Category Archives: Guest Weblogs

Guest Post By Andrew Dessler On The Water Vapor Feedback

Professor Andrew Dessler of the Department of Atmospheric Sciences of Texas A&M University requested the opportunity to respond to my post

Q & A Are Water Vapor Feedbacks From Added CO2 Well Understood?

I welcome his openess to discuss this issue, and am glad to post his guest weblog. We need more such collegial debate on these topics within the climate community. I will respond in an upcoming post.

Guest Weblog By Andrew Dressler

In a recent post, Prof. Pielke emphasized the uncertainties in our knowledge of the water vapor feedback. In doing so, he failed to recognize the many things that are confidently known about the water vapor feedback.

There are really two questions here: 1) do observations indicate that the water vapor feedback strong and positive, and 2) do models adequately reproduce the observed feedback?

For the first question, the evidence of a strong and positive water vapor feedback is overwhelming. Observations of the response of the atmosphere to events like the eruption of Mount Pinatubo and El Niño cycles show quite clearly that changes in water vapor lead to enhanced trapping of infrared radiation when the climate warms [Soden et al., 2002; Soden et al., 2005; Forster and Collins, 2004; Dessler et al., 2008].  For a more complete summary of why we’re so confident, see Dessler et al. [2009]

It is particularly worth noting that the papers that Prof. Pielke referenced by Dr. Sun and colleagues (which he says casts doubt on models’ ability to simulate the feedback) clearly confirm with observations that the water vapor feedback is strong and positive. 

Given the strong water vapor feedback seen in observations (~2 W/m2/K), combined with estimates of the smaller ice-albedo and lapse rate feedbacks, we can estimate warming over the next century will be several degrees Celsius.  You do not need a climate model to reach this conclusion — you can do a simple estimate using the observed estimates of the feedbacks along with an expectation that increases in carbon dioxide will result in an increase in radiative forcing of a few watts per square meter.

The only way that a large warming will not occur in the face of these radiative forcing is if some presently unknown negative feedback that cancels the water vapor feedback.  My opinion is that the cloud feedback is the only place where such a large negative feedback can lurk.  If it is not there, and the planet does not reduce emissions, then get ready for a much warmer climate.

This brings us to the second question, whether models adequately simulate the feedback.

To investigate this, I have recently compared the global-average radiative response to changes in water vapor during El Niño cycles in climate models to that in reanalyses [Dessler and Wong, 2009]. While the details of the comparison are rich, it’s clear that climate models are doing a good job reproducing the radiative response of changes in water vapor to changes in the tropical surface temperature. 

Prof. Pielke points to some Sun et al. papers to argue that the models are overestimating the feedback.  What he fails to mention is that these papers only analyzed a small region of the planet (e.g., the Wu et al. paper looked at 5°N-5°S, 150°E-110°W, corresponding to about 2.4% of the surface area of the globe) and the “overestimate” they found was quite small. 

Thus, it is a stretch to view the Sun et al. papers as demonstrating some pathological problem with the models’ water vapor feedback, or that this contradicts my global analysis.

The upshot

Thus, we can conclude with extremely high confidence that the water vapor feedback is strong and positive (I would categorize it, in the IPCC’s parlance, as being unequivocal). And I would categorize it as very likely that models are accurately simulating this phenomenon.  While uncertainties do exist (as Prof. Pielke pointed out), those uncertainties are small (which Prof. Pielke fails to point out).  Given this, the most likely outcome of a business-as-usual emissions scenario is significant warming of several degrees Celsius.

Finally, some frequently asked questions about the water vapor feedback:

Didn’t a recent paper show that the water vapor feedback is negative?

There is a recent paper by Paltridge et al. [2009] that shows that water vapor in the tropical upper troposphere in the NCEP/NCAR reanalysis decreased over the past few decades.  I have repeated this calculation with more modern and sophisticated reanalysis data sets (ECMWF interim reanalysis and MERRA reanalysis) and this result does not hold in those data sets.  Given all of the other evidence that the water vapor feedback is positive, all of the ways that long-term trends in reanalyses can be wrong, and lack of verification in more reliable reanalysis data sets, I conclude that the Paltridge et al. result is almost certainly wrong.

Models have biases in their water vapor fields.  Doesn’t this mean their feedbacks are unreliable?

The models do indeed have biases in their predictions of the water vapor base state (it varies from model to model and regionally within a model, but is generally of order 10%) [John and Soden, 2007].  Yet they all simulate about the same water vapor feedback.  How can that be?  It turns out that the water vapor feedback is determined by the fractional change in water vapor, primarily in the tropical upper troposphere. And the models all calculate the same fractional change in water per degree of surface warming [John and Soden, 2007]. This is why they all get basically the same water vapor feedback, despite biases in the predicted base state.

Why is the tropical upper troposphere so important for the water vapor feedback?

It is the changes in water vapor in the tropical upper troposphere that plays the major role in the water vapor feedback. While photons from these water vapor molecules do not directly heat the surface, they do primarily regulate emission of energy to space.  Because the troposphere is rapidly mixed by convection at a rate much faster than radiation, the effect of changes due to radiation fluxes that are entirely internal to the troposphere (e.g., due to changes in lower tropospheric water) will be rapidly wiped out by convection and have a small net impact on surface temperature.  The tropics dominate the effect because of the smaller temperature difference between the surface and the upper troposphere in the mid-latitudes combined with smaller column abundances of water vapor there. 

Dessler, A. E., and S. C. Sherwood (2009), A matter of humidity, Science, 323, doi: 10.1126/Science.1171264, 1020-1021.

Dessler, A. E., and S. Wong (2009), Estimates of the water vapor climate feedback during the El Niño Southern Oscillation, J. Climate, 22, doi: 10.1175/2009JCLI3052.1, 6404-6412.

Dessler, A. E., P. Yang, and Z. Zhang (2008), The water-vapor climate feedback inferred from climate fluctuations, 2003-2008, Geophys. Res. Lett., 35, L20704, doi: 10.1029/2008GL035333.

Forster, P. M. D., and M. Collins (2004), Quantifying the water vapour feedback associated with post-Pinatubo global cooling, Climate Dynamics, 23, 207-214.

John, V. O., and B. J. Soden (2007), Temperature and humidity biases in global climate models and their impact on climate feedbacks, Geophys. Res. Lett., 34, L18704, doi: 10.1029/2007GL030429.

Paltridge, G., A. Arking, and M. Pook (2009), Trends in middle- and upper-level tropospheric humidity from NCEP reanalysis data, Theor. Appl. Climatol., doi: 10.1007/s00704-009-0117-x, 351-359.

Soden, B. J., R. T. Wetherald, G. L. Stenchikov, and A. Robock (2002), Global cooling after the eruption of Mount Pinatubo: A test of climate feedback by water vapor, Science, 296, 727-730.

Soden, B. J., D. L. Jackson, V. Ramaswamy, M. D. Schwarzkopf, and X. Huang (2005), The radiative signature of upper tropospheric moistening, Science, 310, 841-844.

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Guest Weblog By Leonard Ornstein On Ocean Heat Content

Leonard Ornstein has agreed to write a guest weblog on ocean heat content as a diagnostic  to assess global warming. The focus of our discussions by e-mail has been on the meaning of the term “heat in the pipeline”.  Len has provided a guest weblog previously; see “How To Quickly Lower Climate Risks, At ‘Tolerable’ Costs?”. [my reply will appear tomorrow].


Roger has invited me to post some thoughts I have on two points concerning ocean heat, about which we appear to have some small differences.

