Tisdale on model initialization in wake of the leaked IPCC draft

So, in `layman’s terms’, the modelas are crap?
Is that the gist of this post.
And given that the whole argument seems to be about 10ths of a celsius degree, even if they are just a bit crap, that makes the models well nigh useless. Yeah?
God help us.

Absolutely right. Not much left to say after that.
Of course it will still leave the upward multicentennial trend from LIA to date but it is hard to attribute that to human emissions.
Furthermore, adjustment for the ENSO multidecadal signal should make it easier to link variations in the background multicentennial temperature trend to multicentennial variations in solar activity.
It is the net balance between solar and oceanic influences over centuries that dictates the shifting of the permanent climate zones to give us what we perceive as climate change.

The eternal modus operandi of prognosticators: seize on a selected chunk of a complex curve and use linear extrapolation to concoct a scarey scenario. Claim special competence in preventing same, demand profligate funding to achieve that.
You think the world’s fools would have gotten weary of being fleeced by the same old scam. But I guess cutting governments in on the action has given it new life.

John Marshall says:
November 15, 2011 at 1:37 am
I have said this before and I repeat, even though nobody listens (sarc), throw these models away they are lying.
When the IPCC state that the multidecadal variations not being replicated in the models make laymen wary I weep. Does this problem not make scientists wary?
Obviously not since they are wedded to the AGW theory.
———————-
It does not make scientists weep, at least not those who understand what is being said.
The multidecadal osillations do not exhibit a trend, they oscillate. Some are periodic, some, like ENSO, not so much, but they are all oscillations (as far as we know). That is why it is OK to not attempt to model them – over a long enough time, they even out.
Take a look at Figure 1. See how the hindcast does not get the peak at around 1940, but it does get the trend all the way back to 1910 (and look elsewhere you will see the trend captured even further back).
There are many variabilities, but the trend emerges from them and all the evidence points that it is going in one direction.

John B says:
Take a look at Figure 1. See how the hindcast does not get the peak at around 1940, but it does get the trend all the way back to 1910 (and look elsewhere you will see the trend captured even further back).

Take a look again, and note how the models follow the temperatures quite closely in 1975-2000. Obviously, since the natural variability due to oscillations was in an upwards trend from the seventies and until the 1998 El Niño, a model that didn’t include the multidecadal oscillations should trend significantly lower than the actual temperatures in the 1975-2000 period.

So, essentially, they stated that there are no signals of climate change in natural climate, which would indicate that they don’t think natural climate ever change, which of course it never does in neither their bong smoked statistic nor their bubble bong models.

A little bit of background explaining what is meant by “initialised” would be helpful. I am struggling to understand how a model could be run without being initialised. Surely it has to have initial values. Does it mean that these initial values are not as observed in the temperature record? It’s not very clear.

Vince;
Not just temperature; there are a myriad of parameters and measures. The IPCC explicitly states that real world measurements at any point in time are not used to initialize the models, though I don’t have the link to hand. The “initialization” is made up out of whole cloth, just like the rest of the models.

Brian H says:
November 15, 2011 at 4:06 am
John B, et al;
The model runs are not “initialized” on real world conditions at all. They’re just tweaked to see what effect fiddling the forcings has on their simplified assumptions. It’s not for nothing that the IPCC says in the fine print that they create ‘scenarios’, not projections. Even though they then go on to treat them as projections.
————————
The IPCC publishes projections based on scenarios. e.g. if CO2 emissions level off (scenario), we would see something like this (projection).

This is not knew news, here’s Kevin Trenberth in his Nature Blog June 4 2007:
“In fact there are no predictions by IPCC at all. And there never have been. The IPCC instead proffers “what if” projections of future climate that correspond to certain emissions scenarios. There are a number of assumptions that go into these emissions scenarios. They are intended to cover a range of possible self consistent “story lines” that then provide decision makers with information about which paths might be more desirable. But they do not consider many things like the recovery of the ozone layer, for instance, or observed trends in forcing agents. There is no estimate, even probabilistically, as to the likelihood of any emissions scenario and no best guess.
Even if there were, the projections are based on model results that provide differences of the future climate relative to that today. None of the models used by IPCC are initialized to the observed state and none of the climate states in the models correspond even remotely to the current observed climate. In particular, the state of the oceans, sea ice, and soil moisture has no relationship to the observed state at any recent time in any of the IPCC models. There is neither an El Niño sequence nor any Pacific Decadal Oscillation that replicates the recent past; yet these are critical modes of variability that affect Pacific rim countries and beyond. The Atlantic Multidecadal Oscillation, that may depend on the thermohaline circulation and thus ocean currents in the Atlantic, is not set up to match today’s state, but it is a critical component of the Atlantic hurricanes and it undoubtedly affects forecasts for the next decade from Brazil to Europe. Moreover, the starting climate state in several of the models may depart significantly from the real climate owing to model errors. I postulate that regional climate change is impossible to deal with properly unless the models are initialized.”
John B my understanding is that the models can only hindcast the climate if sulphates are fed into them. In fact Trenberth himself says that el Nino and the PDO are critical modes of variability that affec the PAC rim countries. How does that square with them evening out over a decade?

