Can You Trust an AI/ML Model to Forecast?

The latest fashion in model building is adding AI/ML (Artificial Intelligence/Machine Learning) technology to numerical models for weather forecasting.  No doubt soon there will be climate models also claiming improved capability by doing this.  A meteorological example is called Aardvark Weather and a summary is provided at Tallbloke’s Talkshop Scientists say fully AI-driven weather prediction system delivers accurate forecasts faster with less computing power.

Like all inventions there are weaknesses along with the claimed benefits.  Here’s a short list of the things that can go wrong with these new gadgets. The concerns below are listed along with some others in a paper Understanding the Weaknesses of Machine Learning: Challenges and Limitations by Oyo Jude. Excerpts in italics with my bolds.

Introduction

Machine learning (ML) has become a cornerstone of modern technological advancements, driving innovations in areas such as healthcare, finance, and autonomous systems. Despite its transformative potential, ML is not without its flaws. Understanding these weaknesses is crucial for developing more robust and reliable systems. This article delves into the various challenges and limitations faced by ML technologies, providing insights into areas where improvements are needed

Data Quality and Bias

Data Dependency

Machine learning models are highly dependent on the quality and quantity of data used for training. The performance of an ML model is only as good as the data it is trained on. Common issues related to data quality include:

Incomplete Data: Missing or incomplete data can lead to inaccurate models and predictions. Incomplete datasets may not represent the full spectrum of possible inputs, leading to biased or skewed outcomes.
Noisy Data: Noise in data refers to irrelevant or random information that can obscure the underlying patterns the model is supposed to learn. Noisy data can reduce the accuracy of ML models and complicate the learning process.

Data Bias

Bias in data can significantly impact the fairness and accuracy of ML systems. Key forms of data bias include:

Selection Bias: Occurs when the data collected is not representative of the target population. For example, if a model is trained on data from a specific demographic group, it may not perform well for individuals outside that group.
Label Bias: Arises when the labels or categories used in supervised learning are subjective or inconsistent. Label bias can skew the model’s understanding and lead to erroneous predictions.

Model Interpretability and Transparency

Complexity of Models

Many advanced ML models, such as deep neural networks, are often described as “black boxes” due to their complexity. The lack of transparency in these models presents several challenges:

Understanding Model Decisions: It can be difficult to understand how a model arrived at a specific decision or prediction, making it challenging to diagnose errors or biases in the system.
Trust and Accountability: The inability to interpret model decisions can undermine trust in ML systems, particularly in high-stakes applications such as healthcare or criminal justice. Ensuring accountability and fairness becomes challenging when the decision-making process is opaque.
Explainability:  Efforts to improve model interpretability focus on developing techniques and tools to make complex models more understandable. Techniques such as feature importance analysis, surrogate models, and visualization tools aim to provide insights into model behavior and decisions. However, achieving a balance between model performance and interpretability remains an ongoing challenge.

Generalization and Overfitting

Overfitting

Overfitting occurs when a model learns not only the underlying patterns in the training data but also the noise, resulting in poor performance on new, unseen data. This issue can be particularly problematic with complex models and limited data. Strategies to mitigate overfitting include:

Cross-Validation: Using techniques like k-fold cross-validation helps assess model performance on different subsets of the data, reducing the risk of overfitting.
Regularization: Regularization methods, such as L1 and L2 regularization, add penalties to the model’s complexity to prevent it from fitting noise in the training data.

Generalization

Generalization refers to a model’s ability to perform well on unseen data that was not part of the training set. Achieving good generalization is crucial for the practical application of ML models. Challenges related to generalization include:

Domain Shift: When the distribution of the data changes over time or across different domains, a model trained on one dataset may not generalize well to new data. Addressing domain shift requires continuous monitoring and updating of models.
Data Scarcity: In scenarios where limited data is available, models may struggle to generalize effectively. Techniques such as data augmentation and transfer learning can help address data scarcity issues.

Comment:

Many similar issues have been raised against climate models, undermining claims their outputs are valid projections of future climate states.  For example, the issue of detailed and reliable data persists.  It appears that even the AI/ML weather forecasting inventions are dependent on ERA5, which has a record of only ~40 years to use for training purposes.  I’m suspending belief in these things for now–new improved black boxes sound too much like the Sorcerer’s Apprentice.

Disney’s portrayal of the Sorcerer’s Apprentice in over his head.

Climate Scare Based on Lies

link to video: Prof. William Happer – Climate Scare Is Based on Lies

Transcript in italics with my bolds and added images (HS is interviewer Hannes Sarv, WH is William Happer)

HS: If you read about climate in the newspapers or some talk about climate on television, it will be very, very far from the truth.  We’re told that climate change is a direct consequence of human activity, particularly the burning of fossil fuels.  Year after year, you are seeing the dramatic reality of a boiling planet.

And for scientists, it is unequivocal. Humans are to blame, we’re led to believe the climate is boiling. And the accumulated amount is now trapping as much extra heat as would be released by 600,000 Hiroshima-class atomic bombs exploding. That’s what’s boiling the oceans.  Which will have disastrous effects.

But is there really a scientific consensus on man-made climate change? Over a thousand scientists dispute the so-called climate crisis. Many of them are high-ranking experts in their fields. Among them, Dr. William Happer, a respected physicist with decades of groundbreaking research, an emeritus professor at Princeton University, and a leading expert in atomic and molecular physics.  He has deep expertise in the greenhouse effect and the role of CO2 in climate change.  Dr.  Happer argues that the role of human activity and CO2 in global warming is based on flawed science and misinterpretations.

“You know, it’s dangerous to make policy on the basis of lies.”

In this interview, we’ll explore the evidence he believes has been overlooked and why it could transform our understanding of climate change.

HS: As we can see, Professor, you are still working daily in your university office. So what is it? Are you consulting younger colleagues or still involved in some research projects?

WH: Well, yes, I try to stay busy and I’m working now with a former student from Canada who’s a professor there now, William van Wijngaarden.  And we’re working now on how water vapor and clouds affect the Earth’s climate, the radiation transfer details of those.

HS:So still very much involved in climate science.

WH: Well, you know, climate is very important. It’s always been important to humanity. It’s not going to change. I think it’s been having hard times the last 50 years because of this manic focus on demonization of greenhouse gases, which have some effect on climate but not very much.

HS: We’re going to absolutely get to that. But I wanted to start from actually, I was listening to one of your speeches and presentations you held back in 2023 at the Institute of Public Affairs. And what really I think resonated with me was that you started from the notion that freedom is important.  And every generation has their own struggle for freedom and freedom is not free. So I actually wanted to start by asking you what is the state, the current state of freedom in your opinion in the world today?

WH: I think it’s really true that every generation has to struggle to maintain freedom, you know, because every generation has lots of people who don’t like freedom, you know. They would like to be little dictators, you know, and that’s always been true if you read history. And it’s not going to change.

And so I think it’s important that we educate our children to recognize that humans are imperfect and there will always be attempts to get dictatorial control over society. And, you know, our founding fathers in America represented recognize that. They just assumed that their fellow Americans would be not very perfect people, you know, with lots of flawed people, and they tried to design a system of government that would work even with flawed people. Some German philosopher put it right, you know, out of the crooked timber of mankind, no straight thing was ever made. So that’s the problem that we will always face.

HS: What about academic freedom in today’s world? I’m not only speaking about climate science, but in general.

WH: Well, you know, I think academia has always had a problem with groupthink, you know, because you’re typically all together in one small community, and your children and wives interact with each other. And so the temptations, the pressures to all think the same are very great. You know, if you don’t think the same, your kids suffer, your wife suffers, and that’s nothing new. It’s always been like that. You know, there’s a famous… American play, Who’s Afraid of Virginia Woolf? But it’s about this topic and it goes back many, many decades, you know, long before the current woke problems that we’re having in America.

HS:  So as we all know currently, there is a new administration in the United States. So what will happen now? Will the situation, in your opinion, improve or is it just, you know, the challenges are going to remain?

WH: Well, you know, we’ve just elected a new president, and he’s very vigorous and has lots of ideas, and I think that’s a good thing. We’ll see how successful he is. But, you know, our society and our government is designed to be cumbersome and unwieldy. That’s to prevent crazy things from happening too quickly.  And so the president will have to deal with that. And if the Americans support him, if the Congress supports him, he’ll be successful.

HS: Let’s move to climate science. Is there any honest discussion left? It has become so political, in my opinion, that it is really hard to have an open, a normal discussion about it.

WH: Well, I think if you go to a seminar, for example, at Princeton on climate, It’s often pretty good science. It’s not alarmist. But this is professors and students talking to each other. The further you get away from the actual research, the more alarmist and crazy it becomes.

So if you read about climate in the newspapers or listen to some talk about climate on television, it will be very, very far from the truth. And it won’t be the same thing that the professors at universities normally are talking about. But that said, you know, I think there’s been a lot of corruption because of all of the money available. You know, there are huge funds if you do research that supports the idea that there is a climate emergency which requires lots of government intervention. And if you don’t do that, you’re less likely to be funded, you know, you can’t pay your graduate students. So it’s a bad situation. It’s been very corrupting to this branch of science.

HS: Exactly how long has it been going on, this kind of situation?

WH: Well, I think it really got started in the early 90s. I was in Washington at the time as a government bureaucrat, and I could see it getting started. It was being pushed by Senator Al Gore and his allies. There were, at that time, still lots of honest scientists in academia who didn’t go along with all of the alarmism, but they’ve gradually died off and they’ve been replaced by younger people who’ve never known anything except, you know, pleasing your government sponsor with the politically correct research results that they expect.

HS: So basically they are not in a position, if they want to achieve anything in academia or make a career for themselves, they are kind of unable to stay honest even?

WH: They try to be honest, but it’s very difficult because you have to plan to educate your children. You have to maintain your family, and so that means you need money. And the only way to get money is to agree to this alarmist meme that has dominated climate scientists now for several decades.

HS: Of course it affects climate research. So what is the current state, let’s say, the current state of climate research? What’s the quality of it in your opinion?

WH: Well, I think many of the observational programs in climate science are very good. For example, satellite measurements of Earth’s properties, radiation, cloudiness, temperatures, and ground-based observations. They’re often very high-quality work, very useful, and we’re lucky to have them. There are good programs in both Europe and the United States and Japan, and China is becoming quite important nowadays, too.

I think where there’s still huge problems is in computer modeling. I don’t think most computer models mean anything. It’s a complete waste of money, but that’s what’s driving the public perception. So the public is unable to look at model results, which are not alarming at all.  But instead what they see is graphic displays from computer computations which are not tied into observations. So I think the money that’s been spent on computers, and lots of it has been spent, has been mostly wasted.

HS: Let me just understand it correctly because I’ve come to understand that these computer models are something that our current debate or the climate alarm is all based on:  That there’s going to be a warming of how many degrees and then the earth is going to be uninhabitable.  And you’re saying that those models are not things that something like that should be based on.

WH: The Earth is always either warming or cooling. It’s a rare time when it’s got stable temperature. We’re in a warming phase now. But most of the warming is probably a natural recovery from the Little Ice Age when it was much, much colder all over the world. And it began to warm up in the early 1800s.

And it continued to warm, not very fast. No one knows how long this will last. If you look over the last 10,000 years, since the end of the last glacial period, there have been many warmings and coolings similar to the one that we’re in now.

And I think understanding that is quite important, but that understanding has been put back by many, many years because of the sort of crazed focus on greenhouse gases. It’s pretty clear that greenhouse gases don’t have very much to do with these warmings. Nobody was burning fossil fuels in the year 1200-1300 when the poor Greenlanders were frozen out.

They did some pretty good farming in the southern parts of Greenland in the year 1000, the year 1100. Before long, it became just too cold to continue to do that. The same thing happened in parts of my ancestral country of Scotland. You know, you used to be able to farm the uplands of Scotland, which you can’t farm now, it’s too cold. But they’re warming up at some point, maybe you can farm them again. So anyway, the climate is just famous for being unstable.

HS: Let’s talk about those greenhouse gases. Mainly climate change today in mainstream media or by those alarmist politicians, for example, is attributed to carbon dioxide. If someone has not looked into it, this gas might seem to have something even poisonous. What is carbon dioxide? Do we need it?

WH: Well, first of all, carbon dioxide is at the basis of life on Earth. We live because plants are able to chemically transform carbon dioxide and water into sugar. And a byproduct is the oxygen that we breathe. And so we should all be very grateful that we have carbon dioxide in the atmosphere.  You know, life would die without carbon dioxide. If you look over the history of… Life on Earth, carbon dioxide has never been very stable in the atmosphere. There have been times in the past when it’s been much, much higher than today. Life flourished with five times more carbon dioxide than we have today.

And there have been times when it’s been much lower, one-half, one-third, and those were actually quite unpleasant times for life. They were the depths of the last ice ages when carbon dioxide levels dropped to below 200 parts per million, quite low compared to today. We’re at around 400.  So at the depth of the last ice age, it was about half what it is today. In some of the more verdant periods of geological history, it’s been four times, five times what it is today. So the climate is not terribly sensitive to carbon dioxide. It has some sensitivity to it.

More carbon dioxide will make it a little bit warmer. But carbon dioxide is heavily saturated, to use a technical term. You know, there’s so much in the atmosphere today that if you, for example, could double carbon dioxide, that’s 100% increase, you would only decrease the cooling radiation to space by 1%.  So 100% change in carbon dioxide only makes a 1% change in flux. And that’s because of the saturation that I mentioned. And there’s not much you can debate about that. It’s very, very basic physics. It’s the same physics that produces the dark lines of the sun and the stars. So it’s quite well understood.

And so the question is, what temperature change will a 1% change of radiation to space cause? You know, that’s radiation flux, not temperature. And the answer is it will cause an even smaller percentage change of temperature. There’s really no threat from increasing carbon dioxide or any of the other more minor greenhouse gases like methane or nitrous oxide or artificial gases like anesthetic gases. It’s all a made-up scare story.

HS: Where did this scare story come from? Why this fixation on greenhouse gases? If you explain it this way, it seems a bit even absurd to be fixated on these gases all the time.

WH: Well, you know, I’m really good with instruments and differential equations, but I’m not so good at people’s motives. And so I don’t really understand myself exactly how this has happened. I think… There are various motives, some of them fundamentally good. For example, one of the motives has been it’s hard to keep people from fighting with each other, so if we could have a common enemy like a danger to the climate, we could all join forces and defeat climate change, and then we wouldn’t be killing each other off.

So there’s nothing wrong with a motive like that, except that you have to lie.
And so, you know, it’s dangerous to make policy on the basis of lies.

So I don’t know what drives it. It’s a perfect storm of different motives. Lust for power, good motives, lust for peace. All for that. Lust for money. But I’m much more comfortable talking about, as I say, the physics of greenhouse gases and the physics of climate than what drives people.

HS: Yeah, yeah. Well, you have said that this climate change or climate alarmism today is, what was it, you prefer scam, but you are willing to settle with a hoax, is it correct?

