Roy Spencer’s Great Blunder, Part 1

The following is PART 1 of an extended critique of Roy Spencer’s The Great Global Warming Blunder:  How Mother Nature Fooled the World’s Top Climate Scientists (New York:  Encounter Books, 2010).  See also Part 2 and Part 3.  Previous critiques of Spencer’s general approach to climate have been published by Ray Pierrehumbert and Tamino (here, here, and here).  My Utah readers will remember that Roy Spencer was invited to testify before a committee of the Utah Legislature last year.

Summary of Part 1:  In his latest book, The Great Global Warming Blunder, Roy Spencer lashes out at the rest of the climate science community for either ignoring or suppressing publication of his research.  This research, he claims, virtually proves that the climate models used by the IPCC respond much too sensitively to external “forcing” due to changes in greenhouse gas concentrations, variations in solar radiation, and so on.  Instead, Spencer believes most climate change is caused by chaotic, natural variations in cloud cover.  He and a colleague published a peer-reviewed paper in which they used a simple climate model to show that these chaotic variations could cause patterns in satellite data that would lead climatologists to believe the climate is significantly more sensitive to external forcing than it really is.  Spencer admits, however, that his results may only apply to very short timescales.  Since the publication of his book, furthermore, other scientists (including one that initially gave Spencer’s paper a favorable review) have shown that Spencer was only able to obtain this result by assuming unrealistic values for various model parameters.

Roy Spencer is not your average climate contrarian.  He has a PhD in meteorology from the University of Wisconsin–Madison, is a researcher at the University of Alabama–Huntsville, used to work in one of the climate units at NASA, and has published some well respected research on climate.  And yet, in The Great Global Warming Blunder:  How Mother Nature Fooled the World’s Top Climate Scientists, Spencer’s latest book, he isn’t just talking about his accomplishments in mainstream science.  Rather, he’s taking his case “to the people” because he says his latest research has blown the lid off the consensus among climate scientists that humans are causing significant climate change.  But the part of his research that has been published in the peer-reviewed literature has largely been ignored, and the rest has been quashed in the review process.

Ultimately I find enough evidence to virtually prove my theory, but now the research papers that I submit for publication are rejected outright….

The climate modelers and their supporters in government are largely in control of the research funding, which means that most government contracts and grants go toward these investigators who support the party line on global warming.  Sympathizers preside as editors overseeing what can and cannot be published in research journals.  Now they even rule over several of our professional societies, organizations that should be promoting scientific curiosity no matter where it leads.

In light of these developments, I have decided to take my message to the people.  This message is that mankind’s influence on climate is small and will continue to be small.  (pp. xi-xii)

These are serious charges Spencer levels against his fellow scientists, and while he is careful to distinguish between the majority of climate scientists, whom he paints as intellectually lazy malingerers who are “just along for the ride” (p. xvi), and the leadership of the IPCC, whom he paints as conniving, politically driven power-grabbers, he pictures a pretty broad-based conspiracy.

I find it difficult to believe that I am the first researcher to figure out what I describe in this book.  Either I am smarter than the rest of the world’s climate scientists–which seems unlikely–or there are other scientists who also have evidence that global warming could be mostly natural, but have been hiding it.  That is a serious charge, I know, but it is a conclusion that is difficult for me to avoid.  (p. xxvii)

That’s how Roy Spencer sees himself–a persecuted Galileo, boldly speaking scientific truth to power, while most of his fellow scientists succumb to greed and cowardice.  Whether Spencer ultimately turns out to be right or wrong, in this review I will show that at this point, he hasn’t even come close to proving his case.  Furthermore, some of his work has been of demonstrably poor quality, so if his aim is to convince other scientists, he has shot himself in the foot more than once.  Whereas Galileo’s main thesis was eventually universally accepted, the probability of that kind of outcome here seems vanishingly small.

The Gist

Spencer’s two main claims are as follows.  First, “the climate system is much less sensitive to our greenhouse gas emissions than the experts claim it to be” (p. vii).   Second, “the climate system itself is probably responsible for most of the warming we have seen in the last 100 years or so.  Contrary to popular belief, you don’t need a change in the sun or a volcanic eruption or pollution by humankind to cause global warming or cooling” (p. viii).

