His latest posting there highlights research findings that show that extreme weather events during last summer and the previous two winters can be fully explained by natural climate variability—and that “global warming” need not (and should not) be invoked.

This topic—whether or not weather extremes (or at least some portion of them) can be attributed to anthropogenic global warming (or, as Dr. Pielke Sr., prefers, anthropogenic climate change)—has been garnering a lot of attention as of late. It was a major reason for holding the House Subcommittee hearing last week, is a hot topic of discussion in the press, and is the subject of an in-progress major report from the Intergovernmental Panel on Climate Change (IPCC).

As such, I wanted to highlight some of the findings that Pat reported on. I encourage a visit to the full article “Overplaying the Human Contribution to Recent Weather Extremes” over at Cato@Liberty.

The Great Russian Heat Wave of 2010

A new paper by Randall Dole and colleagues from the Physical Sciences Division (PSD) of the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) examined the events leading up to and causing the big heat wave in Russia last summer (which was also part of an atmospheric pattern that was connected to the floods in Pakistan). Here is what they found:

“Our analysis points to a primarily natural cause for the Russian heat wave. This event appears to be mainly due to internal atmospheric dynamical processes that produced and maintained an intense and long-lived blocking event. Results from prior studies suggest that it is likely that the intensity of the heat wave was further increased by regional land surface feedbacks. The absence of long-term trends in regional mean temperatures and variability together with the [climate] model results indicate that it is very unlikely that warming attributable to increasing greenhouse gas concentrations contributed substantially to the magnitude of this heat wave.”

As Pat commented, “Can’t be much clearer than that.”

Recent Winter Severity

From Pat’s article:

Another soon-to-be released paper to appear in Geophysical Research Letters describes the results of using the seasonal weather prediction model from the European Center for Medium-Range Weather Forecasts (ECMWF) to help untangle the causes of the unusual atmospheric circulation patterns that gave rise to the harsh winter of 2009-2010 on both sides of the Atlantic. A team of ECMWF scientists led by Thomas Jung went back and did experiments changing initial conditions that were fed into the ECMWF model and then assessed how well the model simulated the known weather patterns of the winter of 2009-2010. The different set of initial conditions was selected so as to test all the pet theories behind the origins of the harsh winter. Jung et al. describe their investigations this way: “Here, the origin and predictability of the unusual winter of 2009/10 are explored through numerical experimentation with the ECMWF Monthly forecasting system. More specifically, the role of anomalies in sea surface temperature (SST) and sea ice, the tropical atmospheric circulation, the stratospheric polar vortex, solar insolation and near surface temperature (proxy for snow cover) are examined.”

In a nutshell, here is what Jung et al. found:

“The results of this study, therefore, increase the likelihood that both the development and persistence of negative NAO phase [an atmospheric circulation pattern that was largely behind the harsh winter conditions] resulted from internal atmospheric dynamical processes.”

Or, as Pat put it “Translation: Random variability.”

Pat also examined a third study by Roseanne D’Arrigo and colleagues who found an historical analog of the conditions responsible for the harsh winter of 2009-2010 way back in 1783-1784. The winter of 1783-1784 was a historically extreme one on both sides of the Atlantic and has long been associated with a large volcanic eruption that occurred in Iceland during the summer of 1783. Even Benjamin Franklin connected the winter conditions to the volcano. But D’Arrigo and colleagues now suggest a different mechanism. According to Pat:

But in their new study, Roseanne D’Arrigo and colleagues conclude that the harshness of that winter primarily was the result of anomalous atmospheric circulation patterns that closely resembled those observed during the winter of 2009-10, and that the previous summer’s volcanic eruption played a far less prominent role:

“Our results suggest that Franklin and others may have been mistaken in attributing winter conditions in 1783-4 mainly to Laki or another eruption, rather than unforced variability.

“Similarly, conditions during the 2009-10 winter likely resulted from natural [atmospheric] variability, not tied to greenhouse gas forcing… Evidence thus suggests that these winters were linked to the rare but natural occurrence of negative NAO and El Niño events.”

Bottom Line

The take home message of Pat’s post is worth repeating:

The point is that natural variability can and does produce extreme events on every time scale, from days (e.g., individual storms), weeks (e.g., the Russian heat wave), months (e.g., the winter of 2009-10), decades (e.g., the lack of global warming since 1998), centuries (e.g., the Little Ice Age), millennia (e.g., the cycle of major Ice Ages), and eons (e.g., snowball earth).

Folks would do well to keep this in mind next time global warming is being posited for the weather disaster du jour. Almost assuredly, it is all hype and little might.

Be sure to check out Pat’s full article which includes much more in depth coverage of these three soon-to-be-released scientific studies.

His succinct testimony, reprinted below, provides a viewpoint on climate change science that is (refreshingly) different from the somewhat limited one espoused by the IPCC. While the IPCC sports blinders that prevent it from seeing much beyond human emissions as being the primary culpable agent of climate change, Roger sees the much bigger, more complex, picture. And Roger suggests that a response considered for the big climate change picture would likely be much different from that being considered for human emissions alone.

