Global warming inside the Dyson Sphere

"I'm not an expert on any of these things. Much of what I say should be taken with a grain of salt."

So said Freeman Dyson, Professor Emeritus at Princeton's Institute for Advanced Physics, all-round brilliant scientist, and self-professed global warming "heretic," during a round of questions and answers following his talk Tuesday night at Furman University in Greenville, S.C. "I am not speaking to you as a scientist, but as a story-teller ... of science fiction."

So why then, I asked, should we pay attention to what you have to say on climate change, considering that those who are experts in the field -- James Hansen, to pick one mentioned in last weekend's New York Times Magazine profile on you -- tend to disagree?

"Because," he replied, "I'm speaking from a broader picture."

And that, in a nutshell, was Dyson's argument against worrying too much about climate change. It's not that the Jim Hansens and Al Gores are fundamentally wrong -- he admits that they could be right and he could very easily be wrong. It's just that professional climatologists have narrower points of view. Dyson says his understanding of biology and ecology, in addition to physics, leads him to different conclusions about the threat of rising carbon dioxide levels than someone like Hansen, who, while knowledgeable about paleoclimatic trends and computer modeling, doesn't grasp the big picture.

If this sounds reasonable, you can get a good idea of what Dyson told the audience at the 2009 Charles H. Townes Lecture in Faith and Reason, an annual event made possible by the namesake's Templeton prize in 2005, by reading Dyson's essay in The Edge. He lifted long sections from it Tuesday night.

Incidentally, those skeptical of anything associated with Templeton prizes -- Dyson won it in 2000 -- needn't worry. Dyson began his talk by warning that he :won't have anything to say about faith and reason. I'm only here to talk about reason."

Which is pretty much what he did. Contrary to some suspicions floated by commenters to an earlier post here, Dyson is still sharp as a tack. He clearly remains a substantial thinker, and from what I can tell a witty fellow with whom sharing a beer would be a privilege. But there's a problem. While he first applied his considerable brain to the relationship between CO2 and the planet's climate more than 30 years ago, it was clear from some of his criticisms of the prevailing consensus ("dogma" he calls it), that he just hasn't kept up. He even admitted as much in another response to a question from the audience.

"I really haven't been busy with climate change all my life," he said, explaining that he abandoned climate change as a field of inquiry that had become too political for his tastes 20 years ago, and only just recently returned to it.

At this point, it's easy to see why Dyson isn't claiming to have all the answers. For example, he claims that too few climatologists, including Hansen, fail to take into account the possible effects of the current lull in sunspots and the associated dip in the solar magnetic field. He hints that it may possible that we are repeating the "Maunder Minumum" of the 1600s that coincided (but not necessarily causes) the Little Age in Europe.

Just as his description of Hansen's field of expertise as too narrow will strike anyone familiar with Hansen's wide-ranging recent papers as wide of the mark, so here is Dyson's failure to keep up with recent developments glaringly obvious. For example, Hansen and a couple of colleagues at NASA's Goddard Institute for Space Studies recently wrote about the subject in some detail:

Solar irradiance: the solar irradiance remains low ... at the lowest level in the period since satellite measurements began in the late 1970s, and the time since the prior solar minimum is already 12 years, two years longer than the prior two cycles. This has led some people to speculate that we may be entering a "Maunder Minimum" situation, a period of reduced irradiance that could last for decades. Most solar physicists expect the irradiance to begin to pick up in the next several months - there are indications, from the polarity of the few recent sunspots, that the new cycle is beginning. However, let's assume that the solar irradiance does not recover: in that case, the negative forcing, relative to the mean solar irradiance is equivalent to seven years of CO2 increase at current growth rates. So do not look for a new "Little Ice Age" in any case!

Dyson also dismisses climate modeling as a field, repeating this passage for his Edge essay:

It is much easier for a scientist to sit in an air-conditioned building and run computer models, than to put on winter clothes and measure what is really happening outside in the swamps and the clouds. That is why the climate model experts end up believing their own models.

As has been pointed out by others, this is rather insulting. There are plenty of climatologists, including modelers, who have suited up in parkas. They have confidence in their models because the model are quite good as backcasting historical temperature trends. Such language seems a bit incongruous coming from an otherwise genteel and polite fellow. I expect he would be happy to apologize when word gets back to him just how out of touch such statements are.

