"CO2 is Making The World Greener w/ Freeman Dyson" Topic

I thought it was perhaps time for not only something different to help take minds off the anxiety of world events but to also focus on some potentially good news.

Carbon Dioxide is Making The World Greener (w/ Freeman Dyson, Institute for Advanced Studies)

Computer models do a good job of helping us understand climate but they do a very poor job of predicting it.

That is according to physicist Freeman Dyson of the Institute of Advanced Study in Princeton, New Jersey.

Dyson says, "As measured from space, the whole earth is growing greener as a result of carbon dioxide, so it's increasing agricultural yields, it's increasing the forests and it's increasing growth in the biological world, and that's more important and more certain than the effects on climate."

He acknowledges that human activity has an effect on climate but claims it is much less than is claimed. He stresses the non-climate benefits of carbon are overwhelmingly favourable.

Simon Fraser University's Centre for Dialogue presents Conversations That Matter. Join veteran Broadcaster Stuart McNish each week for an important and engaging Conversation about the issues shaping our future.

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This is old, and already dealt with.

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Martin, you didn't even watch this.

Observational and experimental data are the foundation of science. For a scientific statement or conclusion to be valid, it must agree with the data. If a statement/conclusion is contradicted by the data, that statement/conclusion is false.

Dyson's statement about a NON-CLIMATE effect of C02, specifically that increased atmospheric concentrations of C02 lead to increased greening, is supported by the data. Regarding the CLIMATE effects of C02, however, Dyson makes crucial statements that are contradicted by the data and thus are false. Some examples are his statements about why scientists focus on carbon dioxide but not water vapor when discussing greenhouse effects, and his statements about the effect of the solar cycle on global temperature increases.

Let's discuss the non-climate effect first: increased greening.

a) INCREASED CO2 LEADS TO INCREASED GREENING
That increased greening is taking place is not a new, contrarian or controversial conclusion in the scientific community. That increasing C02 levels result in increased greening is clearly supported by the data. For example:

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b) CO2 CLIMATE EFFECTS ARE OBSERVED IN ACTUAL CURRENT DATA
However the climate effects of increasing CO2 levels are also definitely happening. These effects are not merely the uncertain predictions of models, as Dyson implies on several occasions in the interview. No, these climate effects are showing up now in actual observed data.

For example, that sea levels are rising is not some model prediction but actual observational data:

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(click "Global" to see a global view, not just the United States. Click the individual arrows and then click "Linear Trend" to see a plot of sea level data at that location)

The deleterious effects of rising sea levels are affecting nations right now (e.g., land loss in coastal areas and low-lying islands).

Not only does Dyson ignore data, as in the examples above, he also makes statements that are directly contradicted by the data, as discussed in c) and d) below.

c) WATER VAPOR IS SELF-LIMITING AND THUS DOES NOT DRIVE GLOBAL WARMING
In the exchange about why water vapor is ignored when discussing increasing global temperatures while CO2 is not (see time indices ~14:13 to ~15:15) Dyson says you can't take water vapor out of the global warming equation and thus our focusing on CO2 is because we can control it. These conclusions are false.

Water vapor is indeed a greenhouse gas, like carbon dioxide and methane. But unlike carbon dioxide and methane, water vapor is self-limiting. Once it reaches a certain concentration in the atmosphere, it precipitates out as rain, snow, hail, etc. So the concentration of water vapor doesn't keep on increasing like carbon dioxide and methane. That's why scientists focus on carbon dioxide and methane, whose atmospheric concentrations are increasing, but not water vapor, whose atmospheric concentration is self-limited.

d) THE SOLAR CYCLE IS NOT CORRELATED WITH GLOBAL WARMING
Dyson (to his credit) does not claim that global warming is due to increased direct solar warming of the atmosphere. And the data clearly indicate that solar irradiance is NOT the cause of global warming:

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(if there's a problem getting to the link directly, just Google "What is the sun's role in climate change NASA" and you can get there that way).

