Quote of the week – Nature on the failure of climate models

“Kevin Trenberth…says that it could be a decade or more before this research really begins to pay off…”
The trick now for these guys is to put their warming predictions off until they are safely in retirement and no longer accountable.

Schmidt makes a good point that the approach of summing up the measured changes in climate “drivers,” projecting the rates of change into the future, and using that to predict future climate has been given a fair trial and has come up short. Even when the magnitudes can be reasonably easily calculated, the mechanisms can remain elusive.

Failure of Climate Models?
What total complete and utter BS.
Climate Models are just computer models that do what they are programmed to do. They do NOT fail and can never fail – they do what they are built to do and no more and no less.
The FAILURE is with CLIMATE SCIENTISTS and in particular those that made grandiose catastrophic predictions instead of admitting that there is still a lot that we don’t know that we don’t know about climate. The FAILURE is with THEM.
The FAILURE is also with the UN IPCC, Western Governments, media and NGO’s like Sierra, WWF and Greenpeace. These organizations are no longer trustworthy to present science in a balanced unbiased manner – they appear to be governed by agendas and self interest (money) and have completely lost any sense of moral compass. The FAILURE is with THEM.

Jeremy@6:59
Hear hear. That applies the blame to where it belongs, not the ‘models’ which are merely helpless pieces of Code and Algorithms.

Mikeyj says @ July 11, 2013 at 7:06 am
It’s that and much more.
http://wattsupwiththat.com/2010/11/18/ipcc-official-%E2%80%9Cclimate-policy-is-redistributing-the-worlds-wealth%E2%80%9D/

Although I was surprised to see this article in Nature, since they have been AGW cheerleaders/doomsayers in the past, they probably had no choice to print an article like this or they would face a complete loss of credibility. Of course IMO, they have already lost their credibility and are trying to regain it.

From the Nature paper “Smith says. “We don’t really understand at the moment why that is.””
I find this to be a very interesting statement. The UK Met. Office used the Smith et al study as the basis for their prediciton of future climate. Then, at Christmas 2012, they quietly changed the forecast, but gave no reason or analysis about this change. If Smith is right, and I suspect he is, and they dont know why his study did not give the desired result, what is the basis for the Met. Office believing the new forecast is any better that the old one?

philjourdan says: July 11, 2013 at 6:52 am
“He [Gavin Schmidt] argues that it is difficult to attribute success or failure to any particular parameter because the inherent unpredictability of weather and climate is built into both the Earth system and the models. >/blockquote>
And yet they call those who ask the same questions (why) all sorts of childish names. But they admit they have no clue what they are talking about.”
If childish name calling were their only sin, I’d rejoice. Much worse is that they want to rapidly and drastically change the way we produce and use energy. In their feeble minds, “saving the world” (or more accurately, thinking that you’re saving the world) justifies any and all kinds of idiocy.

When the model starts to run forward in time, it immediately begins to drift back to its preferred climate,
===
no…..the computer game does what it was programmed to do
So no matter what you feed into it……it give the results the “scientists” expected
These computer games have been a 100% fail…..got nothing right

“Because the climate does not usually change drastically from one year to the next, the model isbound to start off predicting conditions that are close to reality. But that effect quickly wears off as the real climate evolves. If this is the source of the models’ accuracy, that advantage fades quickly after a few years.”
Clearly there is “climate” and then there is “real climate” ….and of course “real climate” will determine the models accuracy ..no “ifs” about it …..I am astounded this is just now dawning as possibilities in their minds …

Jeremy says:
July 11, 2013 at 6:59 am
“The FAILURE is also with the UN IPCC, Western Governments, media and NGO’s like Sierra, WWF and Greenpeace. These organizations are no longer trustworthy to present science in a balanced unbiased manner – they appear to be governed by agendas and self interest (money) and have completely lost any sense of moral compass. The FAILURE is with THEM.”
Since 1972 the NGO’s work for the UN (Maurice Strong, Earth Summit in Rio). They are funded by the EU. (with the exception of Greenpeace)
You can’t say they failed when they do what they were paid to do. And arguably successfully; the entirety of EU societies has successfully been transformed into communitarians – to a point where even people considering themselves as rightwingers talk like Lenin and don’t even notice.
http://www.iea.org.uk/blog/european-commission-using-taxpayers%E2%80%99-money-to-fund-groups-that-lobby-for-larger-eu-budgets-and-

