Sunday, July 19, 2009

The Corruption of our National Academies -- as discovered by an environmentalist

Up until a few months ago, I was a big supporter of our National Academies. No more.

A fact of life today is that the internet has facilitated the rapid and continuous dissemination of misinformation and disinformation by those promoting nothing more than self-serving interests. Lobbyists are full well aware of this power and have launched an unprecedented "marketing" assault on citizens and politicians. The motivations are simple: greed and power. Yes they have always been around, but today we have the perfect storm. We now toss around "Trillions of dollars" like these are some reasonable amounts! These staggering and unprecedented disbursements have (not surprisingly) spawned the most sophisticated and aggressive breed of profiteers that we have ever encountered.

As a physicist and longtime environmental advocate, I know that it is critically important that (to counter this onslaught) there be a source of competent, objective, scientific information on the technology issues (like energy) that we face today. I had looked to the National Academies to fill that essential role. No more. Here is the tale of woe that came about when I happened to peek under an innocent looking rock. It started by my looking over a report in one of my fields of expertise: "Electricity from Renewable Sources..."

Having read many hundreds of energy reports, it didn't take long to see that this document was nothing more than agenda propaganda, and that any connection with science was inadvertent and purely happenstance. I was surprised that such a PR piece had been released by the Academies, and decided to investigate whether this was an aberration, or a degradation of their standards. I was put in touch with a senior person at the Academies - we'll play Dear Abby here and (to protect the innocent) call him "Dr. D."

I had several lengthy correspondences with Dr. D, and the more I heard, the more concerned I became. In the beginning, after I objected to the lack of science and objectivity in this report, Dr. D tried to dismiss my contentions by stating that I simply didn't like it's conclusions. That, of course, was a disingenuous response, as I had said nothing about the report's conclusions, and had focused my comments on its methodology.

Unfortunately, this was a sign of similar foolishness to come. After receiving a barrage of excuses for the report's unscientific methods, I finally asked Dr. D outright: are you more a defender of the Academies' existing report system, or a person genuinely interested in improving it? He quickly assured me that he was both. Unfortunately that also has proved to be inaccurate, as in our entire 21 pages of correspondence there was not a single matter where he said anything remotely like: "That's a good idea - I will do everything I can to incorporate that into our report process."

My main message to him was: "I have been an ardent supporter of the National Academies. Due to their good standing in the scientific and political community, the Academies have been targeted by lobbyists to become another outlet for promotion of their financial interests." "Despite your belief that that the Academies' report system is robust, it HAS been compromised by the "Electricity from Renewable Resources" report."

I won't bore you with all the details of our communications, but what I eventually did was to boil down the many issues we covered, into four key ones. To make absolutely sure that I was not reading something into what Dr. D might have rashly said to me, I asked him to answer these four questions (regarding reports put out by the Academies):

1 - What's more important: the Process or the Result?

2 - What's more important: "consensus science" or scientific methodology?

3 - What's more important: Confidentiality or Transparency?

4 - Does a committee member whose employment is directly connected to the results of their report have a bias or a conflict of interest?

Please give these some thought, before reading about his answers. I made these particular queries as to me the core issue here is scientific integrity. If the Academies are not an objective bastion of scientific information, then who is? To simplify matters, I purposely phrased each question so that the second option was what I believe is the correct answer. Surprisingly (to me), despite some pontification, Dr. D said that the Academies chose the first option to each of the questions. And I found none of his responses to be satisfactory, or science-based.

My most disturbing observation is that Dr. D studiously avoided the Academies from taking the "scientific role" throughout this whole report process. For instance, his astounding answer to my first question (I'm paraphrasing) was: the less evidence there is available, the more the Academies deviate from scientific standards. (Huh?!) This flies in the face of ALL logic. It would seem to me that "where the available evidence is thin, or not definitive, or when deep ideological divisions exist" that all three of those circumstances would scream out: BE EXTRA CAREFUL, AND GET MORE EMPIRICAL EVIDENCE BEFORE PROCEEDING!