Then there's the peculiar faith that Dyson places in technology. In an approach reminiscent of Ray Kurzweil's approaching singularity of artificial intelligence, he sings the praises of genetic engineering. Even if carbon dioxide levels do induce difficult levels of planetary warming, he says, it shouldn't take more than 20 years to design new crops that fix most of the carbon into new topsoil. ("Carbon eating trees" is the phrase used elsewhere.) According to his calculations, three millimeters of the stuff should suffice to sequester enough carbon to offset the warming.

Maybe he'll be proven prescient. But it's a gamble, one that seems at odds with Dyson's primarily humanistic philosophy. If the gamble fails, it will be the poor who suffer the most from climate change, after all.

Still, it is hard not to like the professor. While he perhaps relishes his role as heretic a bit too much, he does understand the need for skepticism and perspective -- the perspective of someone who's lived long enough to see the world change in remarkable ways thanks to technology, often for the better.

"The prevailing dogmas may be right," he concedes. "But they deserve to be challenged."

That they do. My only quibble is they are best challenged by those with a good grasp of the latest findings.


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I would take issue with the conflation of "dogma" and "finding", to which you too easily acquiesced in the closing passage of this post. I don't see climatologists as any more dogmatic with respect to their findings than biologists are with respect to theirs. There's a close kinship with the rhetoric of ID-creationists that I think Dyson would find embarrassing if he could overcome his intellectual hubris for just a moment. While occasionally backing off from this picture, Dyson frequently employs language indicating he sees climate science as driven in large part by an anti-humanist eco-fundamentalism. His use of the word "dogma" for the scientific findings of climate scientists is emblematic of this perspective, and is, as I said, reminiscent of the creationist characterization of evolutionary biology as ideologically rather than evidentially based.

I'd be a lot more sanguine about the ability of "biology and ecology" to mitigate to rising CO2 levels if we weren't simultaneously wrecking ecosystems in an excitingly diverse range of ways already.

I think Dyson calls it dogma and imputes religious thought to the consensus view because it's the worst insult he can think of for scientists. In reality, what he's complaining about is the political/social movement that has adopted (he might say hijacked) global warming science.

To that point, I don't recall ever reading anything from him conceding that Al Gore might be right about anything; he collegiality extends to scientists, not politicians. The source of Dyson's disappointment with Hansen seems to be Hansen's embrace of social activism on the subject.

N.B. If the defense of climatology rested on "backcasting", climatology would have some serious problems. Backcasting proves nothing - you can do better than that.

By Duncan (not Dunc) (not verified) on 02 Apr 2009 #permalink

Dunc, you're absolutely right. All the pro-climate-destruction people like to wax poetic about the transcendant robustness of nature, even as they advocate destroying it. I mean, sure, nature will find a way. It recovered from the Permian-Triassic event admirably.

It just takes, uh, a couple hundred million years to do so. And it also takes, uh, the end of the extinction event. When should we schedule that end for?

As a long time friend of Freeman's, who does not agree with him on the many of his views, I think he is right to use the dogma term for some of the climate modeling community. Some modelers do not state clearly the uncertainties in their models. Like Freeman I am not up to date with the state of climate modeling but only a few years ago it was clear that there was not a good understanding of physics of clouds related to climate - measurements were significantly different than cloud model estimates. Yet some in the modeling community ignored that fact in their public pronouncements of what their model predicted. The same could be said about the state of the coupling of ocean and atmospheric models. Mr jrshipley comments on the rhetoric of creationists. Unfortunately there is a similarity between the rhetoric of the Global Warming advocates and the anti-vaccinationists. They are not open to rational debate about what we know, what we think and what we believe about global warming.