“Because the climate does not usually change drastically from one year to the next, the model is bound to start off predicting conditions that are close to reality. But that effect quickly wears off as the real climate evolves. If this is the source of the models’ accuracy, that advantage fades quickly after a few years.”
Whoever wrote that cannot think straight. Climate is defined as the 30 year average of weather. A 30 year moving average can by definition NEVER change “drastically” from year to year.

Climate science falsely believes that for any given combination of forcings there is only 1 equilibrium temperature for the earth and only 1 path that will reach equilibrium.
The spaghetti graph of the climate models are telling us quite the opposite. The models show that for any single combination of forcings there are a many possible future temperatures. This range of possible futures shows us that there is inherent variability in climate that is independent of the forcings.
The models are deliver a message that is absolutely clear, Weather is chaotic and the average of weather (climate) will vary naturally over time as a result of this chaos. It will not converge on a single mean because chaotic systems can be better understood as having many means, one for each attractor.
For example, daily temperature has a mean, but this mean varies wildly over the period of a year, and varies even more of the period of the ice ages. Trying to analyze this in terms of a single mean results in statistical nonsense. Which is why the climate models are failing to model reality.
The chaotic model of weather and climate tells us that a single mean cannot be resolved mathematically. It is the mathematical equivalent of the N body problem in orbital mechanics and quantum mechanics. The best that can be done is to place bounds around the problem.
The climate models show us a glimpse of these bounds. The top of the spaghetti graph is the upper limit and the bottom of the spaghetti graph is the lower limit, and what will actually happen is that real temperatures are likely to be found within the bounds. But exactly where can only be predicted by a throw of the dice.
For all intents and purposes, a chaotic system is a bounded system where chance determines the true answer within bounds. Physically this may well not be the case, but mathematically this is as close as we can get to the real answer because we cannot solve the N body problem. It results in an infinitely long series expansion.
The best we can do is to round off the infinite series both up and down, and say that the answer lies somewhere between these bounds. Where exactly cannot be predicted to any better accuracy than is given by a throw of the dice or a toss of the coin.

Because the N body problem is intractable, climate science would be much better off to stop talking about the ensemble mean. It will simply make them look foolish because chaos almost always guarantees that reality will diverge from the ensemble.
Instead, Climate Science should drop the ensemble mean and replace it with upper and lower bounds, representing the inherent uncertainty in the system. Put two lines on the temperature chart. One high and one low, and say that the real answer lies somewhere in between.
And then be honest about this. The answer is no more likely to be found in the middle, 1/2 way between the limits, than it is to be found anywhere else between the limits. Stop pretending that the real answer lies in the middle. It may, but chaos tells us the middle (ensemble mean) is not more likely than any other answer within the bounds.
for example, take any infinite series:
1.23456…..
Now round this series off high and low.
1.2345
1.2346
Where does the true answer lie? We know the missing information is 6….., but climate science does not. Instead they are trying to pretend that the real answer is:
1.23455
The ensemble mean is the extra 5 at the end, but the real answer is 6….. However it could just as easily be 1… or 9…. So we might as well toss a coin because the average is no more likely to be correct than any other possibility.

Since “Nature” can always be expected to put the best face possible on the AGW case (such as it is), this article constitutes a muted bombshell. It does several things that tell me those who have made their scientific “bones” on AGW theory are worried that “the party may be nearing its end” and are hedging their bets while trying to preserve funding:
1) AGW based climate models have failed in their predictions to an abysmal degree and the truth of that is being acknowledged.
2) No one knows why the models have failed (note: they fish around for possible reasons EXCEPT THE OBVIOUS; that AGW’s “positive feedback” theory is wrong).
3) Much more work must be done (and money spent) to research the problem and improve the models. That will take decades.
The article closes with a modest proposal I will paraphrase as, “Maybe if we put all the different climate models together in a kind of voting system they can tell us something worth knowing”.
“I wouldn’t be keen to bet on that at the moment,” Smith says, “but I do think we’re going to make some good progress within a few years.”
SOME GOOD PROGRESS WITHIN A FEW YEARS? (Just keep those taxpayer $ billions coming, boys and girls.)