Yet Dr. D said no to that, and instead stated that it was the Academies' policy to let a select handful of biased people make a guess that suited their agenda. Furthermore, regarding the Renewable's Electricity report, there are some 100,000 turbines actively producing data throughout the world today. Exactly how and why can the data from 100,000 turbines be "thin" or "not definitive"? The only conceivable explanation for that would be that the keepers of such data know that the results do not promote their financial interests, and therefore prefer not to release it. ---------

In Dr. D's answer to my second question, he begrudgingly acknowledged that the result is "important." However, he then stated that results "need to be supported by the best evidence available" which is a good sound bite, but is precisely what did NOT happen with the Renewable's Electricity report - and he already made an excuse for it in his prior answer. Good evidence DOES exist in this case, and if the committee members made a formal, public complaint about it's "non-availability," it is extremely likely that it would then get released. The fact that they took no such action would indicate that the majority (along with their complicit "monitors") were willing to settle for speculation - even though they knew that hard data existed.

This exactly follows Dr. D's full script where he effectively said "the results need to be supported by the best evidence available, but if real evidence isn't easy to come by (or if it doesn't support the agenda of the majority of the committee) then the committee will forgo such evidence, and instead rely on a consensus adjudication."

Amazing. I can't say it any better than this: "The work of science has nothing whatever to do with consensus. Consensus is the business of politics. Science, on the contrary, requires only one investigator who happens to be right, which means that he or she has results that are verifiable by reference to the real world. In science consensus is irrelevant. What is relevant is reproducible results. The greatest scientists in history are great precisely because they broke with the consensus." -----------

Regarding my third question, he again made a token acknowledgment, saying "Transparency is, of course, essential to the results..." The problem is that (despite these good words) there is essentially zero transparency in this report (and evidently in the Academies' normal review process). Transparency is when ALL of the review comments provided are published (e.g. as an addendum and after the report is issued), and each of these are identified as to their source. That did NOT happen here. Based on his words, Dr. D believes that "transparency" simply means listing the names of the reviewers and the monitors.

Right after admitting that transparency was good, he then went about arguing against it. His first claim (unsupported) was that "transparency results in less quality reviews." I sent him a study that concluded otherwise. Despite providing no data that supports his contention, he persists with this illogical opinion. His second justification for doing an inferior job at transparency boiled down to his belief that other institutions do a worse job at transparency than the Academies do. I asked him if he was familiar with the adage "Two wrongs don't make a right?" No reply.


Oregon school textbooks too skeptical

According to the complaint below. Where is the "Reichsministerium für Volksaufklärung und Propaganda" when you need them?

While visiting Portland recently, U.S. Secretary of Transportation Ray LaHood proclaimed that "Portland is the green capital of our country." Well, maybe when it comes to streetcars and light rail, but not when it comes to the public school curriculum.

Today's most pressing environmental issue is climate change. James Hansen, chief climatologist at the National Aeronautics and Space Administration, warns of "a potential for explosive changes with effects that would be irreversible -- if we do not rapidly slow fossil fuel emissions over the next few decades." Climate change, noted environmental writer/activist Bill McKibben declares, is "the one overarching global civilizational challenge that humans have ever faced."

And yet the textbooks used in the Portland area -- texts that are playing a larger and larger role in the curriculum -- adopt a Rush Limbaugh-like skepticism toward global warming.

In Oregon, high school students take only one required class devoted to the state of the world: Global Studies. The textbook for this course in many area school districts -- Portland, Beaverton, Reynolds, Tigard-Tualatin, Sherwood, among others -- is "Modern World History," published by McDougal Littell, a subsidiary of the giant Houghton Mifflin. "Modern World History" buries its discussion of climate change on Page 679. The second of its puny three paragraphs devoted to the issue begins, "Not all scientists agree with the theory of the greenhouse effect."

This is simply false.

