Guest essay by Eric Worrall
In the wake of the science committee testimony, Climate Scientist Kevin Trenberth has insisted that Climate Science does follow the scientific method. But Trenberth himself may have strayed outside accepted scientific methodology.
Yes, we can do ‘sound’ climate science even though it’s projecting the future
Nobody can observe events in the future so to study climate change, scientists build detailed models and use powerful supercomputers to simulate conditions, such as the global water vapor levels seen here, and to understand how rising greenhouse gas levels will change Earth’s systems. NCAR/UCAR, CC BY-NC-ND
April 6, 2017 4.01am AEST
Authors
Kevin Trenberth
Distinguished Senior Scientist, National Center for Atmospheric Research
Reto Knutti
Professor, Eidgenössische Technische Hochschule (ETH) Zürich
Increasingly in the current U.S. administration and Congress, questions have been raised about the use of proper scientific methods and accusations have been made about using flawed approaches.
This is especially the case with regard to climate science, as evidenced by the hearing of the House Committee on Science, Space and Technology, chaired by Lamar Smith, on March 29, 2017.
…
Chairman Smith accused climate scientists of straying “outside the principles of the scientific method.” Smith repeated his oft-stated assertion that scientific method hinges on “reproducibility,” which he defined as “a repeated validation of the results.” He also asserted that the demands of scientific verification altogether preclude long-range prediction, saying, “Alarmist predictions amount to nothing more than wild guesses. The ability to predict far into the future is impossible. Anyone stating what the climate will be in 500 years or even at the end of the century is not credible.”
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Why climate scientists use models
The wonderful thing about science is that it is not simply a matter of opinion but that it is based upon evidence and physical principles, often pulled together in some form of “model.”
In the case of climate science, there is a great deal of data because of the millions of daily observations made mostly for the purposes of weather forecasting. Climate scientists assemble all of the observations, including those made from satellites. They often make adjustments to accommodate known deficiencies and discontinuities, such as those arising from shifts in locations of observing stations or changes in instrumentation, and then analyze the data in various ways.
…
Projections, not predictions
With climate models as tools, we can carry out “what-if” experiments. What if the carbon dioxide in the atmosphere had not increased due to human activities? What if we keep burning fossil fuels and putting more CO2 into the atmosphere? If the climate changes as projected, then what would the impacts be on agriculture and society? If those things happened, then what strategies might there be for coping with the changes?
These are all very legitimate questions for scientists to ask and address. The first set involves the physical climate system. The others involve biological and ecological scientists, and social scientists, and they may involve economists, as happens in a full Intergovernmental Panel on Climate Change (IPCC) assessment. All of this work is published and subject to peer review – that is, evaluation by other scientists in the field.
The question here is whether our models are similar enough in relevant ways to the real world that we can learn from the models and draw conclusions about the real world. The job of scientists is to find out where this is the case and where it isn’t, and to quantify the uncertainties. For that reason, statements about future climate in IPCC always have a likelihood attached, and numbers have uncertainty ranges.
The models are not perfect and involve approximations. But because of their complexity and sophistication, they are so much better than any “back-of-the envelope” guesses, and the shortcomings and limitations are known.
…
Trenberth has a lot of faith in his models – so much so, a few years ago he demanded that the “null hypothesis” be reversed. If accepted, this would have meant a reversal of the burden of proof regarding the assumption of human influence on global climate.
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“Humans are changing our climate. There is no doubt whatsoever,” said Trenberth. “Questions remain as to the extent of our collective contribution, but it is clear that the effects are not small and have emerged from the noise of natural variability. So why does the science community continue to do attribution studies and assume that humans have no influence as a null hypothesis?”
To show precedent for his position Trenberth cites the 2007 report by the Intergovernmental Panel on Climate Change which states that global warming is “unequivocal”, and is “very likely” due to human activities.
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Read more: https://wattsupwiththat.com/2011/11/03/trenberth-null-and-void/
Trenberth’s demands for a reversal of the burden of proof with regard to climate were rejected by the scientific community. Even climate advocate Myles Allen, head of University of Oxford’s Atmospheric, Oceanic and Planetary Physics Department, thought Trenberth’s demands for a reversal of the burden of proof were wrong.
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“The proponents of reversing the null hypothesis should be careful of what they wish for,” concluded Curry. “One consequence may be that the scientific focus, and therefore funding, would also reverse to attempting to disprove dangerous anthropogenic climate change, which has been a position of many sceptics.”
