The Fall meeting of the American Geophysical Union (AGU) here in San Francisco this week is amazing for it’s sheer size: many thousands of Earth scientists presenting talks and posters on just about every Earth science subject imaginable.

Today was my chance to try to convince other scientists who work on the critical issue of feedbacks in the climate system that some fundamental mistakes have been made that have misled climate researchers into believing that the climate system is quite sensitive to our greenhouse gas emissions. A tough sell in only 14 minutes.

It was standing room only…close to 300 scientists by my estimate. There were only a couple of objections to my presentation…rather weak ones. Afterward I had a number of people comment favorably about the ‘different’ way I was looking at the problem.

And while that should be comforting, it is also disturbing. Since when in science did the issue of ‘causation’ become a foreign concept? When did the direction of causation between two correlated variables (in my case, clouds and temperature) become no longer important?

If temperature and clouds vary together in ‘sort of’ the same way in satellite observations as they do in climate models, then the models are considered to be ‘validated’. But my message, which might not have come across as clearly as it should have due to time constraints, was that such agreement does NOT validate the models when it comes to feedback, and feedbacks are what will determine how much of an impact humans have on the climate system.

Andrew Lacis, who works climate modeling with Jim Hansen, came up and said he agreed with me that, in general, the feedback problem is more difficult than people have been assuming. In a talk after mine, Graeme Stephens gave me a backhanded compliment when he agreed with at least my basic message that the way in which we assume the climate system functions (in my terms, what-causes-what to happen) IS important to how we then deduce how sensitive the climate is to such things as our carbon dioxide emissions.

The three organizers of the session were very gracious to invite me, since they knew my views are controversial. One of the three was Andrew Dessler, who works in water vapor feedback. I had never met Andy before, and he’s a super nice guy. They all agreed that there needs to be more debate on the subject.

But most of the talks presented followed the recipe that has become all too common in recent years: analyze the output of climate models that predict substantial global warming, and simply assume the models are somewhere near correct.

There seems to be great reluctance to consider the possibility that these computerized prophets of doom, which have required so many scientists and so much money and so many years to develop, could be wrong. I come along with an extremely simple climate model that explains the behavior of the satellite data in details that are beyond even what has been done with the complex climate models…and then the more complex models are STILL believed because…well…they’re more complex.

Besides, since my simple model would predict very little manmade global warming, it must be wrong. After all, we know that manmade global warming is a huge problem. All of the experts agree on that. Just ask Al Gore and the mainstream news media.

UPDATED 12/16/09 1415 PST with final pdf version of talk…and press release, 1425 PST.

I decided to make my invited presentation on estimating cloud feedbacks from satellite measurements available here (final version-pdf):Spencer-Forcing-Feedback-AGU-09-San-Francisco-final. There will be a UAH press release on Wednesday, December 16, which is embargoed until 11 a.m. PST (1 p.m. CST).

UAHuntsville Press Release
EMBARGOED: For release after 11 a.m., PST, Wednesday, Dec. 16, 2009

Chicken and egg question
looms over climate debate

SAN FRANCISCO, Calif. (Dec. 16, 2009) — Which came first, the warmer temperatures or the clearer skies?

Answers to that and similar “chicken and egg” type questions could have a significant impact on our understanding of both the climate system and manmade global warming.

In an invited talk scheduled for today at the American Geophysical Union’s fall meeting in the Moscone Convention Center, Dr. Roy Spencer from The University of Alabama in Huntsville will discuss the challenge of answering questions about cause and effect (also known as forcing and feedback) in the climate.

“Feedbacks will determine whether the manmade portion of global warming ends up being catastrophic or barely measurable,” Spencer said recently.

Spencer’s interest is in using satellite data and a simple climate model to test the simulated feedback processes contained in climate models that are used to forecast global warming.

“I am arguing that we can’t measure feedbacks the way people have been trying to do it,” he said. “The climate modelers see from satellite data that warm years have fewer clouds, then assume that the warmth caused the clouds to dissipate. If this is true, it would be positive feedback and could lead to strong global warming. This is the way their models are programmed to behave.

“My question to them was, ‘How do you know it wasn’t fewer clouds that caused the warm years, rather than the other way around?’ It turns out they didn’t know. They couldn’t answer that question.”

One problem is the simplicity of the climate models. Because cloud systems are so complex and so poorly understood, all of the climate models used by the United Nations’ Intergovernmental Panel on Climate Change use greatly simplified cloud parameters to represent clouds. But the calculations that set those parameters are based on assumed cause-and-effect relationships.

