Next decade 'may see no warming'

Your point?

I suppose it was a theory when he came up with it in the 50s. But since he was proven right, it is now a FACT.

 

Well, now this thread has just gotten funny. The site linked to above also sells a book which maintains:

In this new and expanded edition of Michel Chossudovsky's 2002 best seller, the author blows away the smokescreen put up by the mainstream media, that 9/11 was an attack on America by "Islamic terrorists". Through meticulous research, the author uncovers a military-intelligence ploy behind the September 11 attacks, and the cover-up and complicity of key members of the Bush Administration.​

The fellow writing the global warming piece linked to by Jimmie84 above, F. William Engdahl, doesn't believe in Fossil Fuels, citing instead the ever-reliable Soviet Science of the 1950's (all hail T.D. Lysenko!).

An entirely alternative theory of oil formation has existed since the early 1950’s in Russia, almost unknown to the West. It claims conventional American biological origins theory is an unscientific absurdity that is un-provable. They point to the fact that western geologists have repeatedly predicted finite oil over the past century, only to then find more, lots more.​

And then Jimmie84 sparked several messages by providing a classical definition of fossil fuel formation, taken apparently from the web at a couple of possible sources (neither of which shows what the reference numbers in the text refer to or bother to state the original souce) which completey contradicts the estimable Mr. Engdahl's declarations regarding the origin of oil.

Does this mean we should ignore Mr. Engdahl's self-published piece on global warming? Should we revisit the discredited Soviet science of the 1950's? Should we bother to keep reading the nonsense posted in this thread?

 

Just a return to the topic of this thread.


Nature article on 'cooling' confuses media, deniers

Perhaps the source of much of the media's confusion is that the authors describe their results in the final line of the abstract this way:

Our results suggest that global surface temperature may not increase over the next decade, as natural climate variations in the North Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming.​

But what they mean by that statement is not what a simple reading of that sentence would suggest: They do not mean that "the global surface temperature may not increase over the next ten years starting now." What they mean is what the lead author, Dr. Noel Keenlyside, wrote me last night when I asked for a clarification:

Thus, based on our results we don't expect an increase in the mean temperature of the next decade (2005-2015).​

They are predicting no increase in average temperature of the "next decade" (2005 to 2015) over the previous decade, which, for them, is 2000 to 2010! And that is, in fact, precisely what the figure shows -- that the 10-year mean global temperature centered around 2010 is the roughly the same as the mean global temperature centered around 2005.

The authors have not predicted that the next 10 years won't see any warming. They have, however, offered an explanation for why temperatures have not risen very much in recent years, and perhaps why ocean temperatures have also not risen very much in the past few years. Dr. Keenlyside continues:

However, as you correctly point out, our results show a pick up in global mean temperature for the following decade (2010-2020). Assuming a smooth transition in temperature, our results would indicate the warming picks up earlier than 2015.​

Again, at that point, Dr. Keenlyside reiterates the disclaimer that this analysis can't be used for year-by year predictions. Indeed, he notes that his main conclusion is not really quantitative but qualitative:

Given the uncertainties that exist in such kinds of preliminary studies, I believe it is more useful to point out that climate on decadal timescales may be quite different from that expected only considering external radiative forcing (as in the IPCC). This is actually an obvious, but I believe mostly overlooked fact. Our results highlight this.​

 

I'm glad to see the misinformation is limited to only a few (or one) ignorant folk in this thread.

Thanks again for posting the article Tim and thank everyone else for their input in teasing out the real information and dispelling the implied conclusion.

 

I can't seem to post material properly since the board came back up.

With regard to the Douglass et al. paper posted here earlier, Realclimate.org has a discussion of that. The upshot is that the Douglas et al. paper is just wrong, and it's wrong for reasons that anyone with a basic background in statistics can understand.

EDIT:

Ah, finally, I can post. Read this analysis on realclimate.org

RealClimate

Briefly, there were issues with data and methods. But mostly, Douglass et al. just plain mis-calculated the uncertainty surrounding the model forecast. They treated the 22 model predictions, which themselves have significant associated uncertainty, as if they were 22 data points, with no associated individual uncertainty. As a result, they calculated the error associated with the average of the 22 predictions as the variance of the predictions divided by 22.

