Climate Modeling Dominates Climate Science
By PATRICK J. MICHAELS and David E. Wojick
What we did
We found two pairs of surprising statistics. To do this we first searched the entire literature of science for the last ten years, using Google Scholar, looking for modeling. There are roughly 900,000 peer reviewed journal articles that use at least one of the words model, modeled or modeling. This shows that there is indeed a widespread use of models in science. No surprise in this.
However, when we filter these results to only include items that also use the term climate change, something strange happens. The number of articles is only reduced to roughly 55% of the total.
In other words it looks like climate change science accounts for fully 55% of the modeling done in all of science. This is a tremendous concentration, because climate change science is just a tiny fraction of the whole of science. In the U.S. Federal research budget climate science is just 4% of the whole and not all climate science is about climate change.
In short it looks like less than 4% of the science, the climate change part, is doing about 55% of the modeling done in the whole of science. Again, this is a tremendous concentration, unlike anything else in science.
We next find that when we search just on the term climate change, there are very few more articles than we found before. In fact the number of climate change articles that include one of the three modeling terms is 97% of those that just include climate change. This is further evidence that modeling completely dominates climate change research.
To summarize, it looks like something like 55% of the modeling done in all of science is done in climate change science, even though it is a tiny fraction of the whole of science. Moreover, within climate change science almost all the research (97%) refers to modeling in some way.
This simple analysis could be greatly refined, but given the hugely lopsided magnitude of the results it is unlikely that they would change much.
What it means
Climate science appears to be obsessively focused on modeling. Modeling can be a useful tool, a way of playing with hypotheses to explore their implications or test them against observations. That is how modeling is used in most sciences.
But in climate change science modeling appears to have become an end in itself. In fact it seems to have become virtually the sole point of the research. The modelers’ oft stated goal is to do climate forecasting, along the lines of weather forecasting, at local and regional scales.
Here the problem is that the scientific understanding of climate processes is far from adequate to support any kind of meaningful forecasting. Climate change research should be focused on improving our understanding, not modeling from ignorance. This is especially true when it comes to recent long term natural variability, the attribution problem, which the modelers generally ignore. It seems that the modeling cart has gotten far ahead of the scientific horse.
Climate modeling is not climate science. Moreover, the climate science research that is done appears to be largely focused on improving the models. In doing this it assumes that the models are basically correct, that the basic science is settled. This is far from true.
The models basically assume the hypothesis of human-caused climate change. Natural variability only comes in as a short term influence that is negligible in the long run. But there is abundant evidence that long term natural variability plays a major role climate change. We seem to recall that we have only very recently emerged from the latest Pleistocene glaciation, around 11,000 years ago.
Billions of research dollars are being spent in this single minded process. In the meantime the central scientific question – the proper attribution of climate change to natural versus human factors – is largely being ignored.
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I don’t have a problem with modelling, per se, provided (a) the boundary conditions are precise, (b) the appropriate science is reasonably described by the mathematics and digital methods chosen to investigate it, (c) the assumptions are properly based, defined, explained, and justified, and(d) the outcome is not predicated on a pre-conceived notion. Modellers need to fully appreciate that Garbage In = Garbage Out, not Gospel Out!
I suspect that this is nonsense. Or at least a fault with the search engine or search terms. Running the same
search on scopus gives the following:
“model” or “modelling” or “modelled” = 5609206 documents
(“model” or “modelling” or “modelled” ) AND “climate change” = 131459 results
so on SCOPUS at least less than 2% of modelling papers are related to climate change.
Just did a quick comparison. Think you are probably wrong. Scopis is abstracts only, but includes conference proceedings and patent filing abstracts. So naturally there would be many more modelling hits. Google Scholar is only papers and books, but full text not just abstracts. So naturally there will be many more models in full climate context hits.
Hi,
In general SCOPUS which just does search abstracts is far more restrictive than google scholar. It includes
far few sources and is more restrictive. So for example searching for “climate change” on SCOPUS for the
last 10 years gives 140007 results while the same search on google scholar gives “About” 1130000, i.e.
almost 10 times as many.
Incidentally on SCOPUS though over 93% of papers on climate change also include the word model. So
while most modelling papers are not about climate change most climate change papers do mention models.
Indeed Geronimo, most climate change papers either start with modeling or hope to feed into modeling . Abstracts are relatively useless in this regard. Modeling dominates the field. That is the point of my research. Does anyone contest this?