WH: Well, this is not too serious, but you know, when someone says hoax, I think of hoax as, to some extent, a practical joke. There’s a certain amount of humor in it. For example, the Piltdown Man was a famous hoax where some brilliant Englishman doctored up a I think it was a chimpanzee skull to make it look like a human skull. And this was not too serious, but lots of learned professors wrote papers about it, you know, and it was all nonsense. But this had no aim to make a lot of money, you know, or to gain power.

It was simply, you know, a great practical joke. That’s a hoax. A scam is different. A scam is where you are deceiving people to enrich yourself, to gain power, you know, and so I think that’s a better description of what’s happening with climate than a hoax. But it’s a small detail, I don’t mind calling it a hoax.

HS: Basically, Professor, there is a lot of money involved in climate change or climate alarmism. Would it be that money is driving this as well or what is your take on that?

Yes, those are trillions of dollars they are projecting.

WH: Well, I think it’s really true that the love of money has been the root of evil as long as humanity has existed. And here we’re talking about trillions of dollars. If you really went to net zero, the economic implications would just be enormous. People would have to lower their standard of living greatly. It would cause enormous damage to the environment. You cover the world with windmills and solar panels. So… And it’s driven by money. Lots of people are making lots of money. So it’s driven by money. It’s driven by power.

And then it’s driven by poor people who fundamentally believe, you know, and that they really have been misled into thinking that there is an emergency. And you have to be sympathetic to them, you know, who wouldn’t want to save the world if the world was in danger? It is not really in danger, but many people are convinced that it’s in danger. But, you know, there’s this old saying, the road to hell is paved with good intentions, and we’re on the road to hell with net zero.

HS: Yes. Well, like you already mentioned, this crisis is often said to be linked with, for example, extreme weather events. But I don’t know, is it even clear today that we have more extreme weather events because of the warming that is happening? Or is it so?

WH: Well, if you look at the data, there’s not the slightest evidence that there’s more extreme weather today than there was 50 years ago. Even the IPCC, you know, the UN body does not claim that there is an increase in extreme weather. They say there’s really no hard evidence for that. And in fact, the evidence is that it’s about the same as the weather has always been. In my country, for example, the worst weather we had was back in the 1930s when we had the Dust Bowl and, you know… people migrating from Oklahoma to California, you know, it was a terrible time.  We’ve not had anything like that since.

HS: Of course, always to talk about floods, always to talk about hurricanes. And as I understand as well, the IPCC is not actually in their scientific reports. They are not actually saying that there are more. But they are saying something, right? So the question here is, what do you think?  You have probably looked into them a bit more than I am. So is it solid science what’s in there? Or is it also motivated the IPCC scientific reports, politically motivated, for example?

WH: You know, there’s this saying in the communications business, if it bleeds, it leads. So if you’ve got a newspaper or a television business, you have to look for disasters because that’s what people pay attention to. And so part of the problem has been the mass media, which has to have emergencies, has to have extreme events.  And the fact is usually hidden that there’s nothing unusual about an event. They try to deceive you into thinking that this has never happened.

For example, just yesterday they had four or five inches of snow in Corpus Christi, Texas. That’s a lot of snow for Corpus Christi. But, you know, if you look at the records of Corpus Christi, it’s not unusual every 20, 30 years as it happens. It’s been happening for thousands of years. But most people, you know, they’re not even 20 or 30 years of age, and so they’ve never seen this before. So it seems like the world is changing rapidly in front of their eyes, but it’s not changing really at all.

HS: Yes, they can look at it on the television, then it must be true when they are saying that it’s because of climate change, right? So this is the thing. One particular graph that is always talked about when climate is the issue is the famous Michael Mann hockey stick.

The first graph appeared in the IPCC 1990 First Assessment Report (FAR) credited to H.H.Lamb, first director of CRU-UEA. The second graph was featured in 2001 IPCC Third Assessment Report (TAR) the famous hockey stick credited to M. Mann.

WH: The graph is phony, and that’s been demonstrated by many, many people. It’s even different from the first IPCC graphs. It’s a graph of temperature versus time since about the year 2000. you know, about the year zero, you know, from the time of Christ to today.  And what it shows is absolutely no change of temperature until the 20th century when it shoots up like the blade of a hockey stick. So that’s why it’s called the hockey stick curve. So the long, flat… Part of the hockey stick is the unchanging temperature. But that was not in the first IPCC report.

Climate reconstructions of the ‘Medieval Warm Period’ 1000-1200 AD. Legend: MWP was warm (red), cold (blue), dry (yellow), wet

The first IPCC report showed that it was much warmer in Northern Europe and United States, North America, in the year 1000 than it is today. There really was a medieval warm period, which was what allowed the Norse to settle in Greenland. and have a century or two of successful agriculture there. It’s never gotten that warm again since.  It may happen, but the hockey stick curve basically erased that, so it was… It’s like these Orwellian novels. 1984, there was this… They continued to rewrite history, you know, so what was history yesterday was not history today, you know. So it was rewriting the past. There clearly was a warm period.There is evidence from all around the globe that it was much warmer in the year 1000 than today. We still have not gotten as warm as it was then.

HS: Yes, yes, and the warm period, as I understand, was followed by the Little Ice Age. So 19th century, the warming that started then is actually, it started at the end of this Little Ice Age.

Earth is still recovering from the Little Ice Age, which was the coldest period of the past 10,000 years, that ended about 150 years ago.

WH: That’s right, that’s right. For example, that’s very clear if you come to Alaska, And look at the Alaska glaciers. In particular, there’s a famous glacier bay in Alaska which was filled with glaciers in the year 1790 when it was first mapped by the British captain Vancouver. the ice came right out to the Pacific.

And already by 1800, it had receded up into the bay. Some of it was melting by 1800. And by 1850, most of the ice was gone. I’m talking about the 1800s, not the 1900s, not the present time. So it’s pretty clear from Glacier Bay that the warming began around the year 1800.  And it’s just been steadily warming since then.

HS: I have been shown another graph many times which shows a correlation between the increase of carbon dioxide in the atmosphere and the temperature rise during the last, let’s say, 150-200 years.  Yeah, it’s a correlation, of course, but is there any causation as well? Because you pointed it out as well that there is a warming effect.  Carbon dioxide has a warming effect in the atmosphere, but it’s not leading as I understand.

► Changes in global atmospheric CO2 are lagging 11–12 months behind changes in global sea surface temperature. ► Changes in global atmospheric CO2 are lagging 9.5–10 months behind changes in global air surface temperature. ► Changes in global atmospheric CO2 are lagging about 9 months behind changes in global lower troposphere temperature. ► Changes in ocean temperatures explain a substantial part of the observed changes in atmospheric CO2 since January 1980. ► Changes in atmospheric CO2 are not tracking changes in human emissions.

WH: Yeah, that’s correct. You know, you can estimate past CO2 levels by looking at bubbles in ice cores from Antarctica or from Greenland. And you can also estimate past temperatures by looking at the ratios of oxygen isotopes in the ice and the other proxies. So there are these proxy estimates of past CO2 levels and past temperature.

And they are indeed tightly correlated. When their temperature is high, CO2 levels are high, and temperature is low, CO2 levels are low. But if you look at the time dependence, in every case, first the temperature changes and then the CO2 changes. Temperature goes up, a little bit later CO2 goes up.

Temperature goes down, a little bit later CO2 goes down. So they are indeed correlated, but the cause is not CO2, the cause is temperature. So something makes the temperature change and the CO2 is forced to follow. That’s easy to understand. It’s mostly due to CO2 dissolving in the ocean. The solubility of CO2 is very temperature dependent.

So if the world ocean’s cool, they suck more CO2 out of the atmosphere. And if they warm, more CO2 can come back into the atmosphere. So there’s nothing surprising about that. The only surprise is nobody really knows why the temperature changes, but it’s certainly not CO2 causing it to change because the CO2 follows the change.

HS: It doesn’t precede it. Causes have to precede their effects.  from the same 2023 presentation that I already mentioned, that I listened. And as a member of Jason in 1982, you were one of the authors of a scientific paper that aimed to measure the effects of CO2 to global warming. The first number you got was too small. Then you just arbitrarily increased it.

WH: You’re asking, the key question is how much warming would be caused if you double carbon dioxide. That’s sometimes called the climate sensitivity or the doubling sensitivity. And the first person to seriously try to calculate that theoretically was your neighbor across the Baltic, Svante Arrhenius. He was a Swede and a very good chemist, and he was interested in this problem. He was the first one to really work on it, and his first paper was written in 1896. So the first climate warming paper was 1896 by Arrhenius, and he estimated that doubling CO2 at that time would warm the earth by around six degrees.

It was a big number. He didn’t know very much, so it was not a bad number given what he knew at the time. As he learned more, he kept bringing that number down, so the last number he published was about four degrees, and it was still going down.  So the number that we published was three degrees, this little Jason study. So it was only a little bit smaller than Arrhenius’ number. But that was because neither he nor we really knew enough about how the climate works to get a reliable answer.

And I think the only way to really get a reliable answer is from good observations over long periods of time. And we simply don’t have good enough empirical data right now to know what that is. But I’m pretty sure that doubling CO2 by itself is unlikely to cause warming of more than about one degree Celsius. You know, if you do the simplest calculation, you find that answer, it’s a bit less than one degree for doubling CO2.

And so three degrees, four degrees, the only way to get that is with enormous positive feedbacks. And so that’s what these computer models do that we’ve been talking about.  They inject feedbacks in a very obscure way so you can’t figure out what they’ve done. But it’s a supercomputer, so how could it be wrong? It must be right, it’s a computer after all. But nevertheless, it’s giving these absurd positive feedbacks. And most feedbacks in nature are not positive, they’re negative.

There’s even a law called Le Chatelier’s Principle, which is that if you perturb some chemical system or physical system, it has feedbacks. And they try to reduce the perturbation. They don’t try to make it bigger. They try to make it smaller. So climate has turned that completely on its head. It says all feedbacks in climate are positive, and if it’s negative, forget about it. You won’t get your research grant renewed next year if you put that in your proposal. So it’s a mess, and it’s going to take a long time to clean this up.

Of course, if someone is not on the right side of this net zero debate, people are starting calling him names. He’s a climate denier or climate skeptic and so on. But those ad hominem arguments are what are used in the media to shut down the arguments of even scientists.  One of them is that if you’re not a climate scientist, you’re not allowed to talk about climate.  Well, of course, that’s nonsense. Climate is really all physics and chemistry. And so anyone with a good grounding in physics and chemistry can know as much about climate as a climate scientist.

In general, climate scientists are not well educated. When I look at American universities, maybe it’s better in Estonia, but you go to a class and your education consists on how do you organize a petition to your local legislator. So that’s your knowledge as a climate scientist. You don’t have to learn physics, you don’t have to learn chemistry, you don’t have to learn electromagnetics and radiation transfer. You have to learn how to work the political process.  So it’s true that most physicists aren’t very good at that. You know, they’re quite good at physics, but they’re not very good at talking to the Congress or to the president.

HS: Yeah, yeah. So basically, climate science has become something more like a social science in that sense.

WH: Yeah, that’s right. It’s been very heavily politicized. There was something very similar to this in the Soviet Union in the field of biology. There was this Ukrainian agronomist, Lysenko, who… got the ear of the Communist Party and was supported for many decades with just crazy theories about biology, you know, you could grow peaches on the Arctic Circle if you just listen to him.  All sorts of nutty things and that there was no such thing as genes, but he had a lot of political support and so he essentially destroyed biology for a generation in the Soviet Union.  You know if you taught your class about genes, you know, Mendel’s wrinkled peas and smooth peas, you were lucky if you were only fired, you know, you could have been sent to a concentration camp and several people were condemned to death for teaching about genes. And so I think climate science is a lot more like Lysenkoism than it is normal science.

HS: Yes, well, yes, this is something that we should be able to learn from because this was the Stalin era, this was the craziest time period, absolutely. In Eastern Europe we also know a lot about that and it does seem to me as well that Löschenkism is something that is like gaslighting the public and ostracizing renowned scientists, for example, like yourself. This is something that has been done related to climate science. Or how do you feel that? Do you feel that you have been targeted by those activists, activist politicians or not?

WH: I don’t feel any pain. I don’t pay much attention to them because I have very little respect for them. The people that I respect, most of them agree with me. I’ve personally not suffered from it, perhaps just because I don’t pay attention to it. I’m older, I’m retired, so I’m not dependent on government grants.  Younger people could not do this. So people in the middle of their career have a very serious problem because they’ll lose their research funding and they won’t be able to continue their career if they don’t sign up to the alarmist Dogma.

HS: And one of the things how they shut down criticism is simply by stating that 97% of climate scientists are saying that our climate change or global warming, it is anthropogenic and you cannot argue with 97%, can you? What do you think? Is science democracy?

WH: There are some small anthropogenic effects on climate. Any big city, for example, is quite a bit warmer than the countryside. If you go 30 kilometers outside of New York City, it’s cooler. Or any other big city. So those are called urban heat island effects. So it’s clearly caused by people.

But if you look at undisturbed areas far from urban centers, there the climate is doing what it has always done. It’s warmed, it’s cooled, it’s done that many, many times over history. And there’s not the slightest sign of anything different resulting from our generation burning fossil fuels.

My own guess is that fossil fuels may have caused about close to a degree, maybe three-quarters of a degree of warming, but that’s not very much. When I got up this morning, it was minus 10 Celsius. Here in my office, it’s quite a bit warmer. One degree, you can hardly feel it.  My air conditioner doesn’t trip on and off at one degree, so it’s not a dangerous increase in temperature. Saving the planet from one and a half degree of warming is just crazy. Who cares about one and a half degree of warming? It won’t be that much anyway. But if it were, it wouldn’t matter.

HS: If the planet warms a bit, is it actually bad to us?

WH: No, of course it’s not bad. For example, I have a backyard garden, and I would welcome another week or two of frost-free growing season in the fall and in the spring. I could have a better garden, and that’s true over much of the world.  And if you look at the warming, most of the warming is in high latitudes where it’s cold. It’s where you live in Estonia, where I live in New Jersey. It doesn’t warm in India. It doesn’t warm in the Congo or in the Amazon. Even, you know, the climate models don’t predict that. They predict the warming, when it comes, will be mostly at high latitudes near the poles. And that’s where actually the warming will be good, not bad.

HS: One more question about climate science. It is being told to us that there is a consensus on anthropogenic climate change. And my question actually here is that in science, can there be a consensus? What is a consensus in science even?

WH: Well, I think you know very well that science has nothing to do with consensus. Michael Crichton was very eloquent about this. And if you don’t know about his work, you should read it. But he says when someone uses the word consensus, they’re really talking about politics, not science.

Science is determined by how well your understanding agrees with observations. If you have a theory and it agrees with observations, then the theory is probably right. But it’s right not because everybody, all your friends agree with it, it’s because it agrees with observation. You make a prediction and you do an experiment to see whether the prediction is right. If the experiment confirms it, then the theory is probably okay. It’s not okay because everybody agrees with you that your theory is right. And so that’s what the climate scientists are trying to claim, that science is made by consensus. It’s not made by consensus.  There really is a science that is independent of people. There is a reality that could care less what the consensus is. It’s just the way the world works. And that’s real science.

HS: What are your views on energy transition? Should we, you know, stop burning fossil fuels? And why, if so?

