![CMIP5-90-models-global-Tsfc-vs-obs-thru-2013[1]](https://wattsupwiththat.files.wordpress.com/2014/06/cmip5-90-models-global-tsfc-vs-obs-thru-20131.png?quality=75)
Dana Nuccitelli has written a defence of climate models, in which he appears to claim that a few models randomly replicating the pause should be considered evidence that climate modelling is producing valid results.
According to The Guardian;
… There’s also no evidence that our expectations of future global warming are inaccurate. For example, a paper published in Nature Climate Change last week by a team from the University of New South Wales led by Matthew England showed that climate models that accurately captured the surface warming slowdown (dark red & blue in the figure below) project essentially the same amount of warming by the end of the century as those that didn’t (lighter red & blue).
There’s also been substantial climate research examining the causes behind the short-term surface warming slowdown. Essentially it boils down to a combination of natural variability storing more heat in the deep oceans, and an increase in volcanic activity combined with a decrease in solar activity. These are all temporary effects that won’t last. In fact, we may already be at the cusp of an acceleration in surface warming, with 2014 being a record-hot year and 2015 on pace to break the record yet again.
The problem I’ve got with this line of reasoning, can best be illustrated with an analogy.
Say your uncle came to you and said “I’ve got an infallible horse betting system. Every time I plug in the results of previous races, plug in last year’s racing data, it gets most of the winners right, which proves the system works.”.
Would you:
- Bet your life savings on the next race?
- Wait and see whether the model produced good predictions, when applied to future races?
- Humour the old fool and make him a nice mug of chocolate?
Anyone with an ounce of common sense would go for option b) or c). We instinctively intuit that it is much easier to fit a model to the past, than to produce genuinely skilful predictions. If your uncle was a professor of mathematics or statistics, someone with some kind of credibility in the numbers game, you might not dismiss his claim out of hand – occasionally skilled people really do find a way to beat the system. But you would surely want to see whether the model could demonstrate real predictive skill.
What if a few months later, your uncle came back to you and said:
“I know my model didn’t pick the winners of the last few months races. But you see, the model doesn’t actually predict exactly which horse will win each race – it produces a lot of predictions and assigns a probability to each prediction. I work out which horse to pick, by kind of averaging the different predictions. The good news though is one of the hundreds of model runs *did* predict the right horses, in the last 4 races – which proves the model is fundamentally sound. According to my calculations, all the models end up predicting the same outcome – that if we stick with the programme, we will end up getting rich”.
I don’t know about you, but at this point I would definitely be tending towards option c).
Earth’s temperature simply won’t continue to increase forever.
It can’t and it won’t. And I don’t see any of the models incorporating that unavoidable fact.
I am having some difficulty reconciling the main plot here with that the “18 year no warming” plot
Are they produced from the same data set?
Paul Westhaver
Yes.
The 18 years is UAH data (shown in the above plot) and RSS data (not shown in the above plot). The HadCRUT4.3 data in the above plot shows no global warming for 19 years.
All these times are for when the linear trend in global average surface temperature anomaly (GASTA) does not differ from zero with 95% confidence.
Richard
Even a broken clock is right twice a day.
Three observations.
1) Dana writes: “There’s also no evidence that our expectations of future global warming are inaccurate.”
By the same token, there’s also no evidence that Dana’s expectations of future global warming are accurate. Absence of evidence is not evidence of absence. The current lack of warming provides evidence that Dana’s expectations of future global warming are not accurate.
2) There is a basic earth science tenet of multiple working hypotheses (T. C. Chamberlin, reprinted here http://www.whoi.edu/cms/files/chamberlin65sci_72744.pdf ) I find it amazing that “climate scientists” will bend over backwards to find multiple working hypotheses to explain the pause; but never, ever consider the possibility of an alternative hypothesis for the prior warming.