“Modeling” is the favorite past time of many climate ‘scientists’. Their second favorite past time is “adjusting” the observational data to match the models.
My grad degree is in modeling. IMO the climate scientists are way too enamored with modeling, especially with projections, rather than interpolations.
What texts did you use in your courses?
Very nice analysis.
There is a fundamental reason the models cannot be right, illustrated in detail in a previous guest post here. In short, there is a 7 order of magnitude (E+7) difference between what that $73 million Cray supercomputer can do and what current weather models need to do to adequately resolve convection cells (e.g. tstorms) for precipitation and tornado warnings. So such crucial GCM processes are parameterized, tuned to produce reasonable hindcasts (for CMIP5, the mandatory tuned hindcast was YE1975 to YE 2005 (30 years) with initialization either avg Dec 2005 or Jan 1 2006). The hindcast tuning period contains a significant warming event statistically indistinguishable from ~1920-1945. Even IPCC AR4 said the earlier was not anthropogenic–not enough change in CO2. It was mostly natural variation. This gives rise to the attribution problem. The 1975-2000 rise is attributed in GCMs to anthropogenic forcings, mainly CO2 as the ‘control knob’. The models subsequent multiple failures (pause, tropical troposphere hotspot, ~twice observational EBM TCR and ECS) simply highlight the obvious attribution error.
All the many gloom and doom CAGW papers are based on faulty models. Because temperatures haven’t risen this century except for the now fading El Nino, or unless Karlized. Neither El Nino nor Karlization has anything to do with CO2 emissions. SLR has not accelerated. The planet is greening. Corals adapt symbionts by bleaching. Polar bears do not rely on late summer sea ice and are thriving. And so on.
spot on………..
Aha!
So I was right, long ago, to interpret CAGW as ‘computer-aided global warming’
I suspect that the heat being generated by all those Cray computers has warmed the planet more than CO2 has.
As has been pointed out in other comments this paper might be overstating the dependence of alarmists on modeling just a bit. However it does seem to at least draw attention to the general problem the alarmists have of ignoring actual evidence. One of the best recent collections of evidence is the recent paper on the natural processes that corals undertake to deal with the inevitable and constant changes in their environments. If that research does not at least quiet the bleaching alarmists, then there is no hope for them.
Of COURSE they focus on modelling – that’s where the funding pig trough is for them to snout at!
It’s like the Scottish wave power generation “testing” – it has been in testing for over 20 years now.
Why?
Becasue they get over £5 million per year for testing and the power generation would get them only around £1.5 million.
So they keep “testing”, “researching”…
It is no surprise to hear that there is so much ‘modelling’ going on in ‘Climate Science’. With ‘modelling’ you can be assured of getting the results that you want. If you conduct actual experiments on the weather and climate, you could get almost any result, even accurate ones. CAGW papers are usually based on models which invariably give the result required by CAGW. When El Nino caused spikes in temperature occur, they are dutifully used to support the CAGW theory and draw attention away from the Pause. Observable facts like the fact that the planet is greening under extra CO2 and that corals can adapt to temperature changes, or that polar bears are increasing in numbers, or that people like warmer weather are just so embarrassing to the CAGW Alarmism, that they serve the Cause to help at all.
From what I’ve seen, the reason that so many Climate Science papers use the word model or modelling, is because they use output from the CMIP models as actual data to use in their own research projects, many of which involve further modelling on what are probably regular desktop computers. This of course produces “projections” that are so far removed from the real world that they serve no purpose other than keeping researchers busy (and getting paid and published in “peer reviewed” journals).
I haven’t noticed any “third generation” models being cited; that is a treat to be looked forward to for our future entertainment.
As long as the data uses a “trend line” then no modeling has occured.
I would imagine that the discovery of the model that predicts this random walk climate would be the holy grail of discoveries.
Not all of science is corrupted. Here’s an astronomy article from phys.org, http://m.phys.org/news/2016-05-stellar-mystery-deepens.html. The last paragraph reads
“Looking to the future research in this field, Professor Lattanzio highlighted the role that advanced computer simulations will play in the next stage of research.
“Computer simulations do not agree with this observation; so as well as continuing observations, new computer models will need to be generated to better understand what is taking place in the cores of these stars,” Professor Lattanzio said.”
The study uses the mention of models in papers as a proxy for the reliance on them. It seems at least as valid as tree rings for temperatures.