WH: Well, of course, we shouldn’t stop burning fossil fuels. We can’t stop, you know. It’s suicide. It’s economic suicide. And more than economic, it’s real suicide. People will die. You know, they tried something like that in Sri Lanka, you know, 15, 20 years ago when the extremist government came in and stopped the use of chemical fertilizer, you know, because it was unnatural. So everyone was supposed to go back to organic farming and the result was that, you know, the rice crop failed, the tea crop failed, you know, the price of food went up, people were starving in the streets. The same thing will happen if we go to net zero.

You can’t run the world without fossil fuels. We’re completely dependent on them, especially for agriculture, but transportation and many other things. There’s nothing bad about them. If you burn them in a responsible way, they cause no harm. They release beneficial carbon dioxide. Carbon dioxide really benefits the world. It’s not a pollutant at all.

HS: There is the question of how much longer will fossil fuels last. There is a finite number and for years people have wondered when will they run out and what will we do when we run out of fossil fuels. And so that’s an interesting question that’s worth talking about.

WH: It’s not an immediate problem, but sooner or later it will be a problem. My own guess, we’re talking about a century or two, not decades. But I think our descendants will have to replace fossil fuels, and my guess is that they will make synthetic hydrocarbon fuels.  No one has ever discovered a better fuel than a hydrocarbon, you know. We ourselves, you know, store energy as hydrocarbons. You know, the fat on our belly, you know, that’s a hydrocarbon. You know, so it’s really good, you know. So we can make hydrocarbons ourselves from limestone and water if you have enough energy.

There are ways to do that chemically. And so my guess is that in 200 years, that’s the way energy will be… handled. We’ll make it from inorganic carbon, limestone probably, and we’ll burn it the same way we do today. You know, we’ll make synthetic diesel, we’ll make synthetic gasoline, and continue to use internal combustion engines.  No one’s invented a better engine than an internal combustion engine.

HS: But what about nuclear energy? What are your thoughts on that?

WH: Well, nuclear energy clearly works. It makes electricity, so you can’t run your automobile on nuclear energy unless you’re stupid enough to buy an electric car. So nuclear has had some of the same problems as fossil fuels. There are these ideological foes of nuclear energy And they have two main arguments. The first argument, and one that does worry me, is that it’s not that difficult to change a nuclear commercial enterprise into a weapon. And nuclear weapons really are very, very dangerous.

So that’s one of the oppositions. But the other is completely phony, is that we can’t handle the waste. That’s not a difficult problem, actually.  It’s technically quite easy to handle the waste. For example, at a typical nuclear plant in the United States, there’s a dry cask storage yard, which is not as big as the parking lot. And it’s got a century worth of fuel. It’s perfectly safe. And you could leave it there for several centuries and nothing would happen to it.  So there’s no need to process it. You can let it sit there and, you know, in a hundred years, maybe people will regard it as a useful mine for various materials. So nuclear is fine, and I think it will play an important role for a long time in human affairs.

You know, the big dream has always been fusion, nuclear fusion energy, where you combine deuterium and tritium, you know, and make power. That’s turned out to be much, much harder than we ever thought it would be. But my guess is it’s a problem that  will eventually be solved.

Someone will have a really good new idea about how to do it. If we keep smart people working on it, someone will figure out how to do it. So I’m optimistic about the future for energy. I think humanity is going to do fine if they don’t self-destruct.

HS: Well, Professor, to kind of sum up, I would like to ask you about what is, in your opinion, what are the real problems? As I understand, and I tend to agree with you, climate change currently at least is not a real problem for humanity. But probably there are some. And what is your feeling? What are they?

Well, the problem has always been living together. How do you keep humanity from self-destructing? And that’s why I have some sympathy for the climate alarmists. They thought that having climate as a common enemy would be one way to prevent this. So you have to admit that that’s not such a bad motive.

I don’t think it’s true.  I don’t think it will work. I think it’s worse than nothing. But I guess the question is how do we keep people in a civilized society indefinitely? And As I said, I’m a lot better with differential equations and instruments than I am with this sort of a question. But just speaking personally, I think everybody should have a feeling that they’re doing something significant with their lives. So I think anything we can do in society is to let young people feel like they’re significant and they’re doing something worthwhile and useful it would be good for the whole world.

 

 

Climate Crusade Is a Dead End

This post presents the main points and exhibits from Professor de Lange’s presentation February 26, 2025.  Most images are self explanatory, with some excerpts in italics lightly edited from captions, and some added images as well. H/T Bud Bromley.

Prof. de Lange demonstrates that there is no credible climate crisis, and that there is much more to climate than CO2 alone. First, he addresses the discrepancy between satellite temperature measurements and results from climate models. Second, he shows the effect of even doubling the CO2 concentration has only minor effects, while it is in fact crucial to photosynthesis. Third, he shows that how the significant lack of experimental data on cloud composition now hampers progress in climate science. Fourth, he demonstrates that there is no convincing correlation between CO2 and temperature on a geological time scale. Fifth, he addresses global future energy supply, demonstrating that renewables are “unaffordables”, just as are untested technologies (batteries, hydrogen), and he concludes that the future has to be based on nuclear power.

1.  Natural Science and Observations versus Models

2.  Atmospheric Physics and Greenhouse Gases

Warm Surface of the earth can be viewed as a radiator in the infrared that radiates Intensity out Into the atmosphere, and again the flow of infrared energy is not interrupted. It is absorbed by the atmosphere and that’s where the clouds turn out to be extremely important. They delay the outgoing energy into the universe. In climate science we balance the yellow incoming solar energy in watts per square meter with the outgoing radiation from the surface and atmosphere. Some is reflected and some is absorbed and emitted as long wave radiation.  The imbalance is shown at the bottom as ~1 W/m2, which is a small difference between two much larger energy flows showing hundreds of W/m2. If for any reason, there is a slight change in either the incoming or outgoing flows, the imbalance would change dramatically.

The fact that Greenhouse gases play very important role in absorbing infrared radiation in the atmosphere is already 150 years old. We shall see that dependence of the temperature of the earth due to greenhouse gases is not linear, the effect on temperature is logarithmic. This is seen in the graph on the left side.

On the horizontal scale we see the frequency scale expressed in common unit in physics in wave numbers. And here we see the continuous Blue Trace results from infrared radiation that would leave the warm surface of the planet if there were no atmosphere at all. The total surface under the blue trace depends on temperature to the fourth power, very temperature dependent.

We see the effect of atmosphere greenhouse gases represented by the black line, which is a bit lower than the blue Trace. The green line shows the where the black line would be, were there to be no CO2 in the atmosphere. The red line shows that there would be little difference from doubling CO2 from 400 ppm to 800 ppm.

The role of water vapor is terribly important.  Water is the most important Greenhouse gas, but when we Go to clouds, he situation becomes much more complicated than in the absence of clouds. So clouds again are the Achilles heel of of climate Science.  As I said an increase in CO2  leads to a little more warming but the increase is logarithmic. meaning less and Less warming at higher CO2 levels.  Doubling CO2 leads to extra forcing of about 1 percent or about 3 watts per square meter.  Since 1850 when temperature measurements really started since, the planet’s surface has warmed up by about 1°C.   That is not very much, and the effect of CO2 can only be very much smaller.

3.  Scattering in Clouds

The post referenced in the exhibit is Clauser’s Case: GHG Science Wrong, Clouds the Climate Thermostat

4. Is CO2 the only and most important culprit of ‘’disastrous’’ climate change, warming in particular?

5. Supplying Energy to a Growing World Population

Koonin: Reckless Claim of Climate Emergency

Transcript

Hubris is a Greek word that means dangerously overconfident. Based on my research, hubris fairly describes our current response to the issue of climate change.

Here’s what many people believe:

One: The planet is warming catastrophically because of certain human behaviors.
Two: Thanks to powerful computers we can project what the climate will be like
20, 40, or even 100 years from now.
Three: That if we eliminate just one behavior, the burning of fossil fuels,
we can prevent the climate from changing for as long we like.

Each of these presumptions—together, the basis of our hubris regarding the changing climate—is either untrue or so far off the mark as to be useless.

Yes, it’s true that the globe is warming, and that humans are exerting a warming influence upon it. But beyond that, to paraphrase a line from the classic movie The Princess Bride, “I do not think ‘The Science’ says what you think it says.”

For example, government reports state clearly that heat waves in the US are now no more common than they were in 1900.

Hurricane activity is no different than it was a century ago.

Floods have not increased across the globe over more than seventy years.

Source: Voice of International Affairs

Greenland’s ice sheet isn’t shrinking any more rapidly today than it was 80 years ago.

Why aren’t these reassuring facts better known?

Because the public gets its climate information almost exclusively from the media.

And from a media perspective, fear sells.

“Things aren’t that bad” doesn’t sell.

Very few people, and that includes journalists who report on climate news, read the actual science. I have. And what the data—the hard science—from the US government and UN Climate reports say is that… “things aren’t that bad.”

Nor does the public understand the questionable basis of all catastrophic climate change projections: computer modeling.

Projecting future climate is excruciatingly difficult. Yes, there are human influences, but the climate is complex. Anyone who says that climate models are “just physics” either doesn’t understand them or is being deliberately misleading. I should know: I wrote one of the first textbooks on computer modeling.

While modelers base their assumptions upon both fundamental physical laws and observations of the climate, there is still considerable judgment involved. And since different modelers will make different assumptions, results vary widely among different models.

Let’s just take one simple, but significant assumption modelers must make: the impact of clouds on the climate.

Natural fluctuations in the height and coverage of clouds have at least as much of an impact on the flows of sunlight and heat as do human influences. But how can we possibly know global cloud coverage say 10, let alone 50 years from now? Obviously, we can’t. But to create a climate model, we have to make assumptions. That’s a pretty shaky foundation on which to transform the world’s economy.

By the way, creating more accurate models isn’t getting any easier. In fact, the more we learn about the climate system, the more we realize how complex it is.

Rather than admit this complexity, the media, the politicians, and a good portion of the climate science community attribute every terrible storm, every flood, every major fire to “climate change.” Yes, we’ve always had these weather events in the past, the narrative goes, but somehow “climate change” is making everything “worse.”

Even if that were true, isn’t the relevant question, how much worse? Not to mention that “worse” is not exactly a scientific term.  And how would we make it better?  For the alarmists, that’s easy: we get rid of fossil fuels.

Not only is this impractical—we get over 80% of the world’s energy from fossil fuels—it’s not scientifically possible. That’s because CO2 doesn’t disappear from the atmosphere in a few days like, say, smog. It hangs around for a really long time.

About 60 percent of any CO2 that we emit today will remain in the atmosphere 20 years from now, between 30 and 55 percent will still be there after a century, and between 15 and 30 percent will remain after one thousand years.

In other words, it takes centuries for the excess carbon dioxide to vanish from the atmosphere. So, any partial reductions in CO2 emissions would only slow the increase in human influences—not prevent it, let alone reverse it.

CO2 is not a knob that we can just turn down to fix everything. We don’t have that ability. To think that we do is… hubris.

Hubris leads to bad decisions.  A little humility and
a little knowledge would lead to better ones.

I’m Steve Koonin, former Undersecretary for Science in the Obama Administration, and author of Unsettled: What Climate Science Tells Us, What It Doesn’t, and Why It Matters, for Prager University.

Addendum  Fossil Fuels and Greenhouse Gases (GHGs) Climate Science

Professors Lindzen, Happer and Koonin CO2 Coalition Paper April 2024

Table of Contents

I. THERE WILL BE DISASTROUS CONSEQUENCES FOR THE POOR, PEOPLE WORLDWIDE, FUTURE GENERATIONS AND THE WEST IF FOSSIL FUELS, CO2 AND OTHER GHG EMISSIONS ARE REDUCED TO “NET ZERO”

A. CO2 is Essential to Our Food, and Thus to Life on Earth
B. More CO2, Including CO2 from Fossil Fuels, Produces More Food.
C. More CO2 Increases Food in Drought-Stricken Areas.
D. Greenhouse Gases Prevent Us from Freezing to Death
E. Enormous Social Benefits of Fossil Fuels
F. “Net Zeroing” Fossil Fuels Will Cause Massive Human Starvation by Eliminating Nitrogen Fertilizer

II. THE IPCC IS GOVERNMENT CONTROLLED AND THUS ONLY ISSUES GOVERNMENT OPINIONS, NOT SCIENCE

III. SCIENCE DEMONSTRATES FOSSIL FUELS, CO2 AND OTHER GHGs WILL NOT CAUSE CATASTROPHIC GLOBAL WARMING AND EXTREME WEATHER

A. Reliable Science is Based on Validating Theoretical Predictions With Observations, Not Consensus, Peer Review, Government Opinion or Cherry-Picked or Falsified Data
B. The Models Predicting Catastrophic Warming and Extreme Weather Fail the Key Scientific Test: They Do Not Work, and Would Never Be Used in Science.
C. 600 Million Years of CO2 and Temperature Data Contradict the Theory That High Levels of CO2 Will Cause Catastrophic Global Warming.
D. Atmospheric CO2 Is Now “Heavily Saturated,” Which in Physics Means More CO2 Will Have Little Warming Effect.
E. The Theory Extreme Weather is Caused by Fossil Fuels, CO2 and Other GHGs is Contradicted by the Scientific Method and Thus is Scientifically Invalid

 

 

 

 

 

Good Reasons to Distrust Climatists

The most recent case of climatists’ bad behavior is the retraction of a peer-reviewed paper analyzing the properties of CO2 as an IR active gas, concluding that additional levels of atmospheric CO2 will have negligible effect on temperatures.  From the Daily Sceptic:

Another important paper taking issue with the ‘settled’ climate narrative has been cancelled following a report in the Daily Sceptic and subsequent reposts that went viral across social media. The paper discussed the atmospheric ‘saturation’ of greenhouse gases such as carbon dioxide and argued that higher levels will not cause temperatures to rise. The work was led by the widely-published Polish scientist Dr. Jan Kubicki and appeared on Elsevier’s ScienceDirect website in December 2023. The paper has been widely discussed on social media since April 2024 when the Daily Sceptic reported on the findings. Interest is growing in the saturation hypothesis not least because it provides a coherent explanation for why life and the biosphere grew and often thrived for 600 million years despite much higher atmospheric levels of greenhouse gases. Alas for control freaks, it also destroys the science backing for the Net Zero fantasy.

Below are some comments responding to a Quora question, text in italics with my bolds and added images:

What are some reasons why some people do not believe in climate change or global warming despite scientific evidence? Is there any additional information that could help us understand their perspective?

Answer from Mike Jonas,  M.A. in Mathematics, Oxford University, UK, 

Good scientists do not lie and cheat to protect their science, they are happy to discuss their evidence and their findings, and they always understand that everything needs to be replicable and verifiable.

When Climategate erupted on the scene, and the climate scientists behind the man-made global warming narrative were found to have lied and cheated, all honest scientists thought that would be the end of it. Instead, what happened was that those climate scientists closed ranks and carried on, supported by a massive amount of government (ie, the public’s) money. One of the first things they did was to deflect Climategate by saying the emails involved had been hacked so should be ignored, but some of the people involved confirmed that all of the emails really were genuine.