The problems with Spencer’s arguments take some background knowledge to recognize, so I’m going to start at a pretty basic level, just as he does in his book, but then go beyond his explanations in the book by including a little more math.  (I’m sorry–I’ll try to walk you through it slowly if you’re a mathphobe.)  Also, I’ve included a small “appendix” at the end of this post with a short explanation of climate “forcing” and “feedback.”  If you’re a climate wonk, you undoubtedly already know all about that, but if not, skip down to the end and read the appendix first.

A Simple Climate Model

To explore his ideas, Spencer employed a “simple climate model”.  And by “simple” I mean it treats the Earth as a well-mixed ocean of a certain depth, and includes some terms for different kinds of forcing, and another for net feedbacks.  I don’t mean to put down Spencer’s work by pointing this out–this kind of “zero-dimensional” climate model is very commonly used by scientists as a first-order approximation of how the system behaves, at least in situations where they aren’t bothering to look at the spatial distribution of climate effects.  In fact, using a simple model like this can be very informative, because there are so few variables that you can easily examine the effects of changing each one.

Spencer’s model is described qualitatively in the book, and is also programmed into an Excel spreadsheet, which Spencer makes available here.  The model is basically the following.

Equation 1:  d(∆T)/dt = (Forcing – Feedback)/Cp

Here, ∆T is the difference between the temperature at time t and the temperature at equilibrium.  (That is, ∆T is the “temperature anomaly” with respect to equilibrium.)  Cp is the total heat capacity of a column of ocean water 1 m^2 on top and h meters deep. (If you’re interested in running such a model yourself, Cp = 4,180,000 J/m^3 * h.  Pay attention to the ocean water depth.  It will be very important in a future installment of this review.)   The reason this column of ocean water is 1 m^2 on top is because the Forcing and Feedback fluxes are both in W/m^2–i.e., they are normalized to 1 m^2 of the Earth’s surface.  A Watt is equivalent to 1 J/s, where Joules (J) are units of energy.  So the Forcing tells us the rate at which extra energy is coming in, while the feedback tells us how the climate system responds to the push, by either enhancing the forcing or hitting the brakes.

So what Eqn. 1 is really saying is that the rate of change of the temperature depends on 1) how much water has to be heated by the incoming radiation (Cp), 2) what the forcing is, and 3) how the climate system responds to the forcing in terms of sending more or less radiation back into space.

Feedback is represented by Eqn. 2.

Equation 2:   Feedback = alpha*∆T

When the “feedback parameter” (alpha) is positive, then there are some “brakes” on the system (notice the minus sign in Eqn. 1).  That is, if the forcing pushes the temperature one way, the feedback will put the brakes on and slow it down.  If alpha is negative, then the system will be unstable, because every time the forcing pushes one way, the feedback will keep pushing the system harder and harder in that direction.

This way of defining climate feedback is a bit non-standard, however, so I should explain the difference.  Typically, when climate scientists say there is zero feedback, alpha is actually about 3.3 W/m^2/°C.  This is the amount of extra energy the Earth would radiate back into space (all else being equal) if the temperature were raised 1 °C, simply because hotter objects give off more radiation.  So if alpha is less than 3.3 W/m^2/°C, scientists say there is a net positive feedback in the system, and if it’s more than that, they say there is a net negative feedback.  Essentially nobody thinks alpha should be less than zero, though, because that would lead to really crazy swings in the climate.  For reference, Spencer indicates that the climate models the IPCC uses to make temperature projections (and which incorporate fairly strong positive feedback) have alpha values of 0.9-1.9 W/m^2/°C.

Short-Term Cloud Feedbacks

Climate scientists don’t just guess at things like alpha values, however.  They can estimate alpha values from the correlation between satellite measurements of changes in radiation fluxes and changes in temperature.  When Spencer examined this method for estimating alpha, he surmised that it assumes the temperature changes are the cause of the changes in net radiation flux.  But what if the causality were reversed?  What if, at least in part, something internal to the system were causing the changes in radiation flux, and that caused the changes in temperature?  Wouldn’t that screw up this method for estimating alpha?