I haven’t worked my way through all the comments yet, but there’s some concern over the term “model” and which type of model each reference may mean. May I suggest searching through again, this time looking for the term “empirical”? I suspect the number of hits will drop significantly in climate change papers, although undoubtedly there will be issues with this too.
Just a suggestion.
Why do they need a model? Can’t the temperature for any range of time at any location be calculated as the average temperature 50 years ago times a constant times the log2 of current ppm/280 ppm
I’m about to drop an apple from my hand that is poised three feet above the floor. I predict the apple will fall to the floor. I just used a scientific model to make a projection.
Explain your ‘model’ in detail.
Parameters, math, altitude, gravity…
@ur momisugly Tom and ATheoK, And is that apple a Mac or a Granny Smith? Inquiring minds need to know.
I modeled it and you’re right! It’ll hit the floor about 433ms after you let it go.
Interesting concept. Simplistic to a fault.
Baying to the ‘climate change’ moon or bowing to the ‘climate change’ delusion is all too necessary for researchers chasing grants.
You need to work out a search on more definitive terms; or read every paper to determine if the ‘climate change’ is an obeisance gesture or genuine delusion.
Not that I think you’ll get different results as I doubt there are all that many disciplines where baying to the ‘climate change’ false science is as requisite as the enviro-nutty and climate science groups are.
The climate models are faulty at best. This one is from 2012. Forecast of drought in Britain brings record April showers. Time to change climate models?
https://lenbilen.com/2012/05/05/forecast-of-drought-in-britain-brings-record-april-showers-time-to-change-climate-models/
Dr. Michaels: The problem with the use of models in climate science is not the models themselves. It is the blatantly dishonest way that modeling results are presented. Steven Schneider once said that ethical scientists “are expected to tell the truth, the whole truth, and nothing but — which means that we must include all the doubts, the caveats, the ifs, ands, and buts.” Every conclusion derived from a climate model therefore should begin with “If our unvalidated climate model(s) correctly describes X, then X is projected to be Y. For example, “If our unvalidated climate model(s) correctly describes global warming under RCP 8.5, then MGST will be 1-6 degC (95% ci) warmer in 2100 under that scenario than it is today.
When did scientists start fooling themselves by presenting 70% confidence intervals – 1/3 of which will be wrong chance and part of the remaining 2/3 will be systematic errors and confirmation bias?
Why is warming reported relative to the pre-industrial conditions when we don’t know how cold it was back then – in the LIA? No living person has experienced pre-industrial climate.
While climate models are based on well-tested physical theories, they require parameters that can’t be systematically optimized. Changes in the entrainment parameter alone have changed model ECS by 1 K/doubling without degrading model performance. The IPCC calls their models “an ensemble of opportunity” and recognizes that no conclusions should be drawn from the spread of the multi-model mean – and then uses their “expert judgment” to draw such conclusions.
PATRICK J. MICHAELS and David E. Wojick are absolutely right about the climate
“modeling” being divorced from reality. Not only are the modelers completely off
the mark with predictions of their pseudo-science, they also change official
temperature records at will which should count as a crime. An example follows. A mainstay of
their doctrine is the belief that carbon dioxide is warming up our atmosphere by its
greenhouse effect. There is no scientific proof of this so they trot out laboratory
measurements of infrared absorption by carbon dioxide. A sneaky part of this is
that carbon dioxide is neither the only nor the most abundant greenhouse gas in air.
Atmosphere water vapor is both, comprising 95 percent of total greenhouse gas
in the atmosphere.. Carbon dioxide, by comparison, is a miserable 3 percent.
And yet the Arrhenius greenhouse theory they think of as justifying
their work. leaves water vapor completely out, and uses only three percent
of existing greenhouse gases to predict the world’s future. This is an absurdity that
Tim Ball pointed out and I agree with him. I made that same point in a comments
I attached to Walter Dnes article in WUWT of April 30th Below is an adaptation of my
comments that cover to their use of pseudoscience to create warming where none
exists. Let’s begin with the existence of the hiatus in the eighties and nineties,
something you probably never heard of. It is present in satellite data which is how
I discovered it in 2008. But it has been covered up by an imaginary “late twentieth
century warming” in all ground-based temperature curves. It is clear from satellite
data hat there simply was no warming from 1979 to 1997. These dates go from the
beginning of the satellite era to the beginning of the giant super El Nino of 1998 You
can see what the real curve looks like in Figure 15 of my book “What Warming?”
