Guest essay by Eric Worrall
The diverse predictions produced by 20 major research centres represent “strength in numbers”, according to UCL Professor of Earth System Science Mark Maslin.
Three reasons why climate change models are our best hope for understanding the future
Mark Maslin
Professor of Earth System Science, UCLIt’s a common argument among climate deniers: scientific models cannot predict the future, so why should we trust them to tell us how the climate will change?
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Deniers often confuse the climate with weather when arguing that models are inherently inaccurate. Weather refers to the short-term conditions in the atmosphere at any given time. The climate, meanwhile, is the weather of a region averaged over several decades.
Weather predictions have got much more accurate over the last 40 years, but the chaotic nature of weather means they become unreliable beyond a week or so. Modelling climate change is much easier however, as you are dealing with long-term averages. For example, we know the weather will be warmer in summer and colder in winter.
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Here’s a helpful comparison. It is impossible to predict at what age any particular person will die, but we can say with a high degree of confidence what the average life expectancy of a person will be in a particular country. And we can say with 100% confidence that they will die. Just as we can say with absolute certainty that putting greenhouses gases in the atmosphere warms the planet.
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Strength in numbers
There are a huge range of climate models, from those attempting to understand specific mechanisms such as the behaviour of clouds, to general circulation models (GCM) that are used to predict the future climate of our planet.
There are over 20 major international research centres where teams of some of the smartest people in the world have built and run these GCMs which contain millions of lines of code representing the very latest understanding of the climate system. These models are continually tested against historic and palaeoclimate data (this refers to climate data from well before direct measurements, like the last ice age), as well as individual climate events such as large volcanic eruptions to make sure they reconstruct the climate, which they do extremely well.
No single model should ever be considered complete as they represent a very complex global climate system. But having so many different models constructed and calibrated independently means that scientists can be confident when the models agree.
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Errors about error
Given the climate is such a complicated system, you might reasonably ask how scientists address potential sources of error, especially when modelling the climate over hundreds of years.
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We scientists are very aware that models are simplifications of a complex world. But by having so many different models, built by different groups of experts, we can be more certain of the results they produce. All the models show the same thing: put greenhouses gases into the atmosphere and the world warms up. We represent the potential errors by showing the range of warming produced by all the models for each scenario.
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Read more: https://theconversation.com/three-reasons-why-climate-change-models-are-our-best-hope-for-understanding-the-future-175936
I have a few problems with these arguments:
- Comparing climate models to life expectancy models in my opinion is a false comparison.
Life expectancy models are constructed from millions of independent observations, medical records vs time of death. By contrast, climate scientists struggle to reconstruct what happened yesterday. There is a significant divergence between temperature reconstructions of the last 30 years, let alone climate projections.
(source Wood for Trees)
- “Millions of lines of code” are not a source of confidence. Millions of lines of code are millions of opportunities to stuff up. As a software developer I’ve worked with physicists and mathematicians. They all think they know how to code, but with very few exceptions they wrote dreadful code.
The problem I saw over and over was that mathematics and physics training creates an irresistible inner compulsion to reduce everything to the simplest possible expression, even when such reduction means ditching software best practices designed to minimise the risk of serious errors. I knew what to expect well before I read Climategate’s “Harry Read Me“. - If the climate models were fit for purpose, scientists would only need one unified model. The fact there are many diverse models is itself evidence climate scientists are struggling to get it right. Compare this plethora of climate models to say models used to predict the motion of satellites. If satellite orbital predictions were as uncertain as climate projections, it would not be possible to create a global position system which can tell you where you are on the Earth’s surface to within a few feet.
- Climate models may contain major physics errors. Lord Monckton, Willie Soon, David Legates and William Briggs created a peer reviewed “irreducibly simple climate model“, which appears to demonstrate that most mainstream climate scientists use a grossly defective climate feedback model.