It has been about 15 years since Climategate, and study after study has shown virtually all of the components of the man-made global warming narrative to be incorrect, even that none of the computer models used by the IPCC are fit for purpose,

And yet they maintained their closed ranks,
and the government money kept pouring in.

Did you know that the IPCC does not do any research (please do check that, on their web page About – IPCC they state “The IPCC does not conduct its own research”). It is, as its name says, an inter-governmental organisation, and it is run by and for governments. They say lots of persuasive sciency things, but the simple fact is that they cherry-pick and corrupt the science to achieve their ends. Regrettably, almost all the scientific societies are on the gravy train too. This is part of what the highly respected physicist Professor Hal Lewis said in his resignation letter to the American Physical Society (APS):

It is of course, the global warming scam, with the (literally) trillions of dollars driving it, that has corrupted so many scientists, and has carried APS before it like a rogue wave. It is the greatest and most successful pseudoscientific fraud I have seen in my long life as a physicist. Anyone who has the faintest doubt that this is so should force himself to read the ClimateGate documents, which lay it bare.

I don’t believe that any real physicist, nay scientist, can read that stuff without revulsion. I would almost make that revulsion a definition of the word scientist.

So what has the APS, as an organization, done in the face of this challenge?
It has accepted the corruption as the norm, and gone along with it.

If you want to find out more about this “greatest and most successful pseudoscientific fraud”, the website Watts Up With That? is a good place to start (the fraudsters absolutely hate it), and it links to many other good websites. It has the full text of Hal Lewis’ resignation letter at:

Hal Lewis: My Resignation From The American Physical Society – an important moment in science history

Answer from Susannah Moyer

It’s curious that climate science is the rare scientific field where dissenting scientists, those with contrarian views, are unwelcome and even ostracized.

There are some well known climate scientists that have doubts about the role of CO2 and man made global warming as it pertains to global temperature. They have raised the issue that computer generated prediction models have been inaccurate in predicting temperature patterns because the modeling requires assumptions that have not been shown to be accurate.

Here is a contrarian view from climate scientists who have published climate research results in Nature, which is no small feat:

McNider and Christy are professors of atmospheric science at the University of Alabama in Huntsville and fellows of the American Meteorological Society. Mr. Christy was a member of the Intergovernmental Panel on Climate Change that shared the 2007 Nobel Peace Prize with former Vice President Al Gore.

It is not a known fact by how much the Earth’s atmosphere will warm in response to this added carbon dioxide. The warming numbers most commonly advanced are created by climate computer models built almost entirely by scientists who believe in catastrophic global warming. The rate of warming forecast by these models depends on many assumptions and engineering to replicate a complex world in tractable terms, such as how water vapor and clouds will react to the direct heat added by carbon dioxide or the rate of heat uptake, or absorption, by the oceans.

We might forgive these modelers if their forecasts had not been so consistently and spectacularly wrong. From the beginning of climate modeling in the 1980s, these forecasts have, on average, always overstated the degree to which the Earth is warming compared with what we see in the real climate.

For instance, in 1994 we published an article in the journal Nature showing that the actual global temperature trend was “one-quarter of the magnitude of climate model results.” As the nearby graph shows, the disparity between the predicted temperature increases and real-world evidence has only grown in the past 20 years.

“Consensus” science that ignores reality can have tragic consequences if cures are ignored or promising research is abandoned. The climate-change consensus is not endangering lives, but the way it imperils economic growth and warps government policy making has made the future considerably bleaker. The recent Obama administration announcement that it would not provide aid for fossil-fuel energy in developing countries, thereby consigning millions of people to energy poverty, is all too reminiscent of the Sick and Health Board denying fresh fruit to dying British sailors.

Another questioner, Dr. Koonin was undersecretary for science in the Energy Department during President Barack Obama’s first term and is currently director of the Center for Urban Science and Progress at New York University. His previous positions include professor of theoretical physics and provost at Caltech, as well as chief scientist of BP, where his work focused on renewable and low-carbon energy technologies.

But—here’s the catch—those questions are the hardest ones to answer. They challenge, in a fundamental way, what science can tell us about future climates.

Firstly, even though human influences could have serious consequences for the climate, they are physically small in relation to the climate system as a whole. For example, human additions to carbon dioxide in the atmosphere by the middle of the 21st century are expected to directly shift the atmosphere’s natural greenhouse effect by only 1% to 2%. Since the climate system is highly variable on its own, that smallness sets a very high bar for confidently projecting the consequences of human influences.

A second challenge to “knowing” future climate is today’s poor understanding of the oceans. The oceans, which change over decades and centuries, hold most of the climate’s heat and strongly influence the atmosphere. Unfortunately, precise, comprehensive observations of the oceans are available only for the past few decades; the reliable record is still far too short to adequately understand how the oceans will change and how that will affect climate.

A third fundamental challenge arises from feedbacks that can dramatically amplify or mute the climate’s response to human and natural influences. One important feedback, which is thought to approximately double the direct heating effect of carbon dioxide, involves water vapor, clouds and temperature.

Climate Science Is Not Settled

Another group questioning what some consider “settled science”:

  • Claude Allegre, former director of the Institute for the Study of the Earth, University of Paris;
  • J. Scott Armstrong, cofounder of the Journal of Forecasting and the International Journal of Forecasting;
  • Jan Breslow, head of the Laboratory of Biochemical Genetics and Metabolism, Rockefeller University;
  • Roger Cohen, fellow, American Physical Society;
  • Edward David, member, National Academy of Engineering and National Academy of Sciences;
  • William Happer, professor of physics, Princeton;
  • Michael Kelly, professor of technology, University of Cambridge, U.K.;
  • William Kininmonth, former head of climate research at the Australian Bureau of Meteorology;
  • Richard Lindzen, professor of atmospheric sciences, MIT;
  • James McGrath, professor of chemistry, Virginia Technical University;
  • Rodney Nichols, former president and CEO of the New York Academy of Sciences;
  • Burt Rutan, aerospace engineer, designer of Voyager and SpaceShipOne;
  • Harrison H. Schmitt, Apollo 17 astronaut and former U.S. senator;
  • Nir Shaviv, professor of astrophysics, Hebrew University, Jerusalem;
  • Henk Tennekes, former director, Royal Dutch Meteorological Service;
  • Antonio Zichichi, president of the World Federation of Scientists, Geneva.

Although the number of publicly dissenting scientists is growing, many young scientists furtively say that while they also have serious doubts about the global-warming message, they are afraid to speak up for fear of not being promoted—or worse. They have good reason to worry. In 2003, Dr. Chris de Freitas, the editor of the journal Climate Research, dared to publish a peer-reviewed article with the politically incorrect (but factually correct) conclusion that the recent warming is not unusual in the context of climate changes over the past thousand years. The international warming establishment quickly mounted a determined campaign to have Dr. de Freitas removed from his editorial job and fired from his university position. Fortunately, Dr. de Freitas was able to keep his university job.

This is not the way science is supposed to work, but we have seen it before—for example, in the frightening period when Trofim Lysenko hijacked biology in the Soviet Union. Soviet biologists who revealed that they believed in genes, which Lysenko maintained were a bourgeois fiction, were fired from their jobs. Many were sent to the gulag and some were condemned to death.

Why is there so much passion about global warming, and why has the issue become so vexing that the American Physical Society (APS), from which Dr. Giaever resigned a few months ago, refused the seemingly reasonable request by many of its members to remove the word “incontrovertible” from its description of a scientific issue?

There are several reasons, but a good place to start is the old question
“cui bono?” Or the modern update, “Follow the money.”

 

 

 

 

Happer: Cloud Radiation Matters, CO2 Not So Much (2025)

This month van Wijngaarden and Happer published a new paper Radiation Transport in Clouds.

Last year William Happer spoke on Radiation Transfer in Clouds at the EIKE conference, and the video is above.  For those preferring to read, below is a transcript from the closed captions along with some key exhibits.  I left out the most technical section in the latter part of the presentation. Text in italics with my bolds.

William Happer: Radiation Transfer in Clouds

People have been looking at Clouds for a very long time in in a quantitative way. This is one of the first quantitative studies done about 1800. And this is John Leslie,  a Scottish physicist who built this gadget. He called it an Aethrioscope, but basically it was designed to figure out how effective the sky was in causing Frost. If you live in Scotland you worry about Frost. So it consisted of two glass bulbs with a very thin capillary attachment between them. And there was a little column of alcohol here.

The bulbs were full of air, and so if one bulb got a little bit warmer it would force the alcohol up through the capillary. If this one got colder it would suck the alcohol up. So he set this device out under the clear sky. And he described that the sensibility of the instrument is very striking. For the liquor incessantly falls and rises in the stem with every passing cloud. in fine weather the aethrioscope will seldom indicate a frigorific impression of less than 30 or more than 80 millesimal degrees. He’s talking about how high this column of alcohol would go up and down if the sky became overclouded. it may be reduced to as low as 15 refers to how much the sky cools or even five degrees when the congregated vapours hover over the hilly tracks. We don’t speak English that way anymore but I I love it.

The point was that even in 1800 Leslie and his colleagues knew very well that clouds have an enormous effect on the cooling of the earth. And of course anyone who has a garden knows that if you have a clear calm night you’re likely to get Frost and lose your crops. So this was a quantitative study of that.

Now it’s important to remember that if you go out today the atmosphere is full of two types of radiation. There’s sunlight which you can see and then there is the thermal radiation that’s generated by greenhouse gases, by clouds and by the surface of the Earth. You can’t see thermal radiation but you you can feel it if it’s intense enough by its warming effect. And these curves practically don’t overlap so we’re really dealing with two completely different types of radiation.

There’s sunlight which scatters very nicely and off of not only clouds but molecules; it’s the blue sky the Rayleigh scattering. Then there’s the thermal radiation which actually doesn’t scatter at all on molecules so greenhouse gases are very good at absorbing thermal radiation but they don’t scatter it. But clouds scatter thermal radiation and plotted here is the probability that you will find Photon of sunlight between you know log of its wavelength and the log of in this interval of the wavelength scale.

Since Leslie’s day two types of instruments have been developed to do what he did more precisely. One of them is called a pyranometer and this is designed to measure sunlight coming down onto the Earth on a day like this. So you put this instrument out there and it would read the flux of sunlight coming down. It’s designed to see sunlight coming in every direction so it doesn’t matter which angle the sun is shining; it’s uh calibrated to see them all.

Let me show you a measurement by a pyranometer. This is a actually a curve from a sales brochure of a company that will sell you one of these devices. It’s comparing two types of detectors and as you can see they’re very good you can hardly tell the difference. The point is that if you look on a clear day with no clouds you see sunlight beginning to increase at dawn it peaks at noon and it goes down to zero and there’s no sunlight at night. So half of the day over most of the Earth there’s no sunlight in the in the atmosphere.

Here’s a day with clouds, it’s just a few days later shown by days of the year going across. You can see every time a cloud goes by the intensity hitting the ground goes down. With a little clear sky it goes up, then down up and so on. On average at this particular day you get a lot less sunlight than you did on the clear day.

But you know nature is surprising. Einstein had this wonderful quote: God is subtle but he’s not malicious. He meant that nature does all of sorts of things you don’t expect, and so let me show you what happens on a partly cloudy day. Here so this is data taken near Munich. The blue curve is the measurement and the red curve is is the intensity on the ground if there were no clouds. This is a partly cloudy day and you can see there are brief periods when the sunlight is much brighter on the detector on a cloudy day than it is on the clear day. And that’s because coming through clouds you get focusing from the edges of the cloud pointing down toward your detector. That means somewhere else there’s less radiation reaching the ground. But this is rather surprising to most people. I was very surprised to learn about it but it just shows that the actual details of climate are a lot more subtle than you might think.

We know that visible light only happens during the daytime and stops at night. There’s a second type of important radiation which is the thermal radiation which is measured by a similar device. You have a silicon window that passes infrared, which is below the band gap of silicon, so it passes through it as though transparent. Then there’s some interference filters here to give you further discrimination against sunlight. So sunlight practically doesn’t go through this at all, so they call it solar solar blind since it doesn’t see the Sun.

But it sees thermal radiation very clearly with a big difference between this device and the sunlight sensing device I showed you. Because actually most of the time this is radiating up not down. Out in the open air this detector normally gets colder than the body of the instrument. And so it’s carefully calibrated for you to compare the balance of down coming radiation with the upcoming radiation. Upcoming is normally greater than down coming.

I’ll show you some measurements of the downwelling flux here; these are actually in Greenland in Thule and these are are watts per square meter on the vertical axis here. The first thing to notice is that the radiation continues day and night you can you if you look at the output of the pyrgeometer you can’t tell whether it’s day or night because the atmosphere is just as bright at night as it is during the day. However, the big difference is clouds: on a cloudy day you get a lot more downwelling radiation than you do on a clear day. Here’s a a near a full day of clear weather there’s another several days of clear weather. Then suddenly it gets cloudy. Radiation rises because the bottoms of the clouds are relatively warm at least compared to the clear sky. I think if you put the numbers In, this cloud bottom is around 5° Centigrade so it was fairly low Cloud. it was summertime in Greenland and this compares to about minus 5° for the clear sky.

So there’s a lot of data out there and there really is downwelling radiation there no no question about that you measure it routinely. And now you can do the same thing looking down from satellites so this is a picture that I downloaded a few weeks ago to get ready for this talk from Princeton and it was from Princeton at 6 PM so it was already dark in Europe. So this is a picture of the Earth from a geosynchronous satellite that’s parked over Ecuador. You are looking down on the Western Hemisphere and this is a filtered image of the Earth in Blue Light at 47 micrometers. So it’s a nice blue color not so different from the sky and it’s dark where the sun has set. There’s still a fair amount of sunlight over the United States and the further west.

Here is exactly the same time and from the same satellite the infrared radiation coming up at 10.3 which is right in the middle of the infrared window where there’s not much Greenhouse gas absorption; there’s a little bit from water vapor but very little, trivial from CO2.

As you can see, you can’t tell which side is night and which side is day. So even though the sun has set over here it is still glowing nice and bright. There’s sort of a pesky difference here because what you’re looking at here is reflected sunlight over the intertropical Convergence Zone. There are lots of high clouds that have been pushed up by the convection in the tropics and uh so this means more visible light here. You’re looking at emission of the cloud top so this is less thermal light so white here means less light, white there means more light so you have to calibrate your thinking. to

But the Striking thing about all of this: if you can see the Earth is covered with clouds, you have to look hard to find a a clear spot of the earth. Roughly half of the earth maybe is clear at any given time but most of it’s covered with clouds. So if anything governs the climate it is clouds and and so that’s one of the reasons I admire so much the work that Svensmark and Nir Shaviv have done. Because they’re focusing on the most important mechanism of the earth: it’s not Greenhouse Gases, it’s Clouds. You can see that here.

Now this is a single frequency let me show you what happens if you look down from a satellite and do look at the Spectrum. This is the spectrum of light coming up over the Sahara Desert measured from a satellite. And so here is the infrared window; there’s the 10.3 microns I mentioned in the previous slide it’s it’s a clear region. So radiation in this region can get up from the surface of the Sahara right up to outer space.