(Other testimony from scientists and House members, including Q&A, can be found here.)

———————————————————–

Testimony to the Subcommittee on Energy and Power entitled “Climate Science and EPA’s Greenhouse Gas Regulation”

Roger A. Pielke Sr.
University of Colorado at Boulder and Colorado State University
8 March 2011

I have worked throughout my career to improve environmental conditions, including air quality, by conducting research, teaching and also by providing scientifically rigorous information to policy makers. At the state level, I served two terms on the Colorado Air Quality Control Commission where we developed the oxygenated fuels program to reduce atmospheric CO emissions from vehicles, promulgated regulations to mandate strict controls on wood and coal burning in residential fireplaces and stoves, and on asbestos concentrations in the air.

Four Main Points

In my testimony today (and in more detail in my written testimony) I have four main points:

1. Research has shown that a focus on just carbon dioxide and a few other greenhouse gases as the dominant human influence on climate is too narrow, and misses other important human influences.(1)

2. The phrases “global warming” and “climate change” are not the same. Global warming is a subset of climate change.

3. The prediction (or projection) of regional weather, including extremes, decades into the future is far more difficult than commonly assumed. As well, the attribution of extreme events to a particular subset of climate forcings is scientifically incomplete, if the research ignores other relevant human and natural causes of extreme weather events.

4. The climate science assessments of the IPCC and CCSP, as well as the various statements issued by the AGU, AMS and NRC, are completed by a small subset of climate scientists who are often the same individuals in each case.

Models–Buyer Beware

The production of multi-decadal climate predictions of regional impacts, whose skill cannot be verified until decades from now, is not a robust scientific approach. Models themselves are hypotheses. The steps of hypothesis written with respect to climate predictions as

1. Make a Prediction

2. Quantitatively Compare the Prediction With Real World Observations [i.e. Test the Hypothesis]

3. Communicate The Assessment the Skill of the Prediction

There is no way to test hypotheses with the multi-decadal global climate model forecasts for decades from now as step 2, as a verification of the skill of these forecasts, is not possible until the decades pass.

Back to Basics: What is Global Warming/Climate Change?

There has also been a misunderstanding of the relationship between global warming and climate variability and longer term change.

Global Warming is typically defined as an increase in the global average surface temperature. A better metric is the global annual average heat content measured in Joules. Global warming involves the accumulation of heat in Joules within the components of the climate system. This accumulation is dominated by the heating and cooling within the upper layers of the oceans.

Climate Change is any multi-decadal or longer alteration in one or more physical, chemical and/or biological components of the climate system. Climate change includes, for example, changes in fauna and flora, snow cover, etc which persists for decades and longer. Climate variability can then be defined as changes which occur on shorter time periods.

With respect to climate change, in 2009 18 Fellows of the American Geophysical Union accepted an invitation to join me in a paper where we discussed three different mutually exclusive hypotheses with respect to the climate system:

Hypothesis 1: Human influence on climate variability and change is of minimal importance, and natural causes dominate climate variations and changes on all time scales. In coming decades, the human influence will continue to be minimal.

Hypothesis 2a: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and involve a diverse range of first- order climate forcings, including, but not limited to, the human input of carbon dioxide (CO2). Most, if not all, of these human influences on regional and global climate will continue to be of concern during the coming decades.

Hypothesis 2b: Although the natural causes of climate variations and changes are undoubtedly important, the human influences are significant and are dominated by the emissions into the atmosphere of greenhouse gases, the most important of which is CO2. The adverse impact of these gases on regional and global climate constitutes the primary climate issue for the coming decades.

Hypothesis 2b is the IPCC perspective. In our EOS paper, we concluded that only Hypothesis 2a has not been refuted. Hypotheses 1 and 2b are inaccurate characterizations of the climate system.

In our 2009 paper we wrote

“In addition to greenhouse gas emissions, other first- order human climate forcings are important to understanding the future behavior of Earth’s climate.

These forcings are spatially heterogeneous and include the effect of aerosols on clouds and associated precipitation [e.g., Rosenfeld et al., 2008], the influence of aerosol deposition (e.g., black carbon (soot) [Flanner et al. 2007] and reactive nitrogen [Galloway et al., 2004]), and the role of changes in land use/land cover [e.g., Takata et al., 2009]. Among their effects is their role in altering atmospheric and ocean circulation features away from what they would be in the natural climate system [NRC, 2005].

As with CO2, the lengths of time that they affect the climate are estimated to be on multidecadal time scales and longer.”

We concluded that

“Therefore, the cost- benefit analyses regarding the mitigation of CO2 and other greenhouse gases need to be considered along with the other human climate forcings in a broader environmental context, as well as with respect to their role in the climate system”

and

“The evidence predominantly suggests that humans are significantly altering the global environment, and thus climate, in a variety of diverse ways beyond the effects of human emissions of greenhouse gases, including CO2. Unfortunately, the 2007 IPCC assessment did not sufficiently acknowledge the importance of these other human climate forcings in altering regional and global climate and their effects on predictability at the regional scale.”