Well, that's just wrong. No other way to put it. If I poll 10 economists about the predicted rate of inflation in 2010, and average it, then poll a million economists, and average that -- well, the uncertainty of the second prediction is NOT going to be 100,000 times smaller than the first one. They are both guesses. Yeah, the average I get is going to be 100,000 times more precisely estimated, but the prediction is not. Unless you calculate it like Douglass et al., in which case, all you need to do to make economic predictions with no uncertainty is to poll a whole lot of people, then average.

Why does this matter? Well, what they were trying to do is show that the actual data disagree with the model predictions. So when they overstated the precision of the prediction, they found that the actual data (for temperatures in the troposphere) lay outside the models prediction plus or minus uncertainty. But they did it wrong. The uncertainty associated with the average of 22 predictions (not data points) is going to be roughly the same as the uncertainty associated with one model. The realclimate article correctly re-calculates the correct error bars for the graph of predicted temperature versus height, and the data fall within 2 standard deviations of the (mean) model prediction. There's no disagreement between the models and this particular set of data.

The article is also worth reading for the links, where you can see what the authors did after the article was published, which was to hold a press conference, declare that they had debunked C02 as a source of global warming (clearly not justified by a single test even if they had done it right), and just generally spin the heck out of the results. And there are links to an earlier, now discredited version of a similar analysis, by the same authors.

Anyway, as always, it's worth reading the reasoned conclusions offered on realclimate:

"To be sure, this isn't a demonstration that the tropical trends in the model simulations or the data are perfectly matched ... But it is a demonstration that there is no clear model-data discrepancy in tropical tropospheric trends once you take the systematic uncertainties in data and models seriously. Funnily enough, this is exactly the conclusion reached by a much better paper by P. Thorne and colleagues. Douglass et al's claim to the contrary is simply unsupportable."

 

Re: Peer Review is fallible

As a scientist who has been on both sides of the peer review process, I can tell you it is far from infallible. All disciplines have the tendency to develop "received wisdom", in which the majority agrees on a theory or mechanism and those who find opposing data have a hard time getting published. I am concerned that the "global warming is caused by CO2" majority may be, albeit unwittingly, steering the knowledge base in their direction.

One example of this peer review effect that I really like is the cause of stomach ulcers. Not too long ago, the medical community (supported by many peer-reviewed papers) were in almost total agreement that ulcers were caused by stress and could be relieved by a bland diet. An upstart Australian doctor who observed a connection between bacteria and ulcer sufferers found it almost impossible to publish his work, even when he produced solid experimental data. He reports that at some conferences he was laughed off the podium and it was years before his ideas were proved correct and accepted.

The doctor and his colleague went on to receive a Nobel prize. The Nobel citation praises the doctors for their tenacity, and willingness to challenge prevailing dogmas.

Lord May of Oxford, President of the Royal Society, said: "The work by Barry Marshall and Robin Warren produced one of the most radical and important changes in the last 50 years in the perception of a medical condition. "Their results led to the recognition that gastric disorders are infectious diseases, and overturned the previous view that they were physiological illnesses."


While I am not going to advance the claim that global warming is a "prevailing dogma", the fact that CO2 is almost completely responsible might be.

Modeling climate is horribly complicated - much like modeling stock markets (and we know how good we are at that). The number of variables is so high that many have to be ignored and predictions are a simplification.

My concern is not that humans could be affecting the climate - there is enough data that this has to be considered as a good probability - but that we might be focusing on the wrong variable. What if, for example, the warming is the result of injection of exhaust gases (say, water vapor) from aircraft high in the atmosphere?

I am quietly skeptical (but please don't use the pejorative term "denier").

Mike

 

Re: Peer Review is fallible

That's not an unreasonable position. But I would suggest that it's not quite as uncertain as you suggest. And that picking a few articles out of the realclimate.org index might convince you of the same.

If I can paraphrase their position, talking about mainstream climate science:

Nobody says C02 is the only driver.

Nobody says there aren't other drivers that are important in the short run.

You can't attribute temperature changes to the individual "forcings" (C02, other GHGs, aerosols, solar cycle, soot, volcanoes etc.) without including them all in the same model. That is, univariate analysis of this or that individual forcing is useless.