Those assumptions might be working in the wrong direction, Spencer said. “What we have found is that cloud cover variations causing temperature changes dominate the satellite record, and give the illusion of positive feedback.”

Using satellite observations interpreted with a simple model, Spencer’s data support negative feedback (or cooling) better than they support positive feedback.

“This critical component in global warming theory – cloud feedback – is impossible to measure directly in the real climate system,” Spencer said. “We haven’t figured out a good way to separate cause and effect, so we can’t measure cloud feedback directly. And if we don’t know what the feedbacks are, we are just guessing at how much impact humans will have on climate change.

“I’m trying to spread the word: Let’s go back to basics and look at what we can and cannot do with measurements of the real climate system to validate both climate models and their predictions.”

A former NASA scientist, Spencer is a principal research scientist in UAHuntsville’s Earth System Science Center.

I’ll admit to being a skeptic when it comes to other skeptics’ opinions on the potential effects of sunspot activity on climate. Oh, it’s all very possible I suppose, but I’ve always said I’ll start believing it when someone shows a quantitative connection between variations in global cloud cover (not temperature) and geomagnetic activity.

Maybe my skepticism is because I never took astronomy in college (oops…my wife reminds me I took it 1st year). Or, maybe it’s because I can’t see or feel cosmic rays. They sound kind of New Age to me. After all, I can see sunlight, and I can feel infrared radiation…but cosmic rays? Some might say, “Well, Roy, you work with satellite microwave data, and you can‘t see or feel those either!” True, but I DO have a microwave oven in my kitchen…where’s your cosmic ray oven?

Now…where was I? Oh, yeah. So, since I’ve been working with 9 years of global reflected sunlight data from the CERES instrument flying on NASA’s Terra satellite, last night I decided to take a look at some data for myself.

The results, I will admit, are at least a little intriguing.

The following plots show detrended time series of monthly running 5-month averages of (top) CERES reflected shortwave deviations from the average seasonal cycle, and (bottom) monthly running geomagnetic Ap index values from the NOAA Space Weather Prediction Center. As I understand it, the Ap index is believed to be related to the level of cosmic ray activity reaching the Earth. (I will address the reason for detrending below).

Note that there is some similarity between the two plots. If we do a scatterplot of the data (below), we get an average linear relationship of about 0.05 W per sq. meter increase in reflected sunlight per 1 unit decrease in Ap index. This is at least qualitatively consistent with a decrease in solar activity corresponding to an increase in cloud cover.
(I’ve also shown a 2nd order polynomial fit (curved line) in the above plot for those who think they see a nonlinear relationship there.)

But just how big is this linear relationship seen in the above scatterplot? From looking at a 70-year plot of Ap data (originally from David Archibald), we see that the 11-year sunspot cycle modulates the Ap index by at least 10 units. Also, there are fairly routine variations on monthly and seasonal time scales of about 10 Ap units, too (click on image to see full-size):

When the 10 Ap unit variations are multiplied by the 0.05 scale factor, it suggests about a 0.5 W per sq. meter modulation of global reflected sunlight during the 11 year solar cycle (as well as in monthly and yearly variations of geomagnetic activity). I calculate that this is a factor of 10 greater than the change in reflected sunlight that results from the 0.1% modulation of the total solar irradiance during the solar cycle.

At face value, that would mean the geomagnetic modulation of cloudiness has about 10 times the effect on the amount of sunlight absorbed by the Earth as does the solar cycle’s direct modulation of the sun’s output. It also rivals the level of forcing due to anthropogenic greenhouse gas emissions, but with way more variability from year to year and decade to decade. (Can anyone say, “natural climate variability”?)

Now, returning to the detrending of the data. The trend relationship between CERES reflected sunlight and the Ap index is of the opposite sign to that seen above. This suggests that the trend in geomagnetic activity during 2000-2008 can not explain the trend in global reflected sunlight over the same period of time. However, the ratio of the trends is very small: +0.004 Watts per sq. meter per unit Ap index, rather than -0.045. So, one can always claim that some other natural change in cloud cover is overpowering the geomagnetic modulation of cloudiness. With all kinds of climate forcings all mingled in together, it would be reasonable to expect a certain signal to emerge more clearly during some periods, and less clearly during other periods.

I also did lag correlation plots of the data (not shown), and there is no obvious lag in the correlation relationship.

All of this, of course, assumes that the observed relationship during 2000-2008 is not just by chance. There is considerable autocorrelation in the reflected sunlight and geomagnetic data, which I have made even worse by computing monthly running 5-month averages (the correlation strengths increased with averaging time). So, there are relatively few degrees of freedom in the data collected during 2000-2008, which increases the probability of getting a spurious relationship just by chance.