And Dana’s statements regarding volcanoes and solar activity are just asinine: “These are all temporary effects that won’t last. In fact, we may already be at the cusp of an acceleration in surface warming, with 2014 being a record-hot year and 2015 on pace to break the record yet again.”
How does he know that these are the real reasons for the pause or that they are temporary and won’t last? Just because Ben Santer wrote a paper that put forth an hypothesis involving volcanoes, solar activity, and heat storage in deep oceans does not mean that the hypothesis is correct. No real increase in volcanic activity is noted. Solar activity for Cycle 24 has apparently peaked and is expected to continue declining as Cycle 24 comes to an end. Cycle 25 has been predicted to be of lower intensity than 24. Dana’s “fact” that we “may” be on the cusp is not a fact, rather it is rampant speculation.
3) Even with hindcasting, less than 3% of the climate model projections predicted the pause (Meehl et al., 2014). What great odds; a casino would love odds like this. Dana compounds the problem by invoking the gambler’s fallacy. The roulette wheel came up red 18 times therefore it’s more probable that it will come up black on the next spin. Casinos love idjits like him.
We can speculate on the reason that the coolest, tiny fraction of global climate models matched pretty good with reality. Maybe they got the ENSO right or something else.
In weather/climate model(projection) ensembles like this, when you have a couple of the ensembles that go off on their own, with a solution much different than the ensemble average, they are referred to as “outliers”.
If you have, 90 ensemble members for instance and only 2 or 4 got it right and those were only the ones considered to be the biggest outliers, what does that mean?
It could mean several things, some that I can’t think of because I really don’t know exactly what the physics were in the correct/cool outliers that caused them to be accurate.
Was it chance?
Only another decade of observations will help to clear that one up.
Did those ensembles have equations that amplified H2O(positive feedback) less?
I doubt that or you would think the problem would be solved and we know what to adjust in the other 86 or 88.
Does that mean that global climate models can project accurately?
4 out of 88 means just the opposite to me. However, I think there is use/value in global climate models if used properly. This means, with time, we should be tweaking parameters/equations and weighting in models as they are compared with observations. By time, that doesn’t mean waiting for the observations to catch up with the model projections, even as they their steeper trend causes them to get farther and farther away. The later is how they are currently being used.
I realize that weather models and climate models are very different. However, the lesson to be learned by climate modelers that meteorologists learn hundreds of times in their career, is to let your ego go. You spend a great deal of time making a forecast based on your best source for prediction………atmospheric models. You can analyze those models better than anybody and know they accurately represent the physics of the atmosphere and your forecast is based entirely on what should happen.
However, when the forecast starts to bust, the sooner you acknowledge it, the sooner you can make the adjustment. I really get where these climate scientists/modelers are coming from. There is no meteorologist, especially if money, pride or a million viewers watching that doesn’t “hope” while watching the actual weather in their forecast pan out.
When it is going the wrong way, we have all looked at the pattern and thought “I know I analyzed this right” or “It’s just taking a bit longer than expected but I know this or that will happen as predicted”
We often wait a bit longer than if we did not have any “skin in the game” to update/adjust because the absolute WORST thing to happen, is if you changed the forecast and then, your first one verified.
The same game is gong on here. With this being climate vs weather, the time frame is just much longer and since no climate scientist can have the experience of having learned the lesson dozens of times before, they are learning it for the first time in most cases(climate models have not been around that long either)……….which means they are still “hoping” for the climate to react in the way that they know it should based on their very accurately analyzed interpretation.
I get that they accurately analyzed the climate and data and models. They understand the known physics better than anyone. However, when a projection is going the wrong way, justifying wrong things in the old projection by dialing in new things that are just temporary “speed bumps” will not work.
If you are so convinced that your climate models have really captured all the physics, then good luck, reading this was a waste of time.
There is an old joke(that is not true, I don’t think) that I’ve heard several times before. Climatologists are just meteorologists that couldn’t forecast. I’m sure that a meteorologist came up with that one.
However, climate scientists, if you don’t start adjusting your climate models, then this will be no joke……….there will be some truth to it!