“I doubt Trenberth’s suggestion will find much support in the scientific community,” said Professor Myles Allen from Oxford University, “but Curry’s counter proposal to abandon hypothesis tests is worse. We still have plenty of interesting hypotheses to test: did human influence on climate increase the risk of this event at all? Did it increase it by more than a factor of two?”
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All three papers are free online:
Trenberth. K, “Attribution of climate variations and trends to human influences and natural variability”: http://doi.wiley.com/10.1002/wcc.142
Curry. J, “Nullifying the climate null hypothesis”: http://doi.wiley.com/10.1002/wcc.141
Allen. M, “In defense of the traditional null hypothesis: remarks on the Trenberth and Curry opinion articles”: http://doi.wiley.com/10.1002/wcc.145
Read more: Same link as above
The problem with climate science is there is no way to test the core prediction, that the Earth will heat substantially in response to anthropogenic CO2 emissions, other than to wait and see.
Important secondary predictions which should be observable by now, such as the missing tropospheric hotspot, or a projected acceleration in sea level rise, have not manifested.
Even more embarrassing, mainstream models cannot even tell us what climate sensitivity to CO2 actually is.
Is equilibrium climate sensitivity 1.5C temperature increase per doubling of CO2? Or is it 4.5C / doubling of CO2? The IPCC Fifth Assessment Summary for Policy Makers cannot give you that answer.
… The equilibrium climate sensitivity quanti es the response of the climate system to constant radiative forcing on multi- century time scales. It is de ned as the change in global mean surface temperature at equilibrium that is caused by a doubling of the atmospheric CO2 concentration. Equilibrium climate sensitivity is likely in the range 1.5°C to 4.5°C (high confidence), extremely unlikely less than 1°C (high confidence), and very unlikely greater than 6°C (medium confidence)16. The lower temperature limit of the assessed likely range is thus less than the 2°C in the AR4, but the upper limit is the same. This assessment re ects improved understanding, the extended temperature record in the atmosphere and ocean, and new estimates of radiative forcing. {TS TFE.6, Figure 1; Box 12.2} …
Read more: IPCC Fifth Assessment WG1 Summary for Policy Makers (page 14)
Why is this range of possible climate sensitivities embarrassing? Consider the Charney Report, from 1979;
… We believe, therefore, that the equilibrium surface global warming due to doubled CO2 will be in the range 1.5C to 4.5 C, with the most probable value near 3°C …
Read more: http://www.ecd.bnl.gov/steve/charney_report1979.pdf (page 16)
As theories are refined, key physical quantities should be resolved with greater accuracy. For example, the first measurements of the speed of light, conducted in 1676, were 26% wrong – a remarkable estimate for that period of history, but still wide of the mark. More research – better quality measurements and calculations resolved the original uncertainty about the speed of light, which is now known to a high degree of accuracy.
This failure of climate science to follow the normal scientific progression to more accurate estimates should be a serious concern. This lack of convergence on a central climate sensitivity estimate, after decades of research effort, strongly suggests something is missing from the climate models.
Whatever the missing or mishandled factor is, it has a big influence on global climate. The evidence for this is the embarrassingly broad range of estimates for climate sensitivity to a doubling of CO2, and the failure of those estimates to converge.
If climate models were capable of producing accurate predictions, if they showed any sign of converging on a reasonable climate sensitivity estimate, if predicted secondary phenomena such as the tropospheric hotspot and sea level rise acceleration were readily observable, there would be a lot less resistance to Trenberth’s apparent demand that climate model projections be accepted as somehow equivalent to empirical observations.
It should be obvious to anyone there are way too many loose ends to even come close to such acceptance.
According to the Oxford English Dictionary, the scientific method is A method of procedure that has characterized natural science since the 17th century, consisting in systematic observation, measurement, and experiment, and the formulation, testing, and modification of hypotheses.
Any suggestion that model projections should be accepted as a substitute for systematic observation and experiment, any suggestion that model output from models which have failed several key tests can be relied upon, any suggestion that defective model output constitutes proof of human influence on global climate, in my opinion utterly violates any reasonable understanding of what the scientific method should be.
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Some years ago, Anthony featured a Christmas-flavored Kevin Trenberth email from the climategate trove, in which Kevin sent a carol around to the Hockey Team^TM with the libretto doctored to tout their commitment to “the cause.”
“The cause” was the transformation of the western world to environmental wonderfulness through the agency of AGW leverage.
