Meyer’s claim is a straw man. Attribution is different form Climate Sensitivity. Estimates of CS are not derived from 20th century warming.

and paper after it, ……4423.

You say “Every time I try to express this, it sounds so ridiculous that people think I must have it wrong. But the main argument supporting a high climate sensitivity to CO2 is that scientists claim to have looked at past warming, particularly from 1950-2000, and they can’t think of any natural cause that could behind it, which leaves CO2 by process of elimination.”

I think you have it exactly right. Here’s a bit of supporting evidence for the picture you portray from a University of Washington course in Global Warming. They have a web page with links to the lecture slides here: http://www.atmos.washington.edu/2009Q4/111/Lecture_Slides.htm

This course features guest lectures from Professor Theodore L. (Tad) Anderson, a researcher in aerosols. Professor Anderson’s lecture slides are refreshingly honest about reliance upon the historical record, the uncertain role played by aerosols in climate models, the overall uncertainty surrounding climate sensitivity, and the manner in which causal attribution is claimed for CO2. In particular, see the lecture slides here: http://www.atmos.washington.edu/2009Q4/111/Lecture_Slides/111Fall09_Tad_Thurs_GW_critique_2perpage.pdf

Warren, I enjoy your blog and videos very much. I particularly like the way you differentiate between the basic science of the green house effect (which we all agree upon) and the alarmist theory of high climate sensitivity based on positive feedbacks. This is a point that needs to be emphasized in the debate that is far from over. Anyone who says this particular bit of science is ‘settled’ doesn’t know anything about it.

John M.

Here’s another line of reasoning, but not so sure how this one would go down with the layman. The trusty Stone-Weierstrass Theorem states that we can approximate any function with a finite polynomial (forgive gross abbreviation of theorem). We could “model” the past two centuries of global temperatures with a ten-term polynomial. And we’d be dead wrong in our predictions. Thus the act of modeling alone is shown to be entirely worthless. It’s the repeated experiments that make the model useful.

Not sure I could make that case to a layman, though.

Thanks, as someone who uses mathematical models, I’m extremely discouraged by what has been termed climate-gate. It only makes it more difficult for me persuade those unfamiliar with mathematical models of their necessity in a subject like biology, where it is so easy to experiment. After about my first sentence everyone looks at me crosswise thinking, “you can make a model do anything and why make a model, instead of just run the experiment anyway?”

As for the noise, that’s definitely a huge problem as well. We see all these graphs, rural temperatures, urban temperatures, adjusted temperatures, etc, and we usually see some sort of curve fit to the data. If we’re lucky we see an R^2, but what we never see is the confidence interval for the beta-value. Many people, even some scientists, don’t know what that is, or why they are needed. Basically we need a measure of your confidence in the slope generated by your regression, to tell us if it is significantly different from zero. This is often not a big deal if you come away with a high R^2 and large slope (either negative or positive). But when we see these slopes of .2 degrees per DECADE and still only an R^2 of maybe .4 (which is OK but not what I would consider high), I’d would bet that your slope is not significantly different from zero. I suppose it would be pretty easy to do this myself with various publicly available data sets, but besides you and maybe 10 other people, I’m not sure anyone would listen to me.

You say “Every time I try to express this, it sounds so ridiculous that people think I must have it wrong. But the main argument supporting a high climate sensitivity to CO2 is that scientists claim to have looked at past warming, particularly from 1950-2000, and they can’t think of any natural cause that could behind it, which leaves CO2 by process of elimination.”

I think you have it exactly right. Here’s a bit of supporting evidence for the picture you portray from a University of Washington course in Global Warming. They have a web page with links to the lecture slides here: http://www.atmos.washington.edu/2009Q4/111/Lecture_Slides.htm

This course features guest lectures from Professor Theodore L. (Tad) Anderson, a researcher in aerosols. Professor Anderson’s lecture slides are refreshingly honest about reliance upon the historical record, the uncertain role played by aerosols in climate models, the overall uncertainty surrounding climate sensitivity, and the manner in which causal attribution is claimed for CO2. In particular, see the lecture slides here: http://www.atmos.washington.edu/2009Q4/111/Lecture_Slides/111Fall09_Tad_Thurs_GW_critique_2perpage.pdf

Warren, I enjoy your blog and videos very much. I particularly like the way you differentiate between the basic science of the green house effect (upon which we all agree) and the alarmist theory of high climate sensitivity based on positive feedbacks. This is a point that needs to be emphasized in the debate that is far from over. Anyone who thinks this bit of science is ‘settled’ doesn’t know anything about it.