… In official climatology, feedback not only accounts for up to 90% of total warming but also for up to 90% of the uncertainty in how much warming there will be. How settled is “settled science”, when after 40 years and trillions spent, the modelers still cannot constrain that vast interval? IPCC’s lower bound is 1.5 K Charney sensitivity; the CMIP5 models’ upper bound is 4.7 K. The usual suspects have no idea how much warming there is going to be.
My co-authors and I beg to differ. Feedback is not the big enchilada. Official climatology has – as far as we can discover – entirely neglected a central truth. That truth is that whatever feedback processes are present in the climate at any given moment must necessarily respond not merely to changes in the pre-existing temperature: they must respond to the entire reference temperature obtaining at that moment, specifically including the emission temperature that would be present even in the absence of any non-condensing greenhouse gases or of any feedbacks. …
Read more: https://wattsupwiththat.com/2019/06/08/feedback-is-not-the-big-enchilada/
Lord Monckton’s point is, since feedback is a function of temperature, feedback processes can’t tell the difference between greenhouse warming and the initial starting temperature, all they see is the total temperature. You have to include the initial starting temperature alongside any greenhouse warming when calculating total feedback, you can’t just use the the change in temperature caused by adding CO2 to the atmosphere. Making this correction dramatically reduces estimated climate sensitivity, slashes future projections of global warming, and removes the need to panic about anthropogenic CO2. - Cloud error. As Dr. Roy Spencer explains in a 2007 paper which supports Richard Lindzen’s Iris Hypothesis, clouds are potentially a very significant player in future climate change. Yet as scientists sometimes admit, climate models do a terrible job of explaining cloud behaviour. If climate models can’t explain major processes which contribute to global surface temperature, they are not ready to be used as a serious guide to future surface temperature.
Why are climate scientists so keen to have models accepted, why do they seem so ready to gloss over the shortcomings? The following quote from a Climategate email provides an important hint as to what might have gone wrong;
… K Hutter added that politicians accused scientists of a high signal to noise ratio; scientists must make sure that they come up with stronger signals. The time-frame for science and politics is very different; politicians need instant information, but scientific results take a long time …
Source: Climategate Email 0700.txt
In my opinion, political paymasters demanded certainty, so certainty is what they got.
Science needs people like Mark Maslin, who are confident and willing to defend their positions and models.
I’m not suggesting Mark Maslin is in any way following the money or acting in a way which is contrary to his conscience. If there is one thing which comes through very clearly in the Climategate emails, that is that the climate scientists who wrote them are utterly sincere.
What in my opinion broke climate science is the other side of this equation was all but eliminated. What I am suggesting is climate scientists who were not confident in their models and their projections mostly got defunded, via a politically driven brutal Darwinian selection process which weeded out almost everyone who wasn’t “certain”.
We can still see this happening today. Climate scientists who support politically approved narratives receive lavish funding, while those like Peter Ridd who question official narratives, not so much.
I’m not against climate models as such, I believe there is a chance, though not a certainty, that eventually we shall have a comprehensive model of climate change which can produce worthwhile projections of future climate. What I dispute is that most current climate models which tend to run way too hot are fit for purpose. In my opinion, climate models should be regarded as a work in progress, not an instrument which is useful for advising government policy.
Correction (EW): Fixed the title in the quoted article.
Correction (EW): h/t Climate believer – fixed a typo.
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Warmer in summer and colder in winter? Duh. This guy is brilliant. The University Clowns London is blessed.
Typo?
I have few problems with these arguments:
I have a few problems with these arguments:
Fixed, thanks 🙂
Maslin is effectively drunk. Happy drunk. Self confident drunk. And as such, there is no point in getting into any serious argument or debate with him.
Because:
He is part of a large crowd that is similarly bouyed-up and hyper – in the way as crowds can be or get – using their own energy to feed back on themselves and create more energy.
Classically, large crowds at football games, when riots break out or when an especially evocative speaker ‘gets them going’
You cannot imagine one person chanting like a football crowd does, or one person ‘rampaging’ through the streets turning over police cars and setting fire to things.
Or starting a war not least.