All of the above was done in a few hours, so it is far from definitive. But it IS enough for me to keep an open mind on the subject of solar activity affecting climate variations. As usual, I’m just poking around in the data and trying to learn something…while also stirring up some discussion (to be enjoyed on other blogs) along the way.

UPDATE (12:30 p.m. 10 December 2009)
There is a question on how other solar indices compare to the CERES reflected sunlight measurements. The following lag correlation chart shows a few of them. I’m open to suggestions on what any of it might mean.

(last updated 9:05 a.m. 9 December 2009).

I get so many questions from readers about a variety of global warming issues that I thought I would whip up some Q&A for those who want to understand the views of skeptics a little better. I will try to update these with links and additional answers as time permits.

Climate science is complex and the study of it is highly specialized. Nevertheless, there is a common theme that runs through the claims of the global warming establishment, from Al Gore’s movie An Inconvenient Truth, to the UN’s Intergovernmental Panel on Climate Change (IPCC): Weather and climate events that happen naturally are being increasingly blamed on the activities of humans. So, causation is at the root of most beliefs about global warming and climate change.

As one digs further into the science, the direction of causation also emerges as a key theme, and it is one that can totally change the degree to which it appears humans affect the climate system. In my own area of research I have found that mixing up cause and effect when examining how cloud cover varies with temperature has greatly misled the scientific establishment regarding how sensitive the climate system is to our addition of greenhouse gases to the atmosphere.

Not all skeptics believe the same things, though, so some skeptics will object to some of what I have listed below. These represent my opinions, not all of which are necessarily ascribed to by other skeptics. Additional details on many of these issues can be found throughout this website, including a Q&A list I published on April 19, 2009.

The following list, in no particular order, are my responses to common claims and accusations about global warming skeptics. If other scientists or laypersons want me to add to the list, or want to argue for changes, email me and I will update it as appropriate. Please be sure to check back for the latest update (posted above).

1. Skeptics deny global warming. No, we deny that warming has been mostly human-caused.

2. Skeptics are paid by big oil. The vast majority of skeptics have never been paid anything by Big Oil (me included).

3. Skeptics don’t publish in the peer reviewed literature. Wrong…but it is true we do not have nearly as many publications as the other side does. But it only takes one scientific study to destroy a scientific hypothesis, which is what anthropogenic global warming theory is.

4. Skeptics are not unified with an alternative explanation for global warming. Well, that’s the way science works in a field as immature as climate change science. The biggest problem is that we really don’t understand what causes natural climate variability. Kevin Trenberth has now famously admitted as much in one of the Climategate emails, where said it’s a “travesty” that we don’t know why warming has stopped in the last 7 to 10 years. For century-time-scale changes, some believe it is cloud cover being modulated by cosmic ray activity, which is in turn affected by sunspot activity. A few others think it is changes in the total energy output of the sun (possible, but I personally doubt it). In my opinion, it is internal, chaotic variability in the ocean and atmosphere circulation causing small changes in cloud cover. Since clouds are a natural sunshade, changing their coverage of the Earth will cause warming or cooling. The IPCC simply assumes this does not happen. If they did, they would have to admit that natural climate change happens, which means they would have to address the possibility that most of the warming in the last 50 has been largely natural in origin.

5. But the glaciers are melting! Many glaciers which have been monitored around the world for a long time have been retreating since the 1800’s, before humans could have been responsible. A few retreating glaciers are even revealing old tree stumps…how did those get there? Planted by skeptics?

6. But the sea ice is melting! Well, the same thing happened back in the 1920’s and 1930’s, with the Northwest Passage opening up in 1940. It was just as warm, or nearly as warm, in the Arctic in the 1930’s. Again, this is before humans could be blamed. There were very low water levels in the Great Lakes in the 1920’s too, just as has happened recently. We have accurate measurements of sea ice cover from satellites only since 1979, so there is no way to really know whether sea ice cover is less than it was before.

7. But we just had the warmest decade in recorded history! Well, if thermometer measurements had started in, say 200, AD (rather than in the 1800’s), and it was now 850 AD, the same thing might well have been said back then. The climate system is always warming or cooling, and the Industrial Revolution (and thus our carbon dioxide emissions) just happened to occur while we were still emerging from the Little Ice Age…a warming period.

