Friday, June 24, 2022

A subversive physicist and climate change


Freeman Dyson was a famous English physicist born in 1923 and died two years ago at the age of 96. He studied at Cambridge University where at the end of the war he graduated in Mathematics.

His friend, the neurologist and writer, Oliver Sacks said of Dyson: "Freeman's favorite word about science and creativity is the word subversive. He feels it's not important to be orthodox, but subversive, and that's what he's done all his life." life."

He moved to the United States, establishing himself at Birmingham University first, then at Cornell University, and finally in 1953 at the Institute for Advanced Study in Princeton, New Jersey, where he would remain for 60 years.

Dyson was one of the main personalities in physics worldwide, he participated in several projects of great importance such as the Orion Project and the Triga nuclear reactor. He also worked on a variety of topics in mathematics, including topology, analysis, number theory, and random matrices. His contributions to physics are innumerable. I invite the audience to consult his copious trajectory in the encyclopedias available on the Internet. In this video we will specifically refer to his views on climate change.

First part

In one of his many lectures, Freeman Dyson recounted that in the 1960s, fluid dynamics expert Syukuro Manabe was running global climate models on

the supercomputer at the Geophysical Fluid Dynamics Laboratory at Princeton.

The models were executed with carbon dioxide with variable amounts in the atmosphere and in the output of the computer the models of it showed an increase in the average temperature of the soil, something that 50 years later was renamed global warming.

Munabe told everyone not to believe the numbers. But the politicians in Washington believed. They wanted numbers, he gave them numbers, so naturally they believed in numbers.

It was not unreasonable for politicians to believe in Manabe's figures. Politics and science are two very different games. In science, you're not supposed to believe the numbers until you've carefully examined the evidence. If the evidence is doubtful, a good scientist will suspend judgment. In politics, you're supposed to make decisions. Politicians are used to making decisions based on shaky evidence. They have to vote yes or no, and they usually don't have the luxury of suspending judgment. Manabe's numbers were clear and simple. They said that if carbon dioxide increases, the planet will heat up. So it was reasonable for the politicians to believe them. Believing for a politician is not the same as believing for a scientist.

Manabe's numbers were unreliable because his computer models did not actually simulate the physical processes taking place in the atmosphere. He over and over again said that his purpose when he ran computer models was not to predict the weather but to understand it. But no one listened. Everyone thought he was predicting the weather, everyone believed his numbers. And here we are still.

Second part

Earth's biosphere contains four carbon reservoirs: the atmosphere, the ocean, vegetation, and soil. All four reservoirs are of comparable size, so the problem of climate is inevitably mixed with problems of vegetation and soil. The intertwining between the four reservoirs is so strong that it makes no sense to consider only the atmosphere and the ocean. Computer models of the atmosphere and ocean, even if they can be made reliable, give at best a partial view of the problem. The large effects of vegetation and soil cannot be calculated, but must be observed and measured.

The way the problem is usually presented to the public is seriously misleading. The public is led to believe that the carbon dioxide problem has only one cause and one consequence. The only cause is the burning of (fossil) fuels, the only consequence is global warming. In reality there are multiple causes and multiple consequences. Atmospheric carbon dioxide driving global warming is just the dog's tail. The dog wagging its tail is global ecology: forests, farms, and swamps, as well as power plants, factories, and automobiles. And the increase in carbon dioxide in the atmosphere has other consequences that may be at least as important as global warming: increasing crop yields and forest growth, for example. To handle the problem intelligently, we need to understand all the causes and all the consequences.

Third part

To sum up what we've learned since then, Dyson gives us some good news and some bad news. The good news is that a lot of effort is finally being put into local observations. Local observations are laborious and time-consuming, but they are essential if we are ever to have an accurate picture of the climate. The bad news is that the climate models that so much effort goes into are not reliable because they still use simulation factors instead of physics to represent important things like evaporation and convection, clouds and rain.

In addition to the general prevalence of misleading factors, the latest and largest climate models have other flaws that make them unreliable. With one exception, they do not predict the existence of El Niño. Since El Niño is an important feature of the observed climate, any model that cannot predict it is clearly flawed. Bad news doesn't mean climate models are useless. They are, as Manabe said thirty years ago, essential tools to understand the climate. They are not yet adequate tools to predict the weather. If we patiently persevere in looking at the real world and improving the models, the time will come when we will be able to both understand and predict. Until then, we must continue to warn politicians and the public: do not believe the numbers just because they come out of a supercomputer.

Freeman J. Dyson, Emeritus Professor of Physics at the Institute for Advanced Study in Princeton, New Jersey, received the 1999 APS Joseph Burton Forum Award and is the author of several books on science for the general public. The most recent is The Sun, the Genome and the Internet, which will be published this year.

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