A major conclusion indicated from these studies is that regional atmospheric and ocean circulation features produce extreme weather events, not a global annual average surface temperature anomaly. It is the multi-decadal change in the statistics of these circulation features, in response to natural and human forcings and feedbacks, which must be skillfully predicted. This level of predictive skill has not yet been achieved even in hindcasts of past decades.

Policymakers and the public rarely encounter this broader view of the climate system, in part due to the limited number of scientists who are leading climate assessments. As just one example, I present my experiences with the first CCSP report. My experience is documented in a public comment. In the executive summary of that report, I wrote:

“The process for completing the CCSP Report excluded valid scientific perspectives under the charge of the Committee. The Editor of the Report systematically excluded a range of views on the issue of understanding and reconciling lower atmospheric temperature trends.

Future assessment Committees need to appoint members with a diversity of views and who do not have a significant conflict of interest with respect to their own work. Such Committees should be chaired by individuals committed to the presentation of a diversity of perspectives and unwilling to engage in strong-arm tactics to enforce a narrow perspective. Any such committee should be charged with summarizing all relevant literature, even if inconvenient, or which presents a view not held by certain members of the Committee.”

Bottom-Up Approach Needed

I have proposed a new approach in the climate community based on a bottom-up, resource-based perspective.

There are five broad areas that we can use to define the need for this type of vulnerability assessment: water, food, energy, human health and ecosystem function. Each sector is critical to societal well-being. The vulnerability concept requires the determination of the major threats to these resources from extreme events including climate, but also from other social and environmental pressures. After these threats are identified for each resource, relative risks can be compared in order to shape the preferred mitigation/adaptation strategy.

(1) IPCC: Intergovernmental Panel on Climate Change; CCSP: U.S. Global Change Research Program; AGU: American Geophysical Union; AMS: American Meteorological Society; NRC: National Research Council
———————————

For more of Roger Pielke, Sr.’s views at MasterResource, see Towards Climate Science Pluralism–and Starting Over With Climate Policy and be sure to check out his excellent Climate Science website.)

This line of reasoning was recently incorporated into statements made by Dr. Patrick Michaels when testifying before the U.S. House of Representatives, Committee on Science and Technology, Subcommittee on Energy and Environment.

During the questions and answers portion of the hearing, one of the other panelists, Dr. Benjamin Santer, quickly objected and claimed that Pat was “wrong” because he didn’t take into account the cooling influence of aerosols when determining how much observed warming should be assigned to greenhouse gases.

A day or so following the testimony, Judith Curry hosted a discussion on her blog site Climate Etc. to further examine Michaels’ logic. In her remarks introducing the thread, she too suggested that Pat was “obliged” to include sulfates in the calculation. When I stepped in to offer additional explanation, RealClimate’s Gavin Schmidt commented that he hoped I was “kidding,” and John Nielsen-Gammon of Texas A&M commented that my explanation was “nonsense.”

So with all these erudite folks claiming that Pat Michaels and I are wrong, I figured I ought to take another look into the logic behind our conclusions.

Our Logic

First let’s get a couple of things out of the way up front. The argument about whether or not the inclusion of sulfates is required to arrive at a logically correct conclusion has nothing whatsoever to do with the veracity and/or applicability of the scientific papers from which I’ve drawn some numbers (see my earlier post for details about these findings). I am not suggesting that there isn’t plenty of room to argue that aspect of things, just that such a discussion does not impinge on the discussion of our logic. So I’ll set aside discussion of those issues in order to focus on the topic at hand.

I’ll state the following things simply as given (if it helps I’ll add this disclaimer “The following are for illustrative purposes only”):

1) The observed warming from 1950-2009 is 0.7°C
2) 0.2°C of that is due to a warm bias in the measurements
3) This leaves 0.5°C of actual warming
4) The anthropogenic increase in well-mixed greenhouse gases is responsible for +3.0 W/m2 of extra climate forcing (positive climate forcing imparts a warming pressure on global temperatures)
5) Sulfate aerosols are responsible for -1.5W/m2 of climate forcing (note this is a negative forcing which imparts a cooling pressure)
6) Black carbon (a.k.a. “soot”) aerosols are responsible for 1 W/m2 of added forcing (warming)
7) Stratospheric water vapor changes are responsible for 0.5W/m2 of added forcing (warming)

I’ll stress again, I use these numbers to make the math cleaner. They are in the ball park, but not intended to represent the exact or even best-guess values. So please set aside any heartburn about them (also note that natural variability is not considered here, but most definitely should be in a more formal evaluation).

Also, the IPCC was unaware of numbers 2, 6, and 7 at the time it made its “most of the observed warming” statement quoted above.