The nature article is throwing the near-term projections under the bus. The article implies that the long-term projections are ok though.
“These near-term forecasts stand in sharp contrast to the generic projections that climate modellers typically produce, which look many decades ahead and don’t represent the actual climate at any given time. “

Tom J says:
July 11, 2013 at 7:58 am
Tom – at the very least, the whole climate industrial complex ™ needs to restructured and streamlined for efficiency. So many tax dollars (that we really don’t have) utterly wasted on dubious research projects and inefficient facilities. For example, why would anyone in their right mind maintain a very expensive branch of NASA GSFC in downtown New York City???

Jeremy says:
July 11, 2013 at 6:59 am
Well said Sir!
I would like to put a question to the Wet Office’s Julia Slingo & Vick Pope. Just how many people have o die on our un-gritted roads de to failed snow forecasts, how many elderly people have to have to freeze to death because they cannot afford to heat their homes, please, put a number on it before you sit up & think “maybe we’ve got it wrong?” What is it? 10, 100, 500, 1000, 5000? Do tell me!

David Borth says: “I am awaiting the next Nature article on the next stage of grief – the pain and the guilt – for what their unsubstantiated beliefs have wrought on the world.”
While I agree that there are quite a few well intentioned but merely misguided climate scientists out there, the more vocal ones, e.g. the ‘Team’, are ‘True Believers’ and will simply take a bounce and rationalize their way to the next catastrophe.

Your assessment leaves out a very key passage, which gives the article a very different complection than your interpretation:
“…In one such analysis4, Doblas-Reyes and his colleagues say that their model anticipated the slowdown in global warming up to five years in advance. Their paper also bolstered the theory that the deep oceans, notably the Atlantic and tropical Pacific, had stalled atmospheric warming by absorbing much of the heat being trapped by rising concentrations of greenhouse-gas concentrations in the air (see ‘Lost heat’).”
In short, the heat is still there; rather than being expressed in more volatile changes in atmospheric temperature, energy is being picked up in the thousands-fold greater reservoir of the ocean.
The limitations of models to provide exacting predictions has actually been discussed for a long time. That does not detract from their utility as analysis and forecasting tools, nor allow us to dismiss empirical observation which demonstrate very clear human-driven changes occurring in our climate. *Even if* data proved change was taking place more slowly (which it does not), all that does is give us more time. It does not give us a “pass” to continue business as usual…..

“Kevin Trenberth, a climate scientist at the National Center for Atmospheric Research in Boulder, Colorado, says that it could be a decade or more before this research really begins to pay off in terms of predictive power, and even then climate scientists will be limited in what they can say about the future.”
Trenberth must have about 10 years until retirement – gotta keep that money pumping!

Frank K. says:
July 11, 2013 at 8:41 am
‘For example, why would anyone in their right mind maintain a very expensive branch of NASA GSFC in downtown New York City???’
Because the restaurants are good?
(Seriously, I’ll bet that’s the reason. They’d probably prefer Marrakech, Morocco; Durban, So. Africa; Cancun, Mexico; and others but that would be too obvious.)

I’m having a hard time reconciling the following statement in the article with “the science is settled”.
“It’s fair to say that the real world warmed even less than our forecast suggested,” Smith says. “We don’t really understand at the moment why that is.”

@Rod Everson:

It (the model) begins to drift back to its preferred climate? Does that mean what it sounds like it means? Because it sure sounds like it means that regardless of the initial inputs, the model is going to end up “drifting” to a preordained (“preferred”) climate prediction. Preferred by the modeler, no doubt.