(By the way, I was able to see the plot on my IPhone but not on my MacBook Pro. If you have problems seeing the plot go to:
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Unfortunately he does make the false assertion that the 11-year-cycle of sunspot activity and cosmic rays are correlated with increases in the Earth's temperature, an assertion that is directly contradicted by the data:

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(see the plots of temperature vs. time (black curve) compared to the number of sunspots vs. time (blue curve))

e) SUMMARY
During the course of his interview Dyson ignores the data, or makes false statements that are contradicted by the data, on several occasions:

a) Completely ignores the observational data indicating that climate-related changes are already taking place;
b) Makes a false claim that water vapor must be considered alongside carbon dioxide as a driver of global warning, ignoring the fact that water vapor is self-limiting, unlike carbon dioxide and methane;
c) Makes a false statement that there's a correlation between the 11-year solar cycle and atmospheric temperature increases, a claim directly contradicted by the data.

Freeman Dyson was clearly a brilliant theoretical physicist who made groundbreaking contributions in areas like quantum electrodynamics. Unfortunately, however, it is equally clear from this interview that Dyson had not acquainted himself with even the basics of current climate research.

He was completely unaware of all the observational data indicating current climate effects. His focus was consistently and solely on the uncertainty of model predictions, as if we were still back in 2000 relying mostly on models and all the climate data collected in the last 20 years never happened. He was not cognizant of a fundamental fact about the difference between water vapor (self-limiting in its atmosphere concentration, because water precipitates out of the atmosphere) and carbon dioxide/methane (on Earth it doesn't rain carbon dioxide or methane, so the atmospheric concentration of C02 and methane continues to increase). And he was unaware that the 11-year solar cycle data and the temperature data directly contradicted his claims about global temperature being correlated with solar activity.

As I mentioned above, observational and experimental data are the foundation of science. Freeman Dyson's work demonstrating the equivalence of the Feynman diagram approach and the operator formalism in quantum electrodynamics, and his work proving that the Pauli exclusion principle is the main cause of bulk stability in matter, are examples of his brilliance because they agree with the data.

However his statements in this interview on climate research, in an area outside of his expertise where he clearly had not learned the basics of current climate research, are NOT examples of his brilliance because his statements do NOT agree with the data.

And his brilliance in QED and in applying quantum mechanics to bulk matter does not make his statements on climate research correct. Only agreement with the data can do that.

Only agreement with the data can do that.

Only if the data is interpreted correctly and without bias.

About that…

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Abstract

Among papers stating a position on anthropogenic global warming (AGW), 97 % endorse AGW. What is happening with the 2 % of papers that reject AGW? We examine a selection of papers rejecting AGW. An analytical tool has been developed to replicate and test the results and methods used in these studies; our replication reveals a number of methodological flaws, and a pattern of common mistakes emerges that is not visible when looking at single isolated cases. Thus, real-life scientific disputes in some cases can be resolved, and we can learn from mistakes. A common denominator seems to be missing contextual information or ignoring information that does not fit the conclusions, be it other relevant work or related geophysical data. In many cases, shortcomings are due to insufficient model evaluation, leading to results that are not universally valid but rather are an artifact of a particular experimental setup. Other typical weaknesses include false dichotomies, inappropriate statistical methods, or basing conclusions on misconceived or incomplete physics. We also argue that science is never settled and that both mainstream and contrarian papers must be subject to sustained scrutiny. The merit of replication is highlighted and we discuss how the quality of the scientific literature may benefit from replication.

Only if the data is interpreted correctly and without bias.

wmyers, what mathematically rigorous, quantitative measures do you use to determine if data are being "correctly interpreted"?

I'm genuinely curious because, as a physicist, "interpreted correctly" is not a term I use when dealing with data. I'd thus like to know what you mean by the term, in a mathematically rigorous and quantitative sense.

I'm not asking for a Ph.D. thesis here. Your answer can be stated in layman's terms, as long as it's mathematically rigorous and quantitative.