In my MasterResource article and in Pat’s testimony, the logic as to how to assign various amounts of observed warming to various factors is as follows:

The 0.5°C of actual warming [in (3)] was caused by three factors, GHGs, black carbon, and stratospheric H2O. In percentage terms, GHG contributed 67%, black carbon contributed 22% and stratospheric H2O contributed 11 percent. This is calculated by taking the positive forcing from each factor and dividing it by the sum of the positive forcings. Thus for GHG, you get 3.0/(3.0+1.0+0.5)=0.67, or 67%. To determine how much of the actual temperature change that GHGs were responsible for, we multiply 0.5°C by 67% and get 0.34°C—which, we pointed out was about 50% of the “observed” warming of 0.7°C (listed in (1)). Thus, the IPCC statement rests on thin ice.

To this, Santer/Schmidt/Nielsen-Gammon/Curry cried “foul!” claiming that we have committed a sin of omission by not factoring in the negative climate forcing contributed by sulfate aerosols.

Their Logic

When calculating the percentage contribution from each climate forcing agent, they maintain that we should have divided each element’s contribution not by the sum of the positive forcing, but by the sum of all forcings (including negative ones). So instead of dividing by (3.0+1.0+0.5)=4.5 like we did, we should have used (3.0+1.0+0.5-1.5)=3.0.

And, they argue, that had we done that, we would have found out that GHGs contribute 100% of the warming, black carbon 33%, stratospheric H2O 17% and sulfates -50%. Therefore, even taking into account measurement errors (listed in (2) above) GHGs still contribute more than half of the observed warming. And the IPCC is right and Michaels and I are wrong (see John Nielsen-Gammon’s explanation at Climate Etc. for further evidence of this line of reasoning).

It is now my turn to reply, “Nonsense!”

Pieces Greater than the Whole?

You can’t divide a physical quantity into pieces that together are greater than the whole. Which is precisely where the latter logic leads you.

The flaw in the Santer/Schmidt/Nielsen-Gammon/Curry logic is in confusing “potential” warming with “observed” or “actual” warming.

I completely agree that using the numbers above, GHGs contribute 0.5°C*100%=0.5°C of potential warming, black carbon contributes 0.5*33%=0.17°C of potential warming, and stratospheric H2O contributes 0.5*17%=0.08°C of potential warming and that of this 0.75°C of potential warming, sulfates offset 0.25°C of it, leaving 0.5°C of observed warming.

But, in employing potential warming to divvy up observed warming is mixing apples and oranges, and leads to results that don’t make practical sense.

Take for instance this hypothetical situation:

GHG = 2 W/m2
Black Carbon = 2 W/m2
Stratospheric H2O = 2 W/m2
Sulfates = -4 W/m2
Observed Warming = 0.5°C

If this were the situation, you would arrive at the answer that GHGs are responsible for 100% of the warming AND black carbon is responsible for 100% of the warming AND stratospheric H2O is responsible for 100% of the warming. This result allows you to assign any and all warming to whatever your favorite postive forcing element is. Certainly this is creative, but it is not practical.

Doing things my way, you get the logical result that each positive forcing element contributes 33.3% to the warming and is equally responsible for what has been observed.

So there you have it, two different ways of describing the observed warming.

I’ll leave it up to you all to decide which one is the more reasonable.

The IPCC’s Take

But before I go, I’ll leave with one additional thing to consider.

Here are two successive statements in the IPCC’s Summary for Policymakers of its Fourth Assessment Report (p. 10).

The first you will recognize:

“Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”

And here is the separate bulleted statement that comes next:

“It is likely that increases in greenhouse gas concentrations alone would have caused more warming than observed because volcanic and anthropogenic aerosols have offset some warming that would have otherwise taken place.”

Clearly the IPCC recognizes the difference between observed warming (as reflected in the first statement) and potential warming (as reflected in the second statement).

Bottom Line

The latter IPCC statement will remain true so long as the value of the net climate forcing remains less than that of the GHG forcing (which would take a significant scientific finding to overturn). I think this is the gist of what Santer/Schmidt/Nielsen-Gammon/Curry are saying, and that such a major development has not occurred.

The former statement, however, and the one whose veracity is being assessed by Pat Michaels and I (and the one highlighted by the IPCC and the EPA), is more readily falsifiable through even relatively minor tweaks to our understanding of the various influences on the climate system. And Pat and I are claiming that such minor tweaks have occurred and have led to a falsification of the IPCC statement—or at the very least, demonstration that it is undeserving of the level of confidence placed upon it by the IPCC.

I welcome on-topic comments.

The article, by Eric Steig and colleagues, described more warming taking place over a larger portion of Antarctica than had previously been recognized. The implication was that the temperature rise across Antarctica was not lagging behind the rest of the world and thus “not bucking the trend of global warming” as apparently some “contrarians” were claiming.

Now, that result must be tempered, as a new paper is forthcoming that improves upon the analytical technique developed by the Steig team and finds significantly less warming across the continent as a whole (about 50% less), and a different geographical pattern of temperature changes across Antarctica—results that fit more closely with the existing (that is, pre-Steig et al.) perception of what was going on down there. Basically, when a more correct analysis was performed, our understanding of what has been occurring in Antarctica has been firmed up, rather than being badly shaken—Antarctica, on average, has warmed a little bit over the past 50 years, with the largest and most significant warming being concentrated in the regions around the Antarctic Peninsula, rather than spread somewhat evenly across the continent (as the Steig et al. result showed).