Excellent work!

John M.

I like your argument about models and controlling observations.

As an appendix to your argument, I think we have to prove that a real-world system is not random before we start building deterministic models. Climate history sure looks like random noise (see here for spectrum of global temperature history).

Has anyone seen a proof that the climate is NOT random? If not, then deterministic models cannot be accurate.

individual plots of raw australian data. more fraud revealed.
She deserves the Pulitzer just like Woodward and Bernstein.
Did you manage to find a synonym for the word HIDE than means anything other than HIDE- as
in ‘HIDE the decline’?

Norman Davies of propaganda
Five Rules of Propaganda:
1) endless repetition, repeating the same messages over and over with different variations

and combinations
2. Disfiguration: discrediting the opposition with slander and crude parodies
3. Unanimity: presenting your point of view as if every right headed person agrees with it
while smearing those who doubt it thanks using appeals of famous people, experts and so
called consensus; hiding/ excluding others from the underlying basis / information of your
position.
4. Transfusion: manipulating the prevailing values of the public to your own advantage
5. Simplification: reducing all facts into a comparison between ‘good and evil’ and
‘friends and enemies’

What the fellows at East Anglia and elsewhere were doing was not science.
You see- when you actually put your own eyes on the raw data.

Shall we have a look at the antarctic now?
http://icecap.us/images/uploads/antarctica_white_paper_final.pdf
Scratch the surface – global warming is a fraud to the bone.
It is Mann made.

From an 11 year old who doesn’t have a vanity blog:
http://www.youtube.com/watch?v=F_G_-SdAN04 home schooled, I’ll bet a dollar.

The UN’s argument:
http://www.youtube.com/watch?v=P_9mjBUSDng
Good reason to supervise what your children see on TV.

Other than the positive feed back issues, which are complete BS even if we assume a logarithmic response, given that we’ve had more CO2 and higher temperatures in the past, my biggest problem is how they use mathematical models.

You state: “Now, they don’t always say it this directly. What they actually say is that they ran their climate models and their climate models could not produce the warming from 1950-2000 with natural forcings alone, but could reproduce this warming with forcings from CO2.”

(I apologize in advance if this has all been said before somewhere else on this site. )

What mathematical models do is force us to be precise with our current understanding of the system (physical, biological or whatever). We then have to use a test, or an experiment in sciences where you can actually experiment, to valid the model. Or, to put it differently, prove that our current understand is correct. What has been done is to include all things we know about the climate and chosen a parameter to play with (effect of CO2) until the model fits the past data. That isn’t validating the model. That’s either creating the model in the first place, or being intentionally deceiving. Meaning, why play with CO2? I find it unlikely, basically to the point of impossibility, that the only way you can fit the data, given the likely size of this mathematical model there must be, to borrow from Aaron, 10^30 different ways to fit some 100-200 data points. Given that scientists can’t experiment on the global climate, the only way to validate the model is to wait for time to pass. The problem is that these aren’t controlled experiments that allow you to isolate the system down to a small number of factors for you to measure. This makes new data difficult to interpret as its limited by your current understanding, same as the old data. Meaning that you don’t know if deviations in cloud formations (for example) from your model predictions are actually due to a change in [CO2] or just from cows farting or again 10^30 other things, remember you can’t control anything. This is in contrast to biology for example, where you’re able to control for and measure the increase in one gene’s expression given the presence of a certain treatment. Thus, its effectively impossible to validate a model for the global climate, at least until we have far more knowledge of the system.

This doesn’t mean climate models are worthless. It just means we should see them similar to financial models. They might provide a rough guide, but its pretty much guaranteed that you haven’t accounted for everything in the system. Heck that’s true for biology as well, only to a lesser degree.

And Hunter, more people might believe you, or even just listen to you, if stopped cursing at them. That’s a pretty clear sign that you either don’t know what you’re talking about or have some sort of agenda that you’re personally attached to.