8. But the Antarctic ice shelves are collapsing! Well, sea ice around Antarctica has been expanding since we started monitoring by satellite in 1979….so which do we use as evidence? There is no convincing evidence of warming in Antarctica, except in the relatively small Antarctic Peninsula, which juts out into the ocean. Just as glaciers naturally flow to the sea, ice shelves must eventually break off. It is very uncertain how often this happens through the centuries, and what has been observed in recent years might be entirely normal. Similarly, it was warmer in Greenland in the 1930’s than it has been more recently.

9. But the sea levels are rising! Yes, and from what we can tell, they have been rising since the end of the last Ice Age. Again, the more recent rise might be just a consequence of our emergence from the Little Ice Age, which bottomed out in the 1600’s.

10. But we keep emitting carbon dioxide, which we know is a greenhouse gas! Yes, I agree. But the direct warming effect of moré CO2 is agreed by all to be small…and I predict that when we better understand how clouds change in response to that small warming influence, the net warming in response to more CO2 will be smaller still. This is the “feedback” issue, which determines “climate sensitivity”, the area of research I spend most of my time on. I and a minority of other scientists believe the net feedbacks in the climate system are negative, probably driven by negative cloud feedback. In contrast, all twenty-something IPCC climate models now exhibit positive cloud feedback.

11. But we can’t keep pumping CO2 into the atmosphere forever! No, and we won’t. Assuming fossil fuels will be increasingly difficult to find and access in the coming decades, the continuing demand for energy ensures that new energy technologies will be developed. It’s what humans do…adapt.

12. But we shouldn’t be interfering with nature! Actually, it would be impossible to NOT interfere with nature. Chaos theory tells us that everything that happens, naturally or anthropogenically, forever alters the future state of the climate system. I predict that science will eventually understand that more CO2 is good for life on Earth. This doesn’t mean it will be good for every single species…but when Mother Nature changes the climate system, there are always winners and losers anyway. In the end, this is a religious issue, not a scientific one. Interestingly I have found that the vast majority of scientists also have the religious belief that we should not be impacting nature. I believe this has negatively affected their scientific objectivity.

Senator Barbara Boxer has said that the e-mails supposedly stolen from a computer at the Climatic Research Unit in the UK should lead to prosecution of the hacker who did it. This rather obvious attempt to divert attention from the content of the emails, to the manner in which the e-mails were obtained, led my wife to make an interesting observation.

What if the intercepted emails uncovered medical researchers discussing the fudging and hiding of cancer research data, and trying to interfere with the peer review process to prevent other medical researchers from getting published? There would be outrage from all across the political spectrum. Scientists behaving badly while the health of people was at stake would not be defended by anyone.

So why should it be any different with Climategate? Unnecessary restrictions on (or price increases for) energy use could needlessly kill millions of people who are already poverty stricken. Cancer research affects many of us, but energy costs affect ALL of us.

In a little over a week I will be giving an invited paper at the Fall meeting of the American Geophysical Union (AGU) in San Francisco, in a special session devoted to feedbacks in the climate system. If you don’t already know, feedbacks are what will determine whether anthropogenic global warming is strong or weak, with cloud feedbacks being the most uncertain of all.

In the 12 minutes I have for my presentation, I hope to convince as many scientists as possible the futility of previous attempts to estimate cloud feedbacks in the climate system. And unless we can measure cloud feedbacks in nature, we can not test the feedbacks operating in computerized climate models.

WHAT ARE FEEDBACKS?

To review, the main feedback issue is this: In response to the small direct warming effect of more CO2 in the atmosphere, will clouds change in ways that amplify the warming (e.g. a cloud reduction letting more sunlight in, which would be a positive feedback), or decrease the warming (e.g. a cloud increase causing less sunlight to be absorbed by the Earth, which would be a negative feedback)?

In the former case, we could be heading for a global warming catastrophe. In the latter case, manmade global warming might be barely measurable (and previous warming would be mostly the result of some natural cause). All climate models tracked by the IPCC now have positive cloud feedbacks, by varying amounts, which partly explains why the IPCC expects anthropogenic global warming to be so strong.

Obviously, we need to know what feedbacks operate in the climate system.

ESTIMATING FEEDBACKS: AN UNSOLVED PROBLEM

I am now quite convinced that most, if not all, previous estimates of feedback from our satellite observations of natural climate variability are in error. Furthermore, this error is usually in the direction of positive feedback, which will then give the illusion of a ‘sensitive’ climate system. More on that later.

The goal seems simple enough: to measure cloud feedbacks, we need to determine how much clouds change in response to a temperature change. But most researchers do not realize that this is not possible without accounting for causation in the opposite direction, i.e., the extent to which temperature changes are a response to cloud changes.

