Archive for the ‘Warming Forecasts’ Category.

Forecasting

One of the defenses often used by climate modelers against charges that climate is simple to complex to model accurately is that “they do it all the time in finance and economics.”  This comes today from Megan McArdle on economic forecasting:

I find this pretty underwhelming, since private forecasters also unanimously think they can make forecasts, a belief which turns out to be not very well supported.  More than one analysis of these sorts of forecasts has found them not much better than random chance, and especially prone to miss major structural changes in the economy.   Just because toggling a given variable in their model means that you produce a given outcome, does not mean you can assume that these results will be replicated in the real world.  The poor history of forecasting definitionally means that these models are missing a lot of information, and poorly understood feedback effects.

Sounds familiar, huh?  I echoed these sentiments in a comparison of economic and climate forecasting here.

Garbage In, Money Out

In my Forbes column last week, I discuss the incredible similarity between the computer models that are used to justify the Obama stimulus and the climate models that form the basis for the proposition that manmade CO2 is causing most of the world’s warming.

The climate modeling approach is so similar to that used by the CEA to score the stimulus that there is even a climate equivalent to the multiplier found in macro-economic models. In climate models, small amounts of warming from man-made CO2 are multiplied many-fold to catastrophic levels by hypothetical positive feedbacks, in the same way that the first-order effects of government spending are multiplied in Keynesian economic models. In both cases, while these multipliers are the single most important drivers of the models’ results, they also tend to be the most controversial assumptions. In an odd parallel, you can find both stimulus and climate debates arguing whether their multiplier is above or below one.

How similar does this sound to climate science:

If macroeconometrics were a viable paradigm, we would have seen major efforts to try to bring this sort of model up to date from its 1975 time warp. However, for reasons I have documented, the profession has decided that this macroeconometric project was a blind alley. Nobody bothered to bring these models up to date, because that would be like trying to bring astrology up to date.

This, from Arnold Kling about macroeconomic models could have been written just as well to describe the process for running climate models

Thirty-five years ago, I was Blinder’s research assistant, doing these sorts of simulations on the Fed-MIT-Penn model for the Congressional Budget Office. I think they are still done the same way. See lecture 13. Here are some of the things that Blinder had to tell his new research assistant to do.1. Make sure that there were channels in the model for credit market conditions to affect consumption and investment.

2. Correct the model’s past forecast errors, so that it would track the actual behavior of the economy over the past two years exactly. With the appropriate “add factors” or correction factors, the model then produces a “baseline scenario” that matches history and then projects out to the future. For the future, a judgment call has to be made as to how rapidly the add factors should decay. That is mostly a matter of aesthetics.

3. Simulate the model without the fiscal stimulus. This will result in the model’s standard multiplier analysis.

4. Make up an alternative path for what you think would have happened in credit markets without TARP and other extraordinary measures. For example, you might assume that mortgage interest rates would have been one percentage point higher than they actually were.

5. Simulate the model with this alternative scenario for credit market conditions.

6. (4) and (5) together create a fictional scenario of how the economy would have performed had the government not taken steps to fight the crisis. According to the model, this fictional scenario would have been horrid, with unemployment around 15 percent.

In the case of climate, the equivalent fictional scenario would be the world without manmade CO2, but the process of tweaking input variables and assuming one’s conclusions is the same.

Computer Model Fail

From the New Scientist:

What’s special about this latest dip is that the sun is having trouble starting the next solar cycle. The sun began to calm down in late 2007, so no one expected many sunspots in 2008. But computer models predicted that when the spots did return, they would do so in force. Hathaway was reported as thinking the next solar cycle would be a “doozy”: more sunspots, more solar storms and more energy blasted into space. Others predicted that it would be the most active solar cycle on record. The trouble was, no one told the sun.

The first sign that the prediction was wrong came when 2008 turned out to be even calmer than expected. That year, the sun was spot-free 73 per cent of the time, an extreme dip even for a solar minimum. Only the minimum of 1913 was more pronounced, with 85 per cent of that year clear.

As 2009 arrived, solar physicists looked for some action. They didn’t get it. The sun continued to languish until mid-December, when the largest group of sunspots to emerge for several years appeared. Finally, a return to normal? Not really.

Even with the solar cycle finally under way again, the number of sunspots has so far been well below expectations. Something appears to have changed inside the sun, something the models did not predict. But what?

Of course, Anthony Watt has been pointing this out for over two years, even pointing to a discontinuity in the Geomagnetic Average Planetary Index as one sign.

The people who model the sun, and failed, are not bad people.  It is an excercise worth attempting.  It turns out we just don’t know enough about the sun to accurately model its behavior.  Models are only as good as our understanding of the natural processes.  Something to think about with climate models.

Your Humble Scribe Quoted in WaPo Article on Computer Models

The article onj climate modelling is here, and is pretty good.  My bit is below, from web page 3:

But Warren Meyer, a mechanical and aerospace engineer by training who blogs at www.climate-skeptic.com, said that climate models are highly flawed. He said the scientists who build them don’t know enough about solar cycles, ocean temperatures and other things that can nudge the earth’s temperature up or down. He said that because models produce results that sound impressively exact, they can give off an air of infallibility.

But, Meyer said — if the model isn’t built correctly — its results can be both precise-sounding and wrong.

“The hubris that can be associated with a model is amazing, because suddenly you take this sketchy understanding of a process, and you embody it in a model,” and it appears more trustworthy, Meyer said. “It’s almost like money laundering.”

I actually like my term “knowlege laundering.”

Is It Wrong to Apply a Simple Amplifier Gain Mental Model to Climate?

Today will actually be fun, because it involves criticism of some of my writing around what I find to be the most interesting issue in climate, that of feedback effects.  I have said for a while that greenhouse gas theory is nearly irrelevant to the climate debate, because most scientists believe that the climate sensitivity to CO2 acting along without feedbacks is low enough (1.2C per doubling) to not really be catastrophic.   So the question whether man-made warming will be catastrophic depends on the assumption of strong net positive feedbacks in the climate system.  B Kalafut believes I have the wrong mental model for thinking about feedback in climate, and I want to review his post in depth.

Naming positive feedbacks is easy. In paleoclimate, consider the effect of albedo changes at the beginning of an ice age or the “lagging CO2″ at the end. In the modern climate, consider water vapor as a greenhouse gas, or albedo changes as ice melts. In everyday experience, consider convection’s role in sustaining a fire. Consider the nucleation of raindrops or snowflakes or bubbles in a pot of boiling water. At the cellular level, consider the voltage-gated behavior of the sodium channels in a nerve axon or the “negative damping” of hair cells in the cochlea.

I am assuming he is refuting my statement that “it is hard to find systems dominated by strong net positive feedbacks that are stable over long periods of time.”  I certainly never said individual positive feedbacks don’t exist, and even mentioned some related to climate, such as ice albedo and increases in water vapor in air.  I am not sure we are getting anywhere here, but his next paragraph is more interesting.

On to the meat of Meyer’s argument: he seizes on one word (“feedback”) and runs madly, from metaphor to mental model. Metaphor: “like in an ideal amplifier”. Model: The climate experiences linear feedback as in an amplifier–see the math in his linked post or in the Lindzen slides from which he gets the idea. And then he makes the even worse leap, to claiming that climate models (GCMs) “use” something called “feedback fractions”. They do not–they take no such parameters as inputs but rather attempt to simulate the effects of the various feedback phenomena directly. This error alone renders Meyer’s take worthless–it’s as though he enquires about what sort of oats and hay one feeds a Ford Mustang. Feedback in climate are also nonlinear and time-dependent–consider why the water vapor feedback doesn’t continue until the oceans evaporate–so the ideal amplifier model cannot even be “forced” to apply.

First, I don’t remember ever claiming that climate models used a straight feedback-amplification method.  And I am absolutely positive I never said GCM’s use feedback fractions.    I would not expect them to.    This is a total straw man.  I am using a simple feedback amplification model as an abstraction to represent the net results of the models in a way layman might understand, and backing into an implied fraction f from published warming forecasts and comparing them to the 1.2C non-feedback number.  Much in the same way that scientists use the concept of climate sensitivity to shortcut a lot of messy detail and non-linearity.  I am, however, open to the possibility that mine is a poor mental model, so lets think about it.