 A. Roger often suggests that the trend in global ocean heat content (GOHC) is a ‘better’ diagnostic than the trend in global mean surface temperature (GMST) for assessing what’s happening to the earth as a result of human-induced changes in the planetary environment. It’s my judgement that both diagnostics are useful – but that at present – the potential uncertainties in GOHC exceed even the large uncertainties in GMST:

 Local heat content of the ocean closely tracks (temperature (°K) x heat capacity x volume). The heat capacity of liquid ocean water varies only slightly with temperature and density/salinity. Deep ocean water, below the thermocline (DOW) makes up about 90% of the ocean volume, has a temperature of about 3°C (~ 276° K) and a salinity of about 3.5%. Therefore, although the temperature of the DOW is colder than most of the sea surface (e.g., sea surface temperatures, SSTs, range from about 18°C (~ 291°K) to 29°C (~ 302°K) from about ± 50° Latitude to the equator), it stores much more heat than the upper 200 meters or so of the thermocline. The low temperature of the DOW is generated and maintained by a quasi-steady-state process. Deep water formation originates near the two poles, by the downwelling of cold dense surface water to create and maintain the famous thermohaline circulation (THC). Most of the THC ultimately upwells in the southern oceans as the completion of the meridional overturning circulation (MOC), with a delay of more than a millennium The DOW is the most poorly explored and measured volume of the ocean. A small brief slowdown of MOC would not necessarily change the GOHC, but would tend to produce a decrease in global mean SSTs that could decrease the GMST (and visa versa). The causal connections might not be readily observed. Such phenomena as ENSO, AMO and PDO represent quasi-cyclic, moderately well-observed exchanges of near-surface waters with deeper waters. When a volume of water is moved downward, some water must move up ‘to maintain the level of the oceans’. It may move up over a very large area below the thermocline, and so be almost imperceptible, as a thermal signature, or it may appear as Ekman-pumped, wind-driven upwelling, in local coastal areas, like with La Nina. But at present, a significant portion of the heat in near-surface water could be advected into the DOW without being observed because of the sparse sampling at depths below 2 km (Argo buoys go no deeper than 2km).

 The sampling situation is the reverse for the atmosphere. The heat capacity varies with density, and therefore barometric pressure (altitude). So near-surface temperatures track a major portion of the heat content of the atmosphere.  Although we would appreciate even better sampling, the density of sampling of global surface temperatures is quite high and we’re observing a substantial portion of the atmosphere.

 For this reason,  I’m somewhat more wary of the amount of uncertainty that is associated with GOHC than is Roger.

 B. James Hansen has pointed out that “even if atmospheric composition and other climate forcings remain fixed at today’s values….additional global warming of …. ~ 0.6° C is “in the pipeline” and will occur in the future”.

 Hansen et al. (2005) Science 308:1431 – 1434.

 Roger interprets Hansen’s use of “in the pipeline” as an error in physics, because once heat has been radiatively deposited in the ocean it is “there”. 

For example, see Roger’s:

 Is There Climate Heating In “The Pipeline”?

Further Comments Regarding The Concept “Heating In The Pipeline” 

 I believe Jim and his colleagues have made their meaning quite clear, and their concept in no way represents wrong physics.

 In the opening sentences of the 2005 paper they state:

“Earth’s climate system has considerable thermal  inertia. This point is of critical importance  to policy- and decision-makers who seek to  mitigate the effects of undesirable anthropogenic  climate change. The effect of the inertia  is to delay Earth’s response to climate forcings,  i.e., changes of the planet’s energy balance that  tend to alter global temperature.”

I believe this clearly describes what he means later, by “heat in the pipeline”. On page 1432, under “Earth’s energy imbalance” he states:

“We infer from the consistency of observed and modeled planetary energy gains that the forcing  still driving climate change, i.e., the forcing  not yet responded to, averaged ~0.75 W/m2 in  the past decade and was ~0.85 T 0.15 W/m2  in 2003 (Fig. 1C). This imbalance is consistent  with the total forcing of ~1.8 W/m2  relative to that in 1880 and climate sensitivity  of ~2/3ºC per W/m2. The observed  1880 to 2003 global warming is 0.6º to
0.7ºC (11, 22), which is the full response to  nearly 1 W/m2 of forcing. Of the 1.8 W/m2  forcing, 0.85 W/m2 remains, i.e., additional  global warming of 0.85 x 0.67 ~ 0.6ºC is  “in the pipeline” and will occur in the future  even if atmospheric composition and other  climate forcings remain fixed at today’s values  (3, 4, 23).”

By “the forcing not yet responded to”  Hansen means not yet responded to by the atmosphere. Roger can fault him here for his semantics; had he added “by the atmosphere” I believe his meaning would be perfectly clear, given the opening paragraph. And it makes perfect sense with his closing “will occur in the future”, meaning after the ocean has equilibrated with the atmosphere.

 Roger emailed me:

 “Here is what Jim Hansen wrote in 2000 [

]  “The remaining global warming of 0.4 – 0.5°C that is “in the pipeline” is consistent with the present planetary energy imbalance of 0.6 ± 0.1  W/m 2….Thus observed ocean heat storage requires a planetary energy  imbalance of the same magnitude”. 


 In the 2000 quote above, I believe that it is fairly clear that “observed ocean heat storage” refers to that ocean heat that has not yet equilibrated with the atmosphere. And “a planetary imbalance of the same magnitude” means the stored heat has yet to equilibrate with the atmosphere and land surface, thus the planet is in imbalance with respect to the distribution of heat – and therefore, temperature.

 Jim has been consistent. He could have been a bit more precise with the inclusion of explicit referents, e.g., “by the atmosphere”.

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Nicola Scafetta Comments on “Solar Trends And Global Warming” by Benestad and Schmidt

On July 22 2009 I posted on the new paper on solar forcing by Lean and Rind 2009 (see). In that post, I also referred to the Benestad and Schmidt 2009 paper on solar forcing which has a conclusion at variance to that in the Lean and Rind paper.

After the publication of my post, Nicole Scafetta asked if he could present a comment (as a guest weblog) on the Benestad and Schmidt paper on my website, since it will take several months for his comment  to make it through the review process. In the interests of presenting the perspectives on the issue of solar climate forcing, Nicola’s post appears below. I also invite Benestad and Schmidt to write responses to the Scaftta contribution which I would be glad to post on my website.


Benestad and Schmidt have recently published a paper in JGR. (Benestad, R. E., and G. A. Schmidt (2009), Solar trends and global warming, J. Geophys. Res., 114, D14101, doi:10.1029/2008JD011639).

This paper criticizes the mathematical algorithms of several papers that claim that the temperature data show a significant solar signature. They conclude that such algorithms are “nonrobust” and conclude that “the most likely contribution from solar forcing a global warming is 7 ± 1% for the 20th century and is negligible for warming since 1980.”

By using the word “robust” and its derivates for 18 times, Benestad and Schmidt claim to disprove two categories of papers: those that use the multilinear regression analysis [Lean and Rind, 2008; Camp and Tung, 2007; Ingram, 2006] and those that present an alternative approach [Scafetta and West, 2005, 2006a, 2006b, 2007, 2008]. (See the references in their paper.)

Herein, I will not discuss the limitation of the multilinear regression analysis nor the limits of Benestad and Schmidt’s critique to those papers. I will briefly focus on Benestad and Schmidt’s criticism to the papers that I coauthored with Dr. West. I found Benestad and Schmidt’s claims to be extremely misleading and full of gratuitous criticism due to poor reading and understanding of the data analysis that was accomplished in our works.

Let us see some of these misleading statements and errors starting with the less serious one and ending with the most serious one:

1.  Since the abstract Benestad and Schmidt claim that they are rebutting several our papers [Scafetta and West, 2005, 2006a, 2006b, 2007, 2008]. Already the abstract is misleading. Indeed, their criticism focuses only on Scafetta and West [2005, 2006a]. The other papers used different data and mathematical methodologies.