Okay I know I'm going to get flamed for this but here it goes anyway. As someone who works regularly with numerical modelers doing fluid flow simulations I can tell you that these models are MUCH simpler in terms of the number and overall understandings of the input parameters than the GCMâs. In addition we are able to do extremely good history matches to a good quality historical data set that contains a lot less assumptions than are in the data set for climate. Yet these models have a horrible time predicting future trends. In fact, most modelers will admit âWhat answer do you want and Iâll get it for youâ. Models are non-unique solutions and even history matched models are only a single solution not âTHEâ solution. There are significantly more input parameters for GCMâs and most of the input parameters have a much larger range of possible values and certain input parameters are so poorly understood that it is not known if they will cause positive or negative forcing. Therefore the answers these models output are next to meaningless for predicting future trends.
Think of it this way
Unique solution
X + 55 = 100
X = 45
Non unique solution 2 variables
X + Y = 100
Range of X, 5 to 15
Range of Y, 80 to 95
Fairly small amount of potential solutions fit data ranges

Non unique solution 5 variables

X + Y + Z + R + T = 100
Range of X, 5 to 10 well understood variable
Range of Y, 20 to 35 well understood variable
Range of Z, 20 to 60 moderately understood variable
Range of R, -30 to + 30 poorly understood variable
Solve for T
The number of valid solutions for T just became enormous
This is where the GCMâs run into trouble as Water Vapour and clouds are variables that are poorly understood with regards to their forcing potential and whether they are positive or negative forcings with HUGE uncertainties. Therefore most GCMâs ignore them. So how can you trust the output ?

By Phyllograptus (not verified) on 02 Apr 2009 #permalink

I think he is right to use the dogma term for some of the climate modeling community. Some modelers do not state clearly the uncertainties in their models.

Cool. Surely you can provide some example - names and cites?

Like Freeman I am not up to date with the state of climate modeling but only a few years ago it was clear that there was not a good understanding of physics of clouds related to climate

Where did you learn this? From the modelers who don't state clearly the uncertainties of their models, perhaps?

So how can you trust the output ?

Due to the fact that models have made predictions that have later been shown to be true? That when there's been significant departure between observations and models - such as the infamous "satellite observations disprove global warming!" snafu a decade ago - the observational data turns out to be wrong?

When critics of climate models preface their criticisms by saying something like "I am not up to date with the state of climate modeling but ..." they ought to stop just before they get to "but."

Look at the ACTUAL data and interpretations the IPCC turns out, not the summary for policy makers. The science is good, if somewhat biased in that it is reporting the answer the overall IPCC wants to hear. The re-interpreted bits that get put into the Summary for Policy Makers are often horrible, if not completely wrong.

Check out.
In section
1.2 Climate Models as Tools for Scientific and Policy
It states

âIn practice, computing limitations do not allow models of high
enough resolution to resolve important sub-grid processes.
Phenomena occurring over length scales smaller than those of
the most highly resolved GCMs, and that cannot be ignored,
include cloud formation and cloud interactions with atmospheric
radiation; sulphate aerosol dynamics and light scattering;
ocean plumes and boundary layers;â¦â

âMismatches between the scale of these processes and computationally
â realizable grid scales in global models is a
well-known problem of Earth system science.â

âTo account for sub-grid climate processes, the approach has
been to âparametrizeâ â that is, to use empirical or
semi-empirical relations to approximate net (or area-averaged)
effects at the resolution scale of the modelâ

In section 2.2.1 Clouds it states
âHowever, most key cloud processes occur at
scales well below the resolution of global models, so that
simple area-average representations (âparametrizationsâ) of
cloud processes are required, thereby introducing the potential
for substantial error in the simulated cloud changesâ

In section 4.1.5 Calculating Radiative Forcing From
Look specifically at Figure 8. The amount of forcing of clouds and water vapour are not considered, neither is the level of understanding of these critical parameters listed.

So what the IPCC is saying is that they are ignoring water vapour and clouds because it is too difficult to deal with and they interpret that by upscaling the model the errors average out and are not an issue therefore a more simple model can predict changes accurately even though they know a more complex model cannot. This is the major fault that a lot of scientists, including myself, have with models, and it is a problem that almost all numerical models have.
However, most models are commisioned by and then presented to groups that understand the limitations and are equipped to evaluate and interpret the results based on that knowledge. The IPCCâs results get presented as gospel and trotted out to the general public at large, which has zero understanding of the inputs, methodology or limitations. Any wonder why lots of scientists have problems believing the media representations of the issues.

By Phyllograptus (not verified) on 02 Apr 2009 #permalink

The idea of genetically modified trees eating up huge amounts of carbon sounds a bit like something out of Kim Stanley Robinson's '40 Signs of Rain' trilogy. Unfortunately it was fiction, and the books largely sucked. So its good to see that he's using the best sources available...