Let’s start with an analogy.  There are very complicated electronic circuits in my stereo amplifier.  Nowadays, when people design those circuits, they have sophisticated modeling programs that can do a time-based simulation of voltage and current at every point in the circuit.  For a simulated input, the program will predict the output, and show it over time, even if it is messy and non-linear.  These models are in some ways like climate models, except that we understand electronic components better so our parametrization is more precise and reliable.    All that being said, it does not change the fact that a simple feedback-gain model for sections of the complex amplifier circuitry is still a useful mental model for the process at some level of abstraction, as long as one understands the shortcomings that come from any such simplification.

The author is essentially challenging the use of Gain = 1/ (1-f) to represent the operation of the feedbacks here.  So let’s think about if this is appropriate.  Let’s begin with thinking about a single feedback, ice albedo.   The theory is that there is some amount of warming from CO2, call it dT.  This dT will cause more ice to melt than otherwise would have  (or less ice to form in the winter).  The ice normally reflects more heat and sunlight back into space than open ocean or bare ground, so when it is reduced, the Earth gets a small incremental heat flux that will result in an increase in temperatures.  We will call this extra increase in temperature f*dT where f is most likely a positive number less than one.  So now our total increase, call it dT’ is dT+f*dT.   But this increase of f*dT will in turn cause some more ice to melt.  By the same logic as above, this increase will be f*f*dT.  And so on in an infinite series.  The solution to this series for a constant value of f is  dT’ = dT/(1-f) … thus the formula above.

So the underlying operation of the feedback is the same:  Input –> output –> output modifies input.   There are not somehow different flavors or types of feedback that operate in radically different ways but have the same name  (as in his Mustang joke).

The author claims the climate models are building up the affects of the processes like ice albedo from its pieces, ie rather than abstracting in to the gain formula, the models are adding up all the individual pieces, on a grid, over time.  I am sure that is true.   The question is not whether they use the simplified feedback formula, but whether it is a useful abstraction.  I see nothing from my description of the ice albedo process to say it is not.

What happens if there are time delays?  Well, as long as f is less than 1, the system will reach steady state at some point and this formula should apply.  What happens if the feedback is non-liner?  Well, in most natural systems, it is almost certainly non-linear.   In our ice albedo example, f is almost certainly different at different temperatures levels  (for example, a change from -30C to -31C has a lot less effect on ice albedo than a change from 0C to 1C.   The factor f is probably also dependent on the amount of ice remaining, since in the limit when all the ice is melted there should be no further effect.  But I would argue that when we pull back and look at the forest instead of the trees, a critical skill for modelers who too often get buried in their minutia while losing the ability to reality-check their results, that the 1/(1-f) is still an interesting if imperfect abstraction for the results, particularly since we are looking at tenths of a degree, and its hard for me to believe that it is wildly non-linear over that kind of range.  (By the way, it is not at all unusual for mainstream alarmist scientists to use this same feedback formula as a useful though imperfect abstraction, for example  in Gerard H. Roe and Marcia B. Baker, “Why Is Climate Sensitivity So Unpredictable?”, Science 318 (2007): 629–632 Not free but summarized here.)

To determine if it is a useful abstraction, I would ask the author what conclusions I draw that fall apart.  I really only made two points with the use of feedback anyway.

  1. I used the discussion to educate people that feedback is the main source of catastrophic warming, so that it should be the main focus of the scientific replication.   We can argue all day about time delays and non-linearity, but if the IPCC says the warming from CO2 alone is going to be 1.2C per doubling and the warming with all feedbacks considered is going to be, say, 4.8C per doubling (the author says himself that the models all converge at constant CO2), then we can say feedback is amplifying the initial man-made input by 4, or alternatively, 75% of the warming is from feedback effects, so these are probably where we need to focus.  I struggle to see how one can argue with this.
  2. I used the simple gain formula to say if feedback were quadrupling temperatures, this implies a feedback factor of 0.75, and that this number is pretty dang high for a long-term stable system.  Yes, the feedback is non-linear, but I don’t think this is an unreasonable reality check on the models to see what sorts of average feedbacks are being produced by the parameters.

The author’s points on non-linearity and time delays are actually more relevant to the discussion in other presentations when I talked about whether the climate models that show high future sensitivities to CO2 are consistent with past history, particularly if warming in the surface temperature record is exaggerated by urban biases.  But even forgetting about these, it is really hard to reconcile sensitivities of, say, four degrees per doubling with history, where we have had about 0.6C (assuming irrationally that its all man-made) of warming in about 42% of a doubling  (the effect, I will add, is non-linear, so one should see more warming in the first half than the second half of a doubling).  Let’s leave out aerosols for today  (those are the great modeler’s miracle cure that allows every model, even those of widely varying CO2 sensitivities and feedback effects, all exactly back-cast to history).  These time delays and non-linearities could help reconcile the two, though my understanding is that the time delay is thought to be on the order of 12 years, which would not reconcile things at all.  I suppose one could assume non-linearity such that the feedback effects accelerate with time past some tipping point, but I will say I have yet to see any convincing physical study that points to this effect.

Well, the weather is lovely outside so I suppose I should get on with it:

Meyer draws heavily from a set of slides from a talk by Richard Lindzen before a noncritical audience. These slides are full of invective and conspiracy talk, and their scientific content is lousy. Specifically, Lindzen supposedly estimates effective linear feedbacks for various GCMs and finds some greater than one. The mathematics presented by Lindzen in his slides does not allow that, and he doesn’t provide details of how such things even could be inferred. An effective linear feedback greater than one implies a runaway process, yet GCMs are always run for finite time, so there cannot be divergence to infinity. Moreover, as far as I know, all of the GCMs are known to converge once CO2 is stabilized.

I draw on Lindzen and Lindzen is wrong about a bunch of stuff and Lindzen uses invective and conspiracy talk so, what?  Lindzen can answer all of this stuff.  I used one chart from Lindzen, and it wasn’t even about feedback  (I will reproduce it below).

I did mention that in theory, if the feedback factor is greater than one, in other words, if the first order feedback addition to input is greater than the original input, then the function rapidly runs away to infinity.  Which it does.  I don’t know what Lindzen has to say about this or what the author is referring to.   My only point is that when folks like Al Gore talk about runaway warming and Earth becoming Venus, they are really implying runaway positive feedback effects with feedback factors greater than one.  Since I really don’t go anywhere with this and in reality the author is debating Lindzen over an argument or analysis I am not even familiar with, I will leave this alone.  The only thing I will say is that his last sentence seems on point, but his second to last is double talk.  All he is saying is that by only solving a finite number of terms in a a divergent infinite series his calculations don’t go to infinity.  Duh.

I am open to considering whether I have the correct mental model.  But I reject the notion that it is wrong to try to simplify and abstract the operation of climate models.  I have not modeled the climate, but I have modeled complex financial, economic, and mechanical systems.  And here is what I can tell you from that experience — the more people tell me that they have modeled a system in the most minute parametrization, and that the models in turn are not therefore amenable to any abstraction, the less I trust their models.  These parameters are guesses, because there just isn’t enough understanding of the complex and chaotic climate system to parse out their different values, or to even be clear about cause and effect in certain processes  (like cloud formation).

I worry about the hubris of climate modelers, telling me that I am wrong and impossible to try to tease out one value for net feedback for the entire climate, and instead I should be thinking in terms of teasing out hundreds or thousands of parameters related to feedback.  This is what I call knowledge laundering:

These models, whether forecasting tools or global temperature models like Hansen’s, take poorly understood descriptors of a complex system in the front end and wash them through a computer model to create apparent certainty and precision.  In the financial world, people who fool themselves with their models are called bankrupt (or bailed out, I guess).  In the climate world, they are Oscar and Nobel Prize winners.

This has incorrectly been interpreted as my saying these folks are wrong for trying to model the systems.  Far from it — I have spend a lot of my life trying to model less complex systems.  I just want to see some humility.