It’s essentially saying that each model has its estimate of climate sensitivity and a few other parameters. Simplistically speaking, these models model how energy from the sun flows into various earth systems and back out again to produce an average of the global temperature. You start with a temperature estimated from the instrumental record for a given time where you also have decent estimates for all of the inputs (CO2 level, volcanic activity, aerosol patterns, methane level…) and jiggle the parameters around until the modelled temperature matches the estimate from the instrumental record. Given no change in the inputs, that model will then keep on producing the same temperature – it’s at equilibrium (if you’ve done it right).
Then you disturb the model by changing one of the input parameters. its temperature estimate will begin to change and (assuming you’ve made a stable model) it will settle at a new equilibrium. But each model will settle at a different equilibrium because each one used a different combination of parameters to match that original temperature estimate. Model A might have a very high CO2 sensitivity but a very low methane sensitivity, for instance, while model B has a very low CO2 sensitivity but a very high methane sensitivity. They will both match the instrumental temperature estimate for a given time, but in model A the heat is mostly trapped by CO2 while in model B it is trapped mostly by methane. But if you change the CO2-concentration input to both models, model A will produce a much higher temperature than model B.
Whether those different responses to input reflect reality or the researchers biases depends very much on the process they used to tune the model. If you base them on theory-based estimates of model processes and parameters then you’d probably say they reflect reality, while if they are just adjusted to arbitrarily match the instrumental estimate then they reflect either the modeller’s prejudices or are entirely random.
The problem is that using the best theoretical estimates of model parameters never produces a model that matches reality even at one point in time, let alone through time. This simply reflects the fundamental defect of climate modelling: We don’t know enough about the system to model it accurately. On some aspects we understand the processes but don’t know enough to estimate the parameters with any certainty. On others we’re entirely ignorant what drives the processes (such as the PDO, AMO etc). No doubt there are entire processes that we don’t know about, or which are still controversial (cosmic ray cloud seeding, for instance). So every climate model, to a greater or lesser degree, is either a tedious curve-fitting exercise, only valid for the range the curve was fitted over, or reflects the prejudices of the modeller. It’s no real surprise (or shouldn’t be) that they spit out garbage.

““Kevin Trenberth, a climate scientist at the National Center for Atmospheric Research in Boulder, Colorado, says that it could be a decade or more before this research really begins to pay off in terms of predictive power, and even then climate scientists will be limited in what they can say about the future.”
This is one of the most profoundly stupid things I have ever read.
Translation: Our previous and current predictions are wrong. You need to wait ten years to see see that we were right, but don’t count on it.
Awesome. Give that man some more money.

I’d like to see some law suits for cost recovery and recovery for damages, deaths, poverty, and lost opportunity these modelers and climate hucksters have caused. This has been a true travesty.
And an apology. There needs to be an apology.

Piers Corbyn predicts climate patterns fairly well with an 80 % approx accuracy. Let’s face it, Solar cycles modulated by lunar and axial tilt/proximity cycles are the overriding input, the system is determined by the exterior influences on it’s current state. Oceanic cycles are merely a consequence of these factors.
I can understand that as a meteorologist Watts may be a bit miffed at Corbyn’s dismissal of meteorological predictions and focus on external influencesm, but Corbyn’s track record speaks for itself.

@Ferd berple
“The spaghetti graph of the climate models are telling us quite the opposite. The models show that for any single combination of forcings there are a many possible future temperatures. This range of possible futures shows us that there is inherent variability in climate that is independent of the forcings. ”
No, no, no. The models only “tell” us this if the models correctly represent the earth’s climate. All we can say at this point is the models are wrong and do not work.

I believe the problem with the models is that they don’t consider that the CO2 is already absorbing all the infrared radiation in the specific wave lengths. Adding more CO2 will not increase the temperature because there isn’t anymore radiation in the wave lengths it can absorb.

To the extent that the models embody the assumptions and theorizings of the AGW paradigm, it has to be accepted that the disparity between their predictions and the observations invalidate those assumptions and theorizings.
In science, actual science of the Scientific Method approach, hypotheses are tested against the predictions they make. And if those predictions fail, then it is the hypotheses that must be reworked, reexamined, or rejected instead of trying to fudge the observations to make them match.