It takes a Certain Number or a Critical Mass to start those sorts of things and Climate Science, by their own words ## has reached that critical mass and is now an out-of-control and self-sustaining entity that feeds off its own energy.
It is, or has become, so large that no individual inside that entity ever gets a glimpse of what life is like outside of the entity.
## We all know the word and it is: Consensus
It’s something that I noticed about the cows I used to keep, both my own and latterly the ones I shepherded for someone else.
It was that when in small groups, they were always placid and docile but if you increased the size of the group, there came a point when ‘something’ changed.
When it did, the large group that was previously several small docile groups, would ‘stampede’
Some tiny trigger would cause the whole group/herd to suddenly go galloping off to the far end of the field/shed/barn and when they got there would ‘bounce’ and come galloping back.
Even just a small rabbit in the field suddenly taking fright and scampering away – the small group would see it and just stand and watch it for a few moments.
The large group/herd would go crazy. Only one animal in the herd saw the rabbit and was startled but it would trigger the whole lot.
That defines Climate Science. A large group has coalesced, where no member of the group gets any contact with the outside world and the are all bouyed-up and hyper by each other.
That was Mackay’s book: Popular Delusions
…. now been rehashed by Douglas Murray
Should Mackay’s book be renamed: Extraordinary Popular Delusions and the Maslin of Crowds
USA actually getting some of that sea level rise right now.
So, what does this have to do in a climate discussion?
If everyone agrees to feel only the leg of the elephant, then everyone will agree it is a tree.
Did he really say that heating due to additional CO2 is a certainty like death? Are we supposed to read beyond that absurdity? Such a statement only confirms our worst fears of blind bias in the “expert” community.
Is there a tested method to even determine the average temperature of the planet? I mean something with accuracy and repeatability numbers?
From all that I have seen, the average temperature of our planet is far colder than today. See repeating ice ages. How many of the models are predicting the next one?
Nope. At any point in time the Northern Hemisphere is warm and the SH is cold. It then swaps each 6 months. That means that you have a multi-nodal distribution of temperatures. What does the average of a multi-nodal distribution tell you? Does the average of the heights of Watusi’s combined with the heights of pygmies actually tell you something useful? Even lifespan distributions are multi-nodal. The average of the lifespan data of Americans combined with the lifespan data of Chinese Uighars is just as meaningless. Why then does combining the July temperature in Chicago with that in Perth tell you something meaningful about the “global” average temperature?
It gets even worse when you try using temperature measurements with uncertainty in the units digit to determine differentials in the average temps in the hundredths digit. That’s like telling a machinist he can measure a crankshaft journal to the thousandths of an inch using a a ruler marked in sixteenths of an inch if he just takes enough measurements and calculates their average!
According to the glossary entry for “Predictability” in the IPCC AR5 (2013):
Because knowledge of the climate system’s past and current states is generally imperfect, as are the models that utilize this knowledge to produce a climate prediction, and because the climate system is inherently nonlinear and chaotic, predictability of the climate system is inherently limited. Even with arbitrarily accurate models and observations, there may still be limits to the predictability of such a nonlinear system.
Weather and climate are both difficult to model. Weather predictions are frequently wrong or significantly off. So far there is no evidence that climate model projections are accurate. The evidence indicates that they predict far more warming and sea level rise than observed. So they’re wrong.
Mark Mason oozes arrogance. Questioning his work makes one a climate denier, whatever that is.
“Here’s a helpful comparison. It is impossible to predict at what age any particular person will die, but we can say with a high degree of confidence what the average life expectancy of a person will be in a particular country.”
But the real comparison is: what is the average life expectancy of a person in a particular country in the year 2100 or 3000?
I would suggest that climate modelling is exactly the same as trying to predict when someone will die, but as you say, that’s impossible.
It’s even worse than this. It’s like trying to determine the average GLOBAL lifespan by using data from all countries. You wind up with a multi-nodal distribution and the global average lifespan probably doesn’t predict anything usable for *any* specific country.
