Climate: UNKNOWNS are greater than KNOWNS

In what Prof Judith Curry describes as “incomprehensible to me” and I would describe as “delusional”, the latest IPCC report (AR5) is likely to say the IPCC are MORE CERTAIN that humans caused the latter 20th century warming or as they put it in AR5:

It is “extremely likely that human influence on climate caused more than half of the increase in global average surface temperature from 1951-2010.”

This assertion by the IPCC is false. It is not backed by the consensus of the experts; it isn’t supported by statistics; it isn’t supported by logic, and it is patently obvious from the 20th century climate data.

Not supported by the consensus of experts
The evidential failure of climate models to forecast the recent pause in warming led last year to Prof Curry presenting to the Royal Society Meeting on Climate a presentation ‘Climate models: fit for what purpose?’ in which she concluded that they were not fit for purpose as a basis for government policy. No one disagreed at the time; no one disagree with the statement prominently positioned in the paper I sent to delegates afterwards. That at the meeting:

No one strongly objected when American Professor Judith Curry (2012) articulated what appears to be the new consensus amongst climate experts: that whilst short term weather/climate models are providing important life-saving information, longer term climate models still left a lot to be desired and were probably not presently fit for purpose as a tool for detailed policy making.


Just recently the Met Office finally admitted after numerous parliamentary questioned went unanswered that there is a proven statistical test that shows natural variation can explain all the changes we saw in the 20th century. As Bishop Hill put it so well:

It has been widely claimed that the increase in global temperatures since the late 1800s is too large to be reasonably attributed to natural random variation. Moreover, that claim is arguably the biggest reason for concern about global warming. The basis for the claim has recently been discussed in the UK Parliament. It turns out that the claim has no basis, and scientists at the Met Office have been trying to cover that up.

The Met Office use one statistical test and use this to state the warming must be man-made. But  apparently, they chose to ignore another more appropriate statistical test and which does not support the IPCC statement (and then hid this fact), or as Bishop Hill puts it …

…the likelihood of the driftless model is about 1000 times that of the trending autoregressive model. Thus the model used by HM Government should be rejected, in favor of the driftless model. With the driftless model, however, the rise in temperatures since 1880 is not significant.

IPCC AR5 figure 1.4 showing predicted versus actual. (spurious grey area removed)

IPCC AR5 figure 1.4 showing predicted versus actual. (spurious grey area removed)


Climate models like those shown to the right, predict global temperature based on what is believed to be known about the climate. This is that “Warming of the climate system is unequivocal”**. Real data (as shown on the right in black) shows us there has been no warming recently. Using the simple illustrative equation that what me measure (DATA) is comprised of what we know and what we do not. Or what we can forecast and that which we cannot we can say that:-


Using the notation KNOWNmodels for what was believed to be known when the models were produced (as opposed to what is now “known”), because there has been no increase in global temperature when the models predicted an increase, we can say that the change in the measured DATA is zero. Therefore it follows that:-

UNKNOWNcurrent ~= KNOWNmodels

From this we can say that what is unknown or commonly termed “natural variation” is equal in scale to what was thought to be known which is the predicted  man-made warming. From this we could say natural variation is similar in scale to the previously predicted level of man-made warming. However, because the temperature has been lower than forecast, the current predictions have also been scaled down. So now the “known” (or presumed known) scale of man-made influence is smaller than that previously predicted. This can be expressed as:

KNOWNcurrent < KNOWNmodels

Combing this with the previous equation we come to the conclusion that

KNOWNcurrent <~ UNKNOWNcurrent

In other words, because there has been no warming when warming was predicted, we can confidently say that: it is likely that man-made warming is smaller than natural variation.

20th Century Climate Data

It is an undeniable conclusion that natural variation is likely greater than the “known” impact of man-made warming for the period of about 15 years where warming has been predicted and not occurred, however can we also conclude this for other periods? The answer is yes. CO2 warming in the latter 20th century carried on at pretty much the same pace or smaller due to lower emissions so any effect in the latter 20th century will be comparable or smaller. But is there any evidence to support the assertion that natural variation is present at the same scale?

Comparison of warming from 1910-1940 with that of 1970-2000 showing exactly the same warming. The 1910-1940 is mainly natural variation showing the same scale of natural variation even if ALL the warming from 1970-2000 were manmade.