Yes, they should be initialized with a natural variability component.
Just call it a temporary ocean circulation energy transfer (additional absorbed for periods and then additional energy released in other periods).
What they will find, however, is that their greenhouse forcing formulae do not work. The GHG impact is much lower in that scenario – less than half in fact.
So, I’m sure some of the climate modelers have played around with some cycles (regular or not) but they soon abandon the effort because then the rest of their math / the GHG forced climate model does not work.

M.A.Vukcevic says:
November 15, 2011 at 5:10 am
——————
I think the AMO and the ENSO are the most important cycles. There are a few others that could be used. But not everyone agrees that the AMO could be like a “forcing” – operating independently and causing its own climate variability.
If some want to use the ocean in general rather than these specific components, then it doesn’t matter and they still end up with a climate model that does not work.

Will somebody please explain to this retired engineer why a linear extrapolation of a curve based on ill defined chaotic sources (especially out to a hundred years) should have any predictive value? It seems to me to be a naive and extremely unscientific approach.

Latitude says:
November 15, 2011 at 4:50 am
,,,
And I say that “climate change signals” are way too small to be modeled…
,,,
Which makes climate models fun games……but worth less than the paper they are printed on
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That doesn’t follow. As an analogy, we can model the tides pretty accurately, but if you stand on a beach and watch the waves crashing in, you might be tempted to say “the tide signal is too small to be modelled”. So it is with climate. And the analogy goes further: we can’t model the details of the beach, the turbulence in the waves, the wind on a particular day, etc., but we can still produce tide tables. The waves may be hugely important if you are swimming on that beach, but they do not affect the longer term trend of the tide.

Solomon Green says:
November 15, 2011 at 5:34 am
Comparing the Mauna Loa CO2 chart from 1975 to the present day it appears that the only
“known physics and various forcings” required to replicate the gradient in the IPCC AR4 sea temperature anomalies model is CO2.
—————-
But we don’t only look at 1975 to the present day. Even Bob’s post goes back to 1910 and, short term variations aside, the models look pretty good. And if CO2 is the major forcing that determines how well they depict reality, that should be telling us something about the reality of the effect of CO2.
Unless, of course, all them lib’rul scientists is lyin’ 🙂

