German Climate Adviser who says "the West's carbon quotas are used up" once co-authored a paper saying climate models are flawed and that "global warming is also overestimated by the models"

Recent studies have shown that Global Warming could increase the frequency of shcizophrenia cases. I think it’s worse than we thought.

Our carbon credits are used up based on what broken model that doesn’t represent reality? Buy your carbon credits today before the price goes down!

Obviously, he’s grown and refined his understanding of the underlying fundamental phenomena.
If he’d gone the other way, Exxon would have been blamed.

OT
For those voting for Obama`s health care, this is what you now get in the UK.
Liverpool Care Pathway: The decision to withdraw treatment from a patient is an incredibly complex one.
http://www.telegraph.co.uk/health/healthadvice/maxpemberton/6139668/Liverpool-Care-Pathway-The-decision-to-withdraw-treatment-from-a-patient-is-an-incredibly-complex-one.html

I’ve been living here in Germany for 19 years, and I know how these people tick. Don’t get me wrong, I admire them in many respects. But many of these people, except for my wife, are posessed with organising everything. I mean every damn thing under the sun.
Ordnung muss sein!
And when you get whacked-out people like Ramstorf and Prof Dr. Schrillhooter directly advising Frau Chancellor Merkel, then be worried. Be very worried!
(If I keep this up, I just might get some greenshirts busting into my house and I may be sentenced to 15 years of hard labour on a bio-food farm or windpark.

Modellers in both cases have substituted empirical work by dice throwing, scientific study by kids’ gambling. This is a study case for psychiatry.
Psychiatrists and psychologists are invited to opine!

Way last year I was also predicting that India and China would be using guilt about a ‘precious conceit of the Western elite’ to insist that the developed countries make a greater sacrifice of carbon than they would. Now, their positions have hardened into refusing to make any carbon concessions while expecting Europe and the US to do so. Frankly, I don’t think the big boys and girls in China and India believe in the paradigm of CO2=AGW anymore. Copenhagen may well be a lot of fun.
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Following up on my previous post, here is a paper by many of the same authors as the original Schellnhuber 2002 paper (although not including Schellnhuber himself) in which they demonstrate how the inclusion of volcanic forcing makes the scaling performance of the climate models considerably better (in agreeing with observations): http://arxiv.org/PS_cache/physics/pdf/0401/0401143v1.pdf
Anthony Watts says:

Joel, he’s no longer a climate scientist. When he starts making policy recommendations on how his and other countries should form policy and who should pay, he is no longer an “honest scientist” but part of the political apparatus.

So, what about people like Luboš Motl, Roy Spencer, and yourself. I hardly think you and they have shied away from telling us what you think about various policies to constrain CO2 emissions. Does that disqualify you and they as honest scientists too?

That, and as Luboš Motl points out, he’s a “hardcore nutcase”. Pretty strong words from Luboš.

Well, Luboš is hardly known as a bastion of calm and reasoned analysis. Strong words are Luboš’s bread-and-butter.

From your perspective, I assume then that following his Robin Hood rich to poor plan is A-OK with you?

Personally, I think that the issue of fairness in how the world deals with the issue of controlling CO2 emissions is a difficult one. Schellnhuber’s criterion (of allowing everyone the same allotment of emissions) seems too simplistic and rigid to me. However, at a broader level, I do think it will be necessary for those nations who have contributed the most to the current problem (through our cumulative emissions) and also have the most resources to solve it to demonstrate leadership and a willingness to help those nations who have contributed less and have fewer resources. How that will work in detail is the legitimate subject of future international negotiations.
This is a complicated issue and there are going to be differences of opinion in how to deal with it. Schellnhuber’s view is one extreme of how to handle the equity issue. I think it is fair to critique it although I think intelligent and thoughtful critiques would be best.