2.  Benestad and Schmidt claim that we have not disclosed nor detailed the mathematical methodology and some parameters that we use. For example:

a) In paragraph 39  Benestad and Schmidt criticize and dismiss my paper with Willson [2009] by claiming that we “did not provide any detailed description of the method used to derive their results, and while they derived a positive minima trend for their composite, it is not clear how a positive minima trend could arise from a combination of the reconstruction of Krivova et al. [2007] and PMOD, when none of these by themselves contained such a trend).” However, the arguments are quite clear in that paper and in the additional figures that we published as supporting material. Moreover, it is not clear to me how Benestad and Schmidt  could conclude that our work is wrong if Benestad and Schmidt acknowledge that they have not understood it. Perhaps, they just needed to study it better.

b) In paragraph 41 Benestad and Schmidt claim that: “It is not clear how the lagged values were estimated by Scafetta and West [2006a]”.  However, in paragraph 9 of SW06a it is written “we adopt the same time-lags as predicted by Wigley’s [1988, Table 1] model.” So, again, Benestad and Schmidt just needed to study better the paper that they wanted to criticize.

c) In paragraph 48 Benestad and Schmidt claim that: “over the much shorter 1980-2002 period and used a global surface temperature from the Climate Research Unit, 2005 (they did not provide any reference to the data nor did they specify whether they used the combined land-sea data (HadCRUT) or land-only temperatures (CRUTEM).” However, it is evident from our work SW05 that we were referring to the combined land-sea data which is properly referred to as “global surface temperature” without any additional specification (Land or Ocean, North or South). We also indicate the webpage where the data could be downloaded.

d) In paragraph 57 Benestad and Schmidt claim that: “The analysis using Lean [2000] rather than Scafetta and West’s own solar proxy as input is shown as thick black lines.” However, in our paper SW06a it is crystal clear that we too use Lean’s TSI proxy reconstruction. In particular we were using Lean 1995 which is not very different from Lean 2000. Benestad and Schmidt apparently do not know that since 1978 Lean 1995 as well as Lean 2000 do not differ significantly from PMOD because PMOD was build  (by altering the published TSI satellite data)  by using Lean 1995 and Lean 2000 as guides. Moreover, we also merge the Lean data with ACRIM since 1978 to obtain an alternative scenario, as it is evident in all our papers.  The discontinuity problem addressed by Benestad and Schmidt in merging two independent sequences (Lean’s proxy model and the ACRIM) is not an issue because it is not possible to avoid it given the fact that there are no TSI satellite data before 1978.

3. In Paragraphs 48-50 Benestad and Schmidt try to explain one of our presumed major mathematical mistakes.  Benestad and Schmidt’s states:  “A change of 2*0.92 W/m2 between solar minimum and maximum implies a change in S of 1.84 W/m2 which amounts to 0.13% of S, and is greater than the 0.08% difference between the peak and minimum of solar cycle 21 reported by Willson [1997] and the differences between TSI levels of the solar maxima and minima seen in this study (~1.2 W/m2; Figure 6).”  Benestad and Schmidt’s are referring to our estimate of the amplitude of the solar cycle referring to the 11-year modulation that we called A7,sun = 0.92 W/m2 in SW05. Benestad and Schmidt are claiming that our estimate is nor reasonable because in their opinion according to our calculations the change of TSI between solar maximum and solar minimum had to be twice our value A7,sun , so they write 2*0.92=1.84 W/m2, and this would be far too large. However, as it is evident from our paper and in figure 4a in SW05 the value A7,sun refers to the peak-to-trough amplitude of the cycle, so it should not be multiplied by 2, as Benestad and Schmidt misunderstood. This is crystal clear in the factor ½ before the equation f(t)= ½ A sin(2pt) that we are referring to and that Benestad and Schmidt also report in their paragraph 48. It is hard to believe that two prominent scientists such as Benestad and Schmidt do not understand the meaning of a factor ½! So, again,  Benestad and Schmidt just needed to think more before writing a study that criticizes ours.

4) Finally, Benestad and Schmidt’s paper is full of misleading claims that they are reproducing our analysis. Indeed, Benestad and Schmidt’s paper is self-contradictory on this crucial issue. In paragraph 85 Benestad and Schmidt claim that theyhave repeated the analyses of Scafetta and West, together with a series of sensitivity tests to some of their arbitrary choices.”  However, in their paragraph 76 Benestad and Schmidt acknowledge: “In our emulation, we were not able to get exactly the same ratio of amplitudes, due to lack of robustness of the SW06a method and insufficient methods description.” It is quite singular that Benestad and Schmidt claim to have repeated our calculation, at the same time they acknowledge that, indeed, they did not succeed in repeating our calculation and, ironically, they blame us for their failure. It is not easy to find in the scientific literature such kind of tortuous reasoning! 

In fact, the reason why Benestad and Schmidt did not succeed in repeating our calculation is because they have misapplied the wavelet decomposition algorithm known as the maximum overlap discrete wavelet transforms (MODWT). This is crystal clear in their figures 4 where it is evident that they applied the MODWT decomposition in a cyclical periodic mode. In other words they are implicitly imposing that the temperature in 2001 is equal to the temperature in 1900, the temperature in 2002 is equal to the temperature in 1901 and so on. This is evident in their figure 4 where the decomposed blue and pink component curves in 2000 just continue in 1900 in an uninterrupted cyclical periodic mode as shown in the figure below which is obtained by plotting their figure 4 side by side with itself:

Any person expert in time series processing can teach Benestad and Schmidt that it is not appropriate to impose a cyclical periodic mode to a non stationary time series such as the temperature or TSI records that present clear upward trends from 1900 to 2000.  By applying a cyclical periodic mode Benestad and Schmidt are artificially introducing two large and opposite discontinuities in the records in 1900 and 2000, as the above figure shows in 2000. These large and artificial discontinuities at the two extremes of the time sequence disrupt completely the decomposition and force the algorithm to produce very large cycles in proximity of the two borders, as it is clear in their figure 4. This severe error is responsible for the fact that Benestad and Schmidt find unrealistic values for Z22y and Z11y that significantly differ from ours by a factor of three. In their paragraph 50 they found Z22y = 0.58 K/Wm-2, which is not realistic as they also realize later, while we found Z22y = 0.17 K/Wm-2, which is more realistic.

This same error in data processing also causes the reconstructed solar signature in their figures 5 and 7 to present a descending trend minimum in 2000 while the Sun was approaching one of its largest maxima. Compare their figures 4a (reported above), 5 and 7 with their figure 6 and compare them also with our figure 3 in SW06a and in SW08! See figure below where I compare Benestad and Schmidt’s  figures 6 and 7 and show that the results depicted in their Figure 7 are non-physical.

Because of the severe and naïve error in applying the wavelet decomposition, Benestad and Schmidt’s calculations are “robustly” flawed. I cannot but encourage Benestad and Schmidt to carefully study some book about wavelet decomposition such as the excellent work by Percival and Walden [2000] before attempting to use a complex and powerful algorithm such as the Maximum Overlap Discrete Wavelet Transform (MODWT) by just loading a pre-compiled computer R package.

There are several other gratuitous claims and errors in Benestad and Schmidt’s paper. However, the above is sufficient for this fast reply. I just wonder why the referees of that paper did not check Benestad and Schmidt’s numerous misleading statements and errors. It would be sad if the reason is because somebody is mistaking a scientific theory such as the “anthropogenic global warming theory” for an ideology that should be defended at all costs.

Nicola Scafetta, Physics Department, Duke University

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Announcement Of Second Edition “The Simple Science of Flight: From Insects to Jumbo Jets (Revised and Expanded Edition)” by Henk Tennekes

Henk Tennekes has a second edition of his book, and I am pleased to announce it on my weblog. Following the announcement, Henk has also provide a review of another book that he has completed.

“The Simple Science of Flight: From Insects to Jumbo Jets (Revised and Expanded Edition)” by Henk Tennekes

From the smallest gnat to the largest aircraft, all things that fly obey the same aerodynamic principles. In The Simple Science of Flight, Henk Tennekes investigates just how machines and creatures fly: what size wings they need, how much energy is required for their journeys, how they cross deserts and oceans, how they take off, climb, and soar. Fascinated by the similarities between nature and technology, Tennekes offers an introduction to flight that teaches by association. Swans and Boeings differ in numerous ways, but they follow the same aerodynamic principles. Biological evolution and its technical counterpart exhibit exciting parallels. What makes some airplanes successful and others misfits? Why does the Boeing 747 endure but the Concorde now seem a fluke? Tennekes explains the science of flight through comparisons, examples, equations, and anecdotes.