French mathematician and physicist Joseph Fourier discovered the "greenhouse effect" in 1824, and today no scientist disagrees with it. The textbook writers likely intended to say that not all scientists agree with the theory that the climate is changing as a result of human-created greenhouse gases. But even if we forgive the book's sloppy scholarship, why are Portland-area schools endorsing material that calls into question the human role in global warming?

The rest of the book's three paragraphs is little better. Acknowledging that the Earth's climate is "slowly warming," the Global Studies textbook tells students that, "To combat this problem, the industrialized nations have called for limits on the release of greenhouse gases. In the past, developed nations were the worst polluters." They still are. Per capita greenhouse gas emissions of the wealthy nations far exceed the emissions of any of the so-called developing countries. Instead, the textbook turns poor countries into eco-villains: "So far, developing countries have resisted strict limits."

Remember, this is not one of those tattered textbooks of yesteryear. This book is copyright 2007 and was adopted by Portland during Vicki Phillips' tenure as superintendent. (Portland purchased these books for all high schools, whether or not teachers wanted them.)

And it's not only social studies texts that adopt a ho-hum attitude about global warming. In the widely used Pearson/Prentice Hall textbook "Physical Science: Concepts in Action," high school students don't meet the concept of climate change until Page 782. The few paragraphs on the human causes of climate change are littered with doubt. The section begins: "Human activities may also change climate over time." May? And then in boldface as the key to the section: "One possible climate change is caused by the addition of carbon dioxide and certain other gases into the atmosphere."

Possible climate change? The text is thick with a mealy language of "might," "could" and "may": "Carbon dioxide emissions from motor vehicles, power plants, and other sources may contribute to global warming."


Models of Illusion

Everyone readily admits that things aren't always what they seem. But are we really applying this knowledge in our daily dealings -- are we consciously ferreting out the illusionary from the reality? I think not. For instance, despite overwhelming evidence to the contrary, we aren't really being run by pandering politicians, self-serving lobbyists, fanatical environmentalists, and greedy Wall Street manipulators! They are the illusion. There is another even more powerful (but much less visible) agent, behind all of these puppets.

The person behind the screen is the computer programmer. And, just like in the Wizard of OZ, they do not want you to look at this real controller. I'll probably have to turn in my membership card, but as a computer programmer (and physicist and environmental activist) I'm here to spill the beans about the Wiz.

The first hint of trouble is spelled out in Wikipedia's explanation about computer programmers: "The discipline differs from many other technical professions in that programmers generally do not need to be licensed or pass any standardized (or governmentally regulated) certification tests in order to call themselves 'programmers' or even 'software engineers.'" Hmmm.

My layperson explanation is that computer programming is all about making assumptions, and then converting these into mathematical (boolean) equations.

The big picture question is this: is it really possible to accurately convert complex real-world situations into one's and zero's? Hal may think so, but higher processing brains say no. Yet this is continuously attempted, with very limited success. Let's pull the screen back a bit more. We'll start with an example about how such a model makes assumptions.

One of the computer programs I wrote was for debt collectors. A typical scenario was that a debtor was given a date to make a payment, and then the collection company doesn't receive it by that date. What response is then appropriate? In such a circumstance the computer program typically sends out an automatic letter (or makes an automatic phone call) to the debtor. (Remember there are thousands of these debtors, and it would be prohibitively time consuming for an agency person to manually check into and follow up each case.)

So what to say in this correspondence to the debtor? Well, it comes down to the assumptions made by the computer programmer. The programmer tries to simplify such situations into mathematical options. In this case they may decide that it comes down to "does the debtor have the money to make this payment: YES or NO?" This relatively basic choice then leads to a Boolean progression within the program. How does the programmer (model) decide on YES or NO? Well other indicators would be used (e.g. were prior payments made on time) to come up with a statistical probability.

Of course any computer model is not ONE set of choices, but rather a whole series of YES/NO (IF/OR) calculations that lead to a conclusion. In a complex situation (e.g. debt collection, climate change, or financial derivatives) there could easily be a hundred such choices to deal with.