By the way, I can’t wait for the sort of folks who want to rob and control us to decide that CO2 is a cooling agent and that that old fart Arrhenius had it backward. After all, we don’t know for sure the sign of the water vapor feedback. If it’s constantly negative, then rising CO2 may cool us. Also, all those ice cores showing CO2 rising 800 years after temperature rising also show temperature dropping sometime later. Give me the help of the statistics experts at UDub and Penn State, and I’ll prove that CO2 cools the earth.
Yes, Eric, you are turning into a joke, too.
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kim says:

Please, get with the latest science…

I know the latest science and it doesn’t say what you seem to think it says.

After all, we don’t know for sure the sign of the water vapor feedback.

Actually, we know its sign and even have quite a good handle on its magnitude. See, here for a brief review: http://www.sciencemag.org/cgi/content/summary/sci;323/5917/1020

If it’s constantly negative, then rising CO2 may cool us.

Even if the sign of the water vapor feedback were negative (which it’s not), it would simply mean that it would reduce the amount of warming due to rising CO2. It would probably not imply that rising CO2 would cause cooling (at least if the feedback operated through the temperature). [Perhaps if it were sufficiently strong and operated through some other mechanism other than the change in temperature changing the water vapor content then it could conceivably cause cooling…but this is all very hypothetical because it is not how the water vapor feedback actually operates.]

Joel
Nice thoughtful posts. I suspect you would enjoy ‘Chill’ by Peter Taylor. My review of in an ecology magazine is here;
http://www.harmlesssky.org/
tonyb

Joel 15:18:00
I’m speaking fairly specifically of the accumulating body of evidence showing that the IPCC’s conception of the greenhouse effect of CO2 is exaggerated.
Poisonallee, I think the water vapor feedback is variable, and poisonallee, I don’t think you got the joke…..well, you did talk about ‘hypothetical’. Maybe I don’t get the joke.
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Carbon Credits are running out… OMG! What next???
First Peak Oil, now Peak Carbon Credits!?
What to do… What to do… I know – lets raise taxes so that everyone can have enough carbon credits.
(Runs shrieking into the night…)

Oops, it looks like I’ve claimed to know the latest science. Honest, I know nahzing. Nahzing much at all. ‘Ducks the squeegee’.
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TonyB: Thanks. I’ll try to have a look at “Chill” the next time I am in Barnes & Noble.

Strange.
Joel Shore seems to imagine that real greenhouses chiefly lose heat by conduction: see above post.
I would have thought any competent physicist, well in fact any schoolboy with an elementary scientific education, would know that whether they use glass or plastic, real greenhouses retain heat by blocking convective action with their transparent barrier so the warm air does not escape upwards. Losses due to conduction or radiation are insignificant by comparison.
What odd ideas some people have.
Kindest Regards.

Joel Shore (14:00:17) :
“Following up on my previous post, here is a paper by many of the same authors as the original Schellnhuber 2002 paper (although not including Schellnhuber himself) in which they demonstrate how the inclusion of volcanic forcing makes the scaling performance of the climate models considerably better (in agreeing with observations):”
Joel, as a Lukewarmer I am in agreement with much of what you say. Thanks
for the reference to this paper ( I think I linked to the original 2002 paper in a previous thread, but nevermind)
Let’s stipulate that this paper that you site is correct. Let’s stipulate that by including volcanic forcing you get a better fit? Agreed? And a better fit means “more truthful” or more skillful or more representative.
Now, I’ll ask you a question or two. They are simple questions and let’s have simple answers. yes or no.
1. Do you think it makes sense to do an ensemble average of GCMs that
include volcanic forcing with those that don’t include volcanic forcing?
2. Would you ever base policy on a study that averaged runs from GCMs
that used volcanic forcing with runs from GCMs that did not?
3. Would you reject a projection based on the average of models where only
some of the models including volcanic forcing?

Remy of GoRemy.com has a brilliant video talking about cap and trade that explains how Cap and Trade works on the tax side.