This is not a crazy idea.  It is well known that weather is chaotic, meaning that slight fluctuations in one part of the system can cause large and unpredictable fluctuations in another part of the system.  (This is also known as the “Butterfly Effect“.)  Climate (which refers to the long-term average of weather) is not necessarily thought to be chaotic, however, except over fairly short time periods.   Over these shorter periods, there are many modes of climate variability, usually involving semi-structured oscillations in sea surface temperatures, like the El Niño-Southern Oscillation, the Pacific Decadal Oscillation, the Arctic Oscillation, and so on.  In turn, random fluctuations in sea surface temperature due to ocean circulation patterns, etc., might cause concomitant changes in cloudiness, which would affect the radiation balance, and hence the temperature.  (If you keep reading, however, you will find that Spencer thinks the causality is the other way around.  Random variations in sea surface temperature are caused by random variations in cloudiness, which are caused by who-knows-what.)

Spencer and his colleague, Danny Braswell, put this idea to the test with their simple climate model, in which they could specify what the alpha value was, and drive the model with a combination of random fluctuations in both external and “internal” forcing.  They could then track both the net radiation flux and the temperature to estimate alpha in the traditional manner.  They found that the traditional estimation method produced systematically low alpha values–i.e., they were skewed toward more positive feedback.  However, they found characteristic patterns in the data (which they called “feedback stripes”) that allowed them to estimate alpha much more accurately.  Furthermore, they could find the same kinds of patterns in the satellite data.  These observations led Spencer and Braswell to conclude that alpha really should be 6 W/m^2/°C or more, indicating very strong negative feedback.

With this interesting result, Spencer and Braswell decided to submit their paper to the Journal of Climate, an excellent scientific journal that publishes climate research.  What happened?  Did some sniveling cowards trash the paper in review out of fear of future reprisals from the people Spencer sarcastically calls “The Keepers of All Climate Knowledge” (p. xxi)?  Did one of those politically motivated sympathizers who have insinuated themselves as editors of all the major climate journals reject it, despite favorable reviews?  Surprisingly (to Spencer), they did not!

I did not have high hopes for getting the paper accepted, though, because of its potential implications regarding the seriousness of manmade global warming.  To my great surprise, two leading climate experts chosen by the journal’s editor to be peer reviewers agreed that we had raised a legitimate issue.  In fact, each reviewer decided to build his own simple climate model to demonstrate the effect for himself.  Both offered constructive advice on how to improve our model in order to demonstrate the effect more clearly.  One even said it was important that the climate modeling community be made aware of the issue.  We modified the paper according to their advice, and it was published in November 2008.  (p. 73)   [Note:  See Spencer and Braswell (2008)–BB.]

What?  Where were all the caviling intellectual lightweights?

Our university put out a press release on the paper–and the mainstream news media totally ignored it.

As far as I can tell, the results of that published work have been largely ignored by the scientific community too.  Chances are, even if they did read the paper they would not recognize its potential significance.  This is because it is almost impossible to get away with saying anything like “this could throw all of our global warming predictions out the window” in a scientific publication.  There will always be at least one peer reviewer of your paper who has so bought into the theory of anthropogenic global warming that he will not permit you to publish anything that directly calls the prevailing orthodoxy into question.  (p. 73)

Oh, there they were.  But wait, isn’t there some more charitable interpretation that could be made?  Here are a few ideas.

1. Spencer himself says it’s unlikely that most scientists who even read their paper would have recognized its Earth-shattering significance, because he deliberately left that part out to sneak the paper past unsuspecting zealots in the review process.

But they should have immediately recognized the significance, anyway?

2. The results aren’t necessarily as significant as Spencer wants us to believe.

In fact, Spencer himself admits that the huge alpha values he estimated don’t necessarily represent the long-term feedback, which is what climatologists actually care about.  In fact, later in the book he argues for a long-term alpha value of about 3.0 W/m^2/°C, indicating a weak positive feedback, rather than a strongly negative one.  Regarding the 6 W/m^2/°C figure, he says,

Note that I am not necessarily claiming that this is the feedback operating on the long time scales associated with global warming–only that it is the average feedback involved in the climate fluctuations occurring during the period when the satellite was making its measurements.  (p. 118)

3. All the other scientists haven’t been ignoring Spencer’s paper, and Spencer is just being a whiner.

It takes time to explore a new idea, and there aren’t that many people working specifically on cloud feedbacks.  After all, there’s no point in getting all hot and bothered about results that, by Spencer’s own admission, may not amount to much.  Even if another scientist read Spencer and Braswell’s paper immediately after it was published and started working on the problems they identified right away, it might have been several months before a paper was ready to submit, and then several more months before the review process, revisions, editing, and publishing were completed.  In other words, you have to expect several months, and more likely a year or more after a paper is published, before responses start coming out.