The models that have done less poorly assume the lowest ECS, ie 2.1 degree C per doubling of CO2 concentration.
From IPCC Chapter 9, “Evaluation of Climate Models”:
9.7.1 Equilibrium Climate Sensitivity, Idealized Radiative
Forcing, and Transient Climate Response in the
Coupled Model Intercomparison Project Phase 5
Ensemble
Equilibrium climate sensitivity (ECS) is the equilibrium change in global
and annual mean surface air temperature after doubling the atmospheric
concentration of CO2 relative to pre-industrial levels. In the AR4,
the range in equilibrium climate sensitivity of the CMIP3 models was
2.1°C to 4.4°C, and the single largest contributor to this spread was
differences among modelled cloud feedbacks. These assessments carry
over to the CMIP5 ensemble without any substantial change (Table
9.5).
See Fig 9.42 on Page 817 for the ECS assumed in each model.
They might also assume a lower rate of CO2 level growth, but I didn’t check that parameter.
“Matthew England showed that climate models that accurately captured the surface warming slowdown [3% of the models] (dark red & blue in the figure below) project essentially the same amount of warming by the end of the century as those that didn’t (lighter red & blue).”
Soooo….the results of the models have low precision — and 3% accuracy — over two decades time because of unforeseen natural variability but in 100 years the models have high precision and by then the 3% accuracy rate will be near 100%? Congratulations Global Warmistas, you’ve reached Cuckoo Level 50!
Nutty and England are just plain wrong. The coolest and so far least wrong model predicts only 0.5 degree C of future warming, while the hottest forecasts 1.6 degrees. Hardly “essentially the same”, but even 1.6 degrees C warmer would not be a catastrophe.
Correction: Not further warming but warming above the reference period. UAH has us already 0.3 degrees warmer than that, so the coolest model foresees only 0.2 degrees more for the projected period.
It appears that the super El Ninos of the 1980s and ’90s are mainly responsible for the steps up in GASTA.
A few models wandered over the pause… and into a bar.
One said “Is it just me, or is it hot in here”?
Barkeep said, “simmer down, take a load off, and have a cold one”.
The other two grumbled, “I bet he’ll crank up the heat when we’re not looking”.
Which one of the 90 models is based on the settled science?
If the science is truly settled, why are there 90 models, and not just one model?
In any case, which of the models (colour runs) is said to have got matters right?
Whilst it is difficult to read the plot, I cannot see any model run that has tracked HadCrut 4, or UAH trosphere. I certainly would like to see the identification of this, and then we can see how the projections of the said run compare to real life observation between now and 2020, and that would probably confirm that even the identified model runs are by then departing from reality.
How much does Dana get paid per wishful thinking or misleading word? It all adds up.
A few models?
If you flip a coin often enough, one day it will stand on it’s edge.
‘Essentially it boils down to a combination of natural variability storing more heat in the deep oceans, and an increase in volcanic activity combined with a decrease in solar activity. These are all
temporary effects that won’t last.
After vomitting he called for the room service and some sanitation works.
@mod: you can stand this?
Hans
“….we may already be at the cusp of an acceleration in surface warming, with 2014 being a record-hot year… ”
As I recall, NASA’s data showed a record of – drum roll please – 2 hundredths of a degree, far smaller than the measurement accuracy. And they stated that the probability of a record was 38% In other words, even NASA had to admit that it was most likely not a record at all.
Talking about computer models, yesterday I was thinking about the claimed “proof” based on computer models, for example in David Attenborough’s 2006 program.
The first suspicious thing is that the data ends in 2000, so six years of data and computer predictions had gone missing. Why? Could it be that the pause was already apparent, and it was just too convenient. I’ve (approximately) updated the graph to 2015.
https://drive.google.com/file/d/0B-r4EiZCGxdrLXJnQ2l5TjdoVXM/view?usp=sharing
The “proof” doesn’t look so good now, does it?