As I will demonstrate in my AGU talk on December 16, for all practical purposes it is not possible (at least not yet) to measure cloud feedbacks because the two directions of causation are intermingled in nature. As a result, it is not possible with current methods to measure feedbacks in response to a radiative forcing event such as a change in cloud cover, or even a major volcanic eruption, such as that from the 1991 eruption of Mt. Pinatubo.

The reason is that the size of the radiative forcing of a temperature change overwhelms the size of the radiative feedback upon that temperature change, and our satellite measurements can not tell the difference. There are only two special situations where it can be done: (1) the theoretical case of an instantaneously imposed, and then constant amount of radiative forcing…which never happens in the real world; and (2) the real world case where temperature changes are caused non-radiatively. While I will not go into the evidence here, satellite observations suggest that cloud feedbacks in the latter case are strongly negative.

Now, if you have an accurate estimate of the radiative forcing of temperature change, accurate estimates of radiative feedback can be made. But we do not have good estimates of this forcing during natural climate variations. Only in climate model simulations where a known amount of radiative forcing is imposed upon the model can this be done. (In another method, if you try to estimate feedback by measuring how fast the ocean responds, you also run into problems because your answer depends upon how fast and how deep in the ocean you assume the temperature change will extend.)

EXAMPLE 1: FEEDBACKS FROM THE CHANGE IN SEASONS

Once one realizes that clouds causing a temperature change (forcing) corrupts our estimates of temperature causing a cloud change (feedback), it becomes apparent that many of the previous attempts to estimate feedback will not work.

For instance, many researchers think that you can estimate feedbacks from the seasonal cycle in average solar illumination of the Earth and the resulting temperature response. There is about a 7% peak-to-peak variation in the amount of solar energy reaching the Earth during the year, with a maximum occurring in March and September, and the minimum in June. So, one would think we could measure by how much this change in solar heating causes a change in temperature.

The trouble is that global circulation patterns also change dramatically with the seasons, mostly due to the large difference in land masses between the Northern and Southern Hemispheres. Since cloud formation is affected by a variety of circulation induced effects (fronts, temperature inversions, etc.), the cloud cover and thus the natural shading of the Earth by clouds also changes with the seasons, through these seasonal circulation changes.

These non-temperature effects on cloud cover will confound the estimation of feedbacks, because their magnitude is considerably larger than the magnitude of the feedbacks. If the Earth was 100% covered by ocean that had a constant depth everywhere, then it might be possible to estimate feedbacks in this way…but not in the real world.

EXAMPLE 2: FEEDBACKS FROM EL NINO & LA NINA

Researchers have also made feedback estimates from the anomalously warm conditions that exist during El Nino, and the cool conditions during La Nina. But this runs into a similar problem as estimating feedbacks from the change in seasons: there are substantial variations in global circulation patterns between El Nino and La Nina, especially in the tropics. These circulation changes can induce cloud changes – wholly apart from temperature-induced changes – and there is no known way to separate the circulation-induced cloud changes (forcing) from the feedback-induced changes.

THE ERRORS WHICH RESULT FROM PREVIOUS FEEDBACK ESTIMATES

So, how do these problems impact our estimates of feedback? Except under certain circumstances, they will always cause a bias toward positive feedback. The reason is that radiative forcing and radiative feedback always work in opposition to each other. (Here I am speaking of the net feedback parameter, which also contains the increase in loss of infrared radiation by the Earth in direct response to warming).

Since our satellites measure the two effects combined, if you assume only feedback is being measured when both feedback and forcing are occurring, then you will underestimate the feedback parameter, which is a bias in the direction of positive feedback.

THE IMPACT ON CLIMATE MODEL VALIDATION

I can predict that the climate modelers will claim that we really do not need to know the direction of causation…we can just measure the temperature/cloud relationships in nature, and then adjust the models until they produce the same temperature/cloud relationships.

While this might sound reasonable, it turns out that the radiative signature of forcing is much larger than that of feedback. As a result, one can get pretty good agreement between models and observations even when the model feedbacks are greatly in error. Another way of saying this is that you can get good agreement between the model behavior and observations whether the cloud feedbacks are positive OR negative. This is another fact I will be demonstrating on December 16.

WHERE DO WE GO FROM HERE?

My first task is to convince both observationalists and modelers that much of what they previously believed about atmospheric feedbacks operating in the real world can be tossed out the window. Obviously, this will be no small task when so many climate experts assume that nothing important could have been overlooked after 20 years and billions of dollars of climate research.