“Personally, I think that the issue of fairness in how the world deals with the issue of controlling CO2 emissions is a difficult one. ”
I don’t see any difficulty when there isn’t the slightest need to control CO2. The true difficulty is when real pollution is ignored to chase this chimera. The effect of any cap and trade legislation in the West (brilliant video by the way John B) would be to drive jobs offshore to places with far slacker clean air regulation than in developed countries.
As far as I can see, every single victory for the green industrial complex (mercury filled light bulbs which cause fits and can poison people and the environment, ethanol in cars which pushes the price of food out of the reach of poor people and creates shortages, windmills which kill birds and bats and causes sickness in people living nearby) has been an environmental disaster. Interesting, isn’t it. I think the answer is simply that the radical greens are far more interested in repressing and controlling people than in any actual effect on the environment.

Yes you are quite correct.
Dr. Latif simply voiced what has been widely known for some time: that the model forecasts are diverging from observed temperatures so fast that little credence can be given to their predictions.
He ascribes this to the effect of the reversal of the NOA. so that natural variation is overriding the effects of CO2.
Quite correctly Dr. Latif then pointed out what amounts to AGW heresy, that if natural causes such as the NOA can produce cooling at the moment then how much did they contribute to the recent warming? He also says he doesn’t know.
In short the models did not predict the current cooling trend, cannot foretell how long it will last or how deep it will be, or even, and with the advantage of hindsight, say how much of the recent warming was due to natural causes rather than CO2.
In short the models have no predictive or analylitic power, you would do as well with a set of Tarot cards.
And although this problem is becoming increasingly acknowledged among climate scientist of the AGW persuasion many console themselves with the idea that warming will return with a vengeance once the current cool phase ends.
Not so. As Dr. Pielke and others have pointed out for that to happen the oceans would have to store up increasing amounts of energy in the form of heat from the supposed imbalance between incoming and outgoing radiation produced by CO2 during this cool phase.
But they are not, rather as ARGO shows the oceans are cooling not warming so there is no heat in the pipeline to emerge when this cool phase ends.
It short it is reasonable to presume that the rise in atmospheric CO2 has had little or no effect on global temperatures nor will it do so.
Kindest Regards.

a jones:

Joel Shore seems to imagine that real greenhouses chiefly lose heat by conduction: see above post.
I would have thought any competent physicist, well in fact any schoolboy with an elementary scientific education, would know that whether they use glass or plastic, real greenhouses retain heat by blocking convective action with their transparent barrier so the warm air does not escape upwards. Losses due to conduction or radiation are insignificant by comparison.
What odd ideas some people have.

You are of course correct. And, in this case, it is not odd ideas that I have, but rather the odd way my brain communicates with my fingers. I meant “convection” and typed “conduction”. In terms of letters, I got 8 out of 10 correct…Nobody’s perfect!

Hi Joel
Good to see you over here again. You’ll be setting WUWT as your home page before you know it 🙂
You said;
“Of course, our understanding of AGW is based on a lot more than just current temperature trends. It is, for example, based on the temperature difference and estimated difference in forcings between the last glacial maximum and now. So, any new competing hypotheses will (at least eventually) also have to explain this empirical data in addition to the current temperature trends.”
I appreciate you were being simplistic, but to broaden it out you obviously know that our understanding of AGW is based on a lot of hypothetical data.
When you parse temperatures, sea level rises etc etc that go back some 150 years or more, to hundredths of a degree or mm, this must surely be in the hope (rather than certainty) that we had accurate data back then that can be parsed and sliced so minutely and therefore has some scientific validity.
Do not certain things worry you about much of this data;
* The notion that 20 stations comprise our 1850 global temperature data and they have changed in numbers and locations ever since? (don’t get me started on whether a GT has any meaning)
* That our global sea level (AArgghh!) is based on highly extrapolated (i.e. non existent) data back to 1700 that relies on three northern European tide gauges?
* That SST were measured in a very haphazard way over a tiny portion of the globes water surface and only highly specific local ones should be given any credence?
* That ice melts and re-freezes with monotonous regularity in the arctic and that current events are not out of the ordinary?
Is there not a scintilla of doubt in your mind that relying on -at best- often highly dubious if not actually meaningless information, is not a sensible way to run a railroad?
Ps That 8 out of 10 letters reference was the first time I have seen you make a joke, keep it up!
PPs Don’t tell Flanagan, but I quite like him posting here as well 🙂
Best regards
tonyb

Video posted by John B (23:18:47): “We’re going green” lyric sung while collecting hands full of dollars. So true!

