Climatologists are no Einsteins, says his successor (Star Ledger)They mention that when Einstein was still around, Dyson was hired by the Institute for Advanced Studies in Princeton after the search for the planet's most brilliant physicist. He has done quite some work to justify these labels although I wouldn't say that it has put him at the #1 spot. He's still one of the giants of the old times who keep on walking on the globe.
Beginning in the GWPF (Benny Peiser et al.)
At any rate, he is saying some things that should be important for everyone, especially every layman, who wants to understand the climate debate. The climatologists don't really understand the climate; they just blindly follow computer models that are full of ad hoc fudge factors to account for clouds and other aspects.
Freeman Dyson also mentioned that increased CO2 is probably making the environment better and he estimated that about 15% of the crop yields are due to the extra CO2 added by the human activity. I agree with this estimate wholeheartedly. The CO2 is elevated by a factor of K = 396/280 = 1.41 and my approximate rule is that the crop yields scale like the square root of K which is currently between 1.15 and 1.20.
Dyson – and the sensible journalist – also mention that the journalists are doing a lousy job, probably because they're lazy and just love to copy things from others. The hatred against the "dissenters" is similar to what it used to be in the Soviet Union; I must confirm that.
The article also contains some older videos in which Dyson was interviewed.
This 13-year-old Gentleman, Alex, who is doing speeches has understood many things about the climate panic that many adults have not. He got an iPad as a reward for that. ;-)
But let me return to the "no Einsteins" claim. It's a very important one because the climate scientists were sometimes painted nearly as the ultimate superior discipline above all of sciences. In reality, the climate scientists are – and even before the climate hysteria took off were – the worst among the worst physical scientists. I am sure that everyone who has studied at a physics department with many possible subfields must know that. My conclusions primarily come from Prague but I feel more or less certain that they hold almost everywhere.
When you're a college freshman in a similar maths-and-physics department, you start to be exposed to various types of scientific results very soon. Some people find the maths too complicated and they give up. Some students survive. Those who survive pretty quickly find out whether they're better in the theory or the experimental approach to physics. Clearly, if they're into experiments, they will drift towards atomic physics, optics, vacuum physics, and perhaps condensed matter physics, aside from several disciplines.
If they feel comfortable in advanced theory, they will lean towards theoretical physics, nuclear physics, and partly theoretical condensed matter physics. But all the statements so far were "politically correct" – implicitly assuming that everyone is equally good and he only has different interests. But that ain't the case.
Some people aren't too good at anything. In Prague, it's been a pretty much official wisdom that those folks are most likely to pick atmospheric physics or geophysics and – if they care about stars – astrophysics. In some sense, these fields are conceptually stuck in the 19th century or perhaps 18th century. They're simple enough. The laymen's common sense is often enough to do them. Quantum mechanics may be viewed as the most characteristic litmus test. If a student finds it impenetrable, he or she must give up ideas about going to particle physics but also condensed matter physics, optics, and some other characteristic "20th century" disciplines.
The people who are sort of good at maths but they really find out they are slower with quantum mechanics tend to go to (general) relativistic physics which is a powerful field in Prague. To some extent, the detachment from quantum mechanics is correlated with the detachment from statistical methods in physics and from experimenter's thinking. So among the smart enough folks, the relativists who have avoided quantum mechanics from their early years are probably the "least experimentally oriented" ones.
But meteorology is the ultimate refugee camp. A stereotypical idea of the job waiting for the meteorology alumni are the "tree frogs" [a Czech synonym for "weather girls"] who forecast the weather on TV screens. Their makeup is usually more important than their knowledge and understanding and yes, meteorology also has the highest percentage of female students (not counting teaching of maths, physics, and IT) which, whether you like it or not, is also correlated with the significantly lower mathematical IQ in that subfield.
I am totally confident that every sufficiently large and representative university with a physics department could reconstruct a correlation between e.g. the grades and the specialization that the students choose that would confirm most of the general patterns above. But at many places, these things are just a taboo. This is extremely unfortunate because the public should know where the smartest people may be looked for – and atmospheric physics or climatology certainly can't be listed in the answer to this question. It's important because when such things are taboo, certain people may play games and pretend that they're something that they're not.
Dyson also touched another interesting topic, the difference between "understanding" and "sitting in front of a computer model that is assumed to understand". I have discussed this difference many times. But let me repeat that they're totally different things. While I would agree it's a waste of time – and a silly sport – to force students to do mechanical operations that may be done by a computer or learn lots of simple rules that may be summarized in a book (because the students are downgraded to a dull memory chip or a simple CPU chip), it's necessary for a student to go through all the key steps and methods at least once so that he or she knows how they work inside. Or at least they may feel confident that if they wanted to improve their understanding what's going on, they could penetrate into all the details within hours of extra study or earlier.
The climate forecasts have so large error margins that it makes no sense to pretend that you need to make a high-precision calculation. But if a high-precision calculation isn't needed, an approximate calculation is enough. And for an approximate calculation, you shouldn't need a terribly complicated algorithm that runs for a very long time. In fact, you should be able to construct a simplified picture and a calculation that may be reconstructed pretty much without a computer. In particular, if you can't derive the order-of-magnitude estimate for a quantity describing the behavior of a physical system, then you just don't understand the behavior! A computer may spit out a magic answer but you are not the computer. If you don't know what the computer is exactly doing, assuming etc., then you can't independently "endorse" the results by the computer, you can't know what they depend upon and how robust the actual outcome of the program is.
Mechanical arithmetic calculations may be boring and of course that it's not what mathematicians and physicists are supposed to be best at or do most of their time (a physicist or a mathematician is something else than an idiot savant, a simple fact that most of my close relatives are completely unaware of). On the other hand, much of the logic behind sciences and behind individual arguments in science is about solid technical thinking that may be sped up with the help of a computer but this thinking is still completely essential because science and mathematics are ultimately composed of these things! If you don't know them, you don't know science and mathematics.
An extra topic in the context of atmospheric physics is the difference between the knowledge and "character of knowledge" of meteorologists and climatologists. I would say that meteorologists are in a much better shape when it comes to their "mental training" because they deal with lots of real-world data that affect their thinking. They have some experience. In comparison, climatologists work with a much smaller amount of data – they talk about 30-year averages but our record isn't too much longer than 30 years so there are just "several numbers". The predictions only face the real-world data after many decades when the climatologist is already retired or dead and this confrontation between real-world data and scientists' opinions is what drives the "natural selection" of ideas in empirically based disciplines – and atmospheric physics disciplines are surely textbook examples of them.
The most extreme form of the intellectual degradation is the idea that the only important quantity to be predicted is the rate of [global] temperature increase (or, almost equivalently in the climate believers' opinion, the climate sensitivity). If someone believes it's the only number to be derived and one can fudge hundreds of parameters to do so, it's too bad! Clearly, such a predictive framework is totally worthless. A predictive framework must be able to predict a larger number of numbers than the number of parameters that have to be inserted. Needless to say, my description of the situation of the "hardcore alarmed climatology" was way too kind because they don't even verify the single only "calculated" result – the climate sensitivity. When it differs by a factor of 3 from the observations, they just don't care. So they don't predict anything. They have absolutely no data – no "threats" for their pet ideas – that could direct their construction and improvement of the theories.