Notice that the units on these scales are very different; over the Sahara the top unit is 200, 150 over the Mediterranean and it’s only 60 over the South Pole. But at least the Mediterranean and the Sahara are roughly similar so the right side here these three curves on the right are observations from satellites and the three curves on the left are are calculations modeling that we’ve done. The point here is that you can hardly tell the difference between a model calculation and observed radiation.

So it’s really straightforward to calculate radiation transfer. If someone quotes you a number in watts per square centimeter you should take it seriously; that probably a good number. If they tell you a temperature you don’t know what to make about it. Because there’s a big step between going from watts per square centimeter to a temperature change. All the mischief in the whole climate business is going from watts per square centimeter to to Centigrade or Kelvin.

Now I will say just a few words about clear sky because that is the simplest. Then we’ll get on to clouds, the topic of this talk. This is a calculation with the same codes that I showed you in the previous slide which as you saw work very well. It’s worth spending a little time because this is the famous Planck curve that was the birth of quantum mechanics. There is Max Planck who figured out what the formula for that curve is and why it is that way. This is what the Earth would radiate at 15° Centigrade if there were no greenhouse gases. You would get this beautiful smooth curve the Planck curve. If you actually look at the Earth from the satellites you get a raggedy jaggedy black curve. We like to call that the Schwarzchild curve because Carl Schwarzchild was the person who showed how to do that calculation. Tragically he died during World War I, a Big Big loss to science.

There are two colored curves that I want to draw your attention. The green curve is is what Earth would radiate to space if you took away all the CO2 so it only differs from the black curve you know in the CO2 band here this is the bending band of CO2 which is the main greenhouse effect of CO2. There’s a little additional effect here which is the asymmetric stretch but it it doesn’t contribute very much. Then here is a red curve and that’s what happens if you double CO2.

So notice the huge asymmetry. If taking all 400 parts per million of CO2 away from the atmosphere causes this enormous change 30 watts per square meter, the difference between this green 307 and and the black 277, that’s 30 watts per square meter. But if you double CO2 you practically don’t make any change. This is the famous saturation of CO2. At the levels we have now doubling CO2, a 100% Increase of CO2 only changes the radiation to space by 3 watts per square meter. The difference between 274 for the red curve and 277 for the curve for today. So it’s a tiny amount: for 100% increase in CO2 a 1% decrease of radiation to space.

That allows you to estimate the feedback-free climate sensitivity in your head. I’ll talk you through the feedback-free climate free sensitivity. So doubling CO2 is a 1% decrease of radiation to space. If that happens then the Earth will start to warm up. But it will radiate as the fourth power of the temperature. So temperature starts to rise but if you’ve got a fourth power, the temperature only has to rise by one-quarter of a percent absolute temperature. So a 1% forcing in watts per square centimeter is a one-quarter percent of temperature in Kelvin. Since the ambient Kelvin temperature is about 300 Kelvin (actually a little less) a quarter of that is 75 Kelvin. So the feedback free equilibrium climate sensitivity is less than 1 Degree. It’s 0.75 Centigrade. It’s a number you can do in your head.

So when you hear about 3 centigrade instead of .75 C that’s a factor of four, all of which is positive feedback. So how is there really that much positive feedback? Because most feedbacks in nature are negative. The famous Le Chatelier principle which says that if you perturb a system it reacts in a way to to dampen the perturbation not increase it. There are a few positive feedback systems that we’re familiar with for example High explosives have positive feedback. So if the earth’s climate were like other positive feedback systems, all of them are highly explosive, it would have exploded a long time ago. But the climate has never done that, so the empirical observational evidence from geology is that the climate is like any other feedback system it’s probably negative Okay so I leave that thought with you and and let me stress again:

This is clear skies no clouds; if you add clouds all this does is
suppress the effects of changes of the greenhouse gas.

So now let’s talk about clouds and the theory of clouds, since we’ve already seen clouds are very important. Here is the formidable equation of transfer which has been around since Schwarzchild’s day. So some of the symbols here relate to the intensity, another represents scattering. If you have a thermal radiation on a greenhouse gas where it comes in and immediately is absorbed, there’s no scattering at all. If you hit a cloud particle it will scatter this way or that way, or some maybe even backwards.

So all of that’s described by this integral so you’ve got incoming light at One Direction and you’ve got outgoing light at a second Direction. And then at the same time you’ve got thermal radiation so the warm particles of the cloud are are emitting radiation creating photons which are coming out and and increasing the Earth glow the and this is represented by two parameters. Even a single cloud particle has an albedo, this is is the fraction of radiation that hits the cloud that is scattered as opposed to absorbed and being converted to heat. It’s a very important parameter for visible light and white clouds, typically 99% of the encounters are scattered. But for thermal radiation it’s much less. So water scatters thermal radiation only half as efficiently as shorter wavelengths.

The big problem is that in spite of all the billions of dollars that we have spent, these things which should be known and and would have been known if there hadn’t been this crazy fixation on carbon dioxide and greenhouse gases. And so we’ve neglected working on these areas that are really important as opposed to the trivial effects of greenhouse gases. Attenuation in a cloud is both scattering and absorption. Of course you have to solve these equations for every different frequency of the light because especially for molecules, there’s a strong frequency dependence.

In summary,  let me show you this photo which was taken by Harrison Schmitt who was a friend of mine on one of the first moonshots. It was taken in December and looking at this you can see that they were south of Madagascar when the photograph was taken. You can see it was Winter because here the Intertropical Convergence Zone is quite a bit south of the Equator; it’s moved Way South of India and Saudi Arabia. By good luck they had the sun behind them so they had the whole earth Irradiated.

There’s a lot of information there and and again let me draw your attention to how much of the Earth is covered with clouds. So only very small parts of the Earth can actually be directly affected by greenhouse gases, of the order of half. The takeaway message is that clouds and water vapor are much more important than greenhouse gases for earth’s climate. The second point is the reason they’re much more important: doubling CO2 as I indicated in the middle of the talk only causes a 1% difference of radiation to space. It is a very tiny effect because of saturation. You know people like to say that’s not so, but you can’t really argue that one, even the IPCC gets the same numbers that we do.

And you also know that covering half of the sky with clouds will decrease solar heating by 50%. So for clouds it’s one to one, for greenhouse gases it’s a 100 to one. If you really want to affect the climate, you want to do something to the clouds. You will have a very hard time making any difference with Net Zero with CO2 if you are alarmed about the warmings that have happened.

So one would hope that with all the money that we’ve spent trying to turn CO2 into a demon that some good science has come out of it. From my point of view this is a small part of it, this scattering theory that I think will be here a long time after the craze over greenhouse gases has gone away. I hope there will be other things too. You can point to the better instrumentation that we’ve got, satellite instrumentation as well as ground instrumentation. So that’s been a good investment of money. But the money we’ve spent on supercomputers and modeling has been completely wasted in my view.

Lacking Data, Climate Models Rely on Guesses

A recent question was posed on  Quora: Say there are merely 15 variables involved in predicting global climate change. Assume climatologists have mastered each variable to a near perfect accuracy of 95%. How accurate would a climate model built on this simplified system be?  Keith Minor has a PhD in organic chemistry, PhD in Geology, and PhD in Geology & Paleontology from The University of Texas at Austin.  He responded with the text posted below in italics with my bolds and added images.

I like the answers to this question, and Matthew stole my thunder on the climate models not being statistical models. If we take the question and it’s assumptions at face value, one unsolvable overriding problem, and a limit to developing an accurate climate model that is rarely ever addressed, is the sampling issue. Knowing 15 parameters to 99+% accuracy won’t solve this problem.

The modeling of the atmosphere is a boundary condition problem. No, I’m not talking about frontal boundaries. Thermodynamic systems are boundary condition problems, meaning that the evolution of a thermodynamic system is dependent not only on the conditions at t > 0 (is the system under adiabatic conditions, isothermal conditions, do these conditions change during the process, etc.?), but also on the initial conditions at t = 0 (sec, whatever). Knowing almost nothing about what even a fraction of a fraction of the molecules in the atmosphere are doing at t = 0 or at t > 0 is a huge problem to accurately predicting what the atmosphere will do in the near or far future. [See footnote at end on this issue.]

Edward Lorenz attempted to model the thermodynamic behavior of the atmosphere by using models that took into account twelve variables (instead of fifteen as posed by the questioner), and found (not surprisingly) that there was a large variability in the models. Seemingly inconsequential perturbations would lead to drastically different results, which diverged (euphemism for “got even worse”) the longer out in time the models were run (they still do). This presumably is the origin of Lorenz’s phrase “the butterfly effect”. He probably meant it to be taken more as an instructive hypothetical rather than a literal effect, as it is too often taken today. He was merely illustrating the sensitivity of the system to the values of the parameters, and not equating it to the probability of outcomes, chaos theory, etc., which is how the term has come to be known. This divergence over time is bad for climate models, which try to predict the climate decades from now. Just look at the divergence of hurricane “spaghetti” models, which operate on a multiple-week scale.

The sources of variability include:

♦  the inability of the models to handle water (the most important greenhouse gas in the atmosphere, not CO2) and processes related to it;
♦  e.g., models still can’t handle the formation and non-formation of clouds;
♦  the non-linearity of thermodynamic properties of matter (which seem to be an afterthought, especially in popular discussions regarding the roles that CO2 plays in the atmosphere and biosphere), and
♦  the always-present sampling problem.

While in theory it is possible to know what a statistically significant number of the air and water molecules are doing at any point in time (that would be a lot of atoms and molecules!), a statistically significant sample of air molecules is certainly not being sampled by releasing balloons twice a day from 90 some odd weather stations in the US and territories, plus the data from commercial aircraft, plus all of the weather data from around the World. Doubling this number wouldn’t help, i.e wouldn’t make any difference. Though there are some blind spots, such as northeast Texas that might benefit from having a radar in the area. So you have to weigh the cost of sampling more of the atmosphere versus the 0% increase in forecasting accuracy (within experimental error) that you would get by doing so.

I’ll go out on a limb and say that the NWS (National Weather Service) is actually doing pretty good job in their 5-day forecasts with the current data and technologies that they have (e.g., S-band radar), and the local meteorologists use their years of experience and judgment to refine the forecasts to their viewing areas. The old joke is that a meteorologist’s job is the one job where you can be wrong more than half the time and still keep your job, but everyone knows that they go to work most, if not all, days with one hand tied behind their back, and sometimes two! The forecasts are not that far off on average, and so meteorologists get my unconditional respect.

In spite of these daunting challenges, there are certainly a number of areas in weather forecasting that can be improved by increased sampling, especially on a local scale. For example, for severe weather outbreaks, the CASA project is being implemented using multiple, shorter range radars that can get multiple scan directions on nearby severe-warned cells simultaneously. This resolves the problem caused by the curvature of the Earth as well as other problems associated with detecting storm-scale features tens or hundreds of miles away from the radar. So high winds, hail, and tornadoes are weather events where increasing the local sampling density/rate might help improve both the models and forecasts.

Prof. Wurman at OU has been doing this for decades with his pioneering work with mobile radar (the so-called “DOW’s”). Let’s not leave out the other researchers who have also been doing this for decades. The strategy of collecting data on a storm from multiple directions at short distances, coupled with supercomputer capabilities, has been paying off for a number of years. As a recent example, Prof. Orf at UW Madison, with his simulation of the May 24th, 2011 El Reno, OK tornado (you’ve probably seen it on the Internet), has shed light on some of the “black box” aspects to how tornadoes form. [Video below is Leigh Orf 1.5 min segment for 2018 Blue Waters Symposium plenary session. This segment summarizes, in 90 seconds, some of the team’s accomplishments on the Blue Waters supercomputer over the past five years.]

Prof. Orf’s simulation is just that, and the resolution is around ~10 m (~33 feet), but it illustrates how increased targeted sampling can be effective in at least understanding the complex, thermodynamic processes occurring within a storm. Colleagues have argued that the small improvements in warning times in the last couple of decades are really due more to the heavy spotter presence these days rather than case studies of severe storms. That may be true. However, in test cases of the CASA system, it picked out the subtle boundaries along which the storms fired that did go unnoticed with the current network of radars. So I’m optimistic about increased targeted sampling for use in an early warning system.

These two examples bring up a related problem-too much data! As commented on by a local meteorologist at a TESSA meeting, one of the issues with CASA that will have to be resolved is how to handle/process the tremendous amounts of data that will be generated during a severe weather outbreak. This is different from a research project where you can take your data back to the “lab”. In a real-time system, such as CASA, you need to have the ability to process the volumes of data rapidly so a meteorologist can quickly make a decision and get that life-saving info to the public. This data volume issue may be less of a problem for those using the data to develop climate models.

So back to the Quora question, with regard to a cost-effective (cost-effect is the operational term) climate model or models (say an ensemble model) that would “verify” say 50 years from now, the sampling issue is ever present, and likely cost-prohibitive at the level needed to make the sampling statistically significant. And will the climatologist be around in 50 years to be “hoisted with their own petard” when the climate model is proven to be wrong? The absence of accountability is the other problem with these long-range models into which many put so much faith.

But don’t stop using or trying to develop better climate models. Just be aware of what variables they include, how well they handle the parameters, and what their limitations are. How accurate would a climate model built on this simplified system [edit: of 15 well-defined variables (to 95% confidence level)] be? Not very!

My Comment

As Dr. Minor explains, powerful modern computers can process detailed observation data to simulate and forecast storm activity.  There are more such tools for preparing and adapting to extreme weather events which are normal in our climate system and beyond our control.  He also explains why long-range global climate models presently have major limitations for use by policymakers.

Footnote Regarding Initial Conditions Problem

What About the Double Pendulum?

Trajectories of a double pendulum

comment by tom0mason at alerted me to the science demonstrated by the double compound pendulum, that is, a second pendulum attached to the ball of the first one. It consists entirely of two simple objects functioning as pendulums, only now each is influenced by the behavior of the other.

Lo and behold, you observe that a double pendulum in motion produces chaotic behavior. In a remarkable achievement, complex equations have been developed that can and do predict the positions of the two balls over time, so in fact the movements are not truly chaotic, but with considerable effort can be determined. The equations and descriptions are at Wikipedia Double Pendulum

Long exposure of double pendulum exhibiting chaotic motion (tracked with an LED)

But here is the kicker, as described in tomomason’s comment:

If you arrive to observe the double pendulum at an arbitrary time after the motion has started from an unknown condition (unknown height, initial force, etc) you will be very taxed mathematically to predict where in space the pendulum will move to next, on a second to second basis. Indeed it would take considerable time and many iterative calculations (preferably on a super-computer) to be able to perform this feat. And all this on a very basic system of known elementary mechanics.

Our Chaotic Climate System

 

 

IPCC Crusade Built on Science Mistakes

“Mistake” definition (American Heritage Dictionary)

Noun

  1. An error or fault resulting from defective judgment, deficient knowledge, or carelessness.
  2. A misconception or misunderstanding.

Five Major IPCC Science Mistakes

♦  Surface stations records have warmed mostly from urban heat sources, not IR-active gases.

♦  Solar climate forcing varies more than IPCC admits.

♦  Experiments show more CO2 does not make air warmer.

♦  On all time scales temperature changes lead and CO2 changes follow.

♦  IPCC climate models exclude natural climate factors to blame all warming on GHGs.