The real problem with the GCMs is that they don’t “predict” the past record, they can’t explain the present, and they generally aren’t very good at extrapolating into the future.
Ultimately, they are nonlinear curve fitting routines, with parametric components in them that can match any curve you like for at least some small chunk of it, especially when that curve is predominantly monotonic.
This is the fundamental problem with the whole debate. We have at least moderately accurate/believable temperature data from e.g. ice cores and other proxies that extends back over hundreds of thousands to millions of years. This record clearly indicates that we are in a five-million year long “ice age” interrupted by interglacials that seem to be order of or less than ten thousand years long, the Holocene being one of the longest, warmest interglacials in the last million years.
We don’t know why the world was warmer 5 million years ago — MUCH warmer than it is today, in all probability. We don’t know why it started to cool. We don’t know why it cooled to the point where extensive glaciation became the rule rather than the exception, with CO_2 levels that dropped to “dangerously low”, almost too low to support atmospheric plant life at the worst/coldest parts of it. We don’t know why it periodically emerges from glaciation for a few thousand years of warmth. We don’t know why it stops and returns to being cold again. Within the interglacials and/or glacial periods, we don’t know why the temperatures vary as they do, up and down by several degrees C on a timescale of millennia.
What we do know is that the best predictor of temperature variation on a timescale of centuries is the state not of the atmosphere but of the Sun, in particular the magnetic state of the sun. The evidence for this is, IMO, overwhelming. I don’t particularly care if the physics of this isn’t well understood — that’s a challenge, not a problem with the conclusion. The analysis of the data itself permits no other conclusion to be made. Sure, other factors (Milankovitch cycles, orbital eccentricity changes in response to orbital resonances, axial precession) seem to come into play with the longer time scales but THEY aren’t predictive either.
I am unaware of any model that can predict the the PAST, and this is the biggest problem of all. AGW is predicated on the assumption that we know what the temperature “should” be by some means other than numerology and reading tea leaves. And we don’t. It’s a non-Markovian problem laced with chaotic dynamics on an entire spectrum of timescales from seconds to epochs. Most of the local (decadal) dynamics is determined by a mix of the solar cycle, various effectively chaotic limit cycles (e.g. the PDO or AO) on TOP of the strong correlation with magnetic state of the sun, with additional near-random modulation by aerosols and greenhouse gases and cloud cover and with various unknown positive and negative feedbacks.
The problem, in other words, is “difficult”. It is complex, in the precise sense of the term. Locally, one can ALWAYS fit a segment of the temperature curve over decades to centuries as long as it has a monotonic trend. In the case of the 20th century, there are at least two completely distinct fits that can be made to work “well enough” given average monotonic warming. One is “CO_2 is dominant, previous thermal history and solar state and so on perturbations”. One fits the general upward trend to the general upward trend of the CO_2, then finds parameters to scale the correlations between solar state and temperture so that they match the perturbations.
The other is the opposite — explain all or nearly all of the temperature trend on the basis of solar state and dynamical history, and treat the CO_2 forcing as a small component that contributes to a general monotonic trend that would be there anyway even if there was no anthropogenic CO_2 at all. After all, only somebody very, very stupid would think that the mean temperature would be CONSTANT in the absence of humans. The entire climactic record stands ready to refute any such silliness. Nearly all of that record consists of century-long stretches of monotonic warming and cooling, with occasional abrupt changes bespeaking the existence of multiple poincare attractors in the general phase space and chaotic transitions between them.
Both of these can work, but the fundamental problem with the former is that it DOES NOT WORK outside of the 20th century. It is utterly incapable of explaining not JUST the MWP and LIA, but all of the OTHER significant variations in average global temperature visible in the long term proxy based temperature reconstructions. It will not work if indeed global temperatures drop — quite possibly drop precipitously — over the next thirty years as the sun’s state returns to levels not seen since the 1800s if not the 1600s.
One simple fact ignored by the AGW crowd is this. The last time the sun was as active as it was in the 20th century was 9000 years ago, at the very start of the holocene. Indeed, that earlier burst of solar activity (a double maximum that spanned some 300 years with an interval in between peaks) may have been the event that really gave the Holocene a robust start and finally ended the previous glacial period after the Younger Dryas. More or less monotonic warming over the 20th century has to be interpreted in light of that fact — the assumption of “everything BUT CO_2 levels is either the same or unimportant in determining climate, so CO_2 is the explanation” is simply not justified when something else is so spectacularly not the same as a 9000-year grand maximum in the sun across the very interval where the greatest warming was observed.
So, requiring GCMs to fit all of the data is good, but it isn’t enough. Not only all of the 20th century data, but ALL of the data. Until they can fit the data over the last 2000 years (say) or the last 10,000 years, their models are pointless, the moral equivalent of saying “look, a monotonic trend, I can fit that” with any function that (for some range of parameters) exhibits a monotonic trend. They have to be able to predict the UPS and the DOWNS, the long term variations. And the only way one can possibly do this is by including the sun — not just insolation but its actual state — as one of the fit parameters.
Once this is done — and we can, any of us, perform such a fit in our own minds, just from looking at a graph — the entire argument inverts. Suddenly, because solar state is the BEST predictor, the ONLY predictor capable of getting the right gross features of the T(t) curve, everything ELSE becomes the perturbations, the moderators of a general trend slaved to the sun. Suddenly the quality (e.g. R) of the curves goes way up. Suddenly CO_2 is a modulator, sure, but a relatively unimportant one, tenths of a degree C and part of that moderated by negative feedback from clouds, almost lost in the chaotic noise.
rgb
(Could somebody in Big Oil now send me a check, please? I keep hearing about how anybody who is a “denier” is in the pay of Big Oil, but I can never seem to find BO and send them a bill…)

OK, scratch that, I think I get it.