TonyB: What you have identified are the kinds of issues that one deals with in science all of the time. Data is seldom available without some (often severe) data quality issues. I don’t know what to tell you except that the way one deals with it is the way that climate scientists have been dealing with it: by having different independent analyses done on the data sets, by making estimates of the errors introduced due to various known data issues, by looking at different measures of a similar thing (e.g., in addition to direct air thermometer measurements, there are ocean temperature measurements, measurements of the advance and retreat of glacials, borehole temperature measurements, and various temperature proxy measurements).
Work at the forefront of science is seldom as easy and straightforward as presented in science textbooks. This is probably one of the main reasons why scientists and “lay people” tend to reach rather different conclusions regarding the strength of the evidence in a field such as climate science where lay people are motivated to investigate the science. If other fields of science were subjected to the similar sort of study by lay people that climate science has been, I think that these people would find similar deficiencies…and they would probably be left believing hardly any of the theories of modern science. And yet, I think these theories have been very important and successful in advancing our knowledge, and the reason I think that is the case is that, while each individual piece of data or each experiment may have its problems, the whole set of data and experiments taken together generally have a high degree of redundancy that means that the overall picture that emerges is more likely to be correct than one would expect by looking at each experiment in isolation.
To be honest, I have spent almost my entire career as a computational physicist being continually surprised at how well the models that I use agree with the experimental data in spite of the fact that I can almost always identify many concerns that I have with either the data or the model (e.g., many things that the model is ignoring).

Perhaps I should explain how these GCM models are constructed.
Except on a molecular and smaller scales, which is why we can develop from first principles statistics such as Max Boltz, larger scale actual natural events are not truly random.
On these larger scales random events are essentially a mechanical artifact about which we can deduce, in the case for example of the roulette wheel, that over time equal numbers of reds and blacks will happen.
We can also observe on this larger scale that the occurence of an individual event, for example being struck by lightning, also shows true randomness. Which is not to say that if you stand where lightning tends to strike you will not be more likely to be struck.
But we cannot predict when that might happen.
Beyond that we cannot go.
We only know that large scale natural systems are not truly random so even if we were to consider the balance of the outcomes over the lifetime of the Universe itself we would be no wiser. For instance we now know that black holes obey the second law of thermodynamics, so the fact that a largish black hole might have a theoretical lifetime longer than the universe itself is irrelevant since it must disappear when the universe itself comes to an end.
In short unlike our roulette wheel the balance of the outcome, equally red or black, does not apply to large scale natural systems even over the lifetime of the universe.
As you might expect given the irreversible nature of change in the universe normally defined as the Arrow of Time.
We now call such variable natural systems chaotic to distinguish them from truly random events and outcomes. But they have a degree of randomness which defies prediction in terms of a balanced outcome over time: even to the end of time itself.
Which is why it is absurd to say that weather, which we cannot predict with any certainty, depending on where you live, for more than few days
is not the same as climate which it is averred we can forecast fifty years ahead. Really?
Well let us see how this supposed GCM prediction is done.
Given that, unlike our roulette wheel, we have no simple mechanical cause, we have to begin by trying to define the variables we think affect the climate and build up a dynamic model from that.
Since we do not know the future we can only test our model against the past, and if it does not fit we can adjust the weighting of the variables until it does.
If of course it turns out it does not predict the future we can then take the new data which show it to be wrong and amend the variables until we now get a perfect hindcast.
Does this mean our model is better than before? And will now predict the future?
No: probably not. So if it fails again we adjust it again to fit the results. Is it now better than before? Probably not.
This fallacy, known to wise gamblers, wise bankers, statisticians and the like, occurs because it is imagined that every variable has not only been accounted for but that moreover as a test if the variables are set to produce a neutral outome then there must necessarily be a balanced outcome over time.
Except in the real world the outome is not necessarily balanced over time, nor is there any reason to suppose it should be.
Yet this fallacy that the outcome must balance over time around the trend line of the model is used to suggest that whilst the model cannot predict the immediate future it can still foretell the far future.
What balderdash.
Worse in large scale GCM models if you do include more than handful of variables the model collapses into a puddle before it has got to the prediction for one year: and simply swings over and settles at on of two extreme outcomes, hellfire or absolute zero, neither of which seem likely.
To prevent the model doing this is it necessary to impose a constraint which forces the model to remain within reasonable limits, although enormities can be committed in defining what reasonable is depending on what the modeller believes might be acceptable to the client.
Whether such a constraint exists in Nature or is merely a figment of the imagination of the modeller I leave you to ponder.
But you might are to note that unlike gamblers fallacies whih tend to fall apart in practice fairly quickly climate change is a long term affair so it has taken the last decade to convincingly falsify the models.
As I said in my post above it is now apparent these models failed to predict the current cooling trend, cannot foretell how long it will last or how deep it will be and cannot even tell us how much of the recent warming was due to natural causes.
Thus in the words of Dr. Stockdale at the IPCC conference the models are biased which is damaging our forecasts. Och aye.
What he did not say was that if you test the models against the actual outcome their predictive power turns out to be no better than random. A test you can do for yourself.
Whih is why I said you would do as well with a set of Tarot cards, or perhaps you might prefer a Mystic Medium.
As for the idea espoused by Dr. Pope that in many ways we know more about the climate in 2050 than we do about next decade or two, it’s enough to make a cat laugh.
Kindest Regards.