Postscript: Here is the only chart that I know of in my presentation from Lindzen, and its not even in the video he links to, it is in this longer and more comprehensive video

That seems a reasonable enough challenge to me, particularly given the data in this post and this quote from Judith Currey, certainly not a skeptic:

They don’t disprove anthropogenic global warming, but we can’t airbrush them away. We need to incorporate them into the overall story. We had two bumps—in the ’90s and also in the ’30s and ’40s—that may have had the same cause. So we may have exaggerated the trend in the later half of the 20th century by not adequately interpreting these bumps from the ocean oscillations. I don’t have all the answers. I’m just saying that’s what it looks like.

Again, as I have said before, man’s CO2 is almost certainly contributing to a warming trend.  But when we really look at history objectively and tease out measurement problems and cyclical phenomena, we are going to find that this trend is entirely consistent with a zero to negative feedback assumption for the climate as a whole, meaning that man’s CO2 is driving 1.2C or less of warming per doubling of CO2 concentrations.

The Single Most Important Point

Given all the activity of late challenging various aspects of the IPCC’s work, I wanted to remind folks of probably the most important assumption in the IPCC (and related climate models) that seldom makes the media.

Greenhouse gas theory alone does not give us a catastrophe.  By the IPCC numbers, originally I think from Michael Mann in 1998, greenhouse warming from CO2 should be about 1.2C per doubling of CO2 concentrations.  But the IPCC gets a MUCH higher final number than this.  The reason is positive feedback.  This is a second theory, that the Earth’s temperature system is dominated by very strong net positive feedback effects.  Even if greenhouse gas theory is “settled,” it does not get us a catastrophe.  The catastrophe comes from the positive feedback theory, and this is most definitely not settled.

I usually put it this way to laymen:  Imagine the Earth’s climate is a car.  Greenhouse gas theory says CO2 will only give the car a nudge.  In most cases, this nudge will only move the car a little bit, because a lot of forces work to resist the nudge.  Climate theory, however, assumes that the car is actually perched precariously at the very top of a steep hill, such that a small nudge will actually start the car rolling downhill until in crashes.  This theory that the Earth is perched precariously on the top of the hill is positive feedback theory, and is far from settled.  In fact, a reasonable person can immediately challenge it by asking the sensible question  — “well, how has the climate managed to avoid a nudge (and resulting crash)  for hundreds of millions of years?”

I got to thinking about all this because I saw a chart of mine in Nicola Scafetta’s SPPI report on climate change, where he uses this chart:

I am happy he chose this chart, because it is one of my favorites.   It shows that most of the forecast warming from major alarmist models comes from the positive feedback theory, and not from greenhouse gas theory.  Let me explain how it is built.

The blue line at the bottom is based on an equation right out of the Third IPCC Report (the Fourth Report seems to assume it is still valid but does not include it anywhere I can find).  The equation seems to be from Mann 1998, and is for the warming effect from CO2 without feedbacks.   The equation is:

∆T = F(C2) – F(C1)
Where F(C) = Ln(1+1.2c+0.005c^2+0.0000014c^3)

So the blue line is just this equation where C1=385ppm and C2 is the concentration on the X axis.

The other lines don’t exist in the IPCC reports that I can find, though they should**.  What I did was to take various endpoint forecasts in the IPCC and from other sources and simply scale the blue line up, which implicitly assumes feedback acts uniformly across the range of concentrations.   So, for example, a forecast after feedback of 4.8C of warming around 800ppm was assumed to scale the blue no feedback line up by a uniform factor of 4.8/1.2 = 4x.  For those who know the feedback formula, we can back into the implied feedback fraction (again not to be found anywhere in the IPCC report) which would be  4=1/(1-f)  so f=75%, which is a quite high factor.

** This seems like a totally logical way to show the warming effect from CO2, but the IPCC always insists on showing just warming over time.  But this confuses the issue because it is also dependent on expected CO2 emissions forecasts.  I know there are issues of time delays, but I think a steady-state version of this chart would be helpful.

Knowlege Laundering

Charlie Martin is looking through some of James Hansen’s emails and found this:

[For] example, we extrapolate station measurements as much as 1200 km. This allows us to include results for the full Arctic. In 2005 this turned out to be important, as the Arctic had a large positive temperature anomaly. We thus found 2005 to be the warmest year in the record, while the British did not and initially NOAA also did not. …

So he is trumpeting this approach as an innovation?  Does he really think he has a better answer because he has extrapolated station measurement by 1200km (746 miles)?  This is roughly equivalent, in distance, to extrapolating the temperature in Fargo to Oklahoma City.  This just represents for me the kind of false precision, the over-estimation of knowledge about a process, that so characterizes climate research.  If we don’t have a thermometer near Oklahoma City then we don’t know the temperature in Oklahoma City and lets not fool ourselves that we do.

I had a call from a WaPo reporter today about modeling and modeling errors.  We talked about a lot of things, but my main point was that whether in finance or in climate, computer models typically perform what I call knowledge laundering.   These models, whether forecasting tools or global temperature models like Hansen’s, take poorly understood descriptors of a complex system in the front end and wash them through a computer model to create apparent certainty and precision.  In the financial world, people who fool themselves with their models are called bankrupt (or bailed out, I guess).  In the climate world, they are Oscar and Nobel Prize winners.

Update: To the 1200 km issue, this is somewhat related.

Water Vapor Feedback

In most all of the climate models, the warming effect from feedback is actually much larger than the warming effect from CO2 alone.   That is why I have said for years that it is a waste of time to debate “greenhouse gas theory” as the real theory that matters to the proposition that climate sensitivity to CO2 is high is the theory that Earth’s temperature system is dominated by strong positive feedback.  And the largest feedback in climate models tends to be water vapor feedback, despite the fact that even the IPCC admits that such feedback is poorly understood.  To this end:

In a third paper, accepted for publication by the Journal of Theoretical and Applied Climatology, three scientists – two Australians and one American, revisit data on upper-atmospheric humidity. The three are Garth Paltridge, Albert Arking and Michael Pook, and they have found that, contrary to climate model predictions, water vapour in the upper atmosphere is acting as a brake on global warming.

Established climate models assume constant humidity at all levels in the atmosphere as the temperature rises. But, using data from weather balloons accumulated over 35 years, these researchers find this is not so. At the lower levels, it is higher than expected, dropping below normal at the higher altitudes.

This, they say, implies that “long-term water vapour feedback is negative – that it would reduce rather than amplify the response of the climate system to external forcing such as that from increasing atmospheric CO2.” This, in one fell swoop, challenges the central premise of the warmists that, once CO2 reaches a certain level, we experience runaway global warming.

Shut Up, For the Children

Thought I would share a couple of bits of an email I got today.  The email showed a distinct lack of familiarity with the nuances of my climate position, so my guess is this may be a form letter.  I find it interesting a 17-year-old knows the term “NGO” but does not know to capitalize the first letter in a sentence (emphasis added).

hello.
this is a (hopefully) reasonable and (hopefully) well thought out message.
firstly i will say that i am 17 years old and not under the sway of any goverments/NGOs.
i believe that what you are doing with your climate skeptic blog is dangerous.
dangerous not only to yourself (in a minor way), but to my generation(in a much bigger way)….  [portion snipped out here basically talking about the writer's view of what science is beyond dispute and lecturing me on the precautionary principle]

you’ll probably think it’s rich, being lectured on ‘responsibility’ by a mere 17 year old, but hear (or read ;) ) me out…
by publishing your blog i believe you are infringing upon successive generations’ fundamental basic human right to life.
denying climate change is fine if you just hold these veiws and keep them to yourself and don’t overtly act upon them.
it does however become infinitely more dangerous to my generation to preach these views as fact(or even air them in a serious manner).
as far as i see it, this is an issue of life and death.
the way i see it, you’re going along the ‘more likely to be death’ route, and please, if only for the sake of your children, or your children’s children, stop updating your blog.

Hmm, I will pass.  But it is nice to know that folks like Al Gore, Michael Mann, and Steve Jones have passed down their fear and loathing of debate to the next generation.    I won’t share my response, but I asked him if he would prefer that my generation, instead of handing his generation a degree or so of warming, instead handed his generation an extra billion or so people in poverty.