To understand the implications of that, let's just consider the case where there are TEN such decision points -- each with a YES or NO answer. At the end of such a pipeline, that means that there are 2 to the tenth power (i.e. 1024) possible results. That's a LOT of different potential conclusions!

Unfortunately there are actually MANY more possibilities! My assumption that this debtor situation could be condensed down to a YES or NO answer, is not accurate. There are several other real situations that fall outside of YES or NO.

For instance, what if the debtor never got a notice in the first place that the amount was due by the date the agency is monitoring? Or what if the debtor sent the money and it got lost in transition? Or what if the debtor made the payment to the original person they owed, rather than the collection agency? Or what if the debtor sent in the money on time, and the collection agency incorrectly didn't credit the debtor for the payment? Etc., etc.

For the computer program (model) to be accurate, ALL of these scenarios need to be able to be handled properly (legally, timely, etc.). Can you begin to see the complexity here, just with this very simple example of a payment not being received on time?

There is still another significant factor (we're up to #4 now) not mentioned yet. What about the situation where the debtor hasn't paid, but it's because his child has MS, and he has no insurance? How does a computer programmer write code for more abstract concepts, like "fairness"? In other words, can ones and zeros be arranged in such a way to represent intangibles? I think not.

So the bottom line question is this: is there any way that a computer program can correctly handle ALL of these real-world possibilities -- even in this simple debt collection case? The answer is no. NO!!!

We have considerable difficulties just translating the relatively simple thing we call language -- e.g. Greek biblical texts into English. How many versions of the Bible are there? Why isn't there just one? Can we possibly hope to translate a process much more complicated than just words? We can certainly try, but clearly the answer is that there is a LOT lost in the translation of any complex scenario (debtors, energy performance, etc.) into mathematical equations and computer code.

Some uninformed parties believe that the user has control of all the variables, and can manually (and accurately) change scenarios. That is incorrect, as the user-controlled elements only represent a small fraction of the actual number of factors that are built into the computer model.

A similar fallacy is to think something like "we know the assumptions that the programmers made, and are adjusting accordingly." Wrong!

In writing a computer program of any complexity, there are literally hundreds of assumptions made. The computer programmer does NOT reveal all these to his customer, for much the same reasons that an accountant does not tell his client all of the assumptions made in preparing a tax return. He goes over a few of the more basic items, and then says "sign here."

Oh, yes, this example brings up still another MAJOR variable (#7): the data the programmer uses as the basis for his creation. Just like preparing a tax return depends on two parties working together, writing a computer model is a collaboration between scientist and programmer. If the taxpayer gives incomplete or inaccurate data to the accountant, the result will be wrong. What's disconcerting is that in many cases, neither party will know that the results are in error...

Similarly if the scientist gives incomplete or inaccurate date to the programmer to use in his creation, the result will likewise be wrong. AND neither party will know it!

I hate to keep going on here, but this is important stuff! Believe it or not, there is still one more significant variable (#8) that we have to take into account. After a computer model is generated, there is then an interpreter (e.g. IPCC) that translates the "results" for politicians and the public (i.e. the media).

Here's a surprise: these public interpretations are influenced by such factors as political, religious, environmental, financial, and scientific opinions. In their public revelations, do the interpreters explain all of their underlying biases? By now you know the answer: absolutely not. When these are introduced into the equation we obviously have strayed so far from scientific fact that it is not even in sight anymore.

Soooo, we need to think VERY CAREFULLY before we take major actions (e.g. spend a few Trillion dollars based on climate predictions, wind energy projected performance, etc.) that are almost entirely based on computer models.

What to do? Should we just scrap all computer models? No, that's the other extreme. Computer models have merit -- but shouldn't be the tail wagging the dog. We should realistically see computer models for what they are: tools to assist us in organizing our thoughts, and highly subjective results that are simply starting points for real scientific analysis. Because of their inherent limitations (which I've just touched on here) ALL computer models should be treated with a very healthy degree of skepticism.