Clear from that email was that Kevin Trenberth and the rest of the team were advocates, rather than scientists. Out to make a case. For those making a case, truth is a convenient incidental.
Kevin also caused Chris Landsea to resign from the IPCC, when he (Kevin) lied about a connection between hurricanes and global warming, during a press conference.
UCAR and Trenberth were totally unrepentant on the event, citing supportive studies based on climate model projections published without any physically valid uncertainty estimates.
Here is Donna Laframboise on that incident, in which she appropriately termed the IPCC as composed of moral midgets.
More from Donna Laframboise on Kevin Trenberth, Chris Landsea, Hurricanes, and the cynical abuse of science for political ends, with special reference to that high-standing group, the Union of Concerned Scientists.
So far as we know, Kenji is the only card-owning member of the UCS in good standing with ethics.
Here’s a model in which I have great faith:
I and a person I choose shall designate an eight-hour work day. I will work 2 hours, and my chosen assistant shall work 6 hours. At the end of the day, I shall receive 75% of the earnings of both my and my assistant’s work efforts.
Let us call the 6/2 ratio of my assistant’s hours and my hours a “forcing”. In other words, I make 75% of the day’s income, because of my forcing of 3 times as much work on my assistant. This is the forcing of my model, and no matter who works with me, we shall use this formula each and every time to determine my income for any given day. Three to one is a given.
This model is flawless, because it works every time. Just insert the hours I work, multiply by three, and then apply the 75% split, no matter how many hours we are talking about.
It’s a very precise formula. You cannot argue with the math.
Where to start??
In summary, CAGW is based almost entirely on computer models. These models are built to curve-fit the (poor quality proxy) historical data. Since the physics is not known, a fudge factor is used in this curve-fitting process. Of course, it is not actually called a fudge factor – it is called a sensitivity factor – that term does not sound quite so bad. If CO2 feedback was the only unknown, there would be one fudge factor common to all models. However, each model has its own fudge factor, and that is why there is such a wide range of these fudge factors.
Now, anyone doing this in the financial or commodity markets, also coupled, non-linear chaotic systems, knows that this is a sure road to bankruptcy. But, climate scientists do not have to be right to get paid. They merely must convince politicians to continue to give them money.
And, please do not respond that, even though they cannot predict weather two weeks out, they can predict a thirty year moving average of weather one hundred years out.
To know why this is so ridiculous, simply read James Gleick’s excellent book “CHAOS: The Making of a New Science” published back in 1987.
I used to love fudge, but since my indoctrination with the truth about how much fudging goes on in climate science, I tend to avoid it now. Fresh fruit is a better choice anyway, although there CAN be problems with being too fruity too.
There’s a balance, I guess, between fudge and fruit. And this BALANCE is what seems missing in traditional climate “science”.
Climate Science loves fudge. You could almost say it is addicted to fudge.
Now, it has diabetes. They still can’t stop eating the fudge, though.
If you’d “followed a scientific method” (rational thinking), you’d know CO2 isn’t a “greenhouse gas”, as proved over a hundred years ago.
Power spectrum analysis was carried out using the 21 stations data series of global solar radiation and 8 stations data series of net radiation. The total solar radiation and net radiation intensities show sunspot cycle. This clearly indicates the influence of sunspot cycles on solar and net radiation intensities. Therefore, it is suggested that during the sunspot cycle period there is certain change in the solar radiation emitted by the sun itself; which in turn, is reflected in other atmospheric processes also. Both presented an increasing trend after 1940s at some industrial stations. It is more pronounced in net radiation due to air pollution related urban heat island factor. [S. Jeevananda Reddy, O. A. Juneja & (Miss) S. N. Lahori, 1977, Indian Journal of Radio & Space Physics, 6:60-66 – presented at the Symposium on Eart’s Near Space Environment, 18-21 February 1975, NPL, New Delhi].
This needs for the globe. This is a must for modellers before presenting the results.
Since 90s, eminent professors changed their path to get more papers published and get more funds and more students. They tried to predict the impacts of raise in temperature using another set of poor quality models. In fact I questioned them in international journals.
Dr. S. Jeevananda Reddy
“A politician needs the ability to foretell what is going to happen tomorrow, next week, next month, and next year. And to have the ability afterwards to explain why it didn’t happen.”
“The truth is incontrovertible. Malice may attack it, ignorance may deride it, but in the end, there it is.”
“It is a mistake to look too far ahead. Only one link of the chain of destiny can be handled at a time.”