Feedback Assumptions Finally Being Challenged

When asked what one thing I would want to tell laymen about catastrophic man-made global warming theory, it is the following:  That this theory is in fact a two-part theory.  Greenhouse gas theory alone only gives us incremental warming and no catastrophe.  It is a second theory that Earth’s climate is dominated by strong positive feedbacks that multiplies warming of perhaps a degree over the next century from CO2 to 3,5, or more degrees of warming.  And while it is fairly well accepted by all that CO2 will cause a bit of warming alone, this second theory is not at all settled and in fact may even the the sign of the feedback wrong.

Two stories came out this week undercutting to of the largest sources of feedback.

1.  Water Vapor Feedback

Water vapor is a highly variable gas and has long been recognized as an important player in the cocktail of greenhouse gases—carbon dioxide, methane, halocarbons, nitrous oxide, and others—that affect climate.

“Current climate models do a remarkable job on water vapor near the surface. But this is different — it’s a thin wedge of the upper atmosphere that packs a wallop from one decade to the next in a way we didn’t expect,” says Susan Solomon, NOAA senior scientist and first author of the study.

Since 2000, water vapor in the stratosphere decreased by about 10 percent. The reason for the recent decline in water vapor is unknown. The new study used calculations and models to show that the cooling from this change caused surface temperatures to increase about 25 percent more slowly than they would have otherwise, due only to the increases in carbon dioxide and other greenhouse gases.

An increase in stratospheric water vapor in the 1990s likely had the opposite effect of increasing the rate of warming observed during that time by about 30 percent, the authors found.

2.  CO2  (outgassing from oceans) Feedback

The most alarming forecasts of natural systems amplifying the human-induced greenhouse effect may be too high, according to a new report.

The study in Nature confirms that as the planet warms, oceans and forests will absorb proportionally less CO2.

It says this will increase the effects of man-made warming – but much less than recent research has suggested….

The most likely value among their estimates suggests that for every degree Celsius of warming, natural ecosystems tend to release an extra 7.7 parts per million of CO2 to the atmosphere (the full range of their estimate was between 1.7 and 21.4 parts per million).

This stands in sharp contrast to the recent estimates of positive feedback models, which suggest a release of 40 parts per million per degree; the team say with 95% certainty that value is an overestimate.

OK readers, let’s see how close you have been paying attention.  The models have over-estimated this important feedback by a factor of 5 (40 to 7.7). As I have shown time and time again, the vast majority of the warming in climate forecasts is from feedback — about 1C per century is directly from CO2, the rest is from feedback multipliers.  Have a forecast that says 5C warming in the next century, then about 4C of that is probably due to feedback.

But remember this post, where I said

…there is a very strong social cost in academia to challenging global warming, so that even when findings in certain studies seem to undercut key pieces of the argument, the researches always add something like “but of course this does not refute the basic theory of global warming” at the end of the paper.

So what do this study’s author’s say?

The authors warn, though, that their research will not reduce projections of future temperature rises.

Further, they say their concern about man-made climate change remains high.

Of course, because if this factor goes down, they will just shore up their forecasts and keep them them high with some other plug variable.  Because no one is funding scientists (or quoting them in newspapers) whose models call for just 1C of warming over the next century.

Lindzen & Choi

In preparing for my climate presentation in Phoenix next week, I went back and read through Lindzen & Choi, a study whose results I linked here.  The study claims to have measured feedback, and have found feedback to temperature changes in the natural climate system to be negative –opposite of the assumption of strong positive feedback in climate models.  I found this interesting, as we often do of studies that confirm our own hypotheses.

Re-reading the study, I was uncomfortable with the methodology, but figured I was missing something.  Specifically, I didn’t understand how an increase in temperature could result in a decrease in outgoing radiation, as Lindzen says is assumed in all the models.   As I have always understood it, the opposite has to be true in a stable system.   With an added forcing, temperature increases which increases outgoing radiation until the radiation budget is back in balance.  Models that assumed otherwise would have near infinite temepratures.   I assumed perhaps that Lindzen & Choi were making measurements during the time the system came back into equilibrium.

Apparently, both Luboš Motl and Roy Spencer have spotted problems as well, and they explain the issue in a more sophisticated way here and here.

But the results I have been getting from the fully coupled ocean-atmosphere (CMIP) model runs that the IPCC depends upon for their global warming predictions do NOT show what Lindzen and Choi found in the AMIP model runs. While the authors found decreases in radiation loss with short-term temperature increases, I find that the CMIP models exhibit an INCREASE in radiative loss with short term warming.

In fact, a radiation increase MUST exist for the climate system to be stable, at least in the long term. Even though some of the CMIP models produce a lot of global warming, all of them are still stable in this regard, with net increases in lost radiation with warming (NOTE: If analyzing the transient CMIP runs where CO2 is increased over long periods of time, one must first remove that radiative forcing in order to see the increase in radiative loss).

So, while I tend to agree with the Lindzen and Choi position that the real climate system is much less sensitive than the IPCC climate models suggest, it is not clear to me that their results actually demonstrate this.

Spencer further makes the point he has made for a couple of years now that feedback is really, really, really hard to measure, because it is so easy to confuse cause and effect.

Spencer by the way points out this admission from the Fourth IPCC report:

A number of diagnostic tests have been proposed…but few of them have been applied to a majority of the models currently in use. Moreover, it is not yet clear which tests are critical for constraining future projections (of warming). Consequently, a set of model metrics that might be used to narrow the range of plausible climate change feedbacks and climate sensitivity has yet to be developed.

This is kind of amazing, in effect saying “we have no idea what the feedbacks are or how to measure them, but lacking any knowlege, we are going to consistently and universally assume very high positive feedbacks with feedback factors > 0.7″

What A Daring Guy

Joe Romm has gone on the record at Climate Progress on April 13, 2009 that the “median” forecast was for warming in the US by 2100 of 10-15F, or 5.5-8.3C, and he made it very clear that if he had to pick a single number, it would be the high end of that range.

On average, the 8.3C implies about 0.9C per decade of warming.  This might vary slightly by what starting point he intended (he is not very clear in the post) and I understand there is a curve so it will be below average in the early years and above in the later.

Anyway, Joe Romm is ready to put his money where his mouth is, and wants to make a 50/50 bet with any comers that warming in the next decade will be… 0.15C.  Boy, it sure is daring for a guy who is constantly in the press at a number around 0.9C per decade to commit to a number 6 times lower when he puts his money where his mouth is.   Especially when Romm has argued that warming in the last decade has been suppressed (somehow) and will pop back up soon.  Lucia has more reasons why this is a chickensh*t bet.

I deconstructed a previous gutless bet by Nate Silver here.

Do Arguments Have to Be Symmetric?

I am looking at some back and forth in this Flowing Data post.

Apparently an Australian Legislator named Stephen Fielding posted this chart and asked, “Is it the case that CO2 increased by 5% since 1998 whilst global temperature cooled over the same period (see Fig. 1)?  If so, why did the temperature not increase; and how can human emissions be to blame for dangerous levels of warming?”

the_global_temperature_chart-545x409

Certainly this could sustain some interesting debate.  Climate is complex, so their might be countervailing effects to CO2, but it also should be noted that none of the models really predicted this flatness in temperatures, so it certainly could be described as “unexpected” at least among the alarmist community.

Instead, the answer that came back from Stephen Few was this (as reported by Flowing Data, I cannot find this on Few’s site):

This is a case of someone who listens only to what he wants to hear (the arguments of a few fringe organizations with agendas) and either ignores or is incapable of understanding the overwhelming weight of scientific evidence. He selected a tiny piece of data (a short period of time, with only one of many measures of temperature), misinterpreted it, and ignored the vast collection of data that contradicts his position. This fellow is either incredibly stupid or a very bad man.

Every alarmist from Al Gore to James Hansen has used this same chart in their every presentation – showing global temperatures since 1950  (or really since 1980) going up in lockstep with Co2.  This is the alarmists #1 chart.  All Fielding has done is shown data after 1998, something alarmists tend to be reluctant to do.  Sure it’s a short time period, but nothing in any alarmist prediction or IPCC report hinted that there was any possibility that for even so short a time as 15 years warming might cease  (at least not in the last IPCC report, which I have read nearly every page of).  So, by using the alarmists’ own chart and questioning a temperature trend that went unpredicted, Fielding is “either incredibly stupid or a very bad man.”  Again, the alarmist modus operandi – it is much better to smear the person in ad hominem attacks than deal with his argument.