To insure appropriate integrity, ALL computer models regarding matters of importance should be subjected to the rigors of scientific methodology. If they can't accurately and continuously replicate the results of real world data, then they should be discarded. Unfortunately that is not what is happening.

We have gotten so addicted to the illusion that these programs are accurate -- and some have become so agenda driven -- that we are now adjusting or discarding real world date that doesn't agree with the model. This is insane!

If a model has not been proven to fully reflect reality, then it has very limited use, and should be treated with the same degree of consideration that one might give a horoscope.


Warming or no warming? It's up in the clouds

Roy Spencer explains how climate models work and points out that altering the assumptions regarding just one variable about which we know little -- clouds -- can alter whether warming or cooling is predicted by the model concerned

Anthropogenic Global Warming in Climate Models

Our addition of carbon dioxide to the atmosphere by burning fossil fuels is estimated to have caused an imbalance of about 1.5 Watts per sq. meter between the 235 to 240 Watts per sq. meter of average absorbed sunlight and emitted infrared radiation. The extra CO2 makes the infrared greenhouse blanket covering the Earth slightly thicker. This energy imbalance is too small to be measured from satellites; it must be computed based upon theory.

So, if the Earth was initially in a state of energy balance, and the rate of sunlight being absorbed by the Earth was exactly 240 Watts per sq. meter, then the rate of infrared loss to outer space would have been reduced from 240 Watts per sq. meter to 238.5 Watts per sq. meter (240 minus 1.5).

This energy imbalance causes warming in the climate model. And since a warmer Earth (just like any warmer object) loses infrared energy faster than a cool object, the modeled climate system will warm up until energy balance is once again is restored. At that point, the rate at which infrared energy is lost to space once again equals the rate at which sunlight is absorbed by the Earth, and the temperature will once again remain fairly constant.

What Determines How Much the Model will Warm?

The largest source of uncertainty in climate modeling is this: will the climate system act to reduce, or enhance, the small amount of CO2 warming? The climate model (as well as the real climate system) has different ways in which an energy imbalance like that from adding CO2 to the atmosphere can be restored. The simplest response would be for the temperature alone to increase. For instance, it can be calculated theoretically that the ~40% increase in atmospheric CO2 humans are believed to have caused in the last 150 years would only cause about 0.5 deg. C warming to restore energy imbalance. This theoretical response is called the “no feedback” case because nothing other than temperature changed.

But a change in temperature can be expected to change other elements of the climate system, like clouds and water vapor. These other, indirect changes are called feedbacks, and they can either amplify the CO2-only warming, or reduce it. As shown in the following figure, all 20+ climate models currently tracked by the United Nations’ Intergovernmental Panel on Climate Change (IPCC) now amplify the warming.

This amplification is mostly through an increase in water vapor — Earth’s main greenhouse gas — and through a decrease in low- and middle-altitude clouds, the primary effect of which is to let more sunlight into the system and cause further warming. These indirect changes in response to warming are called feedbacks. The models amplify the CO2 warming with positive water vapor feedback, and with positive cloud feedback. But is this the way that the real climate system operates?

Uncertainties in Climate Model Cloud and Water Vapor Processes

The climate model equations are only approximations of the physical processes that occur in the atmosphere. While some of those approximations are highly accurate, some of the most important ones from the standpoint of climate change are unavoidably crude. This is because the real processes they represent are either (1) too complex to include in the model and still have the model run fast on a computer, or (2) because our understanding of those processes is still too poor to accurately model them with equations.

This is especially true for cloud formation and dissipation, which in turn has a huge impact on how much sunlight is absorbed by the climate system. The amount of cloud cover generated in the model in response to solar heating helps control the Earth’s temperature, so the manner in which clouds change with warming is of huge importance to global warming predictions.

Climate modelers are still struggling to get the models to produce cloud cover amounts and types like those seen in different regions, and during different seasons. The following NASA MODIS image of the western U.S. and eastern Pacific Ocean shows a wide variety of cloud types which are controlled by a variety of different processes.