Bob Tisdale says:
November 15, 2011 at 7:01 am
John B says: “No, they haven’t done that at all. The models do not work by latching on to trends. They work by simulating the effects of known physics and various forcings on a simplified, gridded model of the atmosphere and oceans. If it happens to generate something close to linear, so be it, but they do not in any way assume a linear trend.”
John B, where did I write that the models “assume a linear trend”? Are you twisting what I wrote? Read what I wrote again.
You continued, “The hindcast shows that the models replicate past climate pretty well over scales of decades…”
The data illustrated in Animation 1 very clearly contradicts this statement. You are wasting your time…and the time of those who have come to discuss this.
————–
Bob, you said “latched on to a trend”, as if that is how the models work. You then go on to linearly extrapolate short periods of the model projections, as if that has some meaning.
Figure 1, the one that shows the largest portion of data, is the one that shows most clearly how well the models have worked. Your animation, extrapolating linear trends to arbitrary parts of the data, is at best misleading.

“What variables should be used in a model that replicates the multidecadal variability of the 20th Century or more centuries back?”
i) The level of solar activity. Though there needs to be more knowledge as to which components of such variability have most impact on the size and intensity of the polar vortices. It is that which controls the behaviour of the mobile polar highs described by Marcel Leroux and thus ultimately gives the sun power over items ii) to iv) below.
ii) The Pacific Multidecadal Oscillation (not PDO which is merely a derivative of ENSO data). Unfortunately we are not yet aware of the reason for the 50 to 60 year cycling as regards that phenomenon but the current position within the cycle would be highly relevant for prediction purposes.
iii) The size, intensity and latitudinal positions of the main permanent climate zones because they control the rate of energy flow from surface to stratosphere which results in net warming or net cooling at any given time.
iv) Global cloudiness and albedo because they indicate how much solar energy is actually gettng into the oceans to fuel the climate system.
Anything else would be subsumed within those parameters.
Needless to say the current models are not well designed in any of those areas.

Bob:
You are a WONDER.
However, I must point out that THE KING HAS NO NEW CLOTHES!
The “sea surface temperatures” are based, prior to the 80’s or 90’s or even the ARGO BOUYS, on fundementally a FICTION.
Ships logs? Guys throwing BUCKETS over the side? Calibration, consistency, QUALITY ASSURANCE? Absolutely lacking. Those data have been manipulated to show WHAT THEY WANTED. I think they are completely BOGUS.
I think others should QUESTION THE SOURCE OF THIS HIGHLY PROCESSED DATA and not accept it at face value.
Max

Yet another brilliant article by Bob Tisdale. Thanks, Mr. Tisdale.
The big lessons are clear to the many who made comments above. The modelers put all their eggs in the CO2 basket. CO2 concentration in the atmosphere increases linearly, at least given their relatively simple minded assumptions. So, the warming had to go up linearly as in the 1975 to 2000 period. In other words, they treated CO2 and its effects on radiation from the sun as the only natural processes that required modeling. Now they are being forced to admit that other natural processes must be treated as important in their own right. The sum total of all those natural processes make up most of what is called natural variability. The natural processes must be understood in their own right as physical theory (physics) has always done. Climate science must investigate those natural processes and create physical hypotheses that describe the natural regularities found in them. Once this project is well under way, climate science will be on its way to becoming a genuine physical science.
Isn’t it amazing that Trenberth can show that he understands the problems with the models yet continue to act as an attack dog for climate science?

If my memory does not betray me, I recall Climate Audit had a post on something similar showing models complinace with temps record. And that Weaver’s model was only working with increasing temps while diverging otherwise…

If you want to move the world you need a long, strong plank, a fulcrum, and a high place to stand before you jump. Actual measurements from the 20th Century sure seem a might more sturdy than guesstimates. At least you get the last hundred years right if nothing else succeeds. What the hay, we ought to give it a try; I’m sure the Chinese will lend us a few more $trillions$ to reprogram their new superdupper computers at 40% interest compounded hourly. It’s only money, right? And we are at war with nature, the biggest, baddest, meanest SOB on the planet, so what-the-hay mate let’s do it! Oh yes, nearly forgot, (SarcOff)
PS: What are we putting in the water? Everyone seems to be going crazy.