Reed Coray says:
July 11, 2013 at 11:02 am
Mark Bofill says: July 11, 2013 at 9:37 am
If you let a member of the “team” construct a model of “how to unzip your pants”, and you use that model, you’re going to have wet pants.
——————————
:> No, I use a model developed some years back by qualified field researchers (my children while potty training). It works fairly well for me.

‘For a farmer in Illinois,’ Trenberth says, ‘any indications about what to expect could turn out rather valuable.’
I’d love to see Josh’s take on ‘American Gothic’. Add Trenberth, and see where the farmer is sticking his pitchfork…. 😉

May I suggest that they re-run their models with the code that implements the assumed effects of CO2 and its related postive feedback inactive. I’ll bet they would then come a lot closer to matching the real masured data.

Dr Norman Page says:
July 11, 2013 at 7:51 am
“…which is now busy suggesting various epicycle like theories…”
That really is THE analogy. Epicycles. Plus ca change…

Pat Frank says:
July 11, 2013 at 10:27 am
“It’s impossible to test models against any conceivable observable. It wouldn’t matter whether the climate was still warming, or not. Climate models would not and could not provide an explanation. They could do only what they have been used for up til now: provide a pseudo-scientific convenience for a political agenda.”
A thorough search of all articles, posts, or comments by Alarmist climate scientists or their supporters will not yield one hit on a substantive use of the word ‘explanation’. The reason is that scientific explanation absolutely requires well-confirmed physical hypotheses, aka physical laws, and Alarmists have none beyond Arrhenius’ original work. Alarmists depend entirely on computer models or time series analysis of questionable data.
It is not possible to engage an Alarmist in discussion of scientific explanation or the larger context that is scientific method. Why? In some cases the answer is ignorance of scientific method. In other cases the answer is an unwillingness to face the challenge of scientific method.
There is no scientific prediction without use of relevant physical laws. A scientific prediction is a demonstration from the relevant set of physical laws that a particular event will occur at a particular time in the future.

lt seems that they are slowly waking up to the fact.
That they is going to be little risk of runaway warming while the Polar jet stream remains in its current waving pattern.

The notion of “settled science” is so comforting to political types: You don’t have to ask questions, examine evidence or think. Just get right on to the fun part – pushing everyone around.

While the TSI trends were still rising well up until 2000s (in fact the turning point of a 4 decades trend since 1964 solar minima to downward TSI trend slope is March 2006 when using Solanki TSI reconstruction data) if they did the modeling in 2005 they likely haven’t had idea about the forthcoming rapid solar activity trends decline which can be now seen both with sunspot number and TSI.
One likely can hardly imagine they coud know it then and incorporate it in their models, especially when we consider the alarmists usually have not much clue about the solar activity variability climate influence, and quite often they even believe the solar activity didn’t rise since 1960s (-which is patently false: for example the 1964-1994 TSI trend using Solanki TSI reconstruction data is +0.146 W/m^2 per decade and the 1964-2002 TSI trend is still + 0.046 W/m^2 per decade – while, moreover, the TSI series comparison shows the satelite TSI series, especially the ACRIM -well agreeing with SORCE-TIM, would likely give even slightly steeper TSI trend slopes), and they sometimes don’t include the solar forcing in their considerations at all.
Now they wonder why the surface temperature anomalies don’t rise with the rising CO2 content in the atmosphere, are baffled with this “mystery” (and their “global warming cargo cult” is apparently still expecting the cargo arrival: ”The dramatic warming predicted after 2008 has yet to arrive.”) and even the more than decade long warming stall should ring the bell and rise a Kremlin size red flag they don’t much care and instead are not much reluctant produce various more or less absurd explanations why it is so while still keeping their petty CO2 hypothesis up – except go back and reconsider the solar activity variability influence.
It’s funny. But the reason for their failure is not just the declining solar activity at rates now comparable to the rates leading to Dalton minimum (and the now significant downward slope TSI trends they rarely consider and never incorporate in their models), it is also the fact that ocean in fact never can be significantly heated by a GHE (even if the GHE would be enhanced by the rising CO2 concentration in the air). That’s because water is relatively extremely opaque to mid-IR spectras at which the atmosphere radiates, so the mid-IR cannot significantly penetrate the ocean and heat it anywhere under like tenth of milimeter ocean surface skin (where almost only what the mid-IR backradiation enhances there is the water evaporation taking considerable latent heat with, transporting it then up to the atmosphere). This results in ocean loosing heat now considerably faster than the solar radiation (the solar spectra unlike the mid-IR spectra penetrate the ocean well, million times better than mid-IR spectra) replenishes it throughout the epipelagic zone and while the ocean’s immense heat content upwelling (warmer water relatively rapidly upwells vertically due to its lower density and has of course no need of ocean currents to transport it on the surface) still more or less offsets the decline in the solar heating of the ocean surface layer, it will not take long to the point when the ocean surface temperature anomaly starts to decline significantly and with it inevitably also the surface air temperature anomaly. This result could be now deemed inevitable, because further significant decline in solar activity is now sure at least for the rest of the current solar cycle, which means until 2020s and highly likely for whole the current Hale solar cycle SC24-25, which means until 2030s. By then the surface temperature anomalies decline would be well in the realm of statisticaly significant decline, while the CO2 content in the atmosphere will be still very significantly rising and so the resulting very significant CO2/surface temperature anomaly anticorrelation will eventually end the CAGW hype as one the biggest scientific blunders in the history.