“However beautiful the strategy, you should occasionally look at the results.”
Sir Winston Churchill
They are going to lie and fabricate data until they die. Cut off the money, ignore them and publish their work where it belongs, in The Onion.
A person this educated should not have so much trouble seeing the problems with what he is evangelizing. If raw data is changed, you need to publish the raw data, the changes to the data, the processes used to change the data, and the justification for the changes. All of this falls under the scrutiny of both supporters and critics to be debated, scrutinized, and improved. Climate Researchers RESIST being scrutinized, and therefore the data they use is simply not scientifically valid. Garbage in-Garbage out.
Models are used in science to find ways to test a theory. You don’t just assume the model is valid, you go back and test what it is predicting. Climate modeling has FAILED completely in predicting anything, and yet they cannot see the issue. This is bias, plain and simple. You invest so much into a work, you will be damned before abandoning it. Human emotion trumping scientific scrutiny.
You cannot extract detail from data that is noisier than what you are attempting to measure. Past temperature data is greatly flawed, and no amount of tweaking it makes it any better – all you are doing is adding in bias – YOUR bias. Satellite measurements are going to be the cleanest source of data (but still require tuning and tweaking to make up for all sorts of problems). Land temperatures are polluted with so much noise (like heat island effect) that it simply is not going to discriminate between natural and man made warming. There is not enough satellite data to tune a model, so catch-22.
There is WAY too much faith in proxies. Proxies are only as good as all the possible effects into them are understood. Tree rings are a perfect example – they depend on temperature, moisture, wind, height, tree species, access to sun light, and who knows what else. You get different results depending on what side of a tree versus the mountain slope you measure in some cases. Proxies are good for generalizations, but not for exact measurements. We should never believe a proxy is a safe substitute for actual measurements, and yet the entire climate science is built on them.
In science, it is the DEBATE that leads to better models and theories. Running and hiding from the DEBATE is a sure sign that something is very wrong. Hiding behind fake consensus is a political tactic. There is no room in GOOD SCIENCE for politics. Trying to silence skeptics is simply shameful. They should be met head on with good reason and facts, not attacked. Attacking your opponents is another sure sign there is something rotten in the theory.
In 20 to 30 years educated people will look back at the 1990’s-2220’s and shake their heads in wonderment that so many educated people could be so poorly trained in science.
To the truth that ” Climate modeling has FAILED completely in predicting anything” should be added that “currently existing climate models do not predict.”
“Projections not predictions” is a deceptive assertion, since cliamte extremists and climate profiteers demand policies be put in place reflecting the most extreme predictions/projections.
Defenders of the consensus only rely on this faux distinction when defending the failure of their policies or predictions/projections. In other words, it is circular and self serving, not a serious argument they offer.
But because of their complexity and sophistication, they are so much better than any “back-of-the envelope” guesses, and the shortcomings and limitations are known.
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nonsense. there is zero evidence that complexity makes any system “better”. There is a large body of mathematics and engineering that argues the exact opposite. Complexity increases unreliability. It does not increase accuracy.
The IPCC says the ensemble mean is more accurate than ANY SINGLE climate model. Yet four years ago Willis showed how a very simple “black box” could recreate the ensemble mean. In other words, his very simple climate model was MORE ACCURATE than any other climate model, according to the same criteria the IPCC uses.
Here is what Willis said on this 4 years ago:
“the climate model global average surface temperature results, individually or en masse, can be replicated with over 99% fidelity by a simple, one-line equation.”
https://wattsupwiththat.com/2013/06/03/climate-sensitivity-deconstructed/
“Projections, not predictions
With climate models as tools, we can carry out “what-if” experiments. ”
Trenberth is clearly deluded here. All of his “what-if” scenarios should start of with
“What if the models/theory are actually correct, and what if …”
I’m sure he regards the assumed correctness of his models as some sort of axiomatic (dogmatic?) truth; but the most significant errors are coming from the formulation of the models themselves – as demonstrated again and again from the empirical observations. Somebody needs to teach Scientific Method 101 to this climate “scientist”.
Right!
A genuine expert can always foretell a thing that is 500 years away easier than he can a thing that’s only 500 seconds off.
– Mark Twain, A Connecticut Yankee in King Arthur’s Court
“To show precedent for his position Trenberth cites the 2007 report by the Intergovernmental Panel on Climate Change which states that global warming is “unequivocal”, and is “very likely” due to human activities.”