Shouldn’t there be symmetry here?  If it is OK for every alarmist on the planet to show 1980-1995 temperature growing in lockstep with CO2 as “proof” of a relationship, isn’t it equally OK to show 1995-2010 temperature not growing in lockstep with CO2 to question the relationship?  Why is one ok but the other incredibly stupid and/or mean-spirited?   I mean graphs like this were frequent five years ago, though they have dried up recently:

zfacts-co2-temp

For extra credit, figure out how they got most of the early 2000’s to be warmer than 1998 in this chart, since I can find no major temperature metric that matches this.  I suspect some endpoint smoothing games here.

I won’t get into arguing the “overwhelming weight of scientific evidence” statement, as I find arguments over counting scientific heads or papers to be  useless in the extreme.  But I will say that as a boy when I learned about the scientific method, there was a key step where one’s understanding of a natural phenomenon is converted into predicted behaviors, and then those predictions are tested against reality.  All Fielding is doing is testing the predictions, and finding them to be missing the mark.  Sure, one can argue that the testing period has not been long enough, so we will keep testing, but what Fielding is trying to do here, however imperfectly, is perfectly compatible with the scientific method.

I must say I am a bit confused about those “many other measures of temperature.”  Is Mr. Few suggesting that the chart would have different results in Fahrenheit?  OK, I am kidding of course.  What I am sure he means is that there are groups other than the Hadley Center that produce temperature records for the globe  (though in Mr. Fielding’s defense the Hadley Center is a perfectly acceptable source and the preferred source of much of the IPCC report).  To my knowledge, there are four major metrics (Hadley, GISS, UAH, RSS).  Of these four, at least three (I am not sure about the GISS) would show the same results.  I think the “overwhelming weight” of temperature metrics makes the same point as Mr. Fielding’s chart.

In the rest of his language, Few is pretty sloppy for someone who wants to criticize someone for sloppiness.  He says that Fielding “misinterpreted” the temperature data.  How?  Seems straight forward to me.  He also says that there is a “vast collection of data that contradicts his position.”  What position is that?  If his position is merely that Co2 has increased for 15 years and temperatures have not, well, there really is NOT a vast collection of data that contradicts that.  There may be a lot of people who have published reasons whythis set of facts does not invalidate AGW, but the facts are still the same.

By the way, I get exhausted by the accusation that skeptics are somehow simplistic and can’t understand complex systems.    I feel like my understanding is pretty nuanced. By the way, its interesting how the sides have somewhat reversed here.  When temperature was going up steadily, it was alarmists saying that things were simple and skeptics saying that climate was complex and you couldn’t necessarily make the 1:1 correlation between CO2 and temperature increases.  Now that temperature has flat lined for a while, it is alarmists screaming that skeptics are underestimating the complexity.  I tend to agree — climate is indeed really really complex, though I think if one accepts this complexity it is hard to square with the whole “settled science” thing.  Really, we have settled the science in less than 20 years on perhaps the most complex system we have ever tried to understand?

The same Flowing Data post references this post from Graham Dawson.  Most of Dawson’s “answers” to Fieldings questions are similar to Few’s, but I wanted to touch on one or two other things.

First, I like how he calls findings from the recent climate synthesis report the “government answer” as if this makes it somehow beyond dispute.  But I digress.

The surface air temperature is just one component in the climate system (ocean, atmosphere, cryosphere). There has been no material trend in surface air temperature during the last 10 years when taken in isolation, but 13 of the 14 warmest years on record have occurred since 1995. Also global heat content of  the ocean (which constitutes 85% of the total warming) has continued to rise strongly in this period, and ongoing warming of the climate system as a whole is supported by a very wide range of observations, as reported in the peer-reviewed scientific literature.

This is the kind of blithe answer that is full of inaccuracies everyone needs to be careful about.  The first sentence is true, and the second is probably close to the mark, though with a bit more uncertainty than he implies.  He is also correct that global heat content of the ocean is a huge part of warming or the lack thereof, but his next statement is not entirely correct.  Ocean heat content as measured by the new ARGO system since 2003 has been flat to down.  Longer term measures are up, but most of the warming comes at the point the old metrics were spliced to the ARGO data, a real red flag to any serious data analyst.  The cryospehere is important as well, but most metrics show little change in total sea ice area, with losses in the NH offset by gains in the SH.

While the Earth’s temperature has been warmer in the geological past than it is today, the magnitude and rate of change is unusual in a geological context. Also the current warming is unusual as past changes have been triggered by natural forcings whereas there are no known natural climate forcings, such as changes in solar irradiance, that can explain the current observed warming of the climate system. It can only be explained by the increase in greenhouse gases due to human activities.

No one on Earth has any idea if the first sentence is true — this is pure supposition on the author’s part, stated as a fact.  We are talking about temperature changes today over a fifty year (or shorter) period, and we have absolutely no way to look at changes in the “geological past” on this fine of a timescale.  I am reminded of the old ice core chart that was supposedly the smoking gun between CO2 and temperature, only to find later as we improved the time resolution that temperature increases came before Co2 increases.

I won’t make too much of my usual argument on the sun, except to say that the Sun has been substantially more active during the warming period of 1950-2000 than it has been in other times.  What I want to point out, though, is the core foundation of the alarmist argument, one that I have pointed out before.  It boils down to:  Past warming must be due to man because we can’t think of what else it could be.   This is amazing hubris, representing a total unwillingness to admit what we do and don’t understand.  Its almost like the ancient Greeks, attributing what they didn’t understand in the cosmos to the hijinx of various gods.

It is not the case that all GCM computer models projected a steady increase in temperature for the period 1990-2008.  Air temperatures are affected by natural variability.  Global Climate Models show this variability in the long term but are not able to predict exactly when such variations will happen. GCMs can and do simulate decade-long periods of no warming, or even slight cooling, embedded in longer-term warming trends.

But none showed zero warming, or anything even close.

Sucker Bet

Vegas casinos love the sucker bet.  Nothing makes the accountants happier than seeing someone playing the Wheel of Fortune, or betting on “12, the hard way” in craps, or taking insurance in blackjack.  While the house always maintains a slim advantage, these bets really stack the deck in the house’s favor.

And just as I don’t feel guilty for leaving Caesar’s Palace without playing the Wheel of Fortune, I don’t feel a bit of guilt for not taking this bet from Nate Silver:

1. For each day that the high temperature in your hometown is at least 1 degree Fahrenheit above average, as listed by Weather Underground, you owe me $25. For each day that it is at least 1 degree Fahrenheit below average, I owe you $25.

I presume Silver is a smart guy and knows what he is doing, because in fact this is not a bet on future warming, but on past warming.  Even without a bit of future warming, he wins this bet.  Why?

I am sitting in my hotel room, and so I don’t have time to dig into the Weather Underground’s data definitions, but my guess is that their average temperatures are based on historic data, probably about a hundred years worth on average.

Over the last 100 years the world has on average warmed about 1F.  This means that today, again on average, most locations will sit on a temperature plateau about 0.5F higher than the average.  So by structuring this bet like this, he is basically asking people  to take “red” in roulette while he takes black and zero and double zero.   He has a built in 0.5F advantage.  Even with zero future warming.

Now, the whole point of this bet may be to take money from skeptics who don’t bother to educate themselves on climate and believe Rush Limbaugh or whoever that there has never been any change in world temperatures.  Fine.  I have little patience with either side of the debate that want to be vocal without educating him or herself on the basic facts.  But to say this is a bet on future warming is BS.

The other effect that may exist here (but I am less certain of the science, commenters can help me out) is that by saying “your hometown” we put the bet into the domain of urban heat islands and temperature station siting issues.  Clearly UHI has substantially increased temperatures in many cities, but that is because average temperatures are generally computed as the average of the daily minimum and maximum.  My sense is that UHI has a much bigger effect on Tmin than Tmax – such that my son and I found a 10 degree F UHI in Phoenix in the evening, but I am not sure if we could find one, or as large of one, at the daily maximum.  Nevertheless, to the extent that such an effect exists for Tmax, most cities that have grown over the last few years will be above their averages just from the increasing UHI component.

