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what’s up with the weather: the debate: dr. s. fred singer

PBS Online

This is an excellent interview from several years ago with Dr. S. Fred Singer.  Dr. Singer is “an atmospheric physicist at George Mason University and founder of the Science and Environmental Policy Project, a think tank on climate and environmental issues.”

I will highlight a few of the statements below but this is an interview that should be read in its entirety so please click through on the link below.  Dr. Singer significantly minimizes the chance of global warming and specifically states that human impact is marginal.

Climate change is a natural phenomenon. Climate keeps changing all the time. The fact that climate changes is not in itself a threat, because, obviously, in the past human beings have adapted to all kinds of climate changes.


Whether or not human beings can produce a global climate change is an important question. This question is not at all settled. It can only be settled by actual measurements, data. And the data are ambiguous. For example, the data show that the climate warmed between 1900 and 1940, long before humanity used much energy. But then the climate cooled between 1940 and 1975. Then it warmed again for a very short period of time, for about five years. But since 1979, our best measurements show that the climate has been cooling just slightly. Certainly, it has not been warming.


Can these models be validated by observations? And the models very clearly show that the climate right now should be warming at about the rate of one degree Fahrenheit per decade, in the middle troposphere, that is, above the surface. But that’s not what the observations show. So until the observations and the models agree, or until one or the other is resolved, it’s very difficult for people–and for myself, of course–to believe in the predictive power of the current models.


I personally believe that there should be some slight warming. But I think the warming will be much less than the current models predict. Much less. And I think it will be barely detectable. Perhaps it will be detectable, perhaps not. And it certainly will not be consequential.


One of the leading climate modelists is Jim Hanson. He actually was the man who, ten years ago, went out on a limb and said he was sure the enhanced greenhouse effect was here. He now says we can’t really tell. He says the forcings are so uncertain that they’re much more important than the climate models. In other words, until we get the forcings straight, the climate-model predictions are not worth very much. That is basically what he said.


A number of researchers have actually tried to reproduce past climates, using models. And to some extent, they’ve been successful. And to another extent, they have not been successful, in the sense that you cannot derive what is called the climate sensitivity. In other words, what we really are after is some way of valiating these models. We’d like to know how much of a temperature change is produced if carbon dioxide doubles in the atmosphere? That’s called the climate sensitivity. What is the climate sensitivity? As I’ve mentioned earlier, it can range from as little as one degree in some models to as much as five degrees Centigrade, which equals eight degrees Fahrenheit, in other models. That’s a big difference, a huge difference.


Well, the question is what you mean by “doing” something. I’m not a great believer in buying insurance if the risks are small and the premiums are high. Nobody in his right mind would do that. But this is the case here. We’re being asked to buy an insurance policy against a risk that is very small, if at all, and pay a very heavy premium. We’re being asked to reduce energy use, not just by a few percent but, according to the Kyoto Protocol, by about 35 percent within ten years. That means giving up one-third of all energy use, using one-third less electricity, throwing out one-third of all cars perhaps. It would be a huge dislocation of our economy, and it would hit people very hard, particularly people who can least afford it.


Now, it’s interesting that the variability of climate is greater when the climate is cold and when CO2 content is low. It’s just a historic fact. When you analyze the data, you find that the variability of climate during the last ice age was much greater than it is during the present warm interglacial. So if you believe this, it would argue that we should have a warmer climate with more carbon dioxide in the atmosphere, because it will make the climate more stable.


In the climate business, the situation is more complicated because there are also political factors involved, and frankly, there’s also money involved. This is an unusual situation. There’s no politics attached to the theory of relativity, for example. But there is to climate science. There are no large sums of money attached to relativity, but there are to climate science.

The federal government pumps about $2 billion a year into climate research. Now, this money has to be spent by someone. It supports a lot of jobs. It supports a lot of people. And inevitably, many of these people begin to feel that what they’re doing is tremendously important and vital. Otherwise, they couldn’t really live with themselves. They’ve talked themselves into the fact that the work they’re doing is somehow helping humanity deal with some kind of a problem. ……. But inevitably, when you have a particular point of view–(and this works both ways–you tend to suppress facts or data that disagree with your point of view, and you tend to favor data, observations that support your point of view. You become selective in the way you present your observations.


I think that we would have to try to get the models to become better, and try to find more specific fingerprints-as I call them– in the observations that can either be verified or falsified by models. And the global average temperature simply isn’t good enough. It has to be based on geographic variation, or variation with altitude, or temporal variation, or much more detailed measurements. Certainly we know that the models do not agree amongst themselves. So I think the first step is to find out why this is so, and work very hard to at least resolve the differences between [models], and then try to resolve differences between models and observations.

As I said before, this is only a small part of the interview and you would be wise to click through and read the entire conversation.

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