Comparison of warming from 1910-1940 with that of 1970-2000 showing exactly the same warming.

The above graph using HADCRUT data shows that the warming from 1910-1940 before CO2 was measured rising, which is considered to be mainly natural variation, is exactly the same size and length as the warming from 1970-2000. So natural variation has always been known to be similar in scale to man-made warming. So, even if all the warming in the period after the global cooling scare were man-made it is not greater in scale than natural variation.

Because the statistics, the logic and plain common sense tells us that man-made warming is smaller than “natural variation” or the “unknowns” that caused the climate models to fail, we can confidently say:

It is unlikely that human influence on climate caused more than half of the increase in global average surface temperature from 1951-2010.

No rational person could support the previous IPCC’s report where they said it was “very likely” that the majority of warming is man-made but to increase this confidence in the face of the failed predictions and the statistical tests that say otherwise  is delusional.

**Although the IPCC statement refers to previous warming, the Wikipedia global warming article, which was created by people with a close connection with the IPCC, makes it clear that this statement is intended to infer future warming is also unequivocal: “Warming of the climate system is unequivocal, and scientists are more than 90% certain that it is primarily caused by increasing concentrations of greenhouse gases produced by human activities such as the burning of fossil fuels and deforestation.”

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8 Responses to Climate: UNKNOWNS are greater than KNOWNS

  1. Good last graph with both on exactly the same slope. if CO2 was not rising as fast pre-1940 there simply cannot honestly be an assumption that there is a close, or even clear, correlation between temperature and CO2 rise.

    Which will not stop our totalitarian state media saying otherwise.

  2. In Britain , the gulf between the Met Office expectations for the last several years and the actual string of cold and snowy winters and mostly wet summers which has occurred has made the Met Office a laughing stock-to the point of recently holding a meeting of 25 “experts” to try to figure out where they went wrong.The answer is simple.Their climate models are incorrectly structured because they are based on three irrational and false assumptions. First that CO2 is the main climate driver ,second that in calculating climate sensitivity the GHE due to water vapour should be added to that of CO2 as a feed back effect and third that the GHE of water vapour is always positive.As to the last point the feedbacks cannot be positive otherwise we wouldn’t be here to talk about it .
    Temperature drives both CO2 and water vapour independently,. The whole CAGW – GHG scare is based on the obvious fallacy of putting the effect before the cause.As a simple (not exact) analogy controlling CO2 levels to control temperature is like trying to lower the temperature of an electric hot plate under a boiling pan of water by capturing and sequestering the steam coming off the top.A corollory to this idea is that the whole idea of a simple climate sensitivity to CO2 is nonsense and the sensitivity equation has no physical meaning unless you already know what the natural controls on energy inputs are already ie the extent of the natural variability.
    Furthermore the modelling approach is inherently of no value for predicting future temperature with any calculable certainty because of the difficulty of specifying the initial conditions of a large number of variables with sufficient precision prior to multiple iterations. There is no way of knowing whether the outputs after the parameterisation of the multiple inputs merely hide compensating errors in the system as a whole. The IPCC AR4 WG1 science section actually acknowledges this fact. Section IPCC AR4 WG1 8.6 deals with forcings, feedbacks and climate sensitivity. The conclusions are in section 8.6.4 which deals with the reliability of the projections.It concludes:
    “Moreover it is not yet clear which tests are critical for constraining the future projections,consequently a set of model metrics that might be used to narrow the range of plausible climate change feedbacks and climate sensitivity has yet to be developed”
    What could be clearer. The IPCC in 2007 said itself that we don’t even know what metrics to put into the models to test their reliability.- ie we don’t know what future temperatures will be and we can’t calculate the climate sensitivity to CO2.This also begs a further question of what mere assumptions went into the “plausible” models to be tested anyway.
    In summary the projections of the IPCC – Met office models and all the impact studies which derive from them are based on specifically structurally flawed and inherently useless models.They deserve no place in any serious discussion of future climate trends and represent an enormous waste of time and money.As a basis for public policy their forecasts are grossly in error and therefore worse than useless.
    For an empirically based forecast of the timing and extent of the coming cooling see

    • Thanks for the reply. Regarding the Met Office, I was quite surprised to find at the Royal Society meeting that there wasn’t a lot of difference between what I was saying and the modellers. I therefore believe that there is a layer above these modellers which is distorting their views and conveying distorted to view to others.