The complexity of clouds is intuitively understood by everyone, experts and non-experts alike. It is probably safe to say that all climate modelers recognize that the modeling of cloud behavior accurately is very difficult, and is something which has not yet been achieved in global climate models.

All of the IPCC climate models reduce low- and middle-altitude cloud cover with warming, a positive feedback. This is the main reason for the differences in warming produced by different climate models (Trenberth and Fasullo, 2009). I predict that this kind of model behavior will eventually be shown to be incorrect. And while the authors were loathe to admit it, there is already some evidence showing up in the peer-reviewed scientific literature that this is the case (Spencer et al., 2007; Caldwell and Bretherton, 2009).

I believe that the modelers have mistakenly interpreted decreased cloud cover with warming in the real climate system as positive cloud feedback (warming causing a cloud decrease), when in reality it was actually the decrease in clouds that mostly caused the warming. This is basically an issue of causation: one direction of causation has been ignored when trying to estimate causation in the opposite direction (Spencer and Braswell, 2008).

The fundamental issue of causation in climate modeling isn’t restricted to just clouds. While warming will, on average, cause an increase in low-level water vapor, precipitation systems control the water vapor content of most of the rest of the atmosphere. As shown in the following illustration, while evaporation over most of the Earth’s surface is continuously trying to enhance the Earth’s natural greenhouse effect by adding water vapor, precipitation is continuously reducing the greenhouse effect by converting that water vapor into clouds, then into precipitation.

But while the physics of evaporation at the Earth’s surface is understood pretty well, the processes controlling the conversion of water vapor into precipitation in clouds are complex and remain rather mysterious. And it is the balance between these two processes — evaporation and precipitation — that determines atmospheric humidity.

Even in some highly complex ‘cloud resolving models’ – computer models that use much more complex computations to actually ‘grow’ clouds in the models – the point at which a cloud starts precipitating in the model is given an ad hoc constant value. I consider this to be a huge source of uncertainty, and one that is not appreciated even by most climate modelers. The modelers tune the models to approximate the average relative humidity of the atmosphere, but we still do not understand from ‘first principles’ why the average humidity has its observed value. We would have to thoroughly understand all of the precipitation processes, which we don’t.

In the end, many of the approximations in climate models will probably end up being not very important for forecasting climate change…but it takes only one critical process to be wrong for model projections of warming to be greatly in error. The IPCC admits that their largest source of uncertainty is low cloud feedback, that is, how low cloud cover will change with warming. And, as just mentioned, I believe how precipitation efficiency might change with temperature is also a wild card in climate model predictions.

Sources of Global Warming: Humans or Nature?

At this point hopefully you understand that climate modelers think global warming is the result of humans ‘upsetting’ the Earth’s radiative energy balance. And I agree with them that adding more carbon dioxide to the atmosphere must have some effect…but how large is this change in comparison the energy imbalances the climate system imposes upon itself?

It turns out that the modelers have made a critical assumption that ends up leading to the their conclusion that the climate system is very sensitive to our greenhouse gas emissions: that the climate system was in a state of energy balance in the first place.

There is a pervasive, non-scientific belief in the Earth sciences that nature is in a fragile state of balance. Whether it is ecosystems or the climate systems, you will hear or read scientists claims about the supposed fragility of nature. But this is a subjective concept, not a scientific one. Still, it makes its way into the scientific literature (read the abstract to this seminal paper on the first satellite measurements of the Earth’s energy budget…look for “delicately balanced”). Just because nature tends toward a balance does not mean that balance is in any way ‘fragile’. And what does ‘fragile’ even mean when nature itself is always upsetting that balance anyway?

Why is this important to climate modeling? Because if climate researchers ignore naturally-induced climate variability, and instead assume that most climate changes are due to the activity of humans, they will inevitably come to the conclusion that the climate system is fragile: that is, that feedbacks are positive. It’s a little like some ancient tribe of people believing that severe weather events are the result of their moral transgressions.