I agree with Bob, John B, why don’t you let people who want to discuss this discuss it, and just go away? It isn’t helpful either to say that skeptics are led by ideology. We are led by facts.
I started being interested in this long before I heard of Gore, and I bet before he heard of global warming. In 1972 my teachers told me that pollution might cause an ice age. By 1980 the New York Times was talking about global warming. I wanted to know what had happened to the ice age that had the same cause. So I have been following this ever since. The day that I see proof that AGW will cause a catastrophe is the day I believe it. So far no such proof exists.

Similar to but slightly different in thrust is Pielke, Sr.’s latest post of the tremendous waste of money and resources in propping up the model memes. http://pielkeclimatesci.wordpress.com/2011/11/15/the-huge-waste-of-research-money-in-providing-multi-decadal-climate-projections-for-the-new-ipcc-report/

Including the multidecadal variation of the observed temperatures in the models, even if the cause is not known, would be a valid change to the models and improve projections significantly. Ignoring it degrades the accuracy of the temperature projections, but accurate projections are not the purpose of the models. The models serve the purpose for which they were written.
I suspect the modelers began with the assumption that without increasing CO2 concentrations, temperatures would be stable, and then built the model to replicate the short term trend in the temperature record. In an email from EPA some years ago, the responder indicated that, indeed, without increasing CO2, they believed temperatures would be stable. He also included a list of all the catastrophes that would occur if nothing is done. There were no positive outcomes, of course.

Jim,
A better way of putting it: the net effect of an individual oscillation “evens out” to zero over a long enough timescale.
John

ax Hugoson says:
November 15, 2011 at 7:38 am
…The “sea surface temperatures” are based, prior to the 80′s or 90′s or even the ARGO BOUYS, on
fundementally a FICTION.
Ships logs? Guys throwing BUCKETS over the side? Calibration, consistency, QUALITY ASSURANCE? Absolutely lacking. Those data have been manipulated to show WHAT THEY WANTED. I think they are completely BOGUS.
I think others should QUESTION THE SOURCE OF THIS HIGHLY PROCESSED DATA and not accept it at face value.
__________________________________
I read here at WUWT that someone who had done this type of measurement at sea is going back and getting the actual records to look at. He had asked for help but I do not have the pointer bookmarked.
Perhaps someone else does. (He noted that the data was actually taken in a “rigorous manner” at least by UK seamen.)

Gail Combs says:
November 15, 2011 at 9:38 am
John B says:
November 15, 2011 at 7:58 am
….. No, I did not contradict myself. Here is my point:
The models do not include mulitdecadal oscillations. They do not need to in order to model long term trends. Your Figure 1 shows this. Your Animation 1 is cherry picking, presumably aimed at showing otherwise
_______________________________
So what you are saying is the model long term trends, which are always shown as a straight line headed off the paper, are correct and the earth is going to become VERY VERY hot??
You are also saying that any influence from “natural variability” is minor and should be ignored???
What is your basis for such believe.
————————–
Pretty much, with a few provisos…
Model long term trends are only shown as straight lines by the likes of those who want to discredit them, but they do indeed show the Earth becoming hot (whether it is “VERY VERY hot” depends on how hot you like things). How hot depends mainly on future CO2 emissions.
It is not that “natural variability” is small, rather that it does not show a trend over the timescales we are interested in (decades to centuries). AMO, PDO, ENSO all have an ‘O’ because they are oscillations. And there are no natural variabilities that can plausibly explain the trends in observations. For example, GCRs: even if it could be shown that GCRs help clouds form, there has been no trend in GCRs that would explain post-industrial temperature trends. And so on.
And the basis for my belief? Well, it’s not a belief, it is an acceptance of the science. The physics says CO2+feedbacks will cause warming, observations and models confirm it. Science has looked for (and in detail at) alternative explanations, but not of them stack up. Yes, the science could be wrong… and you could have a winning lottery ticket in your hand. I don’t think either is a very safe bet.

Climate models should not exist.
Period.
Observe nature.
Period.