I don’t have the contents of my computer hard drive here with me, but a better bet would be from a 10-year average of some accepted metric  (I’d prefer satellites but Hadley CRUT would be OK if we just had to use the old dinosaur surface record).  Since I accept about 1-1.2C per century, I’d insist on this trend line and would pay out above it and collect below it  (all real alarmists consider a 1.2C per century future trend to be about zero probability, so I suspect this would be acceptable).

Take A Deep Breath…

A lot of skeptics’ websites are riled up about the EPA’s leadership decision not to forward comments by EPA staffer Alan Carlin on the Endangerment issue and global warming because these comments were not consistent with where the EPA wanted to go on this issue.   I reprinted the key EPA email here, which I thought sounded a bit creepy, and some of the findings by the CEI which raised this issue.

However, I think skeptics are getting a bit carried away.  Let’s try to avoid the exaggeration and hype of which we often accuse global warming alarmists.  This decision does not reflect well on the EPA, but let’s make sure we understand what it was and was not:

  • This was not a “study” in the sense we would normally use the word.  These were comments submitted by an individual to a regulatory decision and/or a draft report.  The  authors claimed to only have 4 or 5 days to create these comments.  To this extent, they are not dissimilar to the types of comments many of us submitted to the recently released climate change synthesis report (comments, by the way, which still have not been released though the final report is out — this in my mind is a bigger scandal than how Mr. Carlin’s comments were handled).  Given this time frame, the comments are quite impressive, but nonetheless not a “study.”
  • This was not an officially sanctioned study that was somehow suppressed.  In other words, I have not seen anywhere that Mr. Carlin was assigned by the agency to produce a report on anthropogenic global warming.  This does not however imply that what Mr. Carlin was doing was unauthorized.  This is a very normal activity — staffers from various departments and background submitting comments on reports and proposed regulations.  He was presumably responding to an internal call for comments by such and such date.
  • I have had a number of folks write me saying that everyone is misunderstanding the key email — that it should be taken on its face — and read to mean that Mr. Carlin commented on issues outside of the scope of the study or based document he was commenting on.  An example might be submitting comments saying man is not causing global warming to a study discussing whether warming causes hurricanes.   However, his comments certainly seem relevant to Endangerment question — the background, action, and proposed finding the comments were aimed at is on the EPA website here.  Note in particular the comments in Carlin’s paper were totally relevant and on point to the content of the technical support document linked on that page.
  • The fourth email cited by the CEI, saying that Mr. Carlin should cease spending any more time on global warming, is impossible to analyze without more context.  There are both sinister and perfectly harmless interpretations of such an email.  For example, I could easily imagine an employee assigned to area Y who had a hobbyist interest in area X and loved to comment on area X being asked by his supervisor to go back and do his job in area Y.  I have had situations like that in the departments I have run.

What does appear to have happened is that Mr. Carlin responded to a call for comments, submitted comments per the date and process required, and then had the organization refuse to forward those comments because they did not fit the storyline the EPA wanted to put together.  This content-based rejection of his submission does appear to violate normal EPA rules and practices and, if not, certainly violates the standards we would want such supposedly science-based regulatory bodies to follow.  But let’s not upgrade this category 2 hurricane to category 5 — this was not, as I understand it, an agency suppressing an official agency-initiated study.

I may be a cynical libertarian on this, but this strikes me more as a government issue than a global warming issue.  Government bureaucracies love consensus, even when they have to impose it.  I don’t think there is a single agency in Washington that has not done something similar — ie suppressed internal concerns and dissent when the word came down from on high what the answer was supposed to be on a certain question they were supposed to be “studying.”**  This sucks, but its what we get when we build this big blundering bureaucracy to rule us.

Anyway, Anthony Watt is doing a great job staying on top of this issue.  His latest post is here, and includes an updated version of Carlin’s comments.   Whatever the background, Carlin’s document is well worth a read.  I have mirrored the document here.

**Postscript: Here is something I have observed about certain people in both corporate and government beauracracies.  I appologize, but I don’t really have the words for this and I don’t know the language of psychology.   There is a certain type of person who comes to believe, really believe, their boss’s position on an issue.  We often chalk this up from the outside to brown-nosing or an “Eddie Haskell” effect where people fake their beliefs, but I don’t think this is always true.  I think there is some sort of human mental defense mechanism that people have a tendency to actually adopt (not just fake) the beliefs of those in power over them.  Certainly some folks resist this, and there are some issues too big or fundamental for this to work, but for many folks their mind will reshape itself to the beaucracracy around it.  It is why sometimes organizations cannot be fixed, and can only be blown up.

Update: The reasons skeptics react strongly to stuff like this is that there are just so many examples:

Over the coming days a curiously revealing event will be taking place in Copenhagen. Top of the agenda at a meeting of the Polar Bear Specialist Group (set up under the International Union for the Conservation of Nature/Species Survival Commission) will be the need to produce a suitably scary report on how polar bears are being threatened with extinction by man-made global warming….

Dr Mitchell Taylor has been researching the status and management of polar bears in Canada and around the Arctic Circle for 30 years, as both an academic and a government employee. More than once since 2006 he has made headlines by insisting that polar bear numbers, far from decreasing, are much higher than they were 30 years ago. Of the 19 different bear populations, almost all are increasing or at optimum levels, only two have for local reasons modestly declined.

Dr Taylor agrees that the Arctic has been warming over the last 30 years. But he ascribes this not to rising levels of CO2 – as is dictated by the computer models of the UN’s Intergovernmental Panel on Climate Change and believed by his PBSG colleagues – but to currents bringing warm water into the Arctic from the Pacific and the effect of winds blowing in from the Bering Sea….

Dr Taylor had obtained funding to attend this week’s meeting of the PBSG, but this was voted down by its members because of his views on global warming. The chairman, Dr Andy Derocher, a former university pupil of Dr Taylor’s, frankly explained in an email (which I was not sent by Dr Taylor) that his rejection had nothing to do with his undoubted expertise on polar bears: “it was the position you’ve taken on global warming that brought opposition”.

Dr Taylor was told that his views running “counter to human-induced climate change are extremely unhelpful”. His signing of the Manhattan Declaration – a statement by 500 scientists that the causes of climate change are not CO2 but natural, such as changes in the radiation of the sun and ocean currents – was “inconsistent with the position taken by the PBSG”.

GCCI Report #3: Warming and Feedback

One frequent topic on this blog is that the theory of catastrophic anthropogenic global warming actually rests on two separate, unrelated propositions.  One, that increasing CO2 in the atmosphere increases temperatures.  And two, that the Earth’s climate is dominated by positive feedbacks that multiply the warming from Co2 alone by 3x or more.  Proposition one is well-grounded, and according to the IPCC (which this report does not dispute) the warming from Co2 alone is about 1.2C per doubling of Co2 concentrations.  Proposition two is much, much iffier, which is all the more problematic since 2/3 or more of the hypothesized future warming typically comes from the feedback.

We have to do a little legwork, because this report bends over backwards to not include any actual science.  For example, as far as I can tell, it does not actually establish a range of likely climate sensitivity numbers, but we can back into them.

The report uses CO2 concentrations numbers for “do nothing” scenarios (no global warming legislation) of between 850 and 950 ppm in 2100.  These are labeled as the IPCC A2 and A1F1 scenarios.  For these scenarios, between 2000 and 2100 they show warming of 6F and 7F respectively.   Now, I need to do some conversions.  850 and 950 ppm represent about 1.25 and 1.5 doublings from 2000 levels.  The temperatures for these are 3.3C and 3.9C.  This means that the assumed sensitivity in these charts (as degrees Celsius per doubling) is around 2.6, though my guess is that there are time delays in the model and the actual number is closer to 3.  This is entirely consistent with the last IPCC report.