But, perhaps the most interesting part of this story is that the new analysis grew from the blogosphere.

Soon after the Steig et al. article was published, it was being examined and critiqued on various blog sites. Among the criticisms was that the statistical technique pioneered by the Steig team was improperly implemented and that the published results were influenced by these inaccuracies.

An effort grew from these blog discussions to develop a better implementation of the methods and the results revealed a rather different picture of the patterns of temperature evolution across Antarctica than did the original Steig et al. paper (Figure 1).

Figure 1. Patterns of temperature changes over Antarctica (1957-2006) based on the new, updated analysis (left) and as reported by Steig et al. (right) (figure source: The Air Vent)

The Blogosphere at its Best

Now, this type of thing happens fairly frequently in blog space—a spirited critique of a scientific publication. But what doesn’t happen very frequently, is that the blog discussions are formalized and submitted to a scientific journal. And in this case, not only were they submitted, but after a lengthy and extremely thorough review process, the new, improved findings have been accepted for publication in the Journal of Climate—a very well-respected scientific journal.

This shows the utility of blogs at their best—initial informal critical discussion that hits upon a legitimate and important point of science, which is then formalized, submitted, and accepted into the peer-reviewed scientific literature, thereby making a much more permanent, citeable and, in fact, more widely accessible, contribution to the scientific knowledge base.

Kudos to Ryan O’Donnell, Nicholas Lewis, Steve McIntyre, and Jeff Condon.

To read more about how all this came to pass, please visit Jeff’s blog where some of the authors describe all that was involved from start to finish and include a preview of their results.

I wrote in my original MasterResource article “[The Steig et al. paper was] all in all a reasonable approach to the problem—but likely not the final word on the matter.” The new paper by O’Donnell et al. pretty much confirms this, and adds important new words to the story. Lead author Ryan O’Donnell describes it like this:

In my opinion, the Steig reconstruction was quite clever, and the general concept was sound. A few of the choices made during implementation were incorrect; a few were suboptimal. Importantly, if those are corrected, some of the results change. Also importantly, some do not. Hopefully some of the cautions outlined in our paper are incorporated into other, future work. Time will tell!

This is the way science is supposed to work. I am delighted to see the blogosphere opening the doors to scientific contributions to a wider audience. I hope this trend continues—science will be the better for it. But, importantly, to achieve this contribution, it requires a great deal of effort, persistence, and fortitude that extends far beyond a comment thread on a blog somewhere. I encourage more people who really are interested in making a lasting impact to grin and bear it and make the effort—it is an effort that can be rather painful, but which provides great satisfaction in the end, and best of all, it keeps science moving forward.

So blog away, but when you hit upon something that you think is scientifically important, take the time to write it up and send it in to a journal—the end result could be rewarding for all of us.

Thus far, however, this prize has been elusive. Back in 1990, in its very first Assessment Report, the Intergovernmental Panel on Climate Change (IPCC) suggested that the climate sensitivity was somewhere between 1.5°C to 4.5°C. In its latest Fourth Assessment Report published in 2007, the IPCC said the climate sensitivity was likely to be between 2.0°C and 4.5°C, and unlikely be to less than 1.5°C. Not a whole heck of a lot more certain than where things stood 20 years ago—and this despite a veritable scientific crusade to determine a more precise value.

A predominant member of the quest is the University of Alabama in Huntsville’s Dr. Roy Spencer. Dr. Spencer has, for several years now, been trying to untangle climate feedbacks from climate forcings. If apparent feedbacks are really forcings, or vice versa, then the determination of climate sensitivity is confused and prone to being wrong (and likely erring on the high side).

Dr. Spencer has long held that what has generally been taken to be a positive feedback from cloud cover changes in response to climate warming (i.e. cloud changes act to further enhance a CO2-induced warming) is actually the other way around—random cloud cover changes force temperature changes. However, trying to demonstrate that this is the case has proven challenging, and trying to convince the general climate community has been virtually impossible.

To help bring his ideas to a wider audience, Dr. Spencer has written a book about his hypothesis and his research in support of it, and has now, after years of tireless pursuit, published a paper in the peer-reviewed scientific literature.

Realizing that his findings run counter to the extant mainstream view of things, he has taken the step to ask for “physical scientists everywhere” to try to debunk his ideas. The appeal for scrutiny is intended to serve both science and Dr. Spencer in helping to solidify and illuminate a potential new way forward to finding the elusive Grail.

Recently, Dr. Spencer has written a nice summary of his on-going research and what, in his views are its implications. Rather than having me rehash his synopsis, Dr. Spencer has graciously permitted us to reprint a piece that originally appeared on his excellent website (a site well-worth checking from time to time).

Hopefully, readers of MasterResource will find this cutting-edge climate research interesting, and I am sure that if any of you have any pertinent suggestions for Dr. Spencer regarding his work, he would be happy to hear them.