Since no one was listening to me about this I decided to put a warning about it into
the preface of my book when it came out in 2010. No one listened. I used that same figure again in
an article I posted on October 29th last year in WUWT. That article criticized
Karl et al.’s attempt to declare the twenty-first century hiatus non-existent.
Amazingly, a Bob Tisdale, trying to defend the global warming cabal, added a
comment accusing me of having fabricated the data in Figure 15. He is the same
man who thinks that El Ninos are warming up the world. This act is of course
pure libel which he has to publicly retract and apologize for. Fortunately, I
was able to get NASA’s own description of what temperature was doing the eighties
and nineties, issued in 1997. This is what NASA had to say then:
“Unlike the surface-based temperatures, global temperature measurements of
the Earth’s lower atmosphere obtained from satellites reveal no definitive
warming trend over the past two decades. The slight trend that is in the data
actually appears to be downward. The largest fluctuations in the satellite
temperature data are not from any man-made activity, but from natural
phenomena such as large volcanic eruptions from Mt. Pinatubo, and from
El Niño. So the programs which model global warming in a computer say the
temperature of the Earth’s lower atmosphere should be going up markedly,
but actual measurements of the temperature of the lower atmosphere reveal
no such pronounced activity.”
Note the fact that NASA specifically rejects the validity of computer-predicted
temperature rise for this period. I can see now how, despite NASA’s warming,
those modelers’ computer predictions became the seed for changing that section
into a non-existent “late twentieth century warming.” With that, they effectively erased
the first hiatus we had. (But not completely, it is still visible in satellite data). The
second hiatus is the twenty-second century hiatus we are experiencing now.
This is the one that Karl et al. were supposed to have buried. Two hiatuses gone
with these two moves: is there any meaning or pattern to this? The answer is yes,
when we follow through on it. What happens when a hiatus arrives is that from
that point on there is no increase of global temperature while atmospheric carbon
dioxide just keeps increasing. Why is this a big deal? you may ask. It is a big deal
because according to the Arrhenius greenhouse theory, any increase of atmospheric
carbon dioxide must be accompanied by an increase of global temperature. This is
the greenhouse effect at work. But what we have experienced instead for the last
18 years or so is a steady increase of atmospheric carbon dioxide with no
corresponding increase of global temperature. If true, this means that Arrhenius
greenhouse theory is simply not working – it predicts warming and we don’t get
any. Therefore, that vaunted greenhouse effect the IPCC and 200 plus world
governments are supposed to be fighting is simply not there! How can this be
when the science is settled and our fate is sealed by the global greenhouse
effect? The answer: there is no global greenhouse effect. With that, the theory
of global warming by the greenhouse effect dies. And all multi-billion mitigation
projects must be defunded because there is nothing to mitigate. The largest
amount of global greenhouse gas is water vapor which
makes up 95 percent of total global greenhouse gas by volume,
as we saw. But the Arrhenius greenhouse theory leaves water vapor
completely out. Small wonder that its predictions of warming are false. But
there is another greenhouse theory that does include both carbon dioxide
and water vapor as its subjects. It is the Miskolczi greenhouse theory or MGT. According to
MGT the greenhouse effect predicted by Arrhenius does not exist.
MGT does predict the existence of today’s hiatus accurately and should be used in
place of the Arrhenius greenhouse theory that makes false predictions about
a non-existent greenhouse effect. To understand why MGT is correct and Arrhenius is wrong read:
Arno Arrak (2014) “The Miskolczi Greenhouse Theory.” http://energiaakademia.lapunk.hu/tarhely/energiaakademia/dokumentumok/201406/miskolczi_greenhouse.pdf
Thanks for the post Arno. Good to read multiple perspectives. still digesting. And will be for the rest of the evening.
Beautiful, gorgeous night on the patio with my iPad here in Tucson Az. Near full moon, Mars, and my puppy dog for company. Life’s good.
It is worse than that:
1) CO2 shows a logarithmic decay in its absorption. The data adjustments are to make the relationship between CO2 and temperature linear. That is clear fraud, and demonstrates that they are manipulation the data in a manner that will make sense to the average person that doesn’t understand math, and is contrary to the actual science.
2) All the efforts are towards modeling CO2, H20 is completely ignored. That is like doing a study on lung cancer and ignoring smoking as a factor, and concentrating on how many candle someone has in a room.