Here’s a timeline of how the response to Spencer and Braswell’s paper evolved up until Spencer published his book.  Spencer and Braswell published their paper in November, 2008, but it was originally submitted in September 2007.  (That’s right, the review, revision, editing, and publishing processes for Spencer’s own paper took over a year!)  Piers Forster was one of the reviewers, so he had about 1 year advance notice of the content of the paper.  In December 2008, Gregory and Forster (2008) published a paper on a related topic, in which they mentioned that some of their results were consistent with the earlier paper.  McLean et al. (2009) submitted a paper in December 2008, which was published in July 2009, about how a certain mode of climate variation (the Southern Oscillation) seems to control a lot of the short-term fluctuations in global temperature.  But when they discussed changes in cloud cover, they mentioned that they couldn’t tell from their data whether Spencer and Braswell’s thesis about cause and effect applied.  Spencer’s book came out in April 2010, about 1.5 years after his paper, and I assume it was probably a few months from the time he submitted the final manuscript to the publisher till it actually came off the presses.   The bottom line is that Spencer was ready to start whining about the injustice if his paper was rejected, and he was ready to start whining if all the other scientists didn’t immediately respond to his paper within about a year–which is about the same time it took his paper to be published after he submitted it.  (Who knows how long it took him to do the work and write it up in the first place?)

What has the response to Spencer and Braswell (2008) been like since the publication of The Great Global Warming Blunder?  Three more papers have been published that respond in some way to Spencer and Braswell (2008) and two of them deserve our special attention.

First, Andrew Dessler of Texas A&M University published a paper in Science magazine (Dessler, 2010) in which he estimated the cloud feedback in a way that he claimed gets around the cause-and-effect problem Spencer and Braswell (2008) identified.  He found that the cloud feedback is probably positive, but there is some statistically non-negligible probability that it could be very weakly negative, too.  This result is consistent with the IPCC models.  Roy Spencer actually held a press conference (!) to talk about how he disagreed with Dessler’s interpretations, and Spencer and Dessler had an e-mail exchange, which is discussed (and linked) at the RealClimate site.  The crux of the issue is that, based on a single figure in another modeling paper he published last year (Spencer and Braswell, 2010), Spencer thinks clouds cause El Niño, which would go against decades of research.

Second, do you remember Piers Forster?  One of the scientists who gave a favorable review of Spencer and Braswell’s paper, and even suggested ways to improve it?  The guy who published a paper mentioning Spencer and Braswell’s work, and saying his results were consistent with theirs?  Well, Murphy and Forster (2010) went ahead and did a more thorough examination of Spencer and Braswell’s approach, and the result wasn’t pretty.  Here’s the abstract of their paper.

Changes in outgoing radiation are both a consequence and a cause of changes in the earth’s temperature. Spencer and Braswell recently showed that in a simple box model for the earth the regression of outgoing radiation against surface temperature gave a slope that differed from the model’s true feedback parameter. They went on to select input parameters for the box model based on observations, computed the difference for those conditions, and asserted that there is a significant bias for climate studies. This paper shows that Spencer and Braswell overestimated the difference. Differences between the regression slope and the true feedback parameter are significantly reduced when 1) a more realistic value for the ocean mixed layer depth is used, 2) a corrected standard deviation of outgoing radiation is used, and 3) the model temperature variability is computed over the same time interval as the observations. When all three changes are made, the difference between the slope and feedback parameter is less than one-tenth of that estimated by Spencer and Braswell. Absolute values of the difference for realistic cases are less than 0.05 W/m^2/K, which is not significant for climate studies that employ regressions of outgoing radiation against temperature. Previously published results show that the difference is negligible in the Hadley Centre Slab Climate Model, version 3 (HadSM3).  (Murphy and Forster, 2010)

Ouch.  The short version is that Spencer and Braswell plugged in some unrealistic values of the main variables into their model, and automagically got answers that confirmed their hypothesis that standard climate models might be greatly overestimating climate sensitivity.  When someone else plugged in realistic values, it turned out that Spencer and Braswell’s hypothesis was not confirmed in any significant sense.  We’ll see in a future installment of this review that this kind of sloppy modeling work is one of Roy Spencer’s hallmarks.