But even if I can get a number of mainstream climate scientists to understand that we still do not know whether cloud feedbacks are positive or negative, it is not obvious how to fix the problem. As I suggested a couple of blog postings ago, maybe we should quit trying to test whether a climate model that produces 3 deg. C of warming in response to a doubling of carbon dioxide is “true”, and instead test to see if we can falsify a climate model which only produces 0.5 deg. C of warming. As someone recently pointed out in an email to me, a climate model IS a hypothesis, and in science a hypothesis can only be falsified — not proved true.

From what I have seen from my analysis of output from 18 of the IPCC’s climate models, I’ll bet that we can not falsify such a model with our current observations of the climate system. I suspect that the climate modeling groups have only publicized models that produce the amount of warming they believe “looks about right”, or “looks reasonable”. Through group-think (or maybe the political leanings of, and pressure from, the IPCC leadership?), they might well have tossed out any model experiments which produced very little warming.

In any event, I believe that the scientific community’s confidence that climate change is now mostly human-caused is seriously misplaced. It is time for an independent review of climate modeling, with experts from other physical (and even engineering) disciplines where computer models are widely used. The importance of the issue demands nothing less.

Furthermore, the computer codes for the climate models now being used by the IPCC should be made available to other researchers for independent testing and experimentation. The Data Quality Act for U.S.-supported models already requires this, but this law is being largely ignored.

As a (simple) modeler and computer programmer myself, I know that the modeling groups will protest that the models are far too complex and finely tuned to let amateurs play with them. But that’s part of the problem. If the models are that complex and fragile, should we be basing multi-trillion dollar policy decisions on them?

The lack of coverage of Climategate by the mainstream news media over the last 2 weeks has been breathtaking. Richard North at the EUReferendum blog advanced a way to measure media bias of this kind with what he calls his “Tiger Woods Index”, where he compares the number of Google search web matches to Google search news matches. The idea is that if the media are avoiding an issue, then the number of news matches relative to web matches will decrease. If the media are overly obsessed with an issue compared to what the public is discussing on web pages, then the number of Google search news matches will increase relative to the number of web matches.

I decided to play around with this idea with searches on several names and phrases of my own. Since “media bias” is such an ugly phrase, I will characterize the resulting statistics as a Media Interest Index. I found that for issues where the news media seems to have about the same level of interest as the public, the ratio of web page matches to news page matches was somewhere in the range of 500 to 1,000.

By using a totally scientific process (since I’m a scientist) to compare the media’s interest to the public’s interest, I decided that a ratio of 1,000 would represent equal media and public interest. Please do not ask for the data I used, since I will either hide it or delete it before I give it up.

The Media Interest Index is then 1,000 times the number of news matches divided by the number of web matches. The result is 1 for equal interest between the media and the public. A value of 2 would mean the news media are “twice” as interested as the public. A value of 0.5 would mean that the media are only half as interested as the public.

See? Totally scientific.

The following chart shows the results for Google searches on several words, phrases, and names. The phrase “health care reform” is of great interest to both the media and the public, and we see a Media Interest Index value of 1.27, indicating roughly equal interest between the media and the public.

On this scale, “Climategate” has a MII of only 0.14, suggesting much less interest (about one-seventh) from the media than from the public in general. Of course, some news outlets, especially those in the UK and FoxNews, have been providing heavy coverage, so the low value is being dragged down by some other news organizations.

Similarly, the phrase “media bias” has an MII value of 0.2, indicating the rather obvious fact that the media are reluctant to do news stories on “media bias”, an issue that is of considerable interest at many non-news websites.

But there are even bigger extremes to be seen in the above chart. For instance, there seems to be a disproportionate interest of the media in “Obama”, with an MII value of 6.5. Even that, however, is not as interesting to the media as “Bush’s gaffe”, with an index value over 27!

And while “Obama” has a disproportionately large interest from the media, the interest in “Obama’s gaffe” is disproportionately small, with an MII value of only 0.01! Thus, the media seems to be about 2,000 times more interested in gaffes uttered by Bush than those uttered by Obama. Similarly, comparing the media’s interest in “global warming” to their interest in “Climategate”, the ratio of those two MII values approaches 30.

For any social scientists, pollsters, or political pundits who might object to the above analysis and would like to vent, you can contact me at idontreallycare@hotmail.com.
This research was not supported by any coal or oil company…but I wish it was.

It has been two weeks since Climategate revealed that some of the IPCC’s leading researchers have conspired to manipulate temperature data, hide data from other researchers, and bully those scientists who do not agree with them by interfering with the peer review process.

