdown, but are not really a slowdown.
I developed a method to analyse date ranges, for slowdowns and speedups, which does NOT cherry-pick date ranges. It does this, by giving equal weight to EVERY possible date range. So when I analyse 1970 to 2018, I calculate about 150,000 linear regressions (one for every possible date range). Then I look at which date ranges have a low warming rate. To make it easier, I colour code all of the results from the 150,000 linear regressions, and plot them on a single graph. I call this graph, a “Global Warming Contour Map”.
If I find that 2002 to 2012 has a low warming rate, then that means that it had a low warming rate, compared to the thousands and thousands of other date ranges that I checked. Every date range has an equal chance of being a slowdown or a speedup, based on its warming rate. The warming rate is an objective measurement, based on a temperature series.
But wait. I don’t stop there. I check every temperature series that I can find. This includes GISTEMP, NOAA, UAH, RSS, BEST, CLIMDIV, RATPAC (weather ballon data), etc.
But wait. I don’t stop there. I check every type of measurement that I can find. Land and Ocean. Land only. Ocean only. Lower troposphere. Upper troposphere, Stratosphere.
But wait. I don’t stop there. I check every region that I can find. Northern hemisphere. Southern hemisphere. Tropical. Extratropical. Polar.
But wait. I don’t stop there. I check every latitude that I can find. 90N to 48N. 48N to 30N. 30N to 14N. 14N to Equator. Equator to 14S. 14S to 30S. 30S to 48S. 48S to 90S
When I say that there was a slowdown, that means that I have found evidence of a slowdown, in most of the major temperature series, types of measurements, regions, and latitudes.
I have made literally hundreds of global warming contour maps, for nearly every type of global warming data, that you can imagine. Each one, based on about 150,000 linear regressions.
I have probably done more linear regressions, than any other person in the world. I may have even done more linear regressions, than everybody in the world, put together.
And all of those linear regressions, tell me that there was a slowdown, sometime after the year 2001. It was strongest from 2002 to 2012. You can measure it in different ways, and get slightly different results. But there is overwhelming evidence for the slowdown.
I didn’t cherry-pick 2002 to 2012. This interval leapt out of my computer screen, slapped me on the face, and yelled, “I am a slowdown, stop ignoring me !!!”
Alarmists, are the real “Deniers”. They ignore the evidence that they can’t explain away. They insult the people who try to show the truth. They lie, when other methods don’t work.
It is time for Alarmists to admit the truth. There was a slowdown. It was not enormously long. It was temporary. It is now over. The fact that it existed, didn’t prove that global warming isn’t happening.
My personal belief, is that the slowdown was caused by ocean cycles, like the PDO and AMO. There are climate scientists, who believe the same thing. We need to acknowledge the slowdown, so that we can learn more about climate. Lying about the slowdown, won’t solve global warming. Understanding the slowdown, might help us to understand global warming.
If anybody would like to learn more about my method, and “Global Warming Contour Maps”, then there are lots of them, on my website. I wrote a special article, called “Robot-Train contour maps”, which explains how contour maps work, using simple “train trips”, as an analogy for global warming.
Here is a small selection of articles about slowdowns, and “global warming contour maps”.
– No, I am not obsessed with slowdowns.
– I didn’t choose slowdowns, they chose me.
– Being the “proud father” of “global warming contour maps”, I am always happy to answer questions, and show you pictures, of my clever baby.
[ this article shows how “global warming contour maps” work ]
https://agree-to-disagree.com/robot-train-contour-maps
[ this article shows why Alarmist thinking on slowdowns, in one-dimensional ]
https://agree-to-disagree.com/alarmist-thinking-on-the-slowdown
[ this article investigates the Alarmist myth, that the slowdown was caused by the 1998 super El Nino ]
https://agree-to-disagree.com/was-the-slowdown-caused-by-1998
[ this article shows why the slowdown is so special (No, no, no, no, no! It only LOOKS special. It isn’t really special.) ]
https://agree-to-disagree.com/how-special-was-the-recent-slowdown
[ A guide to the CORRECT way to look for slowdowns. Please try to stay quiet. Slowdown scare easily, and then they run away and hide. ]
https://agree-to-disagree.com/how-to-look-for-slowdowns
[ this article investigates warming in the USA, using NOAA’s new ClimDiv temperature series ]
https://agree-to-disagree.com/usa-warming
[ this article investigates regional warming, by dividing the earth into 8 equal sized areas, by latitude ]
https://agree-to-disagree.com/new-regional-warming
[ this weather balloon article has global warming contour maps with very nice colours ]
https://agree-to-disagree.com/weather-balloon-data-ratpac
[ this article uses global warming contour maps to compare GISTEMP and UAH ]
https://agree-to-disagree.com/gistemp-and-uah
Pingback: A crisis of overconfidence in climate science - Fabius Maximus website
Judith: Some comments that may be ofvalue:
1) All too often “confidence” is the Bayesian output of evidence and a prior based on personal expectations/objectives. That may explain why the description of levels of confidence all sound more confident than you find appropriate. You might want to try to get such descriptions vetted by a group without an agenda and that doesn’t know how they will be used.