If the AGW alarmists actually created useful regional and local predictions of climate they might be useful in actually isolating confounding factors that can be worked on where they need to be worked on. Instead we get a one-size-fits-all prescription that doesn’t actually fit anyone!
Is it just me, but does CliSciFi practitioner, Mark Mason, not understand the difference between the statistical average life expectancy of a group and the uncertainties of modeled (assumed) ECS and projections of future atmospheric CO2 concentrations, among all the other uncertainties of modeling a dynamic and chaotic system?
Modelling climate change is much easier however, as It will be a long time before people see you are wrong.
Ah, a real professional tosser
Eric says:
Not sure how Eric gets ‘significant divergence’ from that chart. Maybe it’s because he hasn’t off-set the data to a single anomaly period, as described in the WfT notes? For instance, UAH uses the period 1991-2020; whereas GISS uses the much cooler period of 1951-1980.
In order to properly compare UAH and GISS, the average GISS anomaly 1991-2020 (0.61C) has to be deducted, or ‘off-set’, otherwise you are bound to get the misleading temperature divergence apparent in Eric’s WfT chart, where UAH appears to be much cooler than the other data sources.
When you do that (see the amended chart below), you can immediately see that, in terms of relative temperatures, the divergence between GISS and UAH since 1990 (Eric’s chosen start year) is actually quite small.
Furthermore, GISS and UAH both show statistically significant warming since 1990; GISS: +0.21 ±0.06; UAH +0.14 ±0.08 (both °C/dec, 2σ). Also, you can see that the uncertainty margins easily overlap. GISS’s best estimate is +0.21°C/dec, but it might be as low as +0.15; UAH’s best estimate is +0.14°C/dec, but it might be as high as +0.22. Therefore, there is no way this divergence can be described as ‘significant’; certainly not in formal statistical terms.
Interestingly overlapping confidence intervals is not enough to determine whether a difference is statistically significant.
https://towardsdatascience.com/why-overlapping-confidence-intervals-mean-nothing-about-statistical-significance-48360559900a
Having said that, I suggest that even if GISStemp & UAH pass the test of not being significantly different right now, it seems likely they will continue diverging.
Interesting link Eric, but in this case we are comparing trend errors in temperature anomaly time series, so we really are comparing like with like. It is simply a fact that the margin of error in UAH’s warming trend is wide enough to incorporate the best estimate warming trend in GISS, plus a little higher. At the 2σ confidence level, GISS and UAH error margins overlap from +0.15 to +0.22°C/dec warming since 1990.
I like how the ‘not significantly different’ trends, one shows a change over 30 years of about 0.3 deg C (0.2->0.1), the other nearly 0.6 deg C (-0.35>0.25)! Where twice the rate is not significantly different, I suspect some basic assumptions are wrong, at the very least.
The climate models ARE weather models. Every calculation they do is for one small patch of atmosphere or ocean over a short time period (typically 20 minutes). What happens in one location over a very short period is by definition weather.
The climate models operate only on weather. That’s why they are useless for climate.
Maslin is not a meteorologist. Took some classes no doubt but apparently not enough to understand this basic truth.
According to a brief pamphlet the UK Independent newspaper published c 2005/6 based on his book ‘Global Warming : A Very Short Introduction’ (OUP 2004) he is a palaeoclimatologist.
And the paleological field’s acceptance of both Mann and Marcotte’s scientific fraud, indicates its a corrupted field of science.
“All the models show the same thing: put greenhouses gases into the atmosphere and the world warms up. ”
That’s not the model out- but the model input, in so far not the proof for model accuracy.
And says nothing about the CliSciFi practitioners’ assumptions as to feedbacks amplifying warming estimates.