Chris
@ur momisugly Mike Maguire May 11, 2015 at 7:46am “My biggest problem on this relates to an element that there can be no disagreement on. On something that those who claim otherwise are blatant frauds and/or scientifically blind. Sun +H2O +CO2 + Minerals = O2 + Sugars(food)
Either you agree that the big increase in CO2 has resulted in a massive increase in the vegetative health of the planet, with big increases in crop yields/world food production or you are a fraud and anything else you state about the effects of CO2 are not credible either.”
+1 and the Global NDVI values show just that. Turns out scientists have known this for at least a couple of decades.
http://www.rationaloptimist.com/blog/the-greening-of-the-planet.aspx
and here:
http://nipccreport.org/articles/2012/jun/26jun2012a1.html
“In discussing the current state of knowledge in this area, De Jong et al. write that “over the last few decades of the 20th century, terrestrial ecosystems acted as net carbon sinks, as evidenced by ecosystem process models and satellite vegetation data (Myneni et al., 1997; Schimel et al., 2001; Zhou et al., 2001).” And they say that “the easing of climatic constraints on plant growth as a result of increased CO2 concentrations and higher temperatures is a likely explanation for this effect (Nemani et al., 2003).” Thus, it can readily be appreciated that the twin evils of the world’s climate alarmists – rising atmospheric CO2 concentrations and global warming – have actually been what has fueled the last quarter-century’s greening of the earth.”
also here:
http://www.lifescientist.com.au/content/life-sciences/news/unexpected-increase-in-global-vegetation-and-carbon-capture-379540886
Hardly unexpected as the first link points out viz Keeling et al.
There is of course the obligatory AGW doom.
“It’s important to recognise that global warming would be happening faster if some of our CO2 emissions were not captured by this vegetation growth.”
Dr Canadell warned that “about 50% of emissions from human activities stay in the atmosphere even after the other half is removed by terrestrial vegetation and oceans. The only way to stabilise the climate system is to reduce global fossil fuel emissions to zero.”
But surely the climate system is never stable, that’s the point and 50% of what’s left after vegetative processing isn’t that alarming given that an average meeting room can reach 1200ppm/v with minimal affects split each way between yawning from CO2 elevation and the meeting itself. I now have to wonder if plant growth acceleration will at some point reach a net increase in CO2 processing leading to a decrease in observable man made CO2 and the cycle starts again. Oh darn it I feel another model coming on.
I had always though the susseration in my garden was due to the wind, perhaps it’s the vegetation applauding in anticipation of the buffet to come. I shall never again look at my petunias the same way.
There is a post by one of the co-authors of the paper, Matthew England, on the un-skeptical site with the doublespeak name Skeptical Science which says:
http://www.skepticalscience.com/climate-hiatus-doesnt-take-heat-off-global-warming.html
“Until now, however, no evaluation has been made of the possible consequences for long-term projections. Specifically, if the variability controlling the current hiatus is linked to longer-term sequestration of heat into the deep ocean, this might require us to recalibrate future projections.
With this in mind, we decided to test whether 21st century warming projections are altered in any way when considering only simulations that capture a slowdown in global surface warming, as observed since 2001.”
So he thinks that models that weren’t dealing with long-term ocean sequestration of heat, but somehow accidentally predicted the pause, have relevance to claims about future warming if the ocean were involved in a way that wasn’t modelled? Wow is that absurd.
They keep saying that you cannot have “infinite growth in a finite world” (probably meaning: economic growth, material growth, energy consumption growth, whatever physical parameter growth), but they sure can have infinite bovine excrement arguments growth.
This there-is-no-pause-and-we-understand-its-cause circus is now actually funny.
The there-is-no-pause-and-we-understand-its-cause-and we-predicted-it-all-along-but-soon-it-will-be-worse-than-we-expected circus is even funnier.
Give it more time and all of the models will be off more and more especially when the global temperature trend starts to decline.