2) Who cares whether the last thirty years is the warmest period in the past millennium or two millennia or ten millennia? If it wasn’t true in 2000 (AR3), it may have hasn’t happened since, and it will happen sooner (if climate sensitivity is high, AOGCMs) or later (EBMs). AFAIK, the nearly 1 K of warming we have experienced in the last half century is one of the biggest fluctuations in the Holocene proxy record – and it comes after the warming that ended the LIA. Mid-century wasn’t an unusually cold starting spot! Recognition of an appropriately larger role for unforced and naturally-forced variability is a reasonable objective, but recognition for the possibility of a lower climate sensitivity is THE most important goal. That drives estimates of the social cost of carbon and all policymaking. And unforced variability undermines confidence in low CS from EBMs. (For me personally, the debate about the MWP is most useful in demonstrating how politics has corrupted climate science.)
3) Why is our National Climate Assessment duplicating the work of the IPCC and not focusing on issues of special importance to the US? In paleoclimate, the extreme droughts in the Southwest during? the MWP are far more important than the temperature of the MWP.
Dr. Curry – well done. Vitally important piece.
With regard to your two requests for comments:
1) “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”.
The public having to live with inappropriate decisions based on this overconfident information is the most serious of crimes in and of itself. Here I think of “scientists” like Trofim Lysenko. So, too is the critical matter of reliance on sound scientific method to highly-advanced industrial societies. Both are victims, and at a level of importance it would be impossible to overstate.
2) There is no shortage of analogues of unjustified, overconfident scientific conclusions:
Ehlich/Holdren & resource depletion
Club of Rome & population/resource “sustainability”
Every IPCC report’s Summary for Policymakers (even if AR5 less so)
Trofim Lysenko
Ruckelshaus’ EPA/DDT
USGS and others – “peak oil”
Eugenics
The Catholic Church vs. Copernicus & Galileo
Your intellectual honesty, courage, and scientific integrity shall be noted by future generations of science historians in relation to climate science. Billions of current and future human residents of planet earth owe you a debt of gratitude you shall never receive from them, directly or indirectly, for your scientific integrity. As one of them, I hereby thank you.
It’s hard to regard with a high interval of confidence a source who has as high an interval of confidencein the Trump administration’s scientific bona fides that which Judith displayed in running Patrick Michaels’
‘National Climate Assessment and the Trump administration
The National Climate Assessment must be redirected or terminated’
eighteen months and a half dozen cabinet members ago.
What an irrelevant and totally unscientific comment Russell.
https://i.imgur.com/SIsjPWO.png
https://i.imgur.com/KbY6Kjd.png
The simplest way to explain the Overconfidence issue is to ask how careers progress if you are not overconfident?
A Climate Science career progresses by multiple peer-reviewed publications with high ‘impact’.
Have you ever tried submitting a paper to Nature saying ‘US hurricane data stubbornly refuses to get worse in the 21st century’?
I can say with high confidence that it will be rejected by return of post.
Not because the data is wrong, the analysis flawed, the implications significant.
No, it will be rejected because it is not politically expedient.
Now imagine you are up for Tenure: you published your rigorous scientific work as an article either here or at e.g. Wattsupwiththat.com i.e. at modern 21st century blogs with little standing in the peer-review-obsessed climate science academic world.
Against you is an overconfident establishment tyro who published ‘Oceanic heat stores show consistently increasing heat stored down to 2000m’, using some dodgy modelling, inconsistent data sets and a total lack of discussion as to the actual change in oceanic temperature (very small), focussing instead on a very big number (total energy stored in Joules). Their work was enthusiastically published in Nature, Science or some other ‘High Impact Journal’.
You do not need to be Judith Curry to go down the bookies and place a bet with Very High Certainty as to who will get tenure. You could do with pulling the wool over the bookie’s eyes a bit to get better odds though.
So we conclude with high certainty that careers advance through gaming the system, and further conclude that the system will select and promote those overconfident hustlers who have gamed it.
You use the same argument with HEIs to conclude that Departments which game the system will be evaluated as being superior, creating a clique of overconfident gaming departments deemed national/global experts.
The Government, being full of arts and humanities graduates, has no way of evaluating science rigorously itself, so outsources it to ‘globally renowned’ scientists. This self-selects overconfident scientists who keep the show on the road by supporting their overconfident friends through judicious selection of topics to focus future funding on.
It is very easy to conclude that overconfidence becomes totally endemic to the Establishment.
This has happened before. In the 1890s, physics ‘was essentially solved’ and a smug self-satisfied elite somehow kept getting paid despite having nothing novel to address.
We all know how that played out. A trumped-up Swiss Patent clerk outraged the Academic Establishment by submitting papers in 1905, receiving responses like ‘Who is this clerk anyway? He is not a Professor in a university!’
The real question in 2019 is simple: ‘How is the unjustified overconfidence of the Establishment going to have its bubble burst?’
Put another way: ‘What level of data dissonance from the Establishment narrative is required to see the whole house of cards come tumbling down?’
It may be rather higher than you might imagine…..