Rod Everson says: July 11, 2013 at 7:32 am “From the paper: “Another challenge stems from the fact that each model has its own equilibrium state — the climate that it generates naturally if left on its own. By plugging in actual values for the ocean and atmosphere, researchers pull the model away from its natural state. When the model starts to run forward in time, it immediately begins to drift back to its preferred climate, which can introduce additional complications.”
It (the model) begins to drift back to its preferred climate? Does that mean what it sounds like it means? Because it sure sounds like it means that regardless of the initial inputs, the model is going to end up “drifting” to a preordained (“preferred”) climate prediction. Preferred by the modeler, no doubt.
–This comment from Rod gets to what I have tried to express in a comment in another WUWT post I think yesterday about modeling.
You either get a runaway model, or one that does not run away.
we have been told that there are tipping points and that the climate will run away to Armageddon. This is because as far as we know up to this point in history, there is some overall governor function operating.
The fact that we are here across time incalculable indicates that either this atmosphere is incredibly lucky for us, or there is some ultimate governing parameter that keeps various influences from running a huge positive feedback loop to oblivion.
I think models thus have to begin with the concept that behavior will be in some range. Then, proceed to add pieces of variability within that overall behavior.
For the AGW Cult, the cause has been to show the opposite: that we have been fortunate ever since – I don’t know – either the dawn of the planet, the dawn of man, or the end of the most recent genuine ice age – but our good fortune has run out, and we are about to see the runaway climate behavior.
You can walk a tight rope or balance beam for a while, but you eventually fall off. AGW says the hospitable climate has been a tightrope walk but we are abt to suffer the inevitable loss of balance, as swaying one direction wildly to catch balance throws us wildly in the other, to the eventual fall.

” laments the dismal failure of climate models to predict climate a mere 5 years into the future, much less a century from now.”
Aren’t they ONLY really lamenting the ability of climate models to make near term forecasts?

I look forward to Bob Tisdale’s excoriation of (my bold):

Although the atmosphere largely controls day-to-day weather, the slow-moving oceans hold so much more energy and heat that they dominate how the climate changes from year to year. Researchers suspect that much of this variability is tied to widespread cycles, such as the El Niño warming and La Niña cooling system in the eastern tropical Pacific.

I have no idea why anyone is getting excited about this paper. It’s claiming that decadal forecasts don’t work. Really? Not much of a shock. It says nothing about longer term forecasting. The underlying assumption here is that the IPCC modelling is still solid.

Pauline Kael, New Yorker Magazine film critic, once supposedly said she didn’t understand how Nixon won the election, since she didn’t know a single person who voted for him.
“The failure of these models is a mystery. I don’t know a single colleague who disbelieves them.”