As far as they can tell, manmade GHGs are both necessary and sufficient to explain the recent rise in temperature. Within the context of well-specified models that account for all the known forcings. You don't predict the current temperature rise without them, and they are large enough to account for the current temperature rise. (The one variable - global mean temperature -- is not the only piece of evidence, but that's the gist of it.)

But, bottom line, I come back to this simplified analysis:

RealClimate

Bottom line, based on the best available estimates (which of course involve some uncertainty), the increase in GHGs should heat the earth up. And by roughly the amount seen. So, if there's something else that's also heating up the earth, the temperature rise should be larger than what's been observed.

In other words, every alternative hypothesis about the "real" cause of the temperature increase needs to be stated in two parts: One, this is what's actually causing the heating (and why), and two, this is why GHG's don't cause heating (and why).

If one can't come up with that second part, then that's not a complete alternative hypothesis. And, because the evidence for some greenhouse effect is pretty good, what you hear, from those offering alternative explanations, is some version of "well, yes, GHGs cause heating, but not as much as mainstream climate modelers say". Fair enough, to the extent that there is credible evidence to support that, and only to the extent. But at which point, given no effective plan for reducing GHG emissions, we're merely on a slower manmade path to a warmer earth, instead of the somewhat faster one that the mainstream models predict. I don't take much comfort in that.

 

Just curious, is it your opinion then, that we should wait until the AGW theory is solidly (to your satisfaction) confirmed before we take any action to avoid it? Or do you agree that it is worth being cautious now, regardless of what the next 10 years may disclose?

 

Glad to hear it!

It's interesting then that it seems you are more inclined to believe the few reports that indicate a lesser effect, to the majority of reports that indicate a catastrophic effect. Maybe it depends on your definition of "catastrophic". Do you have children?

 

As I said, I'm curious about your definition of "catastrophic". I notice you didn't answer my question.

By the way, I work with IPCC modelers and am well aware of the science involved.

 

Ok, I personally think that we may or may not see warming in the next decade, but that whether we do on such a short timescale is irrelevant to the bigger question of whether we as humans are responsible for changing the climate on a scale that induces mass extinction and threatens our own survival. As I'm sure you know, a volcanic eruption on the scale of Pinatubo can cool the global climate on decadal timescales. There are a number of both predictable and unpredictable events like this that could skew the data on such short timescales like this but that are non-anthropogenic. What is important is the ability to separate these effects from those we are responsible for.

I guess I'm dense because I couldn't even disambiguate "DAI".

 

Of course the Douglas paper is wrong. I knew that without reading one word of it. Any rational person would.

The reason I know the paper is wrong is that for a non-validated, non-peer reviewed paper saying climate change probably was not happening to be right, it would mean that hundreds of validated, peer-reviewed papers saying climate change was happening are wrong. The chances of this being true are so remote as to effectively be zero.

Add to this the fact that no validated, peer reviewed paper agrees with Douglas's position and you know his paper is flawed.

On top of this, I know there are many vested interests who will fight to the end saying climate change is not real. They will publish papers that try hard to be credible. Knowing these papers are out there tells me Douglas's is almost certainly one of them. I'd bet he has some direct or indirect connection to the energy industry.

Some people on this post have referred to my comments as being irrational or extreme. That's what people who are more interested in defending vested interests rather than being logical and honest do. Instead of addressing the facts, they simply label the other person's position as extreme, hoping that no one will look at what the other person was actually saying.

No one has directly contested the obvious fact that I keep mentioning. That's because it can't logically be done. It would be like contesting whether or not two plus two equals four.

The key point is that there have been hundreds of peer reviewed scientific studies that say global warming is happening and humans are causing or probably causing it. I believe there are about 500 such studies.

And there are zero studies saying the opposite. No credible (ie: peer reviewed) scientific study says climate change is not happening. Of course the peer review process is not perfect. In several scientific areas there are peer reviewed studies taking opposite positions. But climate change is not one of those areas.

The experts have already spoken and agreed. Non-experts debating whether or not the experts are right is not logical. The real issue here is why is this illogical conversation continuing.