If the IPCC claimed that global warming had only one possible interpretation- ie was unequiviocal- then how can it claim that there was more than one interpretation- ie it was only “very likely” due to human activities, but there was therefor some small likelihood that it was due to other causes.
Of course Trenberth and pals controlled the content of the IPCC report so isn’t that just dandy.
This is their main con trick: redefining speculation as a mere tool. The assumptions going into the models are speculation because they leave so much out. Just because some of it is true (correct science); does not make the whole true. People like Trenberth may have passed Science 101 but they would’ve failed Reason 101. It annoys me how oblique the models are. In contrast, when economist Wynne Godley wanted to explain, and justify, his life’s work: an alternative economic model – the stock-flow consistent model – he published a 530 page book to explain his ‘tool‘.
The major con-trick is application of the equivocation fallacy.
is what Climb It Cyan Tits are all about..
The “climate science” community doesn’t use the Scientific Method…. They use “Mike’s Trick” instead…..
That’s were you take a Proxy record of tree rings that (supposedly)represents temperature over several hundred years, then lop off the last 4 decades of that tree ring Temp Proxy because it’s showing a decline that doesn’t fit with actual observations and splice on the modern Thermometer record to “HIDE THE DECLINE” and instead produce/concoct a “HOCKEY STICK”.
These people have no credibility….. The ClimateGate emails showed that succinctly.
Kevin wouldn’t recognise the ‘scientific method’ if it came up and bit him on the arse.
“it is clear that the effects are not small and have emerged from the noise of natural variability” -Trenberth
Not so. If all the smoothings and averagings were removed, the peak-to-peak noise amplitude of daily and seasonal temperature changes would be fifty times larger than the trend. Attempting to deduce anything from measurements which are so far below the noise floor of the system, is very poor science.
Ian Macdonald:
To analogize natural variation to “noise” and manmade global warming to a “signal” in the context of an attempt at establishing control over global warming is a mistake. To establish control the controller must have information about the outcomes of events before these events occur but for this information to reach us via a signal violates the limit on light speed in relativity theory.
I’m not sure what you mean by c and relativity, but in most scientific circles it’s considered dubious practice to rely on data which lacks a few dB ‘headroom’ above the system noise. Climate data, meanwhile, is about 30dB BELOW the system noise floor. That’s now bad it is.
The reason you don’t see this on the graphs is due to some extreme low-pass filtering.
They got a method! , beyond that is started from what they need and making the data ‘supply ‘ the right result .
Trenberth typifies how through climate ‘science’ third rate scientists , who otherwise would have a hard time getting a job in a second rate high school , can raise to the top of their profession . And enjoy a first rate life style .
So given that does any one thing he will hold his hand up anytime and soon and admit they are often simply ‘wrong’ ?
Over the life of the Earth, CO2 levels have apparently ranged from 100 bar nearly 100% to maybe 0.03 % in 1 bar atmosphere.
Surface temperature has dropped from maybe 5800 K to around 288 K.
The internal regions of the Earth remain molten. All explicable by ordinary known physics.
No reason to suppose that CO2 levels control surface temperature. Trenberth is deluded.
Cheers.
Trenberth on CO2 science
http://www.vukcevic.talktalk.net/CHshow2.gif
Trenberth challenges nothing less than the theory of relativity
E=mc^2
In other words atmospheric energy can vary as the function of atmospheric mass or the speed of light.
Which one is the mankind influencing?
I am really not interested in paying Mr. Trenberth’s salary any longer. Undoubtedly, someone like George Soros will step in to fill the bill, but that will be up to his new patron. Mr. Trenberth appears to lack any sense of humility. He offends me.
He’s the scientific method:
Something may be causing global warming … CO2 is well dispersed so it could cause global temperature change … the satellites, balloon data, sea surface data, show little or no warming – but the Arctic is warming (although Greenland gaining surface ice) … but even if a region is warming it is not global. Conclusion: there is no evidence for current “global warming” so there is no evidence for CO2 warming – instead we must look for regional drivers for regional temperature changes.
Here’s Trenberth’s method
We know CO2 causes warming … we know the satellites, balloon data and sea surface data must be corrupt because they don’t show the warming of NORTHERN Hemisphere LAND (AFTER adjustments to remove rural stations) …. so this very regional warming – in an outlier (or Out-liar?) dataset proves that the globe is warming “as predicted”. The science is settled, the consensus is agreed and anyone who dares quotes the lack of warming from the satellites is a denier of the science.
I believe you understand!!