If the warming observed during the 20th Century was due to human greenhouse gas emissions, then the climate system must be pretty sensitive (positive feedbacks). But if the warming was mostly due to a natural change in cloud cover, then the climate system is more likely to be insensitive (negative feedbacks). And there is no way to know whether natural cloud changes occurred during that time simply because our global cloud observations over the last century are nowhere near accurate enough.

So, climate modelers simply assume that there are no natural long-term changes in clouds, water vapor, etc. But they do not realize that in the process they will necessarily come to the conclusion that the climate system is very sensitive (feedbacks are positive). As a result, they program climate models so that they are sensitive enough to produce the warming in the last 50 years with increasing carbon dioxide concentrations. They then point to this as ‘proof’ that the CO2 caused the warming, but this is simply reasoning in a circle.

Climate modelers have simply assumed that the Earth’s climate system was in a state of energy balance before humans started using fossil fuels. But as is evidenced by the following temperature reconstruction for the last 2,000 years (from Loehle, 2007), continuous changes in temperature necessarily imply continuous changes in the Earth’s energy balance.

And while changes in solar activity are one possible explanation for these events, it is also possible that there are long-term, internally-generated fluctuations in global energy balance brought about by natural cloud or water vapor fluctuations. For instance, a change in cloud cover will change the amount of sunlight being absorbed by the Earth, thus changing global temperatures. Or, a change in precipitation processes might alter how much of our main greenhouse gas — water vapor — resides in the atmosphere. Changes in either of these will cause global warming or global cooling.

But just like the tribe ancient people not understanding that there are physical processes at work in nature that cause storms to occur, climate modelers tend to view climate change as something that is largely human in origin – presumably the result of our immoral burning of fossil fuels.

Faith-Based Climate Modeling

There is no question that much expense and effort has gone into the construction and improvement of climate models. But that doesn’t mean those models can necessarily predict climate 20, 50, or 100 years from now. Ultimately, the climate researcher (and so the politician) must take as a matter of faith that today’s computerized climate models contain all of the important processes necessary to predict global warming.

This is why validating the predictions of any theory is so important to the progress of science. The best test of a theory is to see whether the predictions of that theory end up being correct. Unfortunately, we have no good way to rigorously test climate models in the context of the theory that global warming is manmade. While some climate modelers will claim that their models produce the same “fingerprint” of manmade warming as seen in nature, there really is no such fingerprint. This is because warming due to more carbon dioxide is, for all practical purposes, indistinguishable from warming due to, say, a natural increase in atmospheric water vapor.

The modeler will protest, “But what could cause such a natural change in water vapor?” Well, how about just a small change in atmospheric circulation patterns causing a decrease in low cloud cover over the ocean? That would cause the oceans to warm, which would then warm and humidify the global atmosphere (Compo and Sardeshmukh, 2009). Or how about the circulation change causing a change in wind shear across precipitation systems? This would lead to a decrease in precipitation efficiency, leading to more water vapor in the atmosphere, also leading to a natural ‘greenhouse’ warming (Renno et al., 1994).

To reiterate, just because we don’t understand all of the ways in which nature operates doesn’t mean that we humans are responsible for the changes we see in nature.

The natural changes in climate I am talking about can be thought of as ‘chaos’. Even though all meteorologists and climate researchers agree that chaos occurs in weather, climate modelers seem to not entertain the possibility that climate can be chaotic as well (Tsonis et al., 2007). If they did believe that was possible, they would then have to seriously consider the possibility that most of the warming we saw in the 20th Century was natural, not manmade. But the IPCC remains strangely silent on this issue.