The new edition of this popular book has been thoroughly revised and much expanded. Highlights of the new material include a description of the incredible performance of bar-tailed godwits (7,000 miles nonstop from Alaska to New Zealand), an analysis of the convergence of modern jetliners (from both Boeing and Airbus), a discussion of the metabolization of energy featuring Lance Armstrong, a novel treatment of the aerodynamics of drag and trailing vortices, and an emphasis throughout on evolution, in nature and in engineering. Tennekes draws on new evidence on bird migration, new wind-tunnel studies, and data on new airliners. And his analysis of the relative efficiency of planes, trains, and automobiles is newly relevant. (On a cost-per-seat scale, a 747 is more efficient than a passenger car.)

About the Author
Henk Tennekes is Director of Research Emeritus at the Royal Netherlands Meteorological Institute, Emeritus Professor of Meteorology at the Free University (VU) in Amsterdam, and Emeritus Professor of Aerospace Engineering at Pennsylvania State University. He is the coauthor of A First Course in Turbulence (MIT Press, 1972).

“This was a great little book when it came out in its original edition; this new version is even better, as it contains both Henk’s homage to his favorite flying machine (Boeing 747) and explanations based on some of the unexpected results of recent experiments with bird flight (including a phenomenal gliding jackdaw). Read it, then watch the birds and planes, and then dip into it again and again.”
Vaclav Smil, University of Manitoba, and author of Global Catastrophes and Trends

One gets a fine sense of how so much of aircraft design-whether by humans or by evolution-depends on size and mission. This new version of The Simple Science of Flight broadens the enlightenment that so many of us found appealing in its predecessor. It yields even more of that satisfying ‘now I understand what’s happening’ rather than the usual ‘how brilliant those designers must be.’ And I know of no book that derives such an awesome wealth of insight from such simple quantification. Beyond being informative, it provides pleasant reading-for any one who travels by air, watches animals fly, or dreams of learning to fly.”
Steven Vogel, James B. Duke Professor, Emeritus, Duke University

Review By Henk Tennekes

Alexander’s Jumbo Jets

Alexander, David E. 2009. Why Don’t Jumbo Jets Flap Their Wings? Rutgers University Press. ISBN 978-0-8135-4479-3, hardback, 278 pp, figures. Price 28 euro.

David Alexander is the author of Nature’s Flyers (2002), a deservedly popular introductory biology text on flying insects, bats, and birds. Rutgers University Press recently released Alexander’s second book, Why Don’t Jumbo Jets Flap Their Wings? The new book is written for the general public, not primarily for professional  biologists and engineers. “Science writing at its best,” says professor Sankar Chatterjee of Texas Tech, and I agree. This book is intended for birdwatchers who, like me, are fascinated by everything that flies, natural or technical.

In ten easygoing and enjoyable chapters, focussed on the differences between flying animals and airplanes, Alexander deals successively with evolution, lift, power, manoeuverability, the need for tail surfaces, flight instruments, soaring, hovering, aerial combat, and ornithopters. One major point of divergence: muscles excel in back-and-forth motion such as wing flapping, aircraft engines base their functionality on rotary motion. As far as manoeuverability is concerned, the sophisticated interaction between their nervous system and their flying apparatus that insects, birds, and bats are capable of is a source of envy for pilots and aircraft designers. Bats have no need for tails because their nervous systems are so well integrated. The chapter on predation and aerial combat is a real treat. I knew of course that Eleanora’s falcon feeds on migrating passerines during its breeding season, but I didn’t know that the greater noctule bat does so too, taking advantage of the fact that most passerines are nocturnal migrants. And I was thrilled to learn that some insect-hawking bats “use their wings as tennis rackets, deftly tapping an insect to deflect it into their mouths.” Alexander deals at length with ornithopters. Considering the title of his book, he has to. Flapping wings are not the way to go when size and weight become too large. A jumbo jet does not flap its wings because the hinges, engines, and linkage systems  needed to power it would be far too heavy. Also, flapping flight is like a roller-coaster ride, because the upstroke of the wings delivers little or no lift, so that the body falls until lifted again by the downstroke. All passengers riding a flapping jumbo jet would be airsick for the entire ride. On the other hand, flapping is the preferred solution when sizes are small. Miniature rotary engines cannot compete in that technological niche.

Alexander compares the slow evolution of flight in Nature with the rapid evolution of flight in human technology. “Natural selection works on a time scale of hundreds of thousands or even millions of years. When a one-in-a-million beneficial change does occur, it tends to spread through the species. Changes that might take hundreds of thousands of years of animal evolution can take place in less than a decade of technological development.” He recognizes other differences, too. Animals co-evolve with their environment, human technology often changes the environment. Wheels are unsuitable in rough terrain; the worldwide success of automobiles is due in no small part to the concurrent evolution of highway systems. I feel Alexander tends to underestimate how often technological breakthroughs resemble random genetic mutations in Nature, which, as he correctly states, are “almost always detrimental.” Airplane encyclopedias are filled with planes that can fairly be labeled as evolutionary misfits, as designs that did not live up to their designers’ dreams and disappeared within ten or twenty years. Some, like Howard Hughes’ Spruce Goose made just one brief hop. Others, like the supersonic Concorde, are evolutionary mutants, products of the overheated preoccupations of their designers and sponsors. Even the ultimate aeronautical dream, human-powered flight, lovingly described in Alexander’s book, did not last long. Planes powered by human athletes are unfit for everyday use; they are in fact extinct now.

In the epilogue, Alexander returns to the central theme of his book: how flying animals differ from flying machines. “In the end, what truly sets birds apart from airplanes is versatility versus efficiency. Engineers design airplanes to carry out particular tasks, so airplanes tend to be quite specialized. A Boeing 747 can haul huge loads of passengers over enormous distances, but that is basically all it can do. Animals cannot afford to be so specialized.” I agree, but not without some reservations. Albatrosses are specialized in so-called dynamic soaring in wide-open environments with a uniform wind regime, bar-tailed godwits perform 11,000 km nonstop flights across the Pacific Ocean but have a barely adequate immune system, bats use very sophisticated echo location equipment that is useless in daylight because insects can easily take evasive action, penguins use their wings exclusively for under-water swimming, and so on. And some kinds of airplanes, like the Piper Cub and the Cessna 172, are supreme generalists, much like sparrows and starlings. In fact, the early success of the Piper Cub was based on its usefulness for the US Army: it could land and take off most anywhere, rough terrain or not. The task of evaluating the differences between biological evolution and its technological counterpart is far from being finished, but in Jumbo Jets Alexander makes a giant step in the right direction.

Henk Tennekes


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Comments By Mike Smith of My Weblog “Debate Question For Professor Steve Schneider and Colleagues”

In response to my weblog Debate Question For Professor Steve Schneider and Colleagues Mike Smith and I have exhanged e-mails on these three hypotheses. With Mike’s permission, I have extracted the text from our e-mails and reproduced with minor edits below. 

Mike Smith is CEO of WeatherData Services, Inc., An AccuWeather Company.  Smith is a Fellow of the American Meteorological Society and a Certified Consulting Meteorologist.   He is a recipient of the American Meteorological Society’s Award for Outstanding Contributions to Applied Meteorology and WeatherData has received the Society’s Award for Outstanding Services to Meteorology by a Corporation.

Mike’s comments are in regular text, and mine are italicized.

Mike Smith’s first e-mail

Hi Roger,

I have been reading the exchange regarding the SF articles.  There is something I would like to circle back on.  You say, “only one of these is true” if I am reading you correctly,

1. The human influence is minimal and natural variations dominate
climate variations on all time scale;

2. While natural variations are important, the human influence is significant and involves a diverse range of first-order climate forcings (including, but not limited to the human input of CO2);

3. The human influence is dominated by the emissions into the atmosphere
of greenhouse gases, particularly carbon dioxide.

I do agree with you that, 30 years from now, when we know much more, likely only one of the three contentions will be the “most correct” answer.  But, I don’t believe we are at that point.

Given our current knowledge, why can’t the most likely answer be, “Somewhere between 1 and 2”?  I believe the current state-of-the- science is telling us #3 is not correct.  I agree with you that there are many human forcings that influence climate, but it is not clear to me that the Wichita heat island (which I have informally documented) or the Reno heat island (see Anthony Watts’ website) have much influence on world climate (i.e., would the climate in Rome or Honolulu be different if the RNO and ICT heat islands did not exist?).  Does the deforestation in Brazil influence the climate in South Africa? IF the answer is “no”, then on a planetary scale #1 is the correct answer.