      However, I am also actively investigating the possibility that we sceptics and those like the Met office are divided by differences in culture and approach due to our different professional backgrounds.

      Your description tends to support this viewpoint. Your description is of a highly complex system with a lot of unknowns. This is very typical of real-world engineering situations. From my experience in engineering I can see that this discipline teaches its practitioners to adapt and use a variety of tools and techniques from a disparate group of subjects to enable them to tackle complex and nebulous situations such as that you describe for climate.

      From my science background I can see they are “one club” specialists who may be better at their specialism but don’t have the sceptic adaptability.

      I think the ultimate skill set needed to “fix” the climate (if it needs fixing) is that of the (scientific)engineer rather than the scientist. The scientist’s work is not to “fix” but to “understand”. Although understanding is necessary pre-condition to fixing, it isn’t sufficient to understand the complex often “soft” data and diagnose and formulate an action plan.

      So, we may well need to rethink how we approach this “problem”. It is too complex to consider science. Indeed, it has many aspects of sociology and psychology (which practical engineers learn on the job). Somehow we may need to try to combine skill sets – effectively combine the thinking of sceptics and academics. However, this is a huge problem. Usually practitioners like engineers, doctors and similar professions (who are the main professions of sceptics) who use science in their work, learn “on the job” … the equivalent in this area would be to learn “on the job” treating the “patient” named Gaya.

  3. they can get away with anything, because they have the support of the media and public money

  4. I appreciate that you and I probably have very different views about anthropogenic global warming, so I hope you’ll see this comment as constructive. I had a question and a comment. In your section titled “logic” you mention a statement “Warming of the climate system is unequivocal”. However, the data shown is only surface temperatures (sea surface and land). Do you dispute the evidence suggesting that the ocean heat content has continued to rise despite the slowdown in surface warming or do you regard that as irrelevant? That’s my question.

    My comment relates to the figure showing the two periods with the same warming. I guess you’re not suggesting that because they’re the same they must have the same cause, but you seem to be suggesting that most of the warming in the period 1910-1940 was natural and hence indicates that natural warming can produce the same level of warming as anthropogenic influences. However, in the period 1910-1940 CO2 concentrations rose from about 290 ppm to about 310 ppm. This would produce a change in forcing of 5.35 ln(310/290) = 0.35 W/m^2. Solar forcing also rose during this period (maybe 0.1 to 0.2 W/m^2). So the total solar plus anthropogenic forcing increase during this period was about 0.5 – 0.6 W/m^2. During the period 1970 – 2000, CO2 concentrations rose from about 330 ppm to 365 ppm. This would produce a net change in forcing of about 0.55 W/m^2. Solar forcing probably decreased slightly, but essentially the net known forcings for the two periods are very similar, hence not surprising that the change in temperature was similar (I’ve just read these number of graphs, so exact values may differ somewhat). Also, it’s likely that anthropogenic forcing were not negligible and may well have dominated during the period 1910-1940. Anyway, that’s my comment.

    • On the ocean, if they had predicted ocean warming then it would be a relevant question. The question is what did they say was “KNOWN” and how well does it fit what actually happened.

      On the specific question of ocean heating, I will accept what you say that it does suggest warming, however, the risk of post facto justification is that it is far too easy to have confirmation bias in that additional factors are brought in ONLY if they support your view and IGNORED if they don’t.

      This is why it was so important that climate science was completely impartial and was seen to be taking action against any malpractice. That has not happened. The risk of confirmation bias is far too high and so a small increase in one of many possible “afterthought” measurements doesn’t wash with me.

      Your assertion that CO2 rose is a little hard to justify when there was no systematic measurement of CO2.

      What is more important is that the noise profile is known to be 1/f. This is a complex argument to make within one small section of a longer article. But what it means is that the whole climate signal is indistinguishable from natural variation. Moreover, the long term variation increases substantially compared to short term changes. This e.g. means that because the variance of natural variation increases with longer measurement periods it is far easier to predict the climate one year ahead than 10 years or a century.

      So, I am very confident based on the fact the Met Office yearly global forecasts showed no skill that there is no predictive ability in the 10year or 100year forecasts. In other words, if the one year forecast was no better than just using the last year’s number … then the 10 and 100 year will be worse (if that is possible).

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