3) There are no laboratory experiments or theories as to how atmospheric CO2 can warm the oceans. If you can’t explain how CO2 warms the oceans, you can’t claim CO2 is causing the atmosphere above the oceans to warm.
It’s not that they ignore H2O, it’s that they ignore the affect H2O itself has on the atmosphere.
They assume a simple relationship, that the relative humidity will stay the same regardless of actual temperature. Thus as temperature increases, total H2O in the atmosphere will also increase.
A number of problems with this.
First and foremost, the assumption of constant relative humidity was never experimentally confirmed, they just assumed it must be right. Real world experiments have disproven that assumption, but it’s still in most models.
Secondly, they ignore the impact extra H2O has on the atmosphere. That it makes the atmosphere unstable and hence promotes overturning, which takes the H2O and the rest of the air around it from the ground level to the upper atmosphere where the H20 condenses and releases it’s heat.
Typo: “twenty-second” should be “twenty-first.” Sorry
Far too many climate change papers are just results of model runs with different sets of hypothetical input variables. The essential message is “honey i ran the climate model”.
If they had empirical evidence they would not have to rely on modeling so much.
more on this topic at ssrn.com/author=2220942
Call Guiness, seems we have found the worlds most expensive boondongle!
@benben, May 19, 3: 64 pm,
Anyway, the truth of the matter is that climate research is pretty well done nowadays. Websites like WUWT create this alternative narrative of a bunch of crazy power hungry bureaucrats abusing incredibly simplistic models to undermine democracy. It’s entertaining to read but it’s just really far removed from the boring daily grind of science, of which climate research is very much a part.
Hey, you’re always free to follow a couple of MOOCs on the topic and see for yourself how things are done, instead of rely on stuff like whats posted here!
and this a little later, you said:
Contrast that with the post on which we are commenting here. The guys at WUWT can’t even put together a decent google scholar search.
Now, I understand that most of the stuff on this site is actually a super conservative American flamewar against liberal Americans, but its just weird to see science caught up in it.
Just a wild ass guess, are you a liberal? I am surprised you lower yourself to our level. Frankly your contribution should be a waste of your “valuable time” get a grip ( and leave).
BTW as a “red neck” it took me awhile to simmer down but after thinking about it and assessing your comments I had to speak up and a little later I thought about deleting this but you need to get out of the basement.
Super conservative, now that thar is funny.
hmmm well, it certainly wasn’t my intention to offend. My apologies, asybot. I’m not american so I don’t really follow the distinction american liberal VS american conservative. I wrote that more as an observation.
But, ok, so just out of honest curiosity. It seems to me that almost everybody here is an american republican, or the occasional UK equivalent. And almost all the people being trashed on this website (e.g. Al Gore, Obama, etc.) are american liberals. So it’s an accurate assessment that a lot of the stuff here is about the intersection of climate science and american politics?
Again, I don’t want to offend, but I don’t really see how that observation is offensive.
Cheers,
Ben
Apparently climate change research is a virtual reality career : )
What has disturbed me for the entire history of this debate is the naïve faith in the accuracy of models.
As a professional in the computer industry with a degree in engineering I have followed the use of computer modeling for aircraft design for some time. Finally after decades of development including countless rounds of calibrating program results against real world wind tunnel tests we have codes that can do a reasonable job of predicting the performance of an aircraft design in well-behaved flight before it is ever built.
These same programs however do a poor job of predicting performance for extreme maneuvers because the codes cannot deal well with turbulent flow. The simplest way to describe this is that we can simulate how a plane flies pretty well but not how a parachute will open. The former case is essentially trivial by comparison to the latter (just ask the engineers at JPL trying to design the parachutes for our Mars lander missions) and I would argue that modelling the climate is a similar challenge. There are simply too many unknowns and too many uncertainties involved.
Too drive national policy based on the predictions of climate models is simply dillusional. It’s like believing that you are a great athlete because you excel at video game sports.
MHO anyway.
Mike Nelson wrote: “Too drive national policy based on the predictions of climate models is simply dilusional. It’s like believing that you are a great athlete because you excel at video game sports.
MHO anyway.”
I agree with your opinion.
Excellent comment .
The point I’d make is that calculating a relatively long term global mean is a much simpler task than calculating atmospheric dynamics .
It’s more akin to calculating the mean temperature of a volume of gas from gas laws without any attempt to model the eddies within .
This has led to an ignoring of the non-optional macro physical constraints and careers tweaking the dials on the parameters influencing the eddies .