My best educated guess is the most correct answer is about 70%  #1 and 30%  #2.  I realize you believe this answer would be incorrect. Please tell me where you think I am off base.    If you wish to publish this question and your answer, it would be fine.  I believe we gain with open debate.

Thanks and best wishes,


Roger A. Pielke Sr. Reply and Mike Smith’s further response

Hi Mike

 Thank you for your feedback. I agree that the three hypotheses need to be addressed with respect to scale. Our research (and that of others) indicates that there are well defined effects of land use/land cover change, the human input of aerosols including both changes in atmospheric concentrations and deposition, and biogeochemical effects due to added trace gases including CO2 on local and regional scales. From your e mail, it seems we both agree on this. If true, the first hypothesis is rejected for these spatial scales (as is the third hypothesis).

Mike Smith Response – I agree with this.

Roger A. Pielke Sr’s Comment

With respect to the global scale, the proper metrics include changes in atmospheric concentrations, alterations in circulation patterns, etc. There is no question that added CO2 is from human activities….

Mike Smith Response – I agree

Roger A. Pielke Sr’s Comment

……and this has altered the global average concentration of this gas.

Mike Smith Response

I agree, but I’m not sure we fully know the extent.  There is some evidence for natural variation in CO2 concentrations (i.e., do changes in ocean heat content significantly vary their contribution to atmospheric CO2 concentration?).

Roger A. Pielke Sr’s Comment

In terms of effects on circulations, there are now a number of papers that illustrate with models that there are changes due to several of the human climate forcings listed above.

Mike Smith Response

Yes, but are the models sufficiently robust to make this determination at this time?

Roger A. Pielke Sr’s Comment

I have concluded the first hypothesis is also rejected on the global scale, but agree this needs further investigation (models by themselves, of course, cannot be used to test hypotheses).

Mike Smith Response

I see your point and you may well be proven correct.  However, we seem to be in the early stages of testing the ‘natural variations’ hypothesis.  I am referring to the ‘blank sun.’  The very low levels of sunspot activity the last two years — which seems to be continuing — and which I would call a “natural” variation, may give us a chance to sort out natural from manmade forcings.  The IPCC has (I’m paraphrasing) rejected the hypothesis that variations in the sun’s output have a significant effect on earth’s climate.
The falling temperature trend since 1998 (and, at best, lack of warming in the oceans about which you have written extensively) that seems to parallel the fall in solar output will give us a chance to test several of these hypothesis, especially in view of the record (for modern times) levels of CO2 concentration.  We seem to be getting close to the point where the IPPC’s hypothesis (CO2 is the dominant forcing) is rejected if temperatures and ocean heat content continue to fall while CO2 levels continue to rise.

Other credentialed climate scientists are invited to e-mail me their comments also, and, if appropriate, they can also be posted as a guest weblog.

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Have Changes In Ocean Heat Falsified The Global Warming Hypothesis? – A Guest Weblog by William DiPuccio

Climate Science encourages guest weblogs from all perspectives of the climate science issue. Following is a guest weblog by William DiPuccio, who, although not a published climate scientist,  has provided a view on the global warming discussion which is worth reading.

Guest Weblog By William DiPuccio

The Global Warming Hypothesis

Albert Einstein once said, “No amount of experimentation can ever prove me right; a single experiment can prove me wrong.”  Einstein’s words express a foundational principle of science intoned by the logician, Karl Popper:  Falsifiability.  In order to verify a hypothesis there must be a test by which it can be proved false.  A thousand observations may appear to verify a hypothesis, but one critical failure could result in its demise.  The history of science is littered with such examples.

A hypothesis that cannot be falsified by empirical observations, is not science.  The current hypothesis on anthropogenic global warming (AGW), presented by the U.N.’s Intergovernmental Panel on Climate Change (IPCC), is no exception to this principle.  Indeed, it is the job of scientists to expose the weaknesses of this hypothesis as it undergoes peer review.  This paper will examine one key criterion for falsification: ocean heat.

Ocean heat plays a crucial role in the AGW hypothesis, which maintains that climate change is dominated by human-added, well-mixed green house gasses (GHG).  IR radiation that is absorbed and re-emitted by these gases, particularly CO2, is said to be amplified by positive feedback from clouds and water vapor.  This process results in a gradual accumulation of heat throughout the climate system, which includes the atmosphere, cryosphere, biosphere, lithosphere, and, most importantly, the hydrosphere.  The increase in retained heat is projected to result in rising atmospheric temperatures of 2-6ºC by the year 2100. 

In 2005 James Hansen, Josh Willis, and Gavin Schmidt of NASA coauthored a significant article (in collaboration with twelve other scientists), on the “Earth’s Energy Imbalance:  Confirmation and Implications” (Science, 3 June 2005, 1431-35).  This paper affirmed the critical role of ocean heat as a robust metric for AGW.  “Confirmation of the planetary energy imbalance,” they maintained, “can be obtained by measuring the heat content of the ocean, which must be the principal reservoir for excess energy” (1432). 

Monotonic Heating.  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. 

A reversal of sufficient magnitude could conceivably reset the counter back to “zero” (i.e., the initial point from which a current set of measurements began).  If this were to take place, the process of heat accumulation would have to start again.  In either case, a suspension or reversal of heat accumulation (excepting major volcanic eruptions) would mean that we are dealing with a form of cyclical rather than monotonic heating. 

Most scientists who oppose the conclusions of the IPCC have been outspoken in their advocacy of cyclical heating and cooling caused primarily by natural processes, and modified by long-term human climate forcings such as land use change and aerosols.  These natural forcings include ocean cycles (PDO, AMO), solar cycles (sunspots, total irradiance), and more speculative causes such as orbital oscillations, and cosmic rays.

Temperature is not Heat! 

Despite a consensus among scientists on the use of ocean heat as a robust metric for AGW, near-surface air temperature (referred to as “surface temperature”) is generally employed to gauge global warming.  The media and popular culture have certainly equated the two.  But this equation is not simply the product of a naïve misunderstanding.  NASA’s Goddard Institute for Space Studies (GISS), directed by James Hansen, and the British Hadley Centre for Climate Change, have consistently promoted the use of surface temperature as a metric for global warming.  The highly publicized, monthly global surface temperature has become an icon of the AGW projections made by the IPCC. 

However, 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.

Hype generated by scientists and institutions over short-term changes in global temperature (up or down) has diverted us from the real issue:  heat accumulation.  Heat is not the same as temperature.  Two liters of boiling water contain twice as much heat as one liter of boiling water even though the water in both vessels is the same temperature.  The larger container has more thermal mass which means it takes longer to heat and cool.   

Temperature measures the average kinetic energy of molecular motion at a specific point.  But it does not measure the total kinetic energy of all the molecules in a substance.  In the example above, there is twice as much heat in 2 liters of boiling water because there is twice as much kinetic energy.  On average, the molecules in both vessels are moving at the same speed, but the larger container has twice as many molecules.

Temperature may vary from point to point in a moving fluid such as the atmosphere or ocean, but its heat remains constant so long as energy is not added or removed from the system.  Consequently, heat-not temperature-is the only sound metric for monitoring the total energy of the climate system.  Since heat is a function of both mass and energy, it is normally measured in Joules per kilogram (or calories per gram): 

Q = mc∆T

Where Q is heat (Joules)

m is mass (kg)

c is the specific heat constant of the substance (J/kg/°C)

∆T is the change in temperature (°C)

The Thermal Mass of the Oceans

Water is a more appropriate metric for heat accumulation than air because of its ability to store heat.  For this reason, it is also a more robust metric for assessing global warming and cooling.  Seawater has a much higher mass than air (1030 kg/m3 vs. 1.20 kg/m3at 20ºC), and a higher specific heat (4.18 kJ/kg/°C vs. 1.01 kJ/kg/°C for air at 23°C and 41% humidity).  One kilogram of water can retain 4.18x the heat of an equivalent mass of air.  This amounts to a thermal mass which is nearly 3558x that of air per unit volume.