If the climate models are so good, have been tested to destruction and incorporate everything that is relevant and material, then it must’ve occurred to the modellers to perform runs removing one factor one at a time, i.e. does the model show skill if volcanic aerosols are removed, if variations in solar TSI are removed, solar magnetic flux, manmade aerosols, UV/EUV, oceanic cycles, cloud cover, atmospheric water vapour, etc. If manmade CO2 is dominant, then there should still be a moderate-to-high degree of skill displayed.
We’re often told that only through including man’s CO2 emissions are we able to recreate 20th century temperature trends. OK then, in papers that show 20th century temp recreations by one or numerous models when CO2 is removed as a forcing, are we informed as to what forcings/factors remain and their assigned weightings? If so, are all suspected factors incorporated and, by adjusting weightings, is it impossible to get closer to measured temp trends than the CO2-driven model versions?
I won’t be stunned if there is a model version that does a much better job of anything else published by limiting CO2 to a very minor role and focusing on ALL solar activity, global cloud cover, volcanic aerosols and oceanic cycles. I WILL be stunned, though, if this model version was stuck with and its results and methodology ever published.
Bob, excellent work as ever.

@Robert Knights
http://www.woodfortrees.org/plot/hadsst2gl/from:2001

Here are a couple or simple models that show the relative magnitudes of the cyclic and quadratic components.(result of an exponential rise in CO2 conc)
Basic method is to fit a straight line to dT/dt to account for CO2 and try to characterise the majority of the residual with cosines.
Even one ~58y cosine plus a quadratic is better than just about any super computer model.
CO2 emmissions:
http://tinypic.com/r/r76l4h/5
trivial model
http://tinypic.com/r/2nrn24m/5
better model (also shows Scaffeta)
http://tinypic.com/r/2dw924i/5

>>
The models do not include mulitdecadal oscillations. They do not need to in order to model long term trends.
>>
No, but if you use “the last 50y of 20th c” as your reference period and ignore the cyclic components you are going to confound GH warming and natural cycles and head off in the wrong direction after y2k.

>> The physics says CO2+feedbacks will cause warming
No the feedbacks are pure speculation , not science.

Dr. Syun Akasofu is making a similar point here I think:
http://wattsupwiththat.com/2009/03/20/dr-syun-akasofu-on-ipccs-forecast-accuracy/

Brian H says:
November 15, 2011 at 4:06 am
John B, et al;
The model runs are not “initialized” on real world conditions at all. They’re just tweaked to see what effect fiddling the forcings has on their simplified assumptions. It’s not for nothing that the IPCC says in the fine print that they create ‘scenarios’, not projections. Even though they then go on to treat them as projections.

Given what I understand to be the chaotic nature of our climate, a small variation in initial conditions should mean greatly different results from model runs. Unless the models don’t work the way our climate actually works.
Regardless, I’m not sure our data are good enough to give an accurate set of initial conditions.
I’d also like to see some test runs of various models using a multiple standard sets of initial data. Create perhaps a dozen different sets of initial data and run each model with each set. It would be interesting to see the results of each.

“Leaked IPCC Draft: Climate Change Signals Expected To Be Relatively Small Over Coming 20-30 Years”
“That’s IPCC speak, and it really doesn’t say they’re expecting global surface temperatures to flatten for the next two or three decades.”