Mistakes on Temperature Records and Solar Forcing

The first two misconceptions are described in a recent paper by CERES (Center for Environmental Research and Earth Sciences).  My post below provides the details.

Overview of CERES Study

Our review suggests that the IPCC reports have inadequately accounted for two major scientific concerns when they were evaluating the causes of global warming since the 1850s:

1. The global temperature estimates used in the IPCC reports are contaminated by urban warming biases.
2.  The estimates of solar activity changes since the 1850s considered by the IPCC substantially downplayed a possible large role for the Sun.

We conclude that it is not scientifically valid for the IPCC to rule out the possibility that global warming might be mostly natural.

Fatal Flaw Discredits IPCC Science

By way of John Ray comes this Spectator Australia article A basic flaw in IPCC science.  Excerpts in italics with my bolds and added images.

Detailed research is underway that threatens to undermine the foundations of the climate science promoted by the IPCC since its First Assessment Report in 1992. The research is re-examining the rural and urban temperature records in the Northern Hemisphere that are the foundation for the IPCC’s estimates of global warming since 1850. The research team has been led by Dr Willie Soon (a Malaysian solar astrophysicist associated with the Smithsonian Institute for many years) and two highly qualified Irish academics – Dr Michael Connolly and his son Dr Ronan Connolly. They have formed a climate research group CERES-SCIENCE. Their detailed research will be a challenge for the IPCC 7th Assessment Report due to be released in 2029 as their research results challenge the very foundations of IPCC science.

The climate warming trend published by the IPCC is a continually updated graph based on the temperature records of Northern Hemisphere land surface temperature stations dating from the mid 19th Century. The latest IPCC 2021 report uses data for the period 1850-2018. The IPCC’s selection of Northern Hemisphere land surface temperature records is not in question and is justifiable. The Northern Hemisphere records provide the best database for this period. The Southern Hemisphere land temperature records are not that extensive and are sparse for the 19th and early 20th Century. It is generally agreed that the urban temperature data is significantly warmer than the rural data in the same region because of an urban warming bias. This bias is due to night-time surface radiation of the daytime solar radiation absorbed by concrete and bitumen. Such radiation leads to higher urban night-time temperatures than say in the nearby countryside. The IPCC acknowledges such a warming bias but alleges the increased effect is only 10 per cent and therefore does not significantly distort its published global warming trend lines.


Since 2018, Dr Soon and his partners have analysed the data from rural and urban temperature recording stations in China, the USA, the Arctic, and Ireland. The number of stations with reliable temperature records in these areas increased from very few in the mid-19th Century to around 4,000 in the 1970s before decreasing to around 2,000 by the 1990s. The rural temperature recording stations with good records peaked at 400 and are presently around 200.

Their analysis of individual stations needs to account for any variation in their exposure to the Sun due to changes in their location, OR shadowing due to the construction of nearby buildings, OR nearby vegetation growth. The analysis of rural temperature stations is further complicated as over time many are encroached by nearby cities. Consequently, the data from such stations needs to be shifted at certain dates from the rural temperature database to either an intermediate database or to a full urban database. Consequently, an accurate analysis of the temperature records of each recording station is a time-consuming task.


This new analysis of 4,000 temperature recording stations in China, the USA, the Arctic, and Ireland shows a warming trend of 0.89ºC per century in the urban stations that is 1.61 times higher that a warming trend of 0.55ºC per century in the rural stations. This difference is far more significant than the 10 per cent divergence between urban and rural stations alleged in the IPCC reports; a divergence explained by a potential flaw in the IPCC’s methodology. The IPCC uses a technique called homogenisation that averages the rural and urban temperatures in a particular region. This method distorts the rural temperature records as over 75 per cent of the temperature records used in this homogenisation methodology are urban stations. So, a methodology that attempts to statistically identify and correct some biases that may be in the raw data, in effect, leads to an urban blending of the rural dataset. This result is biased as it downgrades the actual values of each rural temperature station. In contrast, Dr Soon and his coworkers avoided homogenisation so the temperature trends they identify for each rural region are accurate as the rural data are not distorted by the readings from nearby urban stations.


The rural temperature trend measured by this new research is 0.55ºC per century and it indicates the Earth has warmed 0.9ºC since 1850. In contrast, the urban temperature trend measured by this new research is 0.89ºC per century and indicates a much higher warming of 1.5ºC since 1850. Consequently, a distorted urban warming trend has been used by the IPCC to quantify the warming of the whole of the Earth since 1850. The exaggeration is significant as the urban temperature record database used by the IPCC only represents the temperatures on 3-4 per cent of the Earth’s land surface area; an area less than 2 per cent of the Earth’s total surface area. During the next few years, Dr Willie Soon and his research team are currently analysing the meta-history of 800 European temperature recording stations. When this is done their research will be based on very significant database of Northern Hemisphere rural and urban temperature records from China, the USA, the Arctic, Ireland, and Europe.

This new research has unveiled another flaw in the IPCC‘s temperature narrative as trend lines in its revised temperature datasets are different from those published by the IPCC. For example, the rural records now show a marked warming trend in the 1930s and 1940s while there is only a slight warming trend in the IPCC dataset. The most significant difference is the existence of a marked cooling period in the rural dataset for the 1960s and 1970s that is almost absent in the IPCC’s urban dataset. This later divergence upsets the common narrative that rising carbon dioxide levels control modern warming trends. For, if carbon dioxide levels are the driver of modern warming, how can a higher rate of increasing carbon dioxide levels exist within a cooling period in the 1960s and 1970s while a lower increasing rate of carbon dioxide levels coincides with an earlier warming interval in the 1930s and 1940s? Or, in other words, how can carbon dioxide levels increasing at 1.7 parts per million per decade cause a distinct warming period in the 1930s and 1940s while a larger increasing rate of 10.63 parts per million per decade is associated with a distinct cooling period in the 1960s and 1970s! Consequently, the research of Willie Soon and his coworkers is discrediting, not only the higher rate of global warming trends specified in IPCC Reports, but also the theory that rising carbon dioxide levels explain modern warming trends; a lynchpin of IPCC science for the last 25 years.

Willie Soon and his coworkers maintain that climate scientists need to consider other possible explanations for recent global warming. Willie Soon and his coworkers point to the Sun, but the IPCC maintains that variations in Total Solar Irradiance (TSI) are over eons and not over shorter periods such as the last few centuries. For that reason, the IPCC point to changes in greenhouse gases as the most obvious explanation for global warming since 1850. In contrast, Willie Soon and his coworkers maintain there can be short-term changes in solar activity and, for example, refer to a period of no sunspot activity that coincided with the Little Ice Age in the 17th Century. They also point out there is still no agreed average figure for Total Solar Irradiance (TSI) despite 30 years of measurements taken by various satellites. Consequently, they contend research in this area is not settled.

The CERES-SCIENCE research project pioneered by Dr Willie Soon and the father-son Connolly team has questioned the validity of the high global warming trends for the 1850-present period that have been published by the IPCC since its first report in 1992. The research also queries the IPCC narrative that rising greenhouse gas concentrations, particularly carbon dioxide, are the primary driver of global warming since 1850. That narrative has been the foundation of IPCC climate science for the last 40 years. It will be interesting to see how the IPCC’s 7th Assessment Report in 2029 treats this new research that questions the very basis of IPCC’s climate science.

The paper is The Detection and Attribution of Northern Hemisphere Land Surface Warming (1850–2018) in Terms of Human and Natural Factors: Challenges of Inadequate Data. 

Abstract

A statistical analysis was applied to Northern Hemisphere land surface temperatures (1850–2018) to try to identify the main drivers of the observed warming since the mid-19th century. Two different temperature estimates were considered—a rural and urban blend (that matches almost exactly with most current estimates) and a rural-only estimate. The rural and urban blend indicates a long-term warming of 0.89 °C/century since 1850, while the rural-only indicates 0.55 °C/century. This contradicts a common assumption that current thermometer-based global temperature indices are relatively unaffected by urban warming biases.

Three main climatic drivers were considered, following the approaches adopted by the Intergovernmental Panel on Climate Change (IPCC)’s recent 6th Assessment Report (AR6): two natural forcings (solar and volcanic) and the composite “all anthropogenic forcings combined” time series recommended by IPCC AR6. The volcanic time series was that recommended by IPCC AR6. Two alternative solar forcing datasets were contrasted. One was the Total Solar Irradiance (TSI) time series that was recommended by IPCC AR6. The other TSI time series was apparently overlooked by IPCC AR6. It was found that altering the temperature estimate and/or the choice of solar forcing dataset resulted in very different conclusions as to the primary drivers of the observed warming.

Our analysis focused on the Northern Hemispheric land component of global surface temperatures since this is the most data-rich component. It reveals that important challenges remain for the broader detection and attribution problem of global warming: (1) urbanization bias remains a substantial problem for the global land temperature data; (2) it is still unclear which (if any) of the many TSI time series in the literature are accurate estimates of past TSI; (3) the scientific community is not yet in a position to confidently establish whether the warming since 1850 is mostly human-caused, mostly natural, or some combination. Suggestions for how these scientific challenges might be resolved are offered.

Mistake on CO2 Warming Effect

Thomas Allmendinger is a Swiss physicist educated at Zurich ETH whose practical experience is in the fields of radiology and elemental particles physics.  His complete biography is here.

His independent research and experimental analyses of greenhouse gas (GHG) theory over the last decade led to several published studies, including the latest summation The Real Origin of Climate Change and the Feasibilities of Its Mitigation, 2023, at Atmospheric and Climate Sciences journal. The paper is a thorough and detailed discussion of which I provide here the abstract and the excerpt describing the experiment.  Excerpts are in italics with my bolds and added images. Full post is Experimental Proof Nil Warming from GHGs.

Abstract

The actual treatise represents a synopsis of six important previous contributions of the author, concerning atmospheric physics and climate change. Since this issue is influenced by politics like no other, and since the greenhouse-doctrine with CO2 as the culprit in climate change is predominant, the respective theory has to be outlined, revealing its flaws and inconsistencies.

But beyond that, the author’s own contributions are focused and deeply discussed. The most eminent one concerns the discovery of the absorption of thermal radiation by gases, leading to warming-up, and implying a thermal radiation of gases which depends on their pressure. This delivers the final evidence that trace gases such as CO2 don’t have any influence on the behaviour of the atmosphere, and thus on climate.

But the most useful contribution concerns the method which enables to determine the solar absorption coefficient βs of coloured opaque plates. It delivers the foundations for modifying materials with respect to their capability of climate mitigation. Thereby, the main influence is due to the colouring, in particular of roofs which should be painted, preferably light-brown (not white, from aesthetic reasons).

It must be clear that such a drive for brightening-up the World would be the only chance of mitigating the climate, whereas the greenhouse doctrine, related to CO2, has to be abandoned. However, a global climate model with forecasts cannot be aspired to since this problem is too complex, and since several climate zones exist.

4. Thermal Gas Absorption Measurements

If the warming-up behaviour of gases has to be determined by temperature measurements, interference by the walls of the gas vessel should be regarded since they exhibit a significantly higher heat capacity than the gas does, which implicates a slower warming-up rate. Since solid materials absorb thermal radiation stronger than gases do, the risk exists that the walls of the vessel are directly warmed up by the radiation, and that they subsequently transfer the heat to the gas. And finally, even the thin glass-walls of the thermometers may disturb the measurements by absorbing thermal radiation.

By these reasons, quadratic tubes with a relatively large profile (20 cm) were used which consisted of 3 cm thick plates from Styrofoam, and which were covered at the ends by thin plastic foils. In order to measure the temperature course along the tube, mercury-thermometers were mounted at three positions (beneath, in the middle, and atop) whose tips were covered with aluminum foils. The test gases were supplied from steel cylinders being equipped with reducing valves. They were introduced by a connecter during approx. one hour, because the tube was not gastight and not enough consistent for an evacuation. The filling process was monitored by means of a hygrometer since the air, which had to be replaced, was slightly humid. Afterwards, the tube was optimized by attaching adhesive foils and thin aluminum foils (see Figure 13). The equipment and the results are reported in [21].

Figure 13. Solar-tube, adjustable to the sun [21].

The initial measurements were made outdoor with twin-tubes in the presence of solar light. One tube was filled with air, and the other one with carbon-dioxide. Thereby, the temperature increased within a few minutes by approx. ten degrees till constant limiting temperatures were attained, namely simultaneously at all positions. Surprisingly, this was the case in both tubes, thus also in the tube which was filled with ambient air. Already this result delivered the proof that the greenhouse theory cannot be true. Moreover, it gave rise to investigate the phenomenon more thoroughly by means of artificial, better defined light.

Figure 14. Heat-radiation tube with IR-spot [21].

Accordingly, the subsequent experiments were made using IR-spots with wattages of 50 W, 100 W and 150W which are normally employed for terraria (Figure 14). Particularly the IR-spot with 150 W lead to a considerably higher temperature increase of the included gas than it was the case when sunlight was applied, since its ratio of thermal radiation was higher. Thereby, variable impacts such as the nature of the gas could be evaluated.

Due to the results with IR-spots at different gases (air, carbon-dioxide, the noble gases argon, neon and helium), essential knowledge could be gained. In each case, the irradiated gas warmed up until a stable limiting temperature was attained. Analogously to the case of irradiated coloured solid plates, the temperature increased until the equilibrium state was attained where the heat absorption rate was identically equal with the heat emission rate.

Figure 15. Time/temperature-curves for different gases [21] (150 W-spot, medium thermometer-position).

As evident from the diagram in Figure 15, the initial observation made with sunlight was approved that pure carbon-dioxide was warmed up almost to the same degree as air does (whereby ambient air only scarcely differed from a 4:1 mixture between nitrogen and oxygen). Moreover, noble gases absorb thermal radiation, too. As subsequently outlined, a theoretical explanation could be found thereto.

Conclusion

Finally, the theoretically suggested dependency of the atmospheric thermal radiation intensity on the atmospheric pressure could be empirically verified by measurements at different altitudes, namely in Glattbrugg (430 m above sea level and on the top of the Furka-pass (2430 m above sea level), both in Switzerland, delivering a so-called atmospheric emission constant A ≈ 22 W·m−2•bar−1•K−0.5. It explained the altitude-paradox of the atmospheric temperature and delivered the definitive evidence that the atmospheric behavior, and thus the climate, does not depend on trace gases such as CO2. However, the atmosphere thermally reradiates indeed, leading to something similar to a Greenhouse effect. But this effect is solely due to the atmospheric pressure.

Mistake on Warming Prior to CO2 Rising

Changes in CO2 follow changes in global temperatures on all time scales, from last month’s observations to ice core datasets spanning millennia. Since CO2 is the lagging variable, it cannot logically be the cause of temperature, the leading variable. It is folly to imagine that by reducing human emissions of CO2, we can change global temperatures, which are obviously driven by other factors.  Most recent post on this:

10/2024 Update Recent Warming Spike Drives Rise in CO2

Mistake on Models Bias Against Natural Factors

Figure 1. Anthropic and natural contributions. (a) Locked scaling factors, weak Pre Industrial Climate Anomalies (PCA). (b) Free scaling, strong PCA

In  2009, the iconic email from the Climategate leak included a comment by Phil Jones about the “trick” used by Michael Mann to “hide the decline,” in his Hockey Stick graph, referring to tree proxy temperatures  cooling rather than warming in modern times.  Now we have an important paper demonstrating that climate models insist on man-made global warming only by hiding the incline of natural warming in Pre-Industrial times.  The paper is From Behavioral Climate Models and Millennial Data to AGW Reassessment by Philippe de Larminat.  H/T No Tricks Zone. Excerpts in italics with my bolds.