DirkH says: “…Maybe warmism has served its purpose and the powers that be are preparing to use a different tool in the future.”
Jawohl.

I wonder where we would be if climate science HADN’T been derailed for 30+ years.

Wait a dog-gone minute! Isn’t he science settled?

“Kevin Trenberth, a climate scientist at the National Center for Atmospheric Research in Boulder, Colorado, says that it could be a decade or more before this research really begins to pay off in terms of predictive power,….

Within the last 2 weeks the WMO announced that 10 years was good enough to see changes but others say that the 15+ years of temperature standstill is not long enough – because a COUPLE of the climate models predicted projected it. THIS IS A FARCE.

Latitude says:
July 11, 2013 at 7:47 am
no…..the computer game does what it was programmed to do
Anyone who plays a computer game or two knows that there are still bugs and exploits in it, almost every game suffers from this, and that it needs regular updates to adress those bugs and exploits.
Just the suggestion that these (climate modelling) programs can’t be wrong …. unless you want to cheat at the game you are playing and start using those exploits and bug to obtain the upper hand in that game.

jorgekafkazar says:
July 11, 2013 at 8:58 am
Models are either stochastic or determinate.
=========
Deterministic chaotic system are effectively stochastic because they require infinite computational precision. Any round off and the results diverge from reality in a completely random fashion.
Which is what the climate models are showing us. Run the same model twice without any change in the forcings and it gives you a different answer. Run the model a billion time and it will give you a billion different answers, for the exact same combination of forcings.
How then can climate modellers turn around an say that doubling of CO2 will cause X degrees of warming, when their own models tell them this is a lie. The models tell them and us that doubling of CO2 may cause X degrees of warming, or it may cause Y degrees, or it may cause Z degrees.
The models do not say that (X + Y + Z) / 3 is the right answer. That is the model builders saying that. The modes say that X or Y or Z are ALL the right answer. Think about this for a minute. The models are not saying that the answer is X or Y or Z. The models are saying that X or Y or Z are all correct.
The reason we have such difficulty with this is that most people perceive the future as some place we are traveling to. Quantum mechanics tells us something quite different . There are an infinite number of futures, all or them perfectly valid under the laws of physics, and X or Y or Z exist in different futures, but they are all perfectly valid physically.
The climate models are simply confirming something physics has recognized for many years. We will arrive at one of these futures, where X or Y or Z (or some other answer) will be true, but which one is for all intents and purposes a throw of the dice, beyond our ability to calculate in our wildest creams.

”The dramatic warming predicted after 2008 has yet to arrive.”

But in 2007 the Met Office “predicted” that 50% of the decade from 2009 would be warmer than 1998.

Science – 10 August 2007 – Doug M. Smith et. al.
Abstract
Previous climate model projections of climate change accounted for external forcing from natural and anthropogenic sources but did not attempt to predict internally generated natural variability. We present a new modeling system that predicts both internal variability and externally forced changes and hence forecasts surface temperature with substantially improved skill throughout a decade, both globally and in many regions. Our system predicts that internal variability will partially offset the anthropogenic global warming signal for the next few years. However, climate will continue to warm, with at least half of the years after 2009 predicted to exceed the warmest year currently on record.
http://www.sciencemag.org/content/317/5839/796.abstract
http://www.sciencemag.org/content/317/5839/796/F4.medium.gif

Who said climate scientists don’t do predictions?

“Dr Doug Smith
Doug leads the decadal climate prediction research and development at the Met Office Hadley Centre.”……
http://www.metoffice.gov.uk/research/people/doug-smith

With five coin tosses you can get a flawed result compared to the average you expect. Over time the results converge with the average. Not much surprise the same should hold true for climate models, with weather representing coin flips, but this should not be confused with the averaging process on weather and interannual variability regarding centennial models. Fluctuations even out over the long-term.

Within the last 2 weeks the WMO announced that 10 years was good enough to see changes

It’s a pity that some incautious commentary can lead to misconceptions like this. WMO announced that 10 years is the absolute minimum to get a climate state, not a trend. They compared consecutive 10-year blocks, so their minimum period to detect a change in climate is actually 20 years – a comparison of 2 averaged data points. To assess if there is a trend would require at least 3 consecutive decadal averages – 30 years. This is, coincidentally, the classic climate period as defined by the WMO.
It may be that some people come away from this article believing the Nature article canned centennial-scale climate models, which is not the case.