[UPDATE:  A reader pointed out that Spencer responded to Murphy and Forster’s paper on his blog.  He acknowledges some of the mistakes Murphy and Forster pointed out, and objects to others.  It’s worth reading, but also keep in mind that even if he ends up being right about this, he admits that it may not be indicative of long-term climate sensitivity.]

4. Maybe the other climate scientists have other reasons to believe the climate is pretty sensitive to forcing (i.e., dominated by positive feedbacks.)

In fact, they do… whether Roy Spencer likes it, or not.  That’s the topic of my next installment.

References

Dessler, A.E. (2010) A determination of the cloud feedback from climate variations over the past decade, Science, 330, 1523-1527.

Gregory, J.M., and Forster, P.M. (2008) Transient climate response estimated from radiative forcing and observed temperature change, Journal of Geophysical Research, 113, D23105.

McLean, J.D., de Freitas, C.R., and Carter, R. M. (2009) Influence of the Southern Oscillation on tropospheric temperature,  Journal of Geophysical Research, 114, D14104.

Murphy, D.M., and Forster, P.M. (2010) On the accuracy of deriving climate feedback parameters from correlations between surface temperature and outgoing radiation, Journal of Climate, 23, 4983-4988.

Spencer, R.W., and Braswell, W. D. (2008) Potential biases in cloud feedback diagnosis: A simple model demonstration, Journal of Climate, 21, 5624-5628.

Spencer, R.W., and Braswell, W. D. (2010) On the diagnosis of radiative feedback in the face of unknown radiative forcing, Journal of Geophysical Research, 114, D16109.

Appendix:  Forcing vs. Feedback

After some introductory material, Spencer begins his exposition with two chapters devoted to explaining the concepts of “forcing” and “feedback” in the climate system.  Here’s the idea in a nutshell.

The temperature of the part of the atmosphere where we live depends on how fast energy comes in the system and how fast it goes out.  Spencer explains it as analogous to a pot of water on a stove.  Energy comes from the stove into the pot, heating up the water, but as the water heats up, more heat energy leaves the pot and goes out into the air.  At some point, the water will have heated up to a point where the rate of heat input from the stove is exactly balanced with the rate of heat outflow from the water.  At that point, the temperature becomes stable, and the system is in “equilibrium”.

“Forcings” are factors you treat as external to the system, that either change the rate at which energy comes in, or change the rate of energy outflow.  Suppose your pot of water is in thermal equilibrium (stable temperature), and then you turn up the heat.  You have now “forced” the system, making it so the heat inflow temporarily outmatches the outflow.  The temperature of the water will go up until those rates are matched again, but now the equilibrium temperature will be higher.  Likewise, if you cover the pot with a lid, you have forced the system by making it so heat can’t escape the pot as rapidly.  The climate system might be forced when there is a change in the amount of radiation coming in from the Sun, or when we pump into the atmosphere extra greenhouse gases, which slow down the rate at which energy can leave the system.  In either case, something external to the system has caused a change in the energy inflow or outflow rates, and so the system has to adjust to a new temperature.  (For more information on climate forcing, click here.)

A feedback is an internal response to forcing.  Say the climate system is forced by an increase in the incoming solar radiation, and it gets a little hotter.  This initial increase in temperature then causes other things to happen, e.g., more water vapor can be evaporated into the air at a hotter temperature, and water vapor is a greenhouse gas.  This extra greenhouse gas in the atmosphere slows down the rate of outgoing energy, and the temperature becomes even hotter!  In other words, the forcing gave the system an initial push in one direction, and then the feedback enhanced that initial push.  If the feedback enhances the forcing, it’s called a “positive feedback”.  On the other hand, extra water vapor in the air might lead to more clouds forming, and certain types of clouds tend to reflect back more of the incoming solar radiation.  This would tend to cool the system–i.e., push it in a direction opposite the forcing–and so it is called a “negative feedback”.  (For more information on climate feedbacks, click here.)

Different kinds of clouds have different characteristics with respect to how much solar radiation they reflect, and they also can trap outgoing radiation, which would constitute a positive feedback.  Therefore, it’s pretty complicated to sort out whether cloud feedback is net negative or net positive, and that’s one area where Roy Spencer takes issue with the consensus position.  All the climate models used by the IPCC assume that if you add up all the feedbacks in the climate system, the total is net positive.  So if you give the models a push (forcing) toward hotter or cooler temperatures, that push will be enhanced.  Spencer, however, thinks that the feedbacks are near zero or net negative, largely due to clouds.