” I’m not suggesting Mark Maslin is in any way following the money or acting in a way which is contrary to his conscience. If there is one thing which comes through very clearly in the Climategate emails, that is that the climate scientists who wrote them are utterly sincere. ”
Eric, this is perhaps the best part of your post. The best synthesis. Because it contains a whole lot of proposals to understand the current reality in science. If we think deeper on the second sentence (which I boldfaced), we start to ask questions. A cascade of questions. Starting with “Why people who had a scientific training are sincerely uttering such ideas?”
I think there is a place for such people, the problem occurs when everyone else is excluded.
I once attended a lecture from a workplace psychologist who talked about how easily teams could become dysfunctional. A big problem was dominant figures surrounding themselves with people who think just like them – like high powered sales people only hiring hyper alphas like themselves, then wondering why everyone fights like cats in a bag.
The secret is, trust our evolutionary heritage. We evolved with our current crop of personality types because this mix works – tamper with the balance nature bequeathed to us at your peril.
As a past supervisor and manager, I can attest to the folly of only hiring or promoting those most like oneself.
I’m not sure they are all sincere. Some must know their models are rubbish.
Gavin Schmidt now admits it to the modeling community, but denies it to the policymakers.
Yes. I agree. But my impression is, there are many who are sincere: they just take he subject from a moral point of view, start to classify observations as “good” or “bad”, then organize their research to justify (to find “proof”) what they think is “good” and disregard any need to test the oposite (no use to investigate because it is “bad”).
My question is, how has the avademic system produced such minds, that cannot understand their bias and cannot assume a “neutral”, objective stance.
As a professional in computers across varied fields the first thing I learned was to understand the limits logic machines have when it comes to using them for any particular purpose. They are great at storing data provided the system prevents garbage entry of same. They are great at processing data providing it strictly conforms to standards set before you even begin thinking about designing a computer based system. Computers are brilliant for many things but not so good at, for example, verbatim real time voice recognition despite decades of trying to improve them. Computers have limits and sometimes humans do much better at things the logic machine do not do well. If you program seriously you soon understand what computers are lousy at and how your programming has to get around the problems involved or avoid them altogether.
What is climate if it isn’t an ongoing longer term weather record? What is a weather record if it lacks consistency over the recording period simply because the record keeper couldn’t be bothered to be purposefully accurate? In ancient times our ancestors saw a purpose to observing phases of the Moon, the annual movement of the Sun, and the movement of the planets against the stars and maintaining accurate details of what they observed. Observers from East to West were gifted, intelligent, and experienced. They had local importance as soothsayers with knowledge gleaned over a lifetime. In some cases a misappropriated prognostication could cost them their life.
To believe records faithfully maintained over long periods are better than short term equivalents is wise but only when the data has been and is consistent and responsibly recorded. Manipulations would be taboo. Assumptions would be avoided unless tested to known limits. The same intelligence in design existed across all the ancient models via the shared understanding of what mattered in the survival of local dynasties. They would only incorporate things they understood in those models and not rely on guesswork. The wise would be in demand and the foolish would be banished.. They were, unlike today’s equivalent, intelligent scientists and not unworthy holders of letters after their names in an academic setting which has long lost its way.
Stupid question, but: will advanced quantum computers allow for better climate change modeling?
Only if the date input becomes far more advanced, and includes data from repeating ice ages.
To the extent that faster computers allow small grid cells and less parameterization, the models have the potential of being less wrong.
well, quantum computers aren’t just faster- they can do tricks normal computers can’t
Even if the computers can do extra “tricks” programming is still programmimg.
The issue is still going to be the quality of the inputs. In his recent tome, WE points out that the heat engine we know as Earth depends a lot on transition temperatures driving heat engine changes. In arbitrarily small cells the ability to measure what is going on in the cell becomes harder and harder. You need more and more measurement devices to determine inputs and infinitely more accurate models of the intra-cell response to those inputs. So small cells are not the whole answer and probably never will be. There will always be a chaotic factor that will be difficult to quantify. Is the salinity in cell 1 (5 miles square) different than in cell 2 (an adjacent 5 mile square)? And what does this difference do to the transition temps and the resulting response from the atmosphere (e.g. cloud formation).