(If you haven’t heard about Climategate, it might be because you are still watching ABC, CBS, or NBC. Google ‘Climategate’, though, and you will get 20,000,000 to 30,000,000 web page matches.)

Supporters have claimed that there is nothing to see there…that the Climategate e-mails released to the world by a whistleblower just show how scientists normally work. This is a particularly bad strategy, and the public knows it. Scientists do NOT behave this way…at least not in my world.

Others have claimed that a few bad apples do not spoil the whole IPCC barrel. Well, if it wasn’t for the fact that these are the core people who gave us the primary thermometer evidence of 20th Century warming (Phil Jones), and the Hockey Stick temperature reconstruction which conveniently did away with the previous 10 or more centuries of natural climate change (Michael Mann), I might be inclined to agree with them.

I will admit that it seems unlikely (but not impossible) that a reanalysis of the thermometer data will lead to a much reduced rate of warming in recent decades. But my bigger concern is that the “it’s-OK-to-fudge” attitude pervades the entire IPCC apparatus.

These e-mails are from the observational side of the IPCC, that is, the research into temperature observations of the past. What I am more concerned about, though, is the manipulation of climate models, which are used to predict the future state of the climate system. Computer models are much easier to manipulate than real data, and one can get just about any answer one wants out of them.

Now that we have seen that the temperature observation guys ‘wanted’ to get a certain result, it is reasonable to wonder whether the modelers are also incentivized to produce particular results. I’m sure the hundreds of millions of dollars being poured into global warming research – money that would dry up if the threat evaporated — has not influenced their objectivity.

Now, trillions of dollars in global warming legislation are riding upon these model ‘black boxes’ that relatively few people understand the inner workings of. The models are so complex, with many adjustable parameters which have no known true values, that it is unlikely that they can ever be replicated by other researchers. In case you hadn’t heard, reproducibility is a basic requirement of scientific research.

The IPCC has gotten around this problem by relying upon many modeling groups running different climate models. The presumption is that the full range of warming estimates produced by 20 different climate models would surely bound the ‘truth’, that is, the true amount of warming that will occur for a given amount of additional greenhouse gas emissions. But do these models really bound the problem?

I’ve been reminded recently that in science you really can not prove any hypothesis to be true; you can only prove a hypothesis false. How does this help us when it comes to model predictions of future warming? Well, if we can not prove whether a model that produces 2, or 4, or 6 deg. C of warming is correct…can we prove whether a model that produces only 0.5 deg. C of warming is false?

If we build a model that produces very little warming – less than that produced by any of the IPCC models – is that model any less realistic in its behavior than the models that produce a lot of warming? In other words, how do we know that the IPCC models really do bound the problem? I suspect that one or more modeling groups have already done this, but the IPCC leadership probably nixed the idea of letting the public find out about it.

Maybe there is a disgruntled modeler out there who is now willing to spill the beans, just as happened with the Climategate emails. We can call it Climategate II.

Of course, the IPCC turns the argument around, and shows us a few models which produce huge amounts of warming. But as I’ve said before, extraordinary claims require extraordinary evidence. If a couple of their models suggest it is theoretically possible to have catastrophic warming, should I be any more concerned than, say, the possibility that a new particle accelerator used by nuclear physicists will suddenly cause the Earth to explode?

While it would be easy to simply not build or use the particle accelerator, it is much more difficult to reduce global fossil fuel use by, say, 50% or more.

In the wake of Climategate, I fully expect a renewed IPCC assault on our common sense using the climate models as their ultimate climate ‘truth’. It will be claimed that the observations involved in Climategate aren’t important anyway…it’s the computer models that are telling us what the future will be.

Yeah, right.

YR MON GLOBE NH SH TROPICS
2009 1 +0.304 +0.443 +0.165 -0.036
2009 2 +0.347 +0.678 +0.016 +0.051
2009 3 +0.206 +0.310 +0.103 -0.149
2009 4 +0.090 +0.124 +0.056 -0.014
2009 5 +0.045 +0.046 +0.044 -0.166
2009 6 +0.003 +0.031 -0.025 -0.003
2009 7 +0.411 +0.212 +0.610 +0.427
2009 8 +0.229 +0.282 +0.177 +0.456
2009 9 +0.422 +0.549 +0.294 +0.511
2009 10 +0.286 +0.274 +0.297 +0.326
2009 11 +0.496 +0.418 +0.575 +0.493

The global-average lower tropospheric temperature anomaly rebounded from +0.29 deg. C in October to +0.50 deg. C in November. Both hemispheres, as well as the tropics, contributed to this warmth. The global anomaly for November of +0.50 deg. C is a period record for November (since 1979); the previous November high was +0.40 deg C. in 2004 2005. [NOTE: These satellite measurements are not calibrated to surface thermometer data, but use on-board redundant precision platinum resistance thermometers.]