Here is the excerpt:

Our JGR Paper on Feedbacks is Published

Roy W. Spencer, Ph. D.

After years of re-submissions and re-writes — always to accommodate a single hostile reviewer — our latest paper on feedbacks has finally been published by Journal of Geophysical Research (JGR).

Entitled “On the Diagnosis of Feedback in the Presence of Unknown Radiative Forcing“, this paper puts meat on the central claim of my most recent book: that climate researchers have mixed up cause and effect when observing cloud and temperature changes. As a result, the climate system has given the illusion of positive cloud feedback.

Positive cloud feedback amplifies global warming in all the climate models now used by the IPCC to forecast global warming. But if cloud feedback is sufficiently negative, then manmade global warming becomes a non-issue.

While the paper does not actually use the words “cause” or “effect”, this accurately describes the basic issue, and is how I talk about the issue in the book. I wrote the book because I found that non-specialists understood cause-versus-effect better than the climate experts did!

This paper supersedes our previous Journal of Climate paper, entitled “Potential Biases in Feedback Diagnosis from Observational Data: A Simple Model Demonstration“, which I now believe did not adequately demonstrate the existence of a problem in diagnosing feedbacks in the climate system.

The new article shows much more evidence to support the case: from satellite data, a simple climate model, and from the IPCC AR4 climate models themselves.

Back to the Basics

Interestingly, in order to convince the reviewers of what I was claiming, I had to go back to the very basics of forcing versus feedback to illustrate the mistakes researchers have perpetuated when trying to describe how one can supposedly measure feedbacks in observational data.

Researchers traditionally invoke the hypothetical case of an instantaneous doubling of the CO2 concentration of the atmosphere (2XCO2). That doubling then causes warming, and the warming then causes radiative feedback which acts to either reducing the warming (negative feedback) or amplify the warming (positive feedback). With this hypothetical, idealized 2XCO2 case you can compare the time histories of the resulting warming to the resulting changes in the Earth’s radiative budget, and you can indeed extract an accurate estimate of the feedback.

The trouble is that this hypothetical case has nothing to do with the real world, and can totally mislead us when trying to diagnose feedbacks in the real climate system. This is the first thing we demonstrate in the new paper. In the real world, there are always changes in cloud cover (albedo) occurring, which is a forcing. And that “internal radiative forcing” (our term) is what gives the illusion of positive feedback. In fact, feedback in response to internal radiative forcing cannot even be measured. It is drowned out by the forcing itself.

Feedback in the Real World

As we show in the new paper, the only clear signal of feedback we ever find in the global average satellite data is strongly negative, around 6 Watts per sq. meter per degree C. If this was the feedback operating on the long-term warming from increasing CO2, it would result in only 0.6 deg. C of warming from 2XCO2. (Since we have already experienced this level of warming, it raises the issue of whether some portion — maybe even a majority — of past warming is from natural, rather than anthropogenic, causes.)

Unfortunately, there is no way I have found to demonstrate that this strongly negative feedback is actually occurring on the long time scales involved in anthropogenic global warming. At this point, I think that belief in the high climate sensitivity (positive feedbacks) in the current crop of climate models is a matter of faith, not unbiased science. The models are infinitely adjustable, and modelers stop adjusting when they get model behavior that reinforces their pre-conceived notions.

They aren’t necessarily wrong — just not very thorough in terms of exploring alternative hypotheses. Or maybe they have explored those, and just don’t want to show the rest of the world the results.

Our next paper will do a direct apples-to-apples comparison between the satellite-based feedbacks and the IPCC model-diagnosed feedbacks from year-to-year climate variability. Preliminary indications are that the satellite results are outside the envelope of all the IPCC models.

But do the experts opinions actually reflect the scientific knowledge on these subjects?

The answer is no.

In fact, the experts’ opinions tended towards the extreme, despite recent science which should have reeled them in. Which is a lesson in and of itself.

How much confidence would you place in expert assessments such as the IPCC reports, when the experts themselves disregard some science in favor of others (namely the science that they themselves have been involved in), despite any good reasons to do so?

Not much would be my answer.

A prime example of experts disregarding scientific knowledge is found in the PNAS survey conducted by Kirsten Zickfeld and colleagues.

Zickfeld et al. interviewed 14 experts about what they thought the climate future holds in store under various scenarios of atmospheric carbon dioxide concentrations. The experts’ responses to the scenario in which atmospheric CO2 levels reach about 1000 parts per million (ppm) by the year 2200 is the one which got the most attention—predictably so, why pay any attention to outcomes which aren’t dramatic.

In fact, as evidence that the experts were themselves prone to the dramatic, Dr. Myles Allen (one of the experts interviewed), was quoted in the UK’s The Independent, that “We are certainly capable of committing ourselves to an emissions trajectory that make 1,000 ppm in 2200 almost inevitable if we make the wrong decisions over the next 20 years.”

This seems a little short-sighted and moralistic, but hey, these guys are experts.