He is no scientist. He is an ArtStudent™.
“we can say with absolute certainty that putting greenhouses gases in the atmosphere warms the planet”
Yuh, OK- probably- but, you can’t say what % of the slight warming is due to greenhouse gases. It’s certainly not all of it. And, don’t forget that the climate has fluctuated greatly over the centuries- long before the industrial revolution.
Yes, the question is whether doubling CO2 warms Earth by one, two, three or four degrees C. Most likely one to two, Higher figures require unphysically large positive feedback effects.
“Just as we can say with absolute certainty that putting greenhouses gases in the atmosphere warms the planet” I call this absolute arrogance .This doesn’t explain, above the Antarctic ice sheet in summer, 10hpa is warmer than the surface. The answer is solar heating (24hr sunlight) not trapped earth’s heat. For the rest of the planet 10hpa is majority higher than 70hpa or 250hpa. Water holds energy, evaporation takes a bit of heat away(not all of it). Earth is 70% water therefore earth retains heat in the oceans, which heats air through conduction and convection. At 70hpa temperatures are below -70°C at lower latitudes. At 10hpa temperatures are higher (again solar heating halts further cooling). Above -66°C no absorption of earth’s heat by any atom occurs, thanks to the atmospheric window. Scientist confuse 15 micrometers with 10 micrometers. They ignore that 15 micrometer band is directly proportional with 70hpa temperatures. Official global mean temperature is a planet where both hemisphere are experiencing summer highs. 19°C is northern hemisphere summer high and 9°C is southern hemisphere summer high. 19+9/2=14. Scientists who ignore contradictory evidence and say with absolute certainty that there hypothesis is absolutely certain shows this is a religion instead of following the scientific method.
“If there is one thing which comes through very clearly in the Climategate emails, that is that the climate scientists who wrote them are utterly sincere.”
“Hide the decline”- doesn’t sound sincere to me.
There are plenty of references to not showing any weakness which deniers could blow out of proportion and use to discredit their important work. A lot of them seemed to think of themselves as victims of unfair persecution from critics.
People who use the word ”denier” about others should not be trusted, becasue they are showing tendency to mix science with religion.
“If satellite orbital predictions were as uncertain as climate projections, it would not be possible to create a global position system which can tell you where you are on the Earth’s surface to within a few feet.”
Wrong. It is the time-scale that differs. A satellite will go on bumbling around on its orbit forever providing it does not hit anything. Because space is very big, collisions are rare. Once they do occur though, orbits are changed radically, leading to a whole new set of conditions. It is only in the short term that they are predictable.
I’ve heard this guy on the radio. He comes across more like an eco-activist than anything else. He’s a co-author on the the Lancet’s April 2009 paper, Managing the Health effects of Climate Change. The Executive Summary contains this line:
During this century, the earth’s average surface temperature rises are likely to exceed the safe threshold of 2°C above pre-industrial average temperature.
Ah yes, safe 2°C of warming, I remember it well. Created at a whim, only to be usurped by safe 1.5°C of warming. Got to love that settled science.
The origins of the 2C warming was the belief that 2C above the bottom of the Little Ice Age would get us warmer than the Medieval Warm period and we don’t know what the climate would do if that happened.
Somewhere along the line, someone changed “we don’t know” to “we’re all gonna die”.
Except that we do know, since the Roman WP was balmier than the Medieval, and the Minoan and Egyptian WPs and Holocene Optimum toastier still.
Many of them are still denying the existence of the MWP. They have recently come up with a chart that “proves” the Holocene Optimum never happened.
Swine!
Lying about “climate change” is much easier than weather forecasting. They have a miriad of ways of lying, too. For example, take his statement that “we can say with absolute certainty that putting greenhouses gases in the atmosphere warms the planet.” Liar. Firstly, there is absolutely no certainty, we can only surmise that our additional “greenhouse gasses” may have contributed some warming, but secondly, the implication is that the supposed warming is both substantial as well as dangerous, which is a double-lie.