Let's deal with the specific data in my post on Freeman Dyson's interview. Let's look once again at the plots of temperature vs. time (black curve) compared to the number of sunspots vs. time (blue curve):

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From those plots, there are at least two mathematically rigorous, quantitative metrics that lead to my statements in my previous post: The data directly contradict Freeman Dyson' assertion that the 11-year-cycle of sunspot activity and cosmic rays are correlated with increases in the Earth's temperature. The solar cycle is not correlated with global warming.

a) Have I "correctly interpreted" the data? If so, what quantitative metrics did you use to determine that my interpretation of the data was correct?

b) If no, what quantitative metrics did you use to determine that my interpretation of the data was NOT correct?

I'm not interested in whether or not you are using the same metrics that I used. The mathematically rigorous, quantitative metrics I chose need not be the mathematically rigorous, quantitative metrics you choose. In fact for the moment I've held off stating what my metrics are, so as to avoid biasing your answer.

What I am interested in knowing is, in looking at those plots of temperature vs. time (black curve) compared to the number of sunspots vs. time (blue curve), what metrics YOU are using to determine whether or not those data are correlated.

Only if the data is interpreted correctly and without bias.

The key thing here is:

without bias

But that is a huge problem because the individuals doing the studies are going to try to push the agenda that they want.

So they will take the data and will do what they will with it so that any report or article aligns with the agenda that they want pushed.

So if that means tweaking the data – they will.

So if that means leaving out things that do not align with their agenda – they will.

So basically like this ABC News Report

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They are trying to say that the real death toll is far higher because they want more Fear & Panic and a death toll that is closer to their initial claims helps with that.

Thing is the death toll is already inflated and the actual numbers are far less since they decided to claim almost everyone as dying from COVID 19.

So anything report (and there has been several already) is going to be suspect and filled with bias or will be misleading.

Because the agenda is what driving the results and not the data.

Prof. Dyson stated facts in a very easy to understand way that did not resort to trying to overload the listener with technical-speak and vocabulary beyond the layman. He can communicate. Something I've noted many pseudo and wanna-be (aspiring?) academics cannot seem to do.

Dyson has nothing to prove. He's been there and done that. He is the bar the standard is measured to.

It's rather humorous when others have to quote in excess from others to try to make their points. It's like they are incapable of using their own voice.

You cannot make any mark by parroting others just like you don't get anywhere as a band by playing cover tunes.

Those who have used their own voices deserve the nod of acknowledgment and respect – regardless of whether it is 100% correct or not.

I'm a data-driven person, like most physicists, so let's get back to the data shall we?

Here's the data on temperature vs. time and the number of sunspots vs. time:

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Here's my statement regarding that data: the 11-year cycle of sunspots is not correlated with increases in the Earth's temperature.

Have I "correctly interpreted" the data, yes or no? If yes, why? If no, why not?

Probably not since the very first paragraph shows that your link and the article is filled with bias.

The past decade (2010-2019) was the hottest on record and five of the top 10 warmest single years have all occurred since 2015, according to reports released by the UK Met Office and the World Meteorological Organisation.

Totally written to push that what they believe to be happening is happening.

The Hottest on Record

Gee, their record is for a very short period of time and is probably using data that was develop from their computing models.

Five of the top 10 warmest single years have all occurred since 2015

Really do they have anything from the time period of 800 BC to 1200 AD?

Would bet that during that time there were probably a few years that might have been warmer.

So they are using only the data that they want and that has been developed by their computer models.

Bad data plus individuals who are completely bias.

Gee, no pushing of agendas at all.

You cannot make any mark by parroting others just like you don't get anywhere as a band by playing cover tunes.

But in Dyson's case, it like having a 50s swing band trying to cover Rammstein. Different skill sets and expertise.

Kind of like this take from XKCD 793 ( xkcd.com/793 ), but in reverse since Dyson just yells it's too complex and thus the models are meaningless.

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Martin, at which part was Dyson yelling?

Fine, I'll retract "yell", and replace with "state emphatically without supporting evidence, nor any willingness to read-up on the subject"

That was in train-wreck e360Yale interview from a decade ago: link

Martin, at which point was Dyson stating

emphatically without supporting evidence, nor any willingness to read-up on the subject

?