The point here isn't to lose or win. It's to protect our children. Normally, I wouldn't care if people want to ignore logic and science and hold a superstitious, silly position. But in this case that position is hurting society.

In climate change and many other areas, we need to figure out why people stick to the obviously wrong position when doing so degrades society.

That's the real issue here, not climate change.

For those that are seriously considering the Douglas paper, rather than just defending an irrational position, consider this. We know that we are removing huge amounts of carbon from the Earth's crust and placing it in the atmosphere as a known heat trapping gas. How could you logically take the default position that this probably won't have an impact. The point here isn't to say climate change absolutely is happening. This is a highly complex area. There are many factors involved. Even if temperature did cool for ten years, it wouldn't mean climate change wasn't happening. This is not a linear process. Other factors might cause the cooling, then warning could quickly accelerate.

The issue here is probability. Do we have enough evidence to say climate change PROBABLY is happening. 500 to zero says in unambiguous terms that we do. Therefore, the issue is what action to take. Of course we don't want to trash the economy. We need to address GCC logically.

However, the idea that addressing GCC would trash the economy is another myth. Addressing it would create thousands of jobs in small and medium businesses as we retrofit homes and buildings with more efficient doors, windows, lighting, HVAC systems, etc. It would lower energy bills since people would be spending less on energy. This would raise disposable income so people had more to spend on other things. It would lower public and private health care costs due to lower SOx, NOx, Mercury and other fossil fuel emissions. This would further increase disposal income. It would make US products more competitive around the world since they'd be more energy efficient. It would conserve oil in Alaska and other places for our children, rather than selfishly waste it to fuel our inefficient vehicles, homes and buildings.

Efficiency is a good thing in economics. Addressing climate change almost completely means improving energy efficiency. Saying that improving efficiency would hurt the economy is another illogical statement that only holds up if you blindly believe it without thinking about it.

The economy would be made stronger by addressing climate change. The main parties getting hurt would be energy companies that weren't willing to change with the times. These companies have the resources to influence government, which they've obviously done. They also have the resources to influence public opinion. It appears that some people on this post have bought into the energy companies' self serving arguments that climate change is not happening.

 

The problems with the Douglass paper have been well-dissected on RealClimate. One comment puts it clearly (in response to asking for a layman's explanation):
RealClimate

A rundown of the study might be this:

Independent computer models (about 23 or so world-wide, I believe), generally show a warming of the surface and even more in the tropsophere in the tropics due to increased water vapor (warm the air up and it has more available water vapor (a greenhouse gas)..so a “new greenhouse gas†comes into play where the air is warmed (ouch, what a simplification).

…the higher up you go the less water vapor you normally get because it is too cold to have available water vapor (the rate of condensation strongly exceeds the rate of evaporation)…unless you warm it and “suddenly water vapor just appears†where it was mostly absent before. However, it did already exist lower down because it was already warm and already contained water vapor because it was warm.

The study states that that instruments do *not* show more warming the higher you go in the tropics…even though the models do.

Hence, independent world-wide computer models are wrong when they predict global warming in the next 100 years…

and secondly, because computer models base their future (and present) warming predictions on increasing greenhouse gases (and they “don’t get the warming correct nowâ€), that greenhouse gases actually are not causing the warming we have been seeing for the last 100 years.

This means then, that mainstream science only predicts global warming based on computer simulations…so global warming is not a problem.
This then means that the warming (most of it) is part of a natural cycle (cosmic rays and solar wind) and is not man-made…

so we can burn all the oil, coal and gas that we want without guilt (and we certainly don’t have to regulate them)…and the IPCC (Intergovernmental Panel on Climate Change) is irrevocably wrong and can be ignored with impunity.

This also would mean that President Bush is “correct†to do nothing right now about global warming even though every other major world country is taking action including the last holdout- Australia on Kyoto, I believe).
Anyway, here are some fatal problems with the study as I understand them that invalidate this study:

1. Even if the study were right…(which it is not) mainstream scientists use *three* methods to predict a global warming trend…not just climate computer models (which stand up extremely well for general projections by the way) under world-wide scrutiny…and have for all intents and purposes already correctly predicted the future-(Hansen 1988 in front of Congress and Pinatubo).