One must ask, well, then, what does “climate change signals” mean, exactly? The only signals it can mean are warming, if it means less signals, and it clearly does, then it means less warming. The only possibly effect CO2 can cause, according to physics, is increased downward longwave radiation. Over the oceans (71% of the earth), this results in a slightly greater amount of evaporation, almost instantly countered by that creating clouds and shade, reducing the incoming shortwave radiation and thus reducing the longwave radiation upward which could be trapped and radiated back down. Only over land does CO2 cause warming, and that only when it does not cause too much evaporation which would produce the above effect. Result, CO2 causes some warming only over some of the land, but it is warming. Thus, if we have less “climate change signals”, we must have (slightly) less warming.
I think this is what the IPCC is saying, basically the same thing you are saying here, that the ocean driven variability means that the warming over the next several decades will be quite small. Of course, the IPCC will then claim that it will start to go up again, and will go up even faster, thus saying that their prediction of doom and gloom was right all along. What you are showing is that, if it goes up at the rate it has been with the natural variability included (which the IPCC has now admitted needs to be included), it will not go up faster in the future, and will slow down one or more times in the future again, and thus 100 years from now, it will be warmer, but not much warmer, not nearly as warm as the IPCC has been claiming all along (not warm enough to wreck the world economy eliminating CO2 over).
The simple fact however is that these models have no predictive value. There is no understanding of what causes the ocean circulations that they are now admitting cause “natural variability” or how and why they add or subtract from atmospheric heat, and there is no understanding of solar dynamics enough to be able to tell us why the sun sometimes goes into long periods of quietness which can cause a little ice age or even perhaps a full blown ice age. As such, any statement that their models can predict anything over 100 years is wrong (which the IPCC makes but Bob Tisdale does not).
Simply put, the models are not based on reality. The reason for that is seen in this quote As Upton Sinclair once said: “It is difficult to get a man to understand something when his job depends on not understanding it.”. basically, the stated job of the IPCC is to “prove” that CO2 causes enough warming that they, the IPCC, needs to take over to prevent this disaster. because of this, they investigate CO2, they do not investigate things like ENSO or other ocean effects, or solar variability and it’s effect on climate. In short, they do not investigate natural climate change causes at all, because they do not wish to. As such, they simply do not understand the climate, and thus cannot tell us what it will do in any future.
The only forecast I saw that may explain some of what will happen in the future was one that correctly hindcasted the Dalton and Maunder minimums, and forecast the current quiet sun ( unlike NASA, which got it completely wrong), and forecast that the next solar cycle (or 2) will be quieter yet. This will of course be moderated by the oceans, which will slow everything down, and make it harder to tell if the sun is doing it since what the sun does will not immediately show down here due to the stored heat of the oceans. I also expect, however, that upper latitudes will most definatly notice it, as the cold from the poles invades their land, especially well away from the oceans moderating influence. I expect increasingly cold winters in places like upper North America and upper Europe and Asia. The IPCC will, of course, try either (or both!) to explain this away as merely local conditions, or somehow blame it on CO2 (and there are plenty of people dumb enough to believe them).
I just had a thought… (it won’t happen again, I promise!):
Let us say that the earth has natural temperature regulators, that tend to keep the temperature relatively stable, despite what the sun does.
The sun was [quiet] several hundred years ago (Maunder and Dalton minimums).
The earth then went into La Nina mode to try and capture more sunlight in the oceans to keep things warm.
This means more trade winds.
In those days, ships used sails.
The discovery and colonization of the new world, and the age of sail and discovery, may have been aided and abetted by the quiet sun and the earths La Nina adjustment to it.
The only way we will know if this may be true is to wait a decade or two and see if the sun goes quiet as predicted, and then see if the earth goes into La Nina mode to catch more rays.

steven mosher says: “Bob its not curve fitting either.”
Sorry, I don’t think that is correct. Until models can derive ALL the fundamentals from first principals , the basic operation does come down to curve fitting. They have a good understanding of a lot of things but the really important factors like cloud formation , precipitation, ocean currents and atmospheric circulation they really have no idea whatsoever.
The bits they can’t model, they have to make up based on empirical data. They give this a fancy name like parametrisation to make it sound scientific but this is basically empirical tweaking of model INPUTS until the hindcast is reasonably close. In other words : curve fitting.
The “curves” in question are the little bits of climate they do know how to model precisely and the “parameters”, rather than pure cosines, but the process is fundamentally the same thing.
Don’t get confused by the detail, climate models are all fundamentally an excersize in curve fitting.

I know I’m a couple of days late to this, but I must say I’m disturbed by the state of global climate modeling, if the results are only discussed on a global scale.
My comments:
1) If multidecadal (20 to 50+ years) timescale variations are important to the global temperature signal, then the model should be run for a minimum of 200 to 400 years, with observed data to compare to. As John B states, multidecadal variations average out over time, so the only way to know if your model is accounting for them well enough, or if they’re averaging out, is to run it over multiple oscillations. Assuming there aren’t multi-century variations that need to be accounted for (not necessarily a good assumption), then 400 years seems to be a good minimum model run time (8 fifty year cycles).
2) How is comparing a global average temperature supposed to indicate the skill of a model?
If it’s a decent global model, then regional variations (at least dividing the globe into 16 to 64 regions or more), should all have results that are reasonable, compared to observed data. If it hasn’t enough skill to match regional temperature variations, then why should I believe its global results?
I model hydrology for a living, and it’s not enough to know that the flow at the outlet of your system compares well to observed data. If you have 4 ‘subwatersheds’ and have data for each, then you should compare your model at the outlet of each ‘subwatershed,’ as well as the combined ‘watershed’ level results. Just because the watershed-level results look OK, doesn’t mean that the model is actually representing reality very well. It’s possible you’re just getting lucky.
Global average results are a horrible comparison, if your model is designed to consider regional or local physical processes.