OK, that seems straight forward.  Except having used these IPCC numbers on pages 23-25, they quickly abandon them in favor of higher numbers.    Here for example, is a chart from page 29:

us-future-temps2

Note the map on the right, which is the end of century projection for the US.  The chart shows a range of warming of 7-11 degrees F for a time period centered on 2090  (they boxed that range on the thermometer, not me), but the chart on page 25 shows average warming in the max emissions case in 2090 to be about 7.5F against the same baseline (you have to be careful, they keep moving the baseline around on these charts).  It could be that my Mark I integrating eyeball is wrong, but that map sure looks like more than an average 7.5F increase.  It could be that the US is supposed to warm more than the world average, but the report never says so that I can find, and the US (even by the by the numbers in the report) has warmed less than the rest of the globe over the last 50 years.

The solution to this conundrum may be on page 24 when they say:

Based on scenarios that do not assume explicit climate policies to reduce greenhouse gas emissions, global average temperature is projected to rise by 2 to 11.5°F by the end of this century90 (relative to the 1980-1999 time period).

Oddly enough (well, oddly for a science document but absolutely predictably for an advocacy paper) the high end of this range, rather than the median, seems to be the number used through the rest of the report.  This 11.5F probably implies a climate sensitivity around 5 C/doubling.  Using the IPCC numaber of 1.2 for CO2 alone, means that this report is assuming that as much as 75% of the warming comes from positive feedback effects.

So, since most of the warming, and all of the catastrophe, comes from the assumption that the climate system is dominated by net positive feedback, one would assume the report would address itself to this issue.  Wrong.

I did a search for the word “feedback” in the document just to make sure I didn’t miss anything.  Here are all the references in the main document (outside of footnotes) to feedback used in this context:

  • P15:  “However, the surface warming caused by human-produced increases in other greenhouse gases leads to an increase in atmospheric water vapor, since a warmer climate increases evaporation and allows the atmosphere to hold more moisture. This creates an amplifying “feedback loop,” leading to more warming.”
  • P16:  “For example, it is known from long records of Earth’s climate history that under warmer conditions, carbon tends to be released, for instance, from thawing permafrost, initiating a feedback loop in which more carbon release leads to more warming which leads to further release, and so on.”
  • P17:  “For example, it is known from long records of Earth’s climate history that under warmer conditions, carbon tends to be released, for instance, from thawing permafrost, initiating a feedback loop in which more carbon release leads to more warming which leads to further release, and so on.

That’s it – the entire sum text of feedbacks.  All positive, no discussion of negative feedbacks, and no discussion of the evidence how we know positive feedbacks outweight negative feedbacks.  The first one of the three is particularly disengenuous, since most serious scientists will admit that we don’t even know the sign of the water vapor feedback loop, and there is good evidence the sign is actually negative (due to albedo effects from increased cloud formation).

Its all About the Feedback

If frequent readers get any one message from this site, it should be that the theory of catastrophic global warming from CO2 is actually based on two parallel and largely unrelated theories:

  1. That CO2 acts as a greenhouse gas and can increase global temperatures as concentrations increase
  2. That the earth’s climate is dominated by strong positive feedback that multiplies the effect of #1 3,4,5 times or more.

I have always agreed with #1, and I think most folks will accept a number between 1-1.2C for a doubling of CO2 (though a few think its smaller).  #2 is where the problem with the theory is, and it is no accident that this is the area least discussed in the media.  For more, I refer you to this post and this video.  (higher resolution video here, clip #3).

In my video and past posts, I have tried to back into the feedback fraction f that models are using.  I used a fairly brute force approach and came up with numbers between 0.65 and 0.85.  It turns out I was pretty close.  Dr Richard Lindzen has this chart showing the feedback fractions f used in models, and the only surprise to me is how many use a number higher than 1 (such numbers imply runaway reactions similar to nuclear fission).

lindzen_graph_icccjune09

Lindzen thinks the true number is closer to -1, which is similar to the number I backed into from temperature history over the last 100 years.  This would imply that feedback actually works to reduce the net effect of greenhouse warming, from a sensitivity of 1.2 to one something like 0.6C per doubling.

Perils of Modeling Complex Systems

I thought this article in the NY Times about the failure of models to accurately predict the progression of swine flu cases was moderately instructive.

In the waning days of April, as federal officials were declaring a public health emergency and the world seemed gripped by swine flu panic, two rival supercomputer teams made projections about the epidemic that were surprisingly similar — and surprisingly reassuring. By the end of May, they said, there would be only 2,000 to 2,500 cases in the United States.

May’s over. They were a bit off.

On May 15, the Centers for Disease Control and Prevention estimated that there were “upwards of 100,000” cases in the country, even though only 7,415 had been confirmed at that point.

The agency declines to update that estimate just yet. But Tim Germann, a computational scientist who worked on a 2006 flu forecast model at Los Alamos National Laboratory, said he imagined there were now “a few hundred thousand” cases.

We can take at least two lessons from this:

  • Accurately modeling complex systems is really, really hard.  We may have hundreds of key variables, and changes in starting values or assumed correlation coefficients between these variables can make enormous differences in model results.
  • Very small changes in assumptions about processes that compound or have exponential growth make enormous differences in end results.  I think most people grossly underestimate this effect.  Take a process that starts at an arbitrary value of “100″ and grows at some growth rate each period for 50 periods.    A growth rate of 1% per period yields an end value of  164.  A growth rate just 1 percentage point higher of 2% per period yields a final value of  269.    A growth rate of 3% yield a final value of 438.  In this case, if we miss the growth rate by just a couple of percentage points, we miss the end value by a factor of three!

Bringing this back to climate, we must understand that the problem of forecasting disease growth rates is grossly, incredibly more simple than forecasting future temperatures.  These guys missed the forecast my miles of a process that is orders of magnitude more amenable to forecasting than is climate.  But I am encouraged by this:

Both professors said they would use the experience to refine their models for the future.

If only climate scientists took this approach to new observations.

Global Warming and Ocean Heat

William DiPuccio has a really very readable and clear post on using ocean heat content to falsify current global warming model projections. He argues pretty persuasively that surface air temperature measurements are a really, really poor way to search for evidence of a man-made climate forcing from CO2.

Since the level of CO2 and other well-mixed GHG is on the rise, the overall accumulation of heat in the climate system, measured by ocean heat, should be fairly steady and uninterrupted (monotonic) according to IPCC models, provided there are no major volcanic eruptions.  According to the hypothesis, major feedbacks in the climate system are positive (i.e., amplifying), so there is no mechanism in this hypothesis that would cause a suspension or reversal of overall heat accumulation.  Indeed, any suspension or reversal would suggest that the heating caused by GHG can be overwhelmed by other human or natural processes in the climate system….

[The] use of surface air temperature as a metric has weak scientific support, except, perhaps, on a multi-decadal or century time-scale.  Surface temperature may not register the accumulation of heat in the climate system from year to year.  Heat sinks with high specific heat (like water and ice) can absorb (and radiate) vast amounts of heat.  Consequently the oceans and the cryosphere can significantly offset atmospheric temperature by heat transfer creating long time lags in surface temperature response time.  Moreover, heat is continually being transported in the atmosphere between the poles and the equator.  This reshuffling can create fluctuations in average global temperature caused, in part, by changes in cloud cover and water vapor, both of which can alter the earth’s radiative balance.

One statement in particular really opened my eyes, and made  me almost embarassed to have focused time on surface temperatures at all:

For any given area on the ocean’s surface, the upper 2.6m of water has the same heat capacity as the entire atmosphere above it

Wow!  So oceans have orders of magnitude more heat capacity than the atmosphere.

The whole article is a good read, but his conclusion is that estimates of ocean heat content changes appear to be way off what they should be given IPCC models:

dipuccio-2

My only concern with the analysis is that I fear the authors may be underestimating the effect of phase change (e.g. melting or evaporation).  Phase change can release or absorb enormous amounts of heat.  As a simple example, observe how long a pound of liquid water at 32.1F takes to reach room temperature.  Then observe how long a pound of ice at 31.9F takes to reach room temperature.  The latter process takes an order of magnitude more time, because it absorbs an order of magnitude more heat.