Now the three scientific methods for predicting the general future warming trend is:

1. Paleoclimate reconstructions which show that there is a direct correlation between carbon dioxide increasing and the warming that follows.

2. Curent energy imbalance situation between the energy coming in at the top of the atmosphere (about 243 watts per square meter WM2) and fewer watts/M2 now leaving due mostly to the driving force of CO2…ergo the Earth has to heat up.

3. Thirdly, climate computer simulations that have been tested against actual records before they actually happened….and were correct.

Now, on to actual problems with the paper:

Any real scientist, ahem, includes error bars in their projections because of possible variables. The study does not include them. If it did, or they were honest enough to, they would fit the real-life records (enough to overlap the two records) and be a non issue.

Secondly, this study is dishonest and does not show all the evidence available (v1.3 and V1.4)…boing…this paper has just failed peer-review. Science is an *open* process and you just don’t cherry pick or real scienists will correctly invalidate your results.

Third, with this omitted data, the computer models agree with the actual data (enough for it to be a non-issue).

Fourthly, the study does not honestly work out the error bars for the models themselves by giving them reasonable uncertainty for accounted-for unknowns such as El Nino (Enso) and other tropical events.

Now however, there are honest unknowns with the models and how they (slightly) mismatch histoical records…but they are accounted for in the big scheme of things…more work needs to be done…but it does not invalidate what the models are saying for general warming trends…unbrella anyone?

In other words, this study is a strawman and the authors know it.

 

Megansprius, see my post #45.

These other issues aside, Douglass et al. made a huge and basic error. They confused "a precise estimate of the average prediction" with "a precise prediction". They literally used the variance of the model predictions, divided by the number of models, to construct their error bars. I didn't believe it when I saw it written up on realclimate, but I went to the trouble of reading the paper and that's exactly what they did. You can take their Table II.a bottom line (the standard deviations of the model predictions at various pressures), divide by square root of 21, and derive the width of the error bars on their Figure 1. Those error bars tell you that you have a precise estimate of the average prediction, they absolutely do not tell you that you have a precise prediction.

Apparently this is a fairly subtle point and/or natural scientists are used to dealing with data points, and not with model predictions (that themselves have an associated standard error of estimate). But I still have a hard time believing that passed peer review.

Anyway, that's what Realclimate's revised graph shows -- the proper error bars including the (irreducible) uncertainty of the individual model predictions themselves. And of course, the properly calculated error bars are far wider than what Douglass et al. (mis)estimated.

Let me rephrase the example of my prior post to make this clear. Because, as I said, I think a lot of people didn't get this.

If I ask 1000 economists to predict the average rate of inflation in the year 2100, and take the average and standard deviation of those predictions, what I have is a very precise estimate of the average prediction. What I most assuredly do not have is a very precise prediction. In fact, it's still just a guess. I should have no expectation that the actual inflation rate in that year will be close to that prediction. And if I then asked 100,000 economists, I'd get ten times more precision in my estimate of the average prediction. But the prediction itself would be no more precise than the first one. (And no more accurate, for that matter.)

That's the big booboo Douglass et al. made. They assumed that if you had (e.g.) 1000 models, and averaged them, the resulting prediction would be 10 times more precise (ten times smaller error bars, ten times smaller standard deviation) than if you had only averaged ten models. (And therefore, but left unsaid, if I averaged a million model runs, I'd be claiming to have predicted temperatures with near-zero uncertainty). But that's just nonsense. What I'd have is a very precise estimate of the average prediction, to which I still need to add the uncertainty of the typical model. (Ie, a guess is still a guess.) Which Douglass et al. didn't do.

If you're used to the language of within-group and between-group variation, you can think of the model estimates as groups, the uncertainty of the model as the within-group variance, the disagreement of the models as the between-groups variance. When you take the average of the model predictions, you reduce the between-groups variation toward zero. (That is, the std dev of the mean is the between-groups sd divided by square root of N). But the within-group variation is constant -- a guess is still a guess, in my example above. Each individual model (group) still has its associated uncertainty, and averaging the model means does not reduce that. Douglass et al ignored with within-groups variation when constructing their error bars. That's just wrong.

 

Thanks Chogan--that's the most lucid explanation of the statistical concepts involved I've read yet.

 

I actually enjoyed reading that.