Meteorologist says man not cause of climate issue

Dave Dahl, chief meteorologist at KSTP in the Twin Cities, told Hudson Rotarians that man is not the culprit when it comes to global warming, or climate change, issues. Dahl spoke to the Hudson Thursday Noon Rotary Club on July 9 and said what was called “global warming” is now tabbed “climate change” because temperatures on the planet have decreased in the past couple years. “Over 30,000 scientists are now saying that humans are not causing changes in global conditions,” Dahl said. “The climate has ‘changed’ since the planet began.”

He said that the heating of the earth — which is mostly a good thing — is caused primarily by water vapor — about 98 percent. He said carbon and other elements account for about 2 percent of the mix. Of that 2 percent, human involvement represents only about 2 percent of that (.0004 percent). “It is my feeling, and the opinion of more and more scientists, that the sun is the driving force behind climate changes — heating and cooling,” Dahl said. “Solar activity, including flares and sunspots, is usually quite active during warm stretches. The activity has been very quiet the past couple of years and the temperatures have dropped.”

He said last year’s solar activity was the quietest in 100 years. So far in 2009, the activity is even less. “In the northern hemisphere, the 2007-08 winter was the coldest in 50 years and 2008-09 was the coldest in a century,” Dahl said.

Another flaw in the entire system is the recording of temperatures around the world, he said. “The United States has the most reputable system, but the recording system in nearly nine out of 10 locations does not meet National Weather Service standards. Many of the sites are located on tar roofs, next to air conditioner exhaust fans, etc. The records are questionable.”

He said we should be using only satellite information, which shows that temperatures have been cooling for several years. “Even believers of man-made ‘global warming’ have begun to realize that we do not face global warming — that’s why the terminology has been changed to ‘climate change,’” Dahl said.

Another key factor in the study of earth temperature is the sequence of events. “People who believe in man-made global warming claim that an increase in carbon dioxide leads to global warming,” Dahl said. “Concrete scientific evidence shows throughout history that temperatures increase first, then carbon levels increase (carbon comes from many sources in addition to man-made pollution). That’s contrary to the claims made in the Al Gore movie (‘Inconvenient Truth’).” Dahl claims that the Gore movie contains at least 50 factual errors — he called them absolutely false.

Dahl said that carbon spewed from one of the many volcanoes around the world adds much, much more carbon to the atmosphere than all the cars combined. “I’m all for limiting pollution, but carbon is not necessarily a pollutant – plants would prefer more carbon,” Dahl said.

He noted that there has been much publicity about the shrinking of the polar ice cap. “Evidence shows that the cap was much smaller in the 1930s when we went through a warm period,” Dahl said. “Siberian ice has grown 20 percent in the past two years.”

Dahl noted that throughout history there is evidence of warm and cold periods. “It’s a recurring pattern and the sun in the key ingredient,” Dahl said. “The fact is, we could very well be headed for a cool period. Some scientists believe we are headed into a 20-30-year cooling trend based on historical patterns.”

He said it is unfortunate that the science of climate has been mixed in with political policy and political agendas. “Many scientists are afraid to speak out because much of the funding comes from the government and they are afraid they will lose funding,” Dahl said. “The political landscape endorses only one view — that humans are causing global warming. The policy-makers and media drive what people hear. People like to think that we can control our destiny — this is one thing we can’t control. People don’t like to hear that.”

Dahl hopes that what he considers to be the truth will become evident in the next five to 10 years.



Herbert Reul is the new head of the EU Parliament's powerful Industry Committee. The Christian Democrat questions the consensus on climate change, defends energy companies and is fighting summer time plans.

On Monday evening, the 42 EU Members of the Christian Democratic parties CDU and CSU, nominated the 56-year-old as chairman of the powerful Industry Committee. As a result, Reul will play a key role in coming years with regards to the EU's legal proceedings following the conclusion of the Copenhagen climate change negotiations.

The former Secretary General of the CDU in North Rhein-Westphalia is known to question the global consensus on climate change. "I doubt that humans really contribute as much to global warming as is generally claimed," Reul admits. "But the political decisions on climate change have been taken and as chairman of the industry committee, I must now ensure that they are implemented in a reasonable way." [transl. BJP]



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