And 13 out of 14 stated that there was a greater than 50% likihood that some sort of climate tipping point would occur by 2200 under the 1000ppm CO2 scenario while 9 of them put the probability as over 80%.

Undoubtedly, a leading factor in these beliefs comes down to the experts’ opinions as to what is the true value of the earth’s climate sensitivity. It turns out, that this has been a hard value to pin down—largely because uncertainties abound in both our understanding of the observed climate as well as how it got that way.

Zickfeld et al. report that the experts consider the leading cause of uncertainty about the behavior of the climate system to lie with cloud processes. Others causes consistently listed near the top were feedbacks involving ice and snow, water vapor feedback, and large-scale ocean circulation.

It is interesting to note that Zickfeld found that the experts had little confidence that scientific research would reduce the impacts of these uncertainties by half even if research budgets were increased by 3 times current levels.

Considering all that we don’t know, the Intergovernmental Panel on Climate Change (IPCC) can only state that the “likely” range (a confidence of between 66 and 90%) of the true value of the climate sensitivity lies between 2°C and 4.5°C, which, as Zickfeld explains, means that the IPCC thinks that there is just a 5% to 17% chance that the climate sensitivity is greater than 4.5°C.

But what to the experts think about the range of climate sensitivity? Figure 1 shows their expert opinion.

Figure 1. Range of values which are thought to contain the true value of the earth’s climate sensitivity, as given by 14 experts. The tick marks on the whiskers bound the 90% range, the boxes bound the 50% range and the small, thick horizonal mark reprents the median value of the distribution. The values in parentheses under the number of each reviewer is the probability that the climate sensitivity is greater than 4.5°C. (the grayed out boxes associated with some experts are how those experts responded to the question in a similar survey more than 10 years ago).

Now, before I go much further, let me discuss briefly who Zickfeld’s experts are. Probably a good half of them have been directly involved in research projects which have determined that very high climate sensitivity values were a distinct possibility, and exactly none of them were involved in research projects (such as those being carried out by Richard Lindzen or Roy Spencer) which suggest that the climate sensitivity is at (or below) the low end of the IPCC range.

So, the following results will hardly be surprising.

Zickfeld et al. report:

The IPCC report assesses that the “equilibrium climate sensitivity is likely to lie in the range 2– 4.5°C, with a most likely value of about 3°C.” IPCC defines likely as a 0.66–0.90 probability, which in Chapter 19, Working Group II (WGII) is interpreted as a 0.05–0.17 probability that climate sensitivity is >4.5°C. Examining the elicited distributions obtained from our experts, we find that 10 of the 14 experts placed >0.17 of their probability above 4.5 °C. [emphasis added]

So 10 of the 14 experts think the chance of a high sensitivity value is greater than that laid out in the IPCC. As a note, the other 4 experts listed the probability at 7%, 10%, 12% and 15%.

Even more enlightening is that 9 of the 14 experts consider a climate sensitivity of greater than 6°C as having a not insignificant 5% chance of being the true value.

What is so incredible about these numbers is that there is solidly argued scientific research (appearing in the peer-reviewed literature) that constrains the climate sensitivity range to a much greater degree than these experts do.

Most notable is a string of papers published by James Annan, a climate researcher at the Research Institute for Global Change of the Japan Agency for Marine-Earth Science and Technology and his colleagues. James argues that his research pretty strongly suggests that the upper end of the range of potential climate sensitivity is much more constrained than the experts realize (or admit to).

In his most recent paper on the subject, James concludes:

Based on some conservative assumptions regarding the value of independent estimates, we conclude that climate sensitivity is very unlikely (<5% probability) to exceed 4.5°C. We cannot assign a significant probability to climate sensitivity exceeding 6°C without making what appear to be wholly unrealistic exaggerations about the uncertainties involved. This represents a significant lowering of the previously-estimated bound.

Apparently, most of Zickfeld’s experts weren’t above “making wholly unrealistic exaggerations about the uncertainties involved” as 9 of them included a probability of 5% or more that the true climate sensitivity was above 6°C (and not a one had a probability as low as 5% for the climate sensitivity being above 4.5°C).

Clearly, the experts did not think too highly of James’ analysis.

All of this has left James shaking his head (from his review of the Zickfeld article):

So even though as far as I can tell everyone accepts that the fundamental points we make in our two papers are valid, they still stick to these old discredited results with long tails to high values. – in fact the answers are more alarmist than 15 years ago. Makes us wonder why we bother…

Read more of why James is disheartened at his blog post “Oh noes we’re all going die…by 2200.”

All of this shines interesting light on the latest entry over at the blog RealClimate—a prayer of sorts, that Gavin Schmidt picked up at a recent climate meeting which he offers for discussion:

Grant us…
The ability to reduce the uncertainties we can;
The willingness to work with the uncertainties we cannot;
And the scientific knowledge to know the difference.

The way I see it, there is real work being done to reduce the uncertainties on the estimate of the climate sensitivity, but the experts would rather not recognize these results and instead, they prefer to treat climate sensitivity as a type of uncertainty that can’t be known, because this allows them to better entertain the high end leading to future catastrophe and tipping points.