My objections to the global warming propaganda are not so much over the technical facts, about which I do not know much, but it's rather against the way those people behave and the kind of intolerance to criticism that a lot of them have. I think that's what upsets me.

Thirty years ago, there was a sort of a political split between the Oak Ridge community, which included biology, and people who were doing these fluid dynamics models, which don't include biology. They got the lion's share of money and attention. And since then, this group of pure modeling experts has become dominant.

I got out of the field then. I didn't like the way it was going. It left me with a bad taste.

What's wrong with the models. I mean, I haven't examined them in detail, (but) I know roughly what's in them. And the basic problem is that in the case of climate, very small structures, like clouds, dominate. And you cannot model them in any realistic way. They are far too small and too diverse.

So they say, ‘We represent cloudiness by a parameter,' but I call it a fudge factor. So then you have a formula, which tells you if you have so much cloudiness and so much humidity, and so much temperature, and so much pressure, what will be the result… But if you are using it for a different climate, when you have twice as much carbon dioxide, there is no guarantee that that's right. There is no way to test it.

Well, it depends on what you mean by sitting down with people. I do sit down with people. I don't go over their calculations in detail. But I think I understand pretty well the world they live in.

I guess one thing I don't want to do is to spend all my time arguing this business. I mean, I am not the person to do that. I have two great disadvantages. First of all, I am 85 years old. Obviously, I'm an old fuddy-duddy. So, I have no credibility.

And, secondly, I am not an expert, and that's not going to change. I am not going to make myself an expert

e360: Do you mind being thrust in the limelight of talking about this when it is not your main interest. You've suddenly become the poster child for global warming skepticism.

Dyson: Yes, it is definitely a tactical mistake to use somebody like me for that job, because I am so easily shot down. I'd much rather the job would be done by somebody who is young and a real expert. But unfortunately, those people don't come forward.

e360: Are there people who are knowledgeable about this topic who could do the job of pointing out what you see as the flaws?

Dyson: I am sure there are. But I don't know who they are.

I have a lot of friends who think the same way I do. But I am sorry to say that most of them are old, and most of them are not experts. My views are very widely shared.

Anyway, the ideal protagonist I am still looking for. So the answer to your question is, I will do the job if nobody else shows up, but I regard it as a duty rather than as a pleasure.

And since then, this group of pure modeling experts has become dominant.

‘We represent cloudiness by a parameter,' but I call it a fudge factor. So then you have a formula, which tells you if you have so much cloudiness and so much humidity, and so much temperature, and so much pressure, what will be the result.

way those people behave and the kind of intolerance to criticism that a lot of them have.

So you got a bunch of individuals who prefer their computer models over anything else and who have develop these models to do what they want.

Martin, you stated:

emphatically without supporting evidence, nor any willingness to read-up on the subject

Your first quote of Prof. Dyson in evidence of this as:

My objections to the global warming propaganda are not so much over the technical facts, about which I do not know much, but it's rather against the way those people behave and the kind of intolerance to criticism that a lot of them have.

What supporting evidence does he need for this?

How is this demonstrative of not being willing to learn more on the subject?

And, secondly, I am not an expert, and that's not going to change. I am not going to make myself an expert

So they are using only the data that they want and that has been developed by their computer models.
Bad data plus individuals who are completely bias.

So you got a bunch of individuals who prefer their computer models over anything else and who have develop these models to do what they want.

No, Mithmee, the links I've presented are for measured data NOT computer model results. And spatially comprehensive data, not just the "data that they want".

So any complaints or accusations you have against computer model results are IRRELEVANT to the temperature and sunspot data:

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and to the sea level data:

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because they are actual measured data, NOT model predictions.

wmyers, in my post on April 29 I asked you the following:

I'm a data-driven person, like most physicists, so let's get back to the data shall we?
Here's the data on temperature vs. time and the number of sunspots vs. time:

link

Here's my statement regarding that data: the 11-year cycle of sunspots is not correlated with increases in the Earth's temperature.
Have I "correctly interpreted" the data, yes or no? If yes, why? If no, why not?

We are dealing with a very simple "yes" or "no" question here. If YES, why? If NO, why not?