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!  Considering the enormous depth and global surface area of the ocean (70.5%), it is apparent that its heat capacity is greater than the atmosphere by many orders of magnitude.  Consequently, as Hansen, et. al. have concluded, the ocean must be regarded as the main reservoir of atmospheric heat and the primary driver of climate fluctuations.

 Heat accumulating in the climate system can be determined by profiling ocean temperature, and from precise measurements of sea surface height as they relate to thermal expansion and contraction of ocean water.  These measurements are now possible on a global scale with the ARGO buoy array and from satellite measurements of ocean surface heights.  ARGO consists of a world-wide network of over 3000 free-drifting platforms that measure temperature and salinity in the upper 2000m of ocean.  The robotic floats rise to the surface every 10 days and transmit data to a satellite which also determines their location. 

Pielke’s Litmus Test

In 2007 Roger Pielke, Sr. suggested that ocean heat should be used not just to monitor the energy imbalance in the climate system, but as a “litmus test” for falsifying the IPCC’s AGW hypothesis (Pielke, “A Litmus Test…”,, April 4, 2007).  Dr. Pielke is a Senior Research Scientist in CIRES (Cooperative Institute for Research in Environmental Sciences), at the University of Colorado in Boulder, and Professor Emeritus of the Department of Atmospheric Science, Colorado State University, Fort Collins.  One of the world’s foremost atmospheric scientists, he has published nearly 350 papers in peer-reviewed journals, 50 chapters in books, and co-edited 9 books. 

Pielke’s test compares the net anthropogenic radiative forcing projected by GISS computer models (Hansen, Willis, Schmidt et al.) with actual ocean heat as measured by the ARGO array.  To calculate the annual projected heat accumulation in the climate system or oceans, radiative forcing (Watts/m2) must be converted to Joules (Watt seconds) and multiplied by the total surface area of the oceans or earth:

      [#1]  Qannum = (Ri Pyear Aearth) .80

 or, [#2]  Qannum = (Ri Pyear Aocean) .85 

Where Qannum is the annual heat accumulation in Joules

Ri is the mean global anthropogenic radiative imbalance in W/m2

P is the period of time in seconds/year (31,557,600)

Aocean is the total surface area of the oceans in m2 (3.61132 x 1014)

 Aearth is the total surface area of the earth in m2 (5.10072 x 1014)

.80 & .85 are reductions for isolating upper ocean heat (see below)

Radiative Imbalance.  The IPCC and GISS calculate the global mean net anthropogenic radiative forcing at ~1.6 W/m2(-1.0, +.8), (see, 2007 IPCC Fourth Assessment Summary for Policy Makers, figure SPM.2 and Hanson, Willis, Schmidt et al., page 1434, Table 1).  This is the effective total of all anthropogenic forcings on the climate system.  Projected heat accumulation is not calculated from this number, but from the mean global anthropogenic radiative imbalance (Ri).  According to Hanson, Willis, Schmidt et al., the imbalance represents that fraction of the total net anthropogenic forcing which the climate system has not yet responded to due to thermal lag (caused primarily by the oceans).  The assumption is that since the earth has warmed, a certain amount of energy is required to maintain the current global temperature.  Continuing absorption will cause global temperatures to rise further until a new balance is reached. 

Physically, the climate system responds to the entire 1.6 W/m2 forcing, not just a portion of it.  But while energy is being absorbed, it is also being lost by radiation.  The radiative imbalance is better described as the difference between the global mean net anthropogenic radiative forcing and its associated radiative loss.  The global radiative imbalance of .75 W/m2 (shown below) would mean that the earth system is radiating .85 W/m2 in response to 1.6 W/m2of total forcing (1.6 – .85 = .75).  For a more detailed discussion of radiative equilibrium see, Pielke Sr., R.A., 2003: “Heat storage within the Earth system.”  Bulletin of the American  Meteorological Society, 84, 331-335.

Projected Ocean Heat.  Since observed heat accumulation is derived from measurements in the upper 700m-750m of the ocean, an “apples to apples” comparison with model projections requires some adjustments.  Eq. #1, used by the GISS model, assumes that nearly all of the energy from anthropogenic radiative forcing is eventually absorbed by the oceans (80%-90% according to Willis, U.S. CLIVAR, 1, citing Levitus, et. al.).  Based on modeling by Hansen, Willis, Schmidt, et. al., (page 1432) upper ocean heat is thought to comprise 80% of the total as shown in the illustration.  So, the calculated heat must be multiplied by 0.8 to subtract deep ocean heat (below 750m) and heat storage by the atmosphere, land, and cryosphere (see discussion on deep ocean heat and melting ice below).

Another method for calculating heat accumulation is shown in Eq. #2.  This method assumes that only 71% (i.e., the fraction of the earth covered by oceans) of the energy from anthropogenic radiative forcing is absorbed by the oceans.  Hence, the net global anthropogenic radiative flux is scaled to ocean surface area.  To compare to upper ocean measurements, deep ocean heat must be subtracted by multiplying the results by ~0.85.  As shown in the illustration above, the deep ocean absorbs about 0.11 W/m2 of the total ocean flux of 0.71 W/m2 (estimates vary, see discussion on deep ocean heat, below).  Since this equation is not used by climate models, it is not included in the following tables.  But, it is displayed in the graph below as a possible lower limit of projected heat accumulation.

In his blog, “Update On A Comparison Of Upper Ocean Heat Content Changes With The GISS Model Predictions” (, Feb. 9, 2009), Pielke projects heat accumulation based on an upper ocean mean net anthropogenic radiative imbalance of  0.6 W/m2as shown below (see Hanson, Willis, Schmidt et al., 1432).  This is only a slight variance from his 2007 blog and affords the best opportunity for the GISS models to agree with observed data.  A failure to meet this benchmark would be a robust demonstration of systemic problems.

Observed Ocean Heat.  A comparison of these projections to observed data is shown below.  Despite expectations of warming, temperature measurements of the upper 700m of the ocean from the ARGO array show no increase from 2003 through 2008.  Willis calculates a net loss of -0.12 (±0.35) x 1022Joules per year (Pielke, Physics Today,55) from mid-2003 to the end of 2008 (Dr. Pielke received permission from Josh Willis to extend the ARGO data to the end of 2008). 

According to a recent analysis of ARGO data by Craig Loehle, senior scientist at the Illinois-based National Council for Air and Stream Improvement, the loss is -0.35 (±0.2) x 1022Joules per year from mid-2003 to the end of 2007 (see Loehle, 2009: “Cooling of the global ocean since 2003.″ Energy & Environment, Vol. 20, No. 1&2, 101-104(4)).  Loehle used a more complex method than Willis to calculate this trend, enabling him to reduce the margin of error.

My calculations for observed global heat, shown below, are based on observed upper ocean heat.  Since upper ocean heat is calculated to be 80% of the global total (Eq. #1), observed global heat equals approximately 125% (1/0.8) of the observed upper ocean heat.

Model Projected Global Heat Accumulation(Joules  x 1022) Observed Global Heat Accumulation (Joules  x 1022) Projected Upper Ocean Heat Accumulation(Joules  x 1022) Observed Upper Ocean Heat Accumulation (Joules  x 1022)
GISS 7.26 -0.83 Willis (5.5 yr)-1.98 Loehle (4.5 yr) 5.82 -0.66 Willis (5.5 yr)-1.58 Loehle (4.5 yr)

 Heat Deficit.  The graph below shows the increasing deficit of upper ocean heat from 2003 through 2008 based on GISS projections by Hansen, Willis, Schmidt, et. al.  Actual heat accumulation is plotted from observed data (using ARGO) and shows the overall linear trend (after Willis and Loehle).  Seasonal fluctuations and error bars are not shown.

The projection displays a range representing the two ways of calculating heat accumulation discussed above.  The upper limit assumes that virtually all of the energy from anthropogenic radiative forcing is eventually absorbed by the oceans (Eq. #1).  The lower limit scales the total radiative imbalance to the surface area of the oceans (Eq. #2).  The upper limit represents the actual GISS model projection.