“Kevin Trenberth, a climate scientist at the National Center for Atmospheric Research in Boulder, Colorado, says that it could be a decade or more before this research really begins to pay off in terms of predictive power, and even then climate scientists will be limited in what they can say about the future.”
Interesting tacit admission that current models have no skill.
If one reads TFA, one notes that it only addresses the effort to predict short term climate, less than a decade. Here the models disagree with the long term climate models and actually have some skill, although they are still too warm.
What Trenberth is asserting is that the long term models have skill because they worked great to predict the temperature rise in the 80s and 90s (bearing in mind that they were built in order to do so). So he claims that the long term models are still skillful, but only in the longer terms, so that nature itself is “incorrect” and so are the short term models, it being only an accident that either one is lower than the long term climate predictions.
He could be correct, but he isn’t correct in asserting the model skill yet, because in predictive modeling the proof of any model isn’t in its ability to predict the training set, it is its ability to predict a trial set independent of the training set and more to the point, to successfully predict new data that is in neither training or trial sets, as this is where the money lives. This is, by the way, not an idle observation as I am a friggin’ professional expert in predictive modeling on my second company in the field.
A number of things speak to a probable lack of skill. One of them was mentioned in the article — even to predict the warming in the training set, the different models explained it with different physical mechanisms. The physics itself of the warming differed, just where one would have expected it to be the same. Also, the models failed (and continue to fail) to predict or explain important details in the observed climate system that one would expect them to get right. But still, Trenberth is right, in a decade or two or ten, the Earth could start to follow the trajectory that the current crop of GCMs sorta, mostly, sometimes, on average, perhaps suggest. (Yet another problem is that the GCMs individually and collectively produce a mass of predictive spaghetti that isn’t even consistent run to run within a single model, and that nature has been evolving on the outer envelope of the range of those model results, which is the way most of us would reject the null hypothesis that “this model is correct”, not assert that nature happens to be following a highly improbable trajectory.)
In the meantime, the article carefully fails to point this out. But that doesn’t matter — the fact that they are publishing it at all suggests that the light is slowly dawning in even the minds of the editors of Nature.
rgb

It may be that some people come away from this article believing the Nature article canned centennial-scale climate models, which is not the case.
Sure the the models diverge from reality in 5 or 10 years, but, really, they are accurate in 100!!
Besides what RGB pointed out, there are numerous quotes in the article by climate scientists admitting the models are crap and they have no clue.
It is a miracle it made it into print at all, let alone in Nature.

barry says:
July 12, 2013 at 3:54 am
With five coin tosses you can get a flawed result compared to the average you expect. Over time the results converge with the average. Not much surprise the same should hold true for climate models,
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no. this is not true. Climate does not converge to an average, except in infinite time. The reasons are well established. the law of large numbers only holds if the data has a constant mean and deviation. which is true for a coin toss, but certainly not true for climate.
chaotic data by its nature does not converge to the average because it has many averages, one for every attractor. Because the attractors operate at different time scales the average changes as the scale changes. Only at infinity is does the average converge.
Thus, because climate is the average of chaos, like a coin toss if will eventually converge on the average, but unlike a coin toss this will not happen on 100 years of 1000 years. Rather the models will converge at infinity.

Chaos tells us the Trenberth was mostly right. the climate models may eventually track reality. but to do so in 80 years will simply be accidental, because the further you forecast into the future the more likely an unexpected attractor will throw your careful calculations out the windows.
Now folks will say these events are rate, but the reply is you are talking about predicting climate 80-90 years in the future. these rare, unexpected attractors become more and more likely the further into the future you try and predict.
It is like a coin toss where at some point in time the coin will develop a 3rd, 4th and 5th side. But you don’t know when. And you are then asked to predict the percentage of heads that will be thrown 90 years from now.

It’s 10 years till models can be reality-tested, and always will be.