a jones (17:34:44) :
Maybe I should once more on this board say how the GCMs are supposed to work, and how they cannot be trusted for unlimited iterations forward in time.
They make a three dimensional grid of the globe. 200*200*20km(height)
They take time steps from 20 minutes or more.
They use known/supposed solutions of equations for the box and keep boundary conditions physical.
Where equations are not available ( cloud generation, wind motion, convection, conduction, albedo, etc) they use average values.
This is about the way weather prediction works too.
Now the solution of the equations are not linear, they can be highly non linear. Average values used for unknown solutions of equations are also assuming linear behavior ( the first term in a putative perturbation series expansion). That is the reason why weather prediction cannot go further than a few days, and sometimes a few hours, if the non linear chaotic reality kicks in.
It is inevitable that GCMs for climate will fail after a certain number of time steps.
The fact that hindcasting may be working is just a multidimensional demonstration of what von Neuman said: “give me four parameters and I can fit any function. With five I can fit an elephant”. The number of parameters in these GCMs is n, where n is a large number ( as my math professor used to say). I suspect that albedo is the most crucial one.

anna v (and a jones): Using your logic, one could conclude that we would be unable to predict that the climate will be warmer here in Rochester in July than it will be in January due to the seasonal forcing.
The actual fact is that the climate modelers understand chaos..and in fact can easily demonstrate it in the climate models by making a perturbation on the initial conditions. And, while two different runs with slightly different initial conditions will diverge in their details (e.g., the “jiggles” up and down in temperature), they will both show approximately the same response to a forcing such as that due to increased GHGs provided the run is over a long enough period that the response to the forcing dominates over the climate noise.
Admittedly, non-linear dynamical systems can be full of surprises and there is always the possibility that driving such a system beyond a certain point will send it into a very different state … However, such potential surprises seem to me to be arguments for more, rather than less, prudence in how hard we drive the system.

The fact that hindcasting may be working is just a multidimensional demonstration of what von Neuman said: “give me four parameters and I can fit any function. With five I can fit an elephant”. The number of parameters in these GCMs is n, where n is a large number ( as my math professor used to say).