 The 5.5 year accumulated heat deficit for GISS model projections (red line) ranges from 6.48 x 1022 Joules (using Willis) to 7.92 x 1022 Joules (Loehle, extrapolated to the end of 2008).  Pielke is more conservative in his calculations, given the substantial margin of error in Willis’ data (±0.35).  Accordingly, he assumes zero heat accumulation for the full 6 year period (2003-2008), yielding a deficit of 5.88 x 1022Joules (Pielke, “Update…”).  Loehle’s work, which was not yet known to Pielke in February of 2009, has a much smaller margin of error (±0.2).

ARGO DataAnalyzed by Willis ARGO DataAnalyzed by Loehle (extrapolated to end of 2008) Pielke(based on Willis)
-6.48 x 1022 Joules -7.92 x 1022 Joules -5.39 x 1022 Joules(-5.88 for 6 full years )

 These figures reveal a robust failure on the part of the GISS model to project warming.   The heat deficit shows that from 2003-2008 there was no positive radiative imbalance caused by anthropogenic forcing, despite increasing levels of CO2.  Indeed, the radiative imbalance was negative, meaning the earth was losing slightly more energy than it absorbed.  Solving for Riin Eq. #1, the average annual upper ocean radiative imbalance ranged from a statistically insignificant -.07 W/m2 (using Willis) to -.22 W/m2(using Loehle).

As Pielke points out (“Update…”), in order for the GISS model to verify by the end of 2012 (i.e., one decade of measurements), the annual radiative imbalance would have to increase to 1.50 W/m2 for the upper ocean which is 2.5x higher than the .6 W/m2projected by Hansen, Willis, Schmidt, et. al. (1432).  This corresponds to an annual average accumulation of 2.45 x 1022 Joules in the upper ocean, or a 4 year total of 9.8 x 1022 Joules. 

Using Loehle’s deficit, the numbers are even more remarkable.  Assuming that heating resumes for the next 4.5 years (2009 to mid 2013), the annual average accumulation of heat would need to be 2.73 x 1022 Joules in the upper ocean, for a 4.5 year total of 12.29 x 1022 Joules.  The derived radiative imbalance for the upper ocean would increase to 1.7 W/m2, or nearly 3x higher than the projected imbalance.

Improbable Explanations for the Failure of Heat Accumulation

Hidden Heat.  A few explanations have been proposed for the change in ocean heat.  One popular suggestion is that there is “hidden” or “unrealized” heat in the climate system.  This heat is being “masked” by the current cooling and will “return with a vengeance” once the cooling abates. 

This explanation reveals a fundamental ignorance of thermodynamics and it is disappointing to see scientists suggest it.  Since the oceans are the primary reservoir of atmospheric heat, there is no need to account for lag time involved with heat transfer.  By using ocean heat as a metric, we can quantify nearly all of the energy that drives the climate system at any given moment.  So, if there is still heat “in the pipeline”, where is it?  The deficit of heat after nearly 6 years of cooling is now enormous.  Heat can be transferred, but it cannot hide.  Without a credible explanation of heat transfer, the idea of unrealized heat is nothing more than an evasion.

Deep Ocean Heat.  Is it possible that “lost” heat has been transferred to the deep ocean-below the 700 meter limit of our measurements?  This appears unlikely.  According to Hansen, Willis, Schmidt et al., model simulations of ocean heat flow show that 85% of heat storage occurs above 750 m on average (with the range stretching from 78 to 91%) (1432).  Moreover, if there is “buried” heat, widespread diffusion and mixing with bottom waters may render it statistically irrelevant in terms of its impact on climate.

The absence of heat accumulation in deep water is corroborated by a recent study of ocean mass and altimetric sea level by Cazenave, et. al.  Deep water heat should produce thermal expansion, causing sea level to rise.  Instead, steric sea level (which measures thermal expansion plus salinity effects) peaked near the end of 2005, then began to decline nearly steadily.  It appears that ocean volume has actually contracted slightly.

Melting Ice.  Another possibility is that meltwater from glaciers, sea ice, and ice caps is offsetting heat accumulation.  Perhaps the ocean temperature has plateaued as the ice undergoes a phase change from solid to liquid (heat of fusion). 

This explanation sounds plausible at first, but it is not supported by observed data or best estimates.  In a 2001 paper published in Science, Levitus, et. al. calculates that the absorption of heat due to melting ice amounts to only 6.85% of the total increase in ocean heat during the 41 year period from about 1955 to 1996:

Observed increase in ocean heat (1955-1996) = 1.82 x 1023 J

Observed/estimated heat of fusion (1950’s-1990’s) = 1.247 x 1022 J

This work is quoted by Hansen, Willis, Schmidt, et. al. and further supported by their calculations (1432), which are even more conservative.  Given a planetary energy imbalance of approximately +0.75 W/m2, their simulations show that only 5.3% (0.04 W/m2) of the energy is used to warm the atmosphere, the land, and melt ice.  The balance of energy is absorbed by the ocean above 750 m (~0.6 W/m2), with a small amount of energy penetrating below 750 m (~0.11 W/m2).

The absorption of heat by melting ice is so small that even if it were to quadruple, the impact on ocean heat would be miniscule. 

Cold Biasing.  The ARGO array does not provide total geographic coverage.  Ocean areas beneath ice are not measured.  However, this would have a relatively small impact on total ocean heat since it comprises less than 7% of the ocean.  As mentioned above, quality controlled water temperature below 700m is not available, though the floats operate to a depth of 2000m.  Above 700m, the analysis performed by Willis includes a quality check of raw data which revealed a cold bias in some instruments.  This bias was removed (Willis, CLIVAR, 1). 

Loehle warns that the complexities of instrumental drift could conceivably create such artifacts (Loehle, 101), but concludes that his analysis is consistent with satellite and surface data which show no warming for the same period (e.g., see Douglass, D.H., J.R. Christy, 2009: “Limits on CO2 climate forcing from recent temperature data of Earth.” Energy & Environment, Vol. 20, No. 1&2, 178-189 (13)). So it is unlikely that cold biasing could account for the observed changes in ocean heat. 

In brief, we know of no mechanism by which vast amounts of “missing” heat can be hidden, transferred, or absorbed within the earth’s system.  The only reasonable conclusion-call it a null hypothesis-is that heat is no longer accumulating in the climate system and there is no longer a radiative imbalance caused by anthropogenic forcing.  This not only demonstrates that the IPCC models are failing to accurately predict global warming, but also presents a serious challenge to the integrity of the AGW hypothesis.

Analysis and Conclusion

Though other criteria, such as climate sensitivity (Spencer, Lindzen), can be used to test the AGW hypothesis, ocean heat has one main advantage:  Simplicity.  While work on climate sensitivity certainly needs to continue, it requires more complex observations and hypotheses making verification more difficult.  Ocean heat touches on the very core of the AGW hypothesis:  When all is said and done, if the climate system is not accumulating heat, the hypothesis is invalid.

Writing in 2005, Hansen, Willis, Schmidt et al. suggested that GISS model projections had been verified by a solid decade of increasing  ocean heat (1993 to 2003).  This was regarded as further confirmation the IPCC’s AGW hypothesis. Their expectation was that the earth’s climate system would continue accumulating heat more or less monotonically.  Now that heat accumulation has stopped (and perhaps even reversed), the tables have turned.  The same criteria used to support their hypothesis, is now being used to falsify it.

It is evident that the AGW hypothesis, as it now stands, is either false or fundamentally inadequate.  One may argue that projections for global warming are measured in decades rather than months or years, so not enough time has elapsed to falsify this hypothesis.  This would be true if it were not for the enormous deficit of heat we have observed.  In other words, no matter how much time has elapsed, if a projection misses its target by such a large magnitude (6x to 8x), we can safely assume that it is either false or seriously flawed.

Assuming the hypothesis is not false, its proponents must now address the failure to skillfully project heat accumulation.  Theories pass through stages of development as they are tested against observations.  It is possible that the AGW hypothesis is not false, but merely oversimplified.  Nevertheless, any refinements must include causal mechanisms which are testable and falsifiable.  Arm waiving and ad hoc explanations (such as large margins of error) are not sufficient. 