The article attached was necessarily a summary, but I am not totally convinced he has accounted for phase change sufficiently.  Both an increase in melting ice as well as an increase in evaporation would tend to cause measured accumulated heat in the oceans to be lower than expected.   He uses an estimate by James Hansen that the number is really small for ice melting (he does not discuss evaporation).  However, if folks continue to use Hansen’s estimate of this term to falsify Hansen’s forecast, expect Hansen to suddenly “discover” that he had grossly underestimated the ice melting term.

Sudden Acceleration

For several years, there was an absolute spate of lawsuits charging sudden acceleration of a motor vehicle — you probably saw such a story:  Some person claims they hardly touched the accelerator and the car leaped ahead at enormous speed and crashed into the house or the dog or telephone pole or whatever.  Many folks have been skeptical that cars were really subject to such positive feedback effects where small taps on the accelerator led to enormous speeds, particularly when almost all the plaintiffs in these cases turned out to be over 70 years old.  It seemed that a rational society might consider other causes than unexplained positive feedback, but there was too much money on the line to do so.

Many of you know that I consider questions around positive feedback in the climate system to be the key issue in global warming, the one that separates a nuisance from a catastrophe.  Is the Earth’s climate similar to most other complex, long-term stable natural systems in that it is dominated by negative feedback effects that tend to damp perturbations?  Or is the Earth’s climate an exception to most other physical processes, is it in fact dominated by positive feedback effects that, like the sudden acceleration in grandma’s car, apparently rockets the car forward into the house with only the lightest tap of the accelerator?

I don’t really have any new data today on feedback, but I do have a new climate forecast from a leading alarmist that highlights the importance of the feedback question.

Dr. Joseph Romm of Climate Progress wrote the other day that he believes the mean temperature increase in the “consensus view” is around 15F from pre-industrial times to the year 2100.  Mr. Romm is mainly writing, if I read him right, to say that critics are misreading what the consensus forecast is.  Far be it for me to referee among the alarmists (though 15F is substantially higher than the IPCC report “consensus”).  So I will take him at his word that 15F increase with a CO2 concentration of 860ppm is a good mean alarmist forecast for 2100.

I want to deconstruct the implications of this forecast a bit.

For simplicity, we often talk about temperature changes that result from a doubling in Co2 concentrations.  The reason we do it this way is because the relationship between CO2 concentrations and temperature increases is not linear but logarithmic.  Put simply, the temperature change from a CO2 concentration increase from 200 to 300ppm is different (in fact, larger) than the temperature change we might expect from a concentration increase of 600 to 700 ppm.   But the temperature change from 200 to 400 ppm is about the same as the temperature change from 400 to 800 ppm, because each represents a doubling.   This is utterly uncontroversial.

If we take the pre-industrial Co2 level as about 270ppm, the current CO2 level as 385ppm, and the 2100 Co2 level as 860 ppm, this means that we are about 43% through a first doubling of Co2 since pre-industrial times, and by 2100 we will have seen a full doubling (to 540ppm) plus about 60% of the way to a second doubling.  For simplicity, then, we can say Romm expects 1.6 doublings of Co2 by 2100 as compared to pre-industrial times.

So, how much temperature increase should we see with a doubling of CO2?  One might think this to be an incredibly controversial figure at the heart of the whole matter.  But not totally.  We can break the problem of temperature sensitivity to Co2 levels into two pieces – the expected first order impact, ahead of feedbacks, and then the result after second order effects and feedbacks.

What do we mean by first and second order effects?  Well, imagine a golf ball in the bottom of a bowl.  If we tap the ball, the first order effect is that it will head off at a constant velocity in the direction we tapped it.  The second order effects are the gravity and friction and the shape of the bowl, which will cause the ball to reverse directions, roll back through the middle, etc., causing it to oscillate around until it eventually loses speed to friction and settles to rest approximately back in the middle of the bowl where it started.

It turns out the the first order effects of CO2 on world temperatures are relatively uncontroversial.  The IPCC estimated that, before feedbacks, a doubling of CO2 would increase global temperatures by about 1.2C  (2.2F).   Alarmists and skeptics alike generally (but not universally) accept this number or one relatively close to it.

Applied to our increase from 270ppm pre-industrial to 860 ppm in 2100, which we said was about 1.6 doublings, this would imply a first order temperature increase of 3.5F from pre-industrial times to 2100  (actually, it would be a tad more than this, as I am interpolating a logarithmic function linearly, but it has no significant impact on our conclusions, and might increase the 3.5F estimate by a few tenths.)  Again, recognize that this math and this outcome are fairly uncontroversial.

So the question is, how do we get from 3.5F to 15F?  The answer, of course, is the second order effects or feedbacks.  And this, just so we are all clear, IS controversial.

A quick primer on feedback.  We talk of it being a secondary effect, but in fact it is a recursive process, such that there is a secondary, and a tertiary, etc. effects.

Lets imagine that there is a positive feedback that in the secondary effect increases an initial disturbance by 50%.  This means that a force F now becomes F + 50%F.  But the feedback also operates on the additional 50%F, such that the force is F+50%F+50%*50%F…. Etc, etc.  in an infinite series.  Fortunately, this series can be reduced such that the toal Gain =1/(1-f), where f is the feedback percentage in the first iteration. Note that f can and often is negative, such that the gain is actually less than 1.  This means that the net feedbacks at work damp or reduce the initial input, like the bowl in our example that kept returning our ball to the center.

Well, we don’t actually know the feedback fraction Romm is assuming, but we can derive it.  We know his gain must be 4.3 — in other words, he is saying that an initial impact of CO2 of 3.5F is multiplied 4.3x to a final net impact of 15.  So if the gain is 4.3, the feedback fraction f must be about 77%.

Does this make any sense?  My contention is that it does not.  A 77% first order feedback for a complex system is extraordinarily high  — not unprecedented, because nuclear fission is higher — but high enough that it defies nearly every intuition I have about dynamic systems.  On this assumption rests literally the whole debate.  It is simply amazing to me how little good work has been done on this question.  The government is paying people millions of dollars to find out if global warming increases acne or hurts the sex life of toads, while this key question goes unanswered.  (Here is Roy Spencer discussing why he thinks feedbacks have been overestimated to date, and a bit on feedback from Richard Lindzen).

But for those of you looking to get some sense of whether a 15F forecast makes sense, here are a couple of reality checks.

First, we have already experienced about .43 if a doubling of CO2 from pre-industrial times to today.  The same relationships and feedbacks and sensitivities that are forecast forward have to exist backwards as well.  A 15F forecast implies that we should have seen at least 4F of this increase by today.  In fact, we have seen, at most, just 1F  (and to attribute all of that to CO2, rather than, say, partially to the strong late 20th century solar cycle, is dangerous indeed).  But even assuming all of the last century’s 1F temperature increase is due to CO2, we are way, way short of the 4F we might expect.  Sure, there are issues with time delays and the possibility of some aerosol cooling to offset some of the warming, but none of these can even come close to closing a gap between 1F and 4F.  So, for a 15F temperature increase to be a correct forecast, we have to believe that nature and climate will operate fundamentally different than they have over the last 100 years.

Second, alarmists have been peddling a second analysis, called the Mann hockey stick, which is so contradictory to these assumptions of strong positive feedback that it is amazing to me no one has called them on the carpet for it.  In brief, Mann, in an effort to show that 20th century temperature increases are unprecedented and therefore more likely to be due to mankind, created an analysis quoted all over the place (particularly by Al Gore) that says that from the year 1000 to about 1850, the Earth’s temperature was incredibly, unbelievably stable.  He shows that the Earth’s temperature trend in this 800 year period never moves more than a few tenths of a degree C.  Even during the Maunder minimum, where we know the sun was unusually quiet, global temperatures were dead stable.

This is simply IMPOSSIBLE in a high-feedback environment.  There is no way a system dominated by the very high levels of positive feedback assumed in Romm’s and other forecasts could possibly be so rock-stable in the face of large changes in external forcings (such as the output of the sun during the Maunder minimum).  Every time Mann and others try to sell the hockey stick, they are putting a dagger in teh heart of high-positive-feedback driven forecasts (which is a category of forecasts that includes probably every single forecast you have seen in the media).

For a more complete explanation of these feedback issues, see my video here.