Abstract

Context. The so called AGW (Anthropogenic Global Warming), is based on thousands of climate simulations indicating that human activity is virtually solely responsible for the recent global warming. The climate models used are derived from the meteorological models used for short-term predictions. They are based on the fundamental and empirical physical laws that govern the myriad of atmospheric and oceanic cells integrated by the finite element technique. Numerical approximations, empiricism and the inherent chaos in fluid circulations make these models questionable for validating the anthropogenic principle, given the accuracy required (better than one per thousand) in determining the Earth energy balance.

Aims and methods. The purpose is to quantify and simulate behavioral models of weak complexity, without referring to predefined parameters of the underlying physical laws, but relying exclusively on generally accepted historical and paleoclimate series.

Results. These models perform global temperature simulations that are consistent with those from the more complex physical models. However, the repartition of contributions in the present warming depends strongly on the retained temperature reconstructions, in particular the magnitudes of the Medieval Warm Period and the Little Ice Age. It also depends on the level of the solar activity series. It results from these observations and climate reconstructions that the anthropogenic principle only holds for climate profiles assuming almost no PCA neither significant variations in solar activity. Otherwise, it reduces to a weak principle where global warming is not only the result of human activity, but is largely due to solar activity.  Full post is here:

Climate Models Hide the Paleo Incline

Latest INM Climate Model Projections Triggered by Scenario Inputs

The latest climate simulation from the Russian INM was published in April 2024: Simulation of climate changes in Northern Eurasia by two versions of the INM RAS Earth system model. The paper includes discussing how results are driven greatly by processing of cloud factors.  But first for context readers should be also aware of influences from scenario premises serving as model input, in this case  SSP3-7.0.

Background on CIMP Scenario  SSP3-7.0

A recent paper reveals peculiarities with this scenario.  Recognizing distinctiveness of SSP3-7.0 for use in impact assessments by Shiogama et al (2024).  Excerpts in italics with my bolds and added images.

Because recent mitigation efforts have made the upper-end scenario of the future GHG concentration (SSP5-8.5) highly unlikely, SSP3-7.0 has received attention as an alternative high-end scenario for impacts, adaptation, and vulnerability (IAV) studies. However, the ‘distinctiveness’ of SSP3-7.0 may not be well-recognized by the IAV community. When the integrated assessment model (IAM) community developed the SSP-RCPs, they did not anticipate the limelight on SSP3-7.0 for IAV studies because SSP3-7.0 was the ‘distinctive’ scenario regarding to aerosol emissions (and land-use land cover changes). Aerosol emissions increase or change little in SSP3-7.0 due to the assumption of a lenient air quality policy, while they decrease in the other SSP-RCPs of CMIP6 and all the RCPs of CMIP5. This distinctive high-aerosol-emission design of SSP3-7.0 was intended to enable climate model (CM) researchers to investigate influences of extreme aerosol emissions on climate.

SSP3-7.0 Prescribes High Radiative Forcing

SSP3-7.0 Presumes High Aerosol Emissions

Aerosol Emissions refer to Black Carbon, Organic Carbon, SO2 and NOx.

•  Aerosol emissions increase or change little in SSP3-7.0 due to the assumption of a lenient air quality policy, while they decrease in the other SSP-RCPs of CMIP6 and all the RCPs of CMIP5.

• This distinctive high-aerosol-emission design of SSP3- 7.0 was intended to enable AerChemMIP to investigate the consequences of continued high levels of aerosol emissions on climate.

SSP3-7.0 Supposes Forestry Deprivation

• Decreases in forest area were also substantial in SSP3- 7.0, unlike in the other SSP-RCPs.
• This design enables LUMIP to analyse the climate influences of extreme land-use and land-cover changes.

SSP3-7.0 Projects High Population Growth in Poorer Nations

Global population (left) in billions and global gross domestic product (right) in trillion US dollars on a purchasing power parity (PPP) basis. Data from the SSP database; chart by Carbon Brief using Highcharts.

SSP3-7.0 Projects Growing Use of Coal Replacing Gas and Some Nuclear

My Summary:  Using this scenario presumes high CO2 Forcing (Wm2), high aerosol emissions and diminished forest area, as well as much greater population and coal consumption. Despite claims to the contrary, this is not a “middle of the road” scenario, and a strange choice for simulating future climate metrics due to wildly improbable assumptions.

How Two Versions of a Reasonable INM Climate Model Respond to SSP3-7.0

The preceding information regarding the input scenario provides a context for understanding the output projections from INMCM5 and INMCM6.  Simulation of climate changes in Northern Eurasia by two versions of the INM RAS Earth system model. Excerpts in italics with my bolds and added images.

Introduction

The aim of this paper is the evaluation of climate changes during last several decades in the Northern Eurasia, densely populated region with the unprecedentedly rapid climate changes, using the INM RAS climate models. The novelty of this work lies in the comparison of model climate changes based on two versions of the same model INMCM5 and INMCM6, which differ in climate sensitivities ECS and TCR, with data from available observations and reanalyses. By excluding other factors that influence climate reproduction, such as different cores of GCM components, major discrepancies in description of physical process or numerical schemes, the assessment of ECS and TCR role in climate reproduction can be the exclusive focus. Also future climate projections for the middle and the end of 21st century in both model versions are given and compared.

After modification of physical parameterisations, in the model version INMCM6 ECS increased from 1.8K to 3.7K (Volodin, 2023), and TCR increased from 1.3K to 2.2K. Simulation of present-day climate by INMCM6 Earth system model is discussed in Volodin (2023). A notable increase in ECS and TCR is likely to cause a discrepancy in the simulation of climate changes during last decades and the simulation of future climate projections for the middle and the end of 21st century made by INMCM5 and INMCM6.

About 20% of the Earth’s land surface and 60% of the terrestrial land cover north of 40N refer to Northern Eurasia (Groisman et al, 2009). The Hoegh-Guldberg et al (2018) states that the topography and climate of the Eurasian region are varied, encompassing a sharply continental climate with distinct summer and winter seasons, the northern, frigid Arctic environment and the alpine climate on Scandinavia’s west coast. The Atlantic Ocean and the jet stream affect the climate of western Eurasia, whilst the Mediterranean region, with its hot summers, warm winters, and often dry spells, influences the climate of the southwest. Due to its location, the Eurasian region is vulnerable to a variety of climate-related natural disasters, including heatwaves, droughts, riverine floods, windstorms, and large-scale wildfires.

Historical Runs

One of the most important basic model experiments conducted within the CMIP project in order to control the model large-scale trends is piControl (Eyring et al, 2016). With 1850 as the reference year, PiControl experiment (Eyring et al, 2016) is conducted in conditions chosen to be typical of the period prior to the onset of large-scale industrialization. Perturbed state of the INMCM model at the end of the piControl is taken as the initial condition for historical runs. The historical experiment is conducted in the context of changing external natural and anthropogenic forcings. Prescribed time series include:

♦  greenhouse gases concentration,
♦  the solar spectrum and total solar irradiance,
♦  concentrations of volcanic sulfate aerosol in the stratosphere, and
♦  anthropogenic emissions of SO2, black, and organic carbon.

The ensemble of historical experiments consists of 10 members for each model version. The duration of each run is 165 model years from 1850 to 2014.

SSP3-7.0 Scenario

Experiments are designed to simulate possible future pathways of climate evolution based on assumptions about human developments including: population, education, urbanization, gross domestic product (GDP), economic growth, rate of technological developments, greenhouse gas (GHG) and aerosol emissions, energy supply and demand, land-use changes, etc. (Riahi et al, 2016). Shared Socio-economic Pathways or “SSP” vary from very ambitious mitigation and increasing shift toward sustainable practices (SSP1) to fossil-fueled development (SSP5) (O’Neill et al, 2016).

Here we discuss climate changes for scenario SSP3-7.0 only, to avoid presentation large amount of information. The SSP3-7.0 scenario reflects the assumption on the high GHG emissions scenario and priority of regional security, leading to societies that are highly vulnerable to climate change, combined with relatively high forcing level (7.0 W/m2 in 2100). On this path, by the end of the century, average temperatures have risen by 3.0–5.5◦C above preindustrial values (Tebaldi et al, 2021). The ensembles of historical runs with INMCM5 and INMCM6 were prolonged for 2015-2100 using scenario SSP3-7.0.

Observational data and data processing

Model near surface temperature and specific humidity changes were compared with ERA5 reanalysis data (Hersbach et al, 2020), precipitation data were compared with data of GPCP (Adler et al, 2018), sea ice extent and volume data were compared with satellite obesrvational data NSIDC (Walsh et al, 2019) and the Pan-Arctic Ice Ocean Modeling and Assimilation System (PIOMAS) (Schweiger et al, 2011) respectively, land snow area was compared with National Oceanic and Atmospheric Administration Climate Data Record (NOAA CDR) of Snow Cover Extent (SCE) reanalysis (Robinson et al, 2012) based on the satellite observational dataset Estilow et al (2015). Following Khan et al (2024) Northern Eurasia is defined as land area lying within boundaries of 35N–75N, 20E–180E. Following IPCC 6th Assessment Report (Masson-Delmotte et al, 2021), the following time horizons are distinguished: the recent past (1995– 2014), near term (2021–2040), mid-term (2041–2060), and long term (2081–2100). To compare observed and model temperature and specific humidity changes in the recent past, data for years 1991–2020 were compared with data for years 1961–1990.

Near surface air temperature change

Fig. 1 Annual near surface air temperature change in Northern Eurasia with respect to 1995–2014 for INMCM6 (red), INMCM5 (blue) and ERA5 reanalysis (Hersbach et al, 2020)(black), K. Orange and lightblue lines show ensemble spread.

Despite different ECS, both model versions show (Fig. 1) approximately the same warming over Northern Eurasia by 2010–2015, similar to observations. However, projections of Northern Eurasia temperature after year 2040 differ. By 2100, the difference in 2-m air temperature anomalies between two model versions reaches around 1.5 K. The greater value around 6.0 K is achieved by a model with higher sensitivity. This is consistent with Huusko et al (2021); Grose et al (2018); Forster et al (2013), which confirmed that future projections show a stronger relationship than historical ones between warming and climate sensitivity. In contrast to feedback strength, which is more important in forecasting future temperature change, historical warming is more associated with model forcing. Both INMCM5 and INMCM6 show distinct seasonal warming patterns. Poleward of about 55N the seasonal warming is more pronounced in winter than in summer (Fig. 2). That means the smaller amplitude of the seasonal temperature cycle in 1991– 2020 compared to 1961–1990. The same result was shown in Dwyer et al (2012) and Donohoe and Battisti (2013). The opposite situation is observed during the hemispheric summer, where stronger warming is observed over the Mediterranean region (Seager et al, 2014; Kr¨oner et al, 2017; Brogli et al, 2019), subtropics and midlatitudinal regions of the Pacific Ocean, leading to an amplification of the seasonal cycle. The spatial patterns of projected warming in winter and summer in model historical experiments for 1991-2020 relative to 1961-1990 are in a good agreement with ERA5 reanalysis data, although for ERA5 the absolute values of difference are greater.

East Atlantic/West Russia (EAWR) Index

The East Atlantic/West Russia (EAWR) pattern is one of the most prominent large-scale modes of climate variability, with centers of action on the Caspian Sea, North Sea, and northeast China. The EOF-analysis identifies the EAWR pattern as the tripole with different signs of pressure (or 500 hPa geopotential height) anomalies encompassing the aforementioned region.

In this study, East Atlantic/ West Russia (EAWR) index was calculated as the projection coefficient of monthly 500 hPa geopotential height anomalies to the second EOF of monthly reanalysis 500 hPa geopotential height anomalies over the region 20N–80N, 60W–140E.

Fig. 5 Time series of June-July-August 5-year mean East Atlantic/ West Russia (EAWR) index. Maximum and minimum of the model ensemble are shown as a dashed lines. INMCM6 and INMCM5 ensemble averaged indices are plotted as a red and blue solid lines, respectively.  The ERA5 (Hersbach et al, 2020) EAWR index is shown in green.

[Note: High EAWR index indicates low pressure and cooler over Western Russia, high pressure and warmer over Europe. Low EAWR index is the opposite–high pressure and warming over Western Russia, low pressure and cooling over Europe.]

East Atlantic/ West Russia (EAWR) index Time series of EAWR index can be seen in Fig. 5. Since the middle of 1990s the sign of EAWR index has changed from positive to negative according to reanalysis data. Both versions of the INMCM reproduce the change in the sign of EAWR index. Therefore, the corresponding climate change in the Mediterranean and West Russia regions should be expected. Actually, the difference in annual mean near-surface temperature and specific humidity between 2001–2020 and 1961–1990 shows warmer and wetter conditions spreading from the Eastern Mediterranean to European Russia both for INMCM6 and INMCM5 with the largest difference being observed for the new version of model.

Fig. 6 Annual mean near surface temperature, K (left) and specific humidity, kg/kg (right) in 2001– 2020 with respect to 1961–1990 for INMCM6 (a,b) and INMCM5 (c,d).

Fig. 7 Annual precipitation change (% with respect to 1995–2014) in Northern Eurasia for INMCM6 (red), INMCM5 (blue) and GPCP analysis (Adler et al, 2018) (black). Orange and lightblue lines show ensemble spread.

Discussion and conclusions

Climate changes during the last several decades and possible climate changes until 2100 over Northern Eurasia simulated with climate models INMCM5 and INMCM6 are considered. Two model versions differ in parametrisations of cloudiness, aerosol scheme, land snow cover and atmospheric boundary layer, isopycnal diffusion discretisation and dissipation scheme of the horizontal components of velocity. These modifications in atmosphere and ocean blocks of the model have led to increase of ECS to 3.7 K and TCR to 2.2 K, mainly due to modification of cloudiness parameterisation.

Comparison of model data with available observations and reanalysis show that both models simulate observed recent temperature and precipitation changes consistently with observational datasets. The decrement of seasonal temperature cycle amplitude poleward of about 55N and its increase over the Mediterranean region, subtropics, and mid-latitudinal Pacific Ocean regions are two distinct seasonal warming patterns that are displayed by both INMCM5 and INMCM6. In the long-term perspective, the amplification of difference in projected warming during June-JulyAugust (JJA) and December-January-February (DJF) increases. Both versions of the INMCM reproduce the observed change in the sign of EAWR index from positive to negative in the middle of 1990s, that allows to expect correct reproduction of the corresponding climate change in the Mediterranean and West Russia regions.

Specifically, the enhanced precipitation in the North Eurasian region since the mid-1990s has led to increased specific humidity over the Eastern Mediterranean and European Russia, which is simulated by the INMCM5 and INMCM6 models. Both versions of model correctly reproduce the precipitation change and continue its increasing trend onwards.