Following is the global-average sea surface temperature anomalies through November 2009 from the AMSR-E instrument on NASA’s Aqua satellite:

As usual, the trend line in the previous figure should not be construed as having any predictive power whatsoever — it is for entertainment purposes only.

Well, maybe not my top 10…but the first ten that I thought of.

1. The term “climate change” itself. Thirty years ago, the term “climate change” would have meant natural climate change, which is what climate scientists mostly studied before that time. Today, it has come to mean human-caused climate change. The public, and especially the media, now think that “climate change” implies WE are responsible for it. Mother Nature, not Al Gore, invented real climate change.

2. “Climate change denier”. A first cousin to the first annoyance. Again, thirty years ago, “climate change denier” would have meant someone who denied that the Medieval Warm Period ever happened. Or that the Little Ice Age ever happened. What a kook fringe thing to believe that would have been! And now, those of us who still believe in natural climate change are called “climate change deniers”?? ARGHH.

3. The appeal to peer-reviewed and published research. I could go on about this for pages. Yes, it is important to have scientific research peer-reviewed and published. But as the Climategate e-mails have now exposed (and what many scientists already knew), we skeptics of human-caused climate change have “peers” out there who have taken it upon themselves to block our research from being published whenever possible. We know there are editors of scientific journals who assist in this by sending our papers to these gatekeepers for the purpose of killing the paper. We try not to complain too much when it happens because it is difficult to prove motivation. I believe the day is approaching when it will be time to make public the evidence of biased peer review.

4. Appeal to authority. This is the last refuge of IPCC scientists. Even when we skeptics get research published, it is claimed that our research is contradicted by other research the IPCC has encouraged, helped to get funded, and cherry-picked to support its case. This is dangerous for the progress of science. If the majority opinion of scientists was always assumed to be correct, then most major scientific advances would not have occurred. The appeal to authority is also a standard propaganda technique.

5. Unwillingness to debate. I have lectured to many groups where the organizers could not find anyone from the IPCC side who would present the IPCC’s side of the story. I would be happy to debate any of the IPCC experts on the central issues of human-caused versus natural climate change, and feedbacks in the climate system. They know where to find me. (For the most common tactic used by the IPCC in a debate, see annoyance #4.)

6. A lack of common sense. Common sense can be misleading, of course. But when there is considerable uncertainty, sometimes it is helpful to go ahead and use a little anyway. Example: It is well known that the net effect of clouds is to cool the Earth in response to radiant heating by the sun. But when it comes to global warming, all climate models do just the opposite…change clouds in ways that amplify radiative warming. While this is theoretically possible, it is critical to future projections of global warming that the reasons why models do this be thoroughly understood. Don’t believe it just because group think within the climate modeling community has decided it should be so.

7. Use of climate models as truth. Because there are not sufficient high-quality, globally-distributed, and long term observations of climate fluctuations to study and better understand the climate system with, computerized climate models are now regarded as truth. The modelers’ belief that climate models represent truth is evident from the language they use: climate models are not “tested” with real data, but instead “validated”. The implication is clear: if the data do not agree with the models, it must be the data’s fault.

8. Claims that climate models have been tested. A hallmark of a good theory is that it should predict something which, upon further investigation, turns out to be correct. To my knowledge, climate models have not yet forecasted anything of significance. And even if they did, models are ultimately being relied upon to forecast global warming (aka ‘climate change’). As far as I can tell, there is no good way to test them in this regard. And please don’t tell me they can now replicate the seasons quite well. Even the public could predict the seasons before there were climate models. Predicting future warming (or cooling) is slightly more difficult, but not by much: a flip a coin will be correct 50% of the time.

9. The claim that the IPCC is unbiased. The IPCC was formed for the explicit purpose of building the case for global warming being our fault, not for investigating the possibility that it is just part of a natural cycle in the climate system. Their accomplices in government have bought off the scientific community for the purpose of achieving specific policy goals.

10. The claim that reducing CO2 emissions is the right thing to do anyway. Oh, really? What if life on Earth (which requires CO2 for its existence) is actually benefiting from more CO2? Nature is always changing anyway…why must we always assume that every single change that humans cause is necessarily a bad thing? Even though virtually all Earth scientists believe this, too, it is not science, but religion. I’m all for religion…but not when it masquerades as science.