If he wanted to be positive, he could have ditched the imaginary techno-fix and simply pointed out that we should stop cutting down out forests and start replanting those that we have lost. But that would be sensible, rather than dramatic.

I sense this is someone whose brilliance has been dimmed by his constant need to be a 'contrarian', no matter what the evidence. Its really rather sad.

If the defense of climatology rested on "backcasting", climatology would have some serious problems. Backcasting proves nothing - you can do better than that.

The only difference between backcasting and forecasting is the date on which the simulation is run. Since "todays date" isn't a factor in any GCM, this difference is completely irrelevant.

"This is where the GCMâs run into trouble as Water Vapour and clouds are variables that are poorly understood with regards to their forcing potential and whether they are positive or negative forcings with HUGE uncertainties. Therefore most GCMâs ignore them. So how can you trust the output ?"

Forgive me if I'm being dense but I thought these were feedbacks, not forcings. Feedback mechanisms are not fully understood although it does appear that if anything the models we're using are underestimating them.

We can't rule out with 100% certainty the possibility that a negative feedback that we don't currently know about will emerge that mitigate the forcing effect of all the C02 we're pumping out. That would be a near miraculous result however, should we wait for it?

To me that would be analogous to jumping off a building in the hope that somebody might erect a trampoline at your point of impact before you hit the ground.

Like Freeman I am not up to date with the state of climate modeling but only a few years ago it was clear that there was not a good understanding of physics of clouds related to climate

Where did you learn this? From the modelers who don't state clearly the uncertainties of their models, perhaps?

No, from a study by DOE's Atmospheric Radiation Measurement (ARM) Program. But then I assume Mr. dhogaza is well enough informed of the science to already know this.

No I will not waste any time getting you the exact reference.

Jose brought up the issue of Feedbacks and Forcings. My understanding is that yes clouds are feedback and, yes we don't understand their role well as I have said. However clouds are made up of water vapour and water vapour is both a Forcing and a Feedback. As a greenhouse gas water vapour has a much higher heat capacity than CO2 and has a higher radiative and cooling potential. Its role as a forcing can either be positive or negative and the feedback it creates can either be positive or negative. Which makes it a very dificult variable too deal with in GCM's and why the mdelors like to ignore it. However its mpact on climate is known to be enormous. So doesn;t that make the model highly suspect when they just ignore it and clouds ???

By Phyllograptus (not verified) on 03 Apr 2009 #permalink

Phyllograptus -- I think you are in danger, here, of using the same tactics that creationists use when they quote phrases out of legitimate geology papers which talk about areas with confused or troublesome radiometric dating results; i.e. taking the phrases which suggest that there is a problem, and pretending that all the paragraphs discussing how the problem is dealt with don't exist.

Looking at the link that you provide above, to the IPCC report, I do indeed find the quotes you mention. I also find, subsequent to some few of them, paragraphs like:

"All climate system models used in the SAR WGI have been
tested for their ability to reproduce key features of the existing climate, as well as historical and palaeo-climatic changes. While the validity of these models cannot be proven for future conditions, their ability to recover a variety of observed features of the atmosphere/ocean/biosphere system and observed changes during the recent past supports their use for projections of future climatic change."

In a few places, they discuss the fact that processes are not well understood, they explicitly name the uncertainties, and then they discuss how the issues are dealt with and falsifiability is ensured, and they explain why and the models still provide insight and a reliable picture of the behavior of the planet within certain parameters.

Essentially, what you are saying is that a model must accurately account for ALL processes before it can offer insight into ANY future behavior. That is not true. They certainly don't do or expect that with models of protein interactions on a cellular level, and yet, these are an integral part of bioinformatics now, because we know that we can demonstrate certain aspects of cellular behavior with good accuracy even when we don't understand or even know about all the interacting processes.

The fact that models can track real-world behavior to a given degree of accuracy means they are working models; if you are quibbling that all the peaks and troughs of a demonstrably matching trend line don't exactly match therefore the model is unreliable, you risk crawling up the bum of sophistry and losing the point.

By Luna_the_cat (not verified) on 04 Apr 2009 #permalink