Both model versions simulate similar temperature, precipitation, Arctic sea ice extent in 1990–2040 in spite of INMCM5 having much smaller ECS and TCR than INMCM6. However, INMCM5 and INMCM6 show differences in the long-term perspective reproduction of climate changes. After 2040, model INMCM6 simulated stronger warming, stronger precipitation change, stronger Arctic sea ice and land snow extent decrease than INMCM5.

My Comment

So both versions of the model replicate well the observed history.  And when fed the SSP3-7.0 inputs, both project a warmer, wetter world out to 2100; INMCM5 reaches 4.5C and INMCM6 gets to 6.0C.  The scenario achieves the desired high warming, and the cloud enhancements in version 6 amplify it.  I would like to see a similar experiment done with the actual medium scenario SSP2-4.5.

Happer: Cloud Radiation Matters, CO2 Not So Much

Earlier this month William Happer spoke on Radiation Transfer in Clouds at the EIKE conference, and the video is above.  For those preferring to read, below is a transcript from the closed captions along with some key exhibits.  I left out the most technical section in the latter part of the presentation. Text in italics with my bolds.

William Happer: Radiation Transfer in Clouds

People have been looking at Clouds for a very long time in in a quantitive way. This is one of the first quantitative studies done about 1800. And this is John Leslie,  a Scottish physicist who built this gadget. He called it an Aethrioscope, but basically it was designed to figure out how effective the sky was in causing Frost. If you live in Scotland you worry about Frost. So it consisted of two glass bulbs with a very thin capillary attachment between them. And there was a little column of alcohol here.

The bulbs were full of air, and so if one bulb got a little bit warmer it would force the alcohol up through the capillary. If this one got colder it would suck the alcohol up. So he set this device out under the clear sky. And he described that the sensibility of the instrument is very striking. For the liquor incessantly falls and rises in the stem with every passing cloud. in fine weather the aethrioscope will seldom indicate a frigorific impression of less than 30 or more than 80 millesimal degrees. He’s talking about how high this column of alcohol would go up and down if the sky became overclouded. it may be reduced to as low as 15 refers to how much the sky cools or even five degrees when the congregated vapours hover over the hilly tracks. We don’t speak English that way anymore but I I love it.

The point was that even in 1800 Leslie and his colleagues knew very well that clouds have an enormous effect on the cooling of the earth. And of course anyone who has a garden knows that if you have a clear calm night you’re likely to get Frost and lose your crops. So this was a quantitative study of that.

Now it’s important to remember that if you go out today the atmosphere is full of two types of radiation. There’s sunlight which you can see and then there is the thermal radiation that’s generated by greenhouse gases, by clouds and by the surface of the Earth. You can’t see thermal radiation but you you can feel it if it’s intense enough by its warming effect. And these curves practically don’t overlap so we’re really dealing with two completely different types of radiation.

There’s sunlight which scatters very nicely and off of not only clouds but molecules; it’s the blue sky the Rayleigh scattering. Then there’s the thermal radiation which actually doesn’t scatter at all on molecules so greenhouse gases are very good at absorbing thermal radiation but they don’t scatter it. But clouds scatter thermal radiation and plotted here is the probability that you will find Photon of sunlight between you know log of its wavelength and the log of in this interval of the wavelength scale.

Since Leslie’s day two types of instruments have been developed to do what he did more precisely. One of them is called a pyranometer and this is designed to measure sunlight coming down onto the Earth on a day like this. So you put this instrument out there and it would read the flux of sunlight coming down. It’s designed to see sunlight coming in every direction so it doesn’t matter which angle the sun is shining; it’s uh calibrated to see them all.

Let me show you a measurement by a pyranometer. This is a actually a curve from a sales brochure of a company that will sell you one of these devices. It’s comparing two types of detectors and as you can see they’re very good you can hardly tell the difference. The point is that if you look on a clear day with no clouds you see sunlight beginning to increase at dawn it peaks at noon and it goes down to zero and there’s no sunlight at night. So half of the day over most of the Earth there’s no sunlight in the in the atmosphere.

Here’s a day with clouds, it’s just a few days later shown by days of the year going across. You can see every time a cloud goes by the intensity hitting the ground goes down. With a little clear sky it goes up, then down up and so on. On average at this particular day you get a lot less sunlight than you did on the clear day.

But you know nature is surprising. Einstein had this wonderful quote: God is subtle but he’s not malicious. He meant that nature does all of sorts of things you don’t expect, and so let me show you what happens on a partly cloudy day. Here so this is data taken near Munich. The blue curve is the measurement and the red curve is is the intensity on the ground if there were no clouds. This is a partly cloudy day and you can see there are brief periods when the sunlight is much brighter on the detector on a cloudy day than it is on the clear day. And that’s because coming through clouds you get focusing from the edges of the cloud pointing down toward your detector. That means somewhere else there’s less radiation reaching the ground. But this is rather surprising to most people. I was very surprised to learn about it but it just shows that the actual details of climate are a lot more subtle than you might think.

We knnow that visible light only happens during the daytime and stops at night. There’s a second type of important radiation which is the thermal radiation which is measured by a similar divice. You have a silicon window that passes infrared, which is below the band gap of silicon, so it passes through it as though transparent. Then there’s some interference filters here to give you further discrimination against sunlight. So sunlight practically doesn’t go through this at all, so they call it solar solar blind since it doesn’t see the Sun.

But it sees thermal radiation very clearly with a big difference between this device and the sunlight sensing device I showed you. Because actually most of the time this is radiating up not down. Out in the open air this detector normally gets colder than the body of the instrument. And so it’s carefully calibrated for you to compare the balance of down coming radiation with the upcoming radiation. Upcoming is normally greater than downcoming.

I’ll show you some measurements of the downwelling flux here; these are actually in Greenland in Thule and these are are watts per square meter on the vertical axis here. The first thing to notice is that the radiation continues day and night you can you if you look at the output of the pyrgeometer you can’t tell whether it’s day or night because the atmosphere is just as bright at night as it is during the day. However, the big difference is clouds: on a cloudy day you get a lot more downwelling radiation than you do on a clear day. Here’s a a near a full day of clear weather there’s another several days of clear weather. Then suddenly it gets cloudy. Radiation rises because the bottoms of the clouds are relatively warm at least compared to the clear sky. I think if you put the numbers In, this cloud bottom is around 5° Centigrade so it was fairly low Cloud. it was summertime in Greenland and this compares to about minus 5° for the clear sky.

So there’s a lot of data out there and there really is downwelling radiation there no no question about that you measure it routinely. And now you can do the same thing looking down from satellites so this is a picture that I downloaded a few weeks ago to get ready for this talk from Princeton and it was from Princeton at 6 PM so it was already dark in Europe. So this is a picture of the Earth from a geosynchronous satellite that’s parked over Ecuador. You are looking down on the Western Hemisphere and this is a filtered image of the Earth in Blue Light at 47 micrometers. So it’s a nice blue color not so different from the sky and it’s dark where the sun has set. There’s still a fair amount of sunlight over the United States and the further west.

Here is exactly the same time and from the same satellite the infrared radiation coming up at 10.3 which is right in the middle of the infrared window where there’s not much Greenhouse gas absorption; there’s a little bit from water vapor but very little, trivial from CO2.

As you can see, you can’t tell which side is night and which side is day. So even though the sun has set over here it is still glowing nice and bright. There’s sort of a pesky difference here because what you’re looking at here is reflected sunlight over the intertropical Convergence Zone. There are lots of high clouds that have been pushed up by the convection in the tropics and uh so this means more visible light here. You’re looking at emission of the cloud top so this is less thermal light so white here means less light, white there means more light so you have to calibrate your thinking. to

But the Striking thing about all of this: if you can see the Earth is covered with clouds, you have to look hard to find a a clear spot of the earth. Roughly half of the earth maybe is clear at any given time but most of it’s covered with clouds. So if anything governs the climate it is clouds and and so that’s one of the reasons I admire so much the work that Svensmark and Nir Shaviv have done. Because they’re focusing on the most important mechanism of the earth: it’s not Greenhouse Gases, it’s Clouds. You can see that here.

Now this is a single frequency let me show you what happens if you look down from a satellite and do look at the Spectrum. This is the spectrum of light coming up over the Sahara Desert measured from a satellite. And so here is the infrared window; there’s the 10.3 microns I mentioned in the previous slide it’s it’s a clear region. So radiation in this region can get up from the surface of the Sahara right up to outer space.

Notice that the units on these scales are very different; over the Sahara the top unit is 200, 150 over the Mediterranean and it’s only 60 over the South Pole. But at least the Mediterranean and the Sahara are roughly similar so the right side here these three curves on the right are observations from satellites and the three curves on the left are are calculations modeling that we’ve done. The point here is that you can hardly tell the difference between a model calculation and observed radiation.

So it’s really straightforward to calculate radiation transfer. If someone quotes you a number in watts per square centimeter you should take it seriously; that probably a good number. If they tell you a temperature you don’t know what to make about it. Because there’s a big step between going from watts per square centimeter to a temperature change. All the mischief in the whole climate business is going from watts per square centimeter to to Centigrade or Kelvin.

Now I will say just a few words about clear sky because that is the simplest. Then we’ll get on to clouds, the topic of this talk. This is a calculation with the same codes that I showed you in the previous slide which as you saw work very well. It’s worth spending a little time because this is the famous Planck curve that was the birth of quantum mechanics. There is Max Planck who figured out what the formula for that curve is and why it is that way. This is what the Earth would radiate at 15° Centigrade if there were no greenhouse gases. You would get this beautiful smooth curve the Planck curve. If you actually look at the Earth from the satellites you get a raggedy jaggedy black curve. We like to call that the Schwarzchild curve because Carl Schwarzchild was the person who showed how to do that calculation. Tragically he died during World War I, a Big Big loss to science.

There are two colored curves that I want to draw your attention. The green curve is is what Earth would radiate to space if you took away all the CO2 so it only differs from the black curve you know in the CO2 band here this is the bending band of CO2 which is the main greenhouse effect of CO2. There’s a little additional effect here which is the asymmetric stretch but it it doesn’t contribute very much. Then here is a red curve and that’s what happens if you double CO2.

So notice the huge asymmetry. If taking all 400 parts per million of CO2 away from the atmosphere causes this enormous change 30 watts per square meter, the difference between this green 307 and and the black 277, that’s 30 watts per square meter. But if you double CO2 you practically don’t make any change. This is the famous saturation of CO2. At the levels we have now doubling CO2, a 100% Increase of CO2 only changes the radiation to space by 3 watts per square meter. The difference between 274 for the red curve and 277 for the curve for today. So it’s a tiny amount: for 100% increase in CO2 a 1% decrease of radiation to space.

That allows you to estimate the feedback-free climate sensitivity in your head. I’ll talk you through the feedback-free climate free sensitivity. So doubling CO2 is a 1% decrease of radiation to space. If that happens then the Earth will start to warm up. But it will radiate as the fourth power of the temperature. So temperature starts to rise but if you’ve got a fourth power, the temperature only has to rise by one-quarter of a percent absolute temperature. So a 1% forcing in watts per square centimeter is a one-quarter percent of temperature in Kelvin. Since the ambient Kelvin temperature is about 300 Kelvin (actually a little less) a quarter of that is 75 Kelvin. So the feedback free equilibrium climate sensitivity is less than 1 Degree. It’s 0.75 Centigrade. It’s a number you can do in your head.

So when you hear about 3 centigrade instead of .75 C that’s a factor of four, all of which is positive feedback. So how is there really that much positive feedback? Because most feedbacks in nature are negative. The famous Le Chatelier principle which says that if you perturb a system it reacts in a way to to dampen the perturbation not increase it. There are a few positive feedback systems that were’re familiar with for example High explosives have positive feedback. So if the earth’s climate were like other positive feedback systems, all of them are highly explosive, it would have exploded a long time ago. But the climate has never done that, so the empirical observational evidence from geology is that the climate is like any other feedback system it’s probably negative Okay so I leave that thought with you and and let me stress again:

This is clear skies no clouds; if you add clouds all this does is
suppress the effects of changes of the greenhouse gas.

So now let’s talk about clouds and the theory of clouds, since we’ve already seen clouds are very important. Here is the formidable equation of transfer which has been around since Schwarzchild’s day. So some of the symbols here relate to the intensity, another represents scattering. If you have a thermal radiation on a greenhouse gas where it comes in and immediately is absorbed, there’s no scattering at all. If you hit a cloud particle it will scatter this way or that way, or some maybe even backwards.

So all of that’s described by this integral so you’ve got incoming light at One Direction and you’ve got outgoing light at a second Direction. And then at the same time you’ve got thermal radiation so the warm particles of the cloud are are emitting radiation creating photons which are coming out and and increasing the Earth glow the and this is represented by two parameters. Even a single cloud particle has an albedo, this is is the fraction of radiation that hits the cloud that is scattered as opposed to absorbed and being converted to heat. It’s a very important parameter for visible light and white clouds, typically 99% of the encounters are scattered. But for thermal radiation it’s much less. So water scatters thermal radiation only half as efficiently as shorter wavelengths.

The big problem is that in spite of all the billions of dollars that we have spent, these things which should be known and and would have been known if there hadn’t been this crazy fixation on carbon dioxide and greenhouse gases. And so we’ve neglected working on these areas that are really important as opposed to the trivial effects of greenhouse gases. Attenuation in a cloud is both scattering and absorption. Of course you have to solve these equations for every different frequency of the light because especially for molecules, there’s a strong frequency dependence.

In summary,  let me show you this photo which was taken by Harrison Schmitt who was a friend of mine on one of the first moonshots. It was taken in December and looking at this you can see that they were south of Madagascar when the photograph was taken. You can see it was Winter because here the Intertropical Convergence Zone is quite a bit south of the Equator; it’s moved Way South of India and Saudi Arabia. By good luck they had the sun behind them so they had the whole earth Irradiated.

There’s a lot of information there and and again let me draw your attention to how much of the Earth is covered with clouds. So only very small parts of the Earth can actually be directly affected by greenhouse gases, of the order of half. The takeaway message is that clouds and water vapor are much more important than greenhouse gases for earth’s climate. The second point is the reason they’re much more important: doubling CO2 as I indicated in the middle of the talk only causes a 1% difference of radiation to space. It is a very tiny effect because of saturation. You know people like to say that’s not so, but you can’t really argue that one, even the IPCC gets the same numbers that we do.

And you also know that covering half of the sky with clouds will decrease solar heating by 50%. So for clouds it’s one to one, for greenhouse gases it’s a 100 to one. If you really want to affect the climate, you want to do something to the clouds. You will have a very hard time making any difference with Net Zero with CO2 if you are alarmed about the warmings that have happened.

So one would hope that with all the money that we’ve spent trying to turn CO2 into a demon that some good science has come out of it. Fom my point of view this is a small part of it, this scattering theory that I think will be here a long time after the craze over greenhouse gases has gone away. I hope there will be other things too. You can point to the better instrumentation that we’ve got, satellite instrumentation as well as ground instrumentation. So that’s been a good investment of money. But the money we’ve spent on supercomputers and modeling has been completely wasted in my view.