While it is true that one can usually fit a curve with a well-chosen model containing only a few parameters, one can also devise a system with millions of parameters where you could not fit some simple piece of data. The distinction is what sort of model it is and what things the parameters control. To fit the global temperature record, the simplest thing to perform such a fit would simply be an empirical model that writes temperature T as a function of time t (e.g., a polynomial in t).
However, this is not in any way shape or form the sort of models that climate models are and the parameters in climate models are not designed in such a way that it would be easy to reproduce a given global temp vs time curve. Rather, the parameters tend to control microphysics such as the nucleation of clouds and other such stuff. You could probably tinker with these parameters all day and never fit the global temperature record as long as the history of the climate forcings vs time are not approximately correct. (And, in fact, I know of no skeptic who has claimed that he/she can take a GCM and play with the parameters to fit the global temperature record while including only natural forcings and not including any anthropogenic forcings.) Furthermore, there is a lot more data that a climate model can be compared to than simply the global temperature vs time. The parameters in the climate models are generally constrained by either getting the physics on smaller scales approximately correct or reproducing current climatology.
The one exception to the above is that the aerosol forcing is not currently well-constrained empirically, so it is possible to get reasonable fits to the global temperature record with a range of possible efficacies for the aerosol forcing coupled with a range of possible climate sensitivities in the model. This is a true limitation of the use of the 20th century temperature record to determine the climate sensitivity…and is one of the reasons why the range of estimates for the climate sensitivity remains rather broad.

Joel Shore (14:27:50) :
And, in fact, I know of no skeptic who has claimed that he/she can take a GCM and play with the parameters to fit the global temperature record while including only natural forcings and not including any anthropogenic forcings.
Albedo,varied between its error band can do the job nicely, for one other parameter than aerosols.
Well, I could take your word that GCM modellers understand chaotic dynamics, but, from the last IPCC report it is clear that they do not understand statistical propagation of errors in their models, ( chapter 8) so you will allow me to be doubtful as far as their expertise in chaos is concerned.
IPCC AR$WG! chapter 8
8.1.2.2 Metrics of Model Reliability
…..
The above studies show promise
that quantitative metrics for the likelihood of model projections
may be developed, but because the development of robust
metrics is still at an early stage, the model evaluations presented
in this chapter are based primarily on experience and physical
reasoning, as has been the norm in the past.
This means in simple language that for all I know a true error propagation could show the model outputs anywhere, from zero anomaly to humongous, and the outputs have no predictive value at all.
When using a simple model that contains albedo and one varies albedo within its errors , for example in http://junkscience.com/Greenhouse/Earth_temp.html
varying the albedo from 0.31 to 0.30
the temperature goes from 15C to 16.1C
and do we really know the albedo so well? measurements say NO.
http://bbso.njit.edu/Research/EarthShine/literature/Palle_etal_2006_EOS.pdf

Joel,
http://rankexploits.com/musings/2008/effect-of-including-volcanic-eruptions-on-hindcastforecast-of-gmst/

Joel Shore (10:24:50) :
Albedo vs. time is not an adjustable parameter in the models. It is a quantity that comes out of the models. And, even if there is uncertainty in the precise absolute value of the albedo, what matters is how it changes in runs with increasing GHGs vs control runs.
Thanks for the clarification. Seems the GCMs are not doing that well on that anyway:
http://www3.interscience.wiley.com/journal/118587917/abstract?CRETRY=1&SRETRY=0
A comprehensive comparison of characteristics of the planetary albedo (α) in data from two satellite measurement campaigns (ERBE and CERES) and output from 20 GCMs, simulating the 20th-century climate, is performed. Discrepancies between different data sets and models exist; thus, it is clear that conclusions about absolute magnitude and accuracy of albedo should be drawn with caution. Yet, given the present calibrations, a bias is found between different estimates of α, with modelled global albedos being systematically higher than the observed. The difference between models and observations is larger for the more recent CERES measurements than the older ERBE measurements. Through the study of seasonal anomalies and space and time distribution of correaltions between models and observations, specific regions with large discrepancies can be identified. It is hereby found that models appear to over-estimate the albedo during boreal summer and under-estimate it during austral summer. Furthermore, the seasonal variations of albedo in subtropical areas dominated by low stratiform clouds, as well as in dry desert regions in the subtropics, seem to be poorly simulated by the models.
Not surprising since clouds are badly simulated by the models too.( at least in the IPCC report figures).