One possibility for the breakdown may relate back to climate sensitivity.  It is assumed that most feedbacks are positive, amplifying the slight warming (.3º-1.2ºC) caused by CO2.  This may only be partially correct.  Perhaps these feedbacks undergo quasi-cyclical changes in tandem with natural fluctuations in climate.  The net result might be a more punctuated increase in heat accumulation with possible reversals, rather than a monotonic increase.  The outcome would be a much slower rate of warming than currently projected.  This would make it difficult to isolate and quantify anthropogenic forcing against the background noise of natural climate signals. 

On the other hand, the current lapse in heat accumulation demonstrates a complete failure of the AGW hypothesis to account for natural climate variability, especially as it relates to ocean cycles (PDO, AMO, etc.).  If anthropogenic forcing from GHG can be overwhelmed by natural fluctuations (which themselves are not fully understood), or even by other types of anthropogenic forcing, then it is not unreasonable to conclude that the IPCC models have little or no skill in projecting global and regional climate change on a multi-decadal scale.  Dire warnings about “runaway warming” and climate “tipping points” cannot be taken seriously.  A complete rejection of the hypothesis, in its current form, would certainly be warranted if the ocean continues to cool (or fails to warm) for the next few years.

Whether the anthropogenic global warning hypothesis is invalid or merely incomplete, the time has come for serious debate and reanalysis.  Since Dr. Pielke first published his challenge in 2007, no critical attempts have been made to explain these failed projections.  His blogs have been greeted by the chirping of crickets.  In the mean time costly political agendas focused on carbon mitigation continue to move forward, oblivious to recent empirical evidence.  Open and honest debate has been marginalized by appeals to consensus.  But as history has often shown, consensus is the last refuge of poor science.


Cazenave, A., et al., 2008: “Sea level budget over 2003-2008: A reevaluation from GRACE space gravimetry, satellite altimetry and Argo,” Glob. Planet. Change, doi:10.1016/j.gloplacha.2008.10.004.

Douglass, D.H., J.R. Christy, 2009: “Limits on CO2 climate forcing from recent temperature data of Earth.” Energy & Environment, Vol. 20, No. 1&2, 178-189 (13).

Hansen, J., L. Nazarenko, R. Ruedy, Mki. Sato, J. Willis, A. Del Genio, D. Koch, A. Lacis, K. Lo, S. Menon, T. Novakov, Ju. Perlwitz, G. Russell, G.A. Schmidt, and N. Tausnev, 2005: “Earth’s energy imbalance: Confirmation and implications.Science, 308, 1431-1435.

IPCC, 2007: Summary for Policymakers. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change[Solomon, S., D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M.Tignor and H.L. Miller (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.  See

Levitus, S., J.I. Antonov, J. Wang, T.L. Delworth, K.W. Dixon, and A.J. Broccoli, 2001: “Anthropogenic warming of Earth’s climate system.” Science, 292, 267-268.

Loehle, Craig, 2009:  “Cooling of the global ocean since 2003.″ Energy & Environment, Vol. 20, No. 1&2, 101-104(4).

 Pielke Sr., R.A., 2008: “A broader view of the role of humans in the climate system.” Physics Today, 61, Vol. 11, 54-55.

Pielke Sr., R.A., 2003: “Heat storage within the Earth system.”  Bulletin of the American Meteorological Society, 84, 331-335.

Pielke Sr., R.A., “A Litmus Test For Global Warming – A Much Overdue Requirement“,, April 4, 2007.

Pielke Sr., R.A., “Update On A Comparison Of Upper Ocean Heat Content Changes With The GISS Model Predictions“,, Feb. 9, 2009.

Willis, J.K., D. Roemmich, and B. Cornuelle, 2004: “Interannual variability in upper ocean heat content, temperature, and thermosteric expansion on global scales.”  J. Geophys. Res., 109, C12036.

Willis, J. K., 2008: “Is it Me, or Did the Oceans Cool?”, U.S. CLIVAR, Sept, 2008, Vol. 6, No. 2.

* William DiPuccio was a weather forecaster for the U.S. Navy, and a Meteorological/Radiosonde Technician for the National Weather Service.  More recently, he served as head of the science department for St. Nicholas Orthodox School in Akron, Ohio (closed in 2006).  He continues to write science curriculum, publish articles, and conduct science camps.

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Limits on CO2 Climate Forcing from Recent Temperature Data of Earth: A Guest Weblog by David Douglass and John Christy

Our paper

Limits on CO2 Climate Forcing from Recent Temperature Data of Earth

has just been published in Energy and Environment. (Vol 20, Jan 2009). [Copies may be downloaded from . preprint with figures in color at]  

We show in Figure 1 the well established observation that the global atmospheric temperature anomalies of Earth reached a maximum in 1998.


This plot shows oscillations that are highly correlated with El Nino/La Nina and volcanic eruptions. There also appears to be a positive temperature trend that could be due to CO2 climate forcing.

We examined this data for evidence of CO2 climate forcing.  We start by assumed that CO2 forcing has the following signature.

1. The climate forcing of CO2 according to the IPCC varies as ln(CO2) which is nearly linear over the range of this data. One would expect that the temperature response to follow this function.

2. The atmospheric CO2 is well mixed and shows a variation with latitude which is less than 4% from pole to pole. Thus one would expect that the latitude variation of the temperature anomalies from CO2 forcing to be also small.

Thus, changes in the temperature anomaly T that are oscillatory, negative or that vary strongly with latitude are inconsistent with CO2 forcing.

The latitude dependence of the UAH data is shown in Figure 2.


The anomalies are for NoExtropics, Tropics, SoExtropics and Global. The average trends are 0.28, 0.08, 0.06, and 0.14 K/decade respectively. If  the climate forcing were only from CO2 one would expect from property #2 a small variation with latitude.  However, NoExtropics is 2 times that of the global and 4 times that of the Tropics.  Thus one concludes that the climate forcing in the NoExtropics includes more than CO2 forcing. These non-CO2 effects include: land use [Pielke et al. 2007]; industrialization [McKitrick and Michaels 2007, Kalnay and Cai 2003, DeLaat and Maurellis 2006]; high natural variability, and daily nocturnal effects [Walters et al. 2007].

Thus we look to the tropical anomalies. If one is able to determine an underlying trend in the tropics, then assuming that the latitude variation of the intrinsic CO2 effect is small (CO2 property #2), then the global trend should be close to this value.

Figure 3 shows the tropical UAH data and the nino3.4 time-series. (Results consistent with these were found using RSS microwave temperatures, but evidence also presented here and elsewhere indicates RSS is less robust for trend calculations.)

One sees that the value at the end of the data series is less than at the beginning. However, one should not conclude from this observation that the trend is negative because of the obvious strong correlation between UAH and nino3.4.

The desired underlying trend, the ENSO effect, the volcano effect can all be determined by a multiple regression analysis. The regression analysis yields the underlying trend

            trend = 0.062±0.010 K/decade; R2 = 0.886.                 (1)

 Warming from CO2 forcing
How big is the effect from CO2 climate forcing?  From IPCC [2001]

             ΔT (CO2 ) ≈λ* ΔF (CO2 )                                             (2)

             ΔF (CO2 )  ≈ 5.33 ln (C/C0)*

where l is the climate sensitivity parameter whose value is 0.30 ºK/(W m-2) for no-feedback; C is the concentration of CO2, and C0 is a reference value. From the data the mean value of the slope of ln(C(t)/C(t0)) vs. time from 1979 to 2004 is 0.044/decade.


                          ΔT (CO2 ) ≈ 0.070  K/decade                     (3)

This estimate is for no-feedback. If there is feedback leading to a gain g, then multiply Eq. 3 by g. The underlying trend  is consistent with CO2 forcing with no-feedback. It is frequently argued that the gain g is larger than 1, perhaps as large as 3 or 4. This possibility requires there to be some other climate forcing of negative sign to cancel the excess. From the results of Chylek [2007], this cancellation cannot come from aerosols. One candidate is the apparent negative feedback associated with changes in cirrus clouds when warmed [Spencer et al. 2007].

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