Which gets to the bottom of the bigger issue—that is, what is wrong with Assessment reports such as those from the IPCC.

Simply put, they reflect the opinion of experts rather than a comprehensive, or even unbiased, review of the scientific literature. The assumption that expert assessments draw upon the best scientific knowledge is a false one—what experts do drawn upon are their own ideas, some borne by their own work, and even if subsequent work seriously calls their own work into question, they stick to their old ideas. This is on display here, and also throughout the Climategate emails.

References:

Annan, J. D., and J. C. Hargreaves, 2006. Using multiple observationally-based constraints to estimate climate sensitivity. Geophysical Research Letters, 33, L06704.

Zickfeld, K., et al., 2010. Expert judgments about transient climate response to alternative future trajectories of radiative forcing. Proceedings of the National Academy of Sciences, doi:10.1073/pnas.0908906107.

One time in the House of Representatives [a colleague] told me a story about a proposition that a teacher put to a boy. He said, ‘Johnny, a cat fell in a well 100 feet deep. Suppose that cat climbed up 1 foot and then fell back 2 feet. How long would it take the cat to get out of the well?

Johnny worked assiduously with his slate and slate pencil for quite a while, and then when the teacher came down and said, ‘How are you getting along?’ Johnny said, ‘Teacher, if you give me another slate and a couple of slate pencils, I am pretty sure that in the next 30 minutes I can land that cat in hell.

The nation needs Johnny. In fact, it may be time we hired a team of people like Johnny for every large science-based policy proposal Congress contemplates funding.

Carbon Capture and Storage: A Known Boondoggle

Consider, for example, the $4.4 billion Congress is putting into carbon capture and sequestration (CCS) research, nearly half of that to come from the Kerry-Lieberman climate bill. As Robert Bryce points out in the New York Times, “That’s a lot of money for a technology whose adoption faces three potentially insurmountable hurdles: it greatly reduces the output of power plants; pipeline capacity to move the newly captured carbon dioxide is woefully insufficient; and the volume of waste material is staggering.”

Those of us familiar with the coal-fired power plant industry have long recognized that CCS may be slightly more than a pipe-dream, but will never be affordable or practicable for the vast majority of coal-fired plants. Yet no one in the bureaucracy has had the courage to stand up and refute this politically correct but scientifically bankrupt concept.

Lessons from a Broken Hockey Stick

Nor is CCS the only example. Perhaps the highest visibility science that needed a “Johnny” is the now infamous global warming hockey stick. Andrew Montford’s “The Hockey Stick Illusion – Climategate and the Corruption of Science” deconstructs the woeful practices leading to this canard that propelled the entire world toward economic investments that are likely as not to be entirely wasted.

In his book, Montford identifies individuals within the paleoclimatology community who argued that they would not have used the invalid data upon which the hockey stick depended. But, they did not come forward, nor were they allowed to “peer review” the work before its publication. And why was that?

It took an act of Congress to find a “Johnny” to sort out the hockey stick and explain why no one came forward. The resultant Wegman report concluded, among many other important things:

The politicization of academic scholarly work leads to confusing public debates. Scholarly papers published in peer reviewed journals are considered the archival record of research. There is usually no requirement to archive supplemental material such as code and data. Consequently, the supplementary material for academic work is often poorly documented and archived and is not sufficiently robust to withstand intense public debate. In the present example there was too much reliance on peer review, which seemed not to be sufficiently independent.

And Wegman recommended:

Especially when massive amounts of public monies and human lives are at stake, academic work should have a more intense level of scrutiny and review. It is especially the case that authors of policy-related documents like the IPCC report, Climate Change 2001: The Scientific Basis, should not be the same people as those that constructed the academic papers.

The “Plan B” Idea

Having indepdent peer review is not a new idea. In 2005, Steven Hayward suggested “Perhaps the time has come to consider competition as the means of checking the Intergovernmental Panel on Climate Change’s monopoly and generating more reliable climate science.”

The Heartland Institute made such an attempt with its “Non-Governmental International Panel on Climate Change” report and the Center for the Study of Carbon Dioxide and Global Climate has mounted an effort to continue this work. But these efforts have failed to produce a meaningful impact on the political process, largely because the authors do not operate within the “peer” community and do not publish in the peer-reviewed literature.

There are better models, however, and these could be adapted to science-based policy analyses. For example, by federal law, an investment prospectus must include sufficient specification of risk assumptions as to permit independent analysis of the proposal. In like measure, financial institutions’ annual reports require independent audit analysis before publication.

The key is independent replication of the analysis and evaluation of important assumptions.

In the cold war days, the military used an approach called “Team B.” This team (alternatively called the Red team) developed approaches to counter the efforts of Team A (the Blue team). Still in use today, it has some strengths and some weaknesses. Without question, however, it always sharpened the quality of Team A’s work, finding errors in analysis, weaknesses of assumptions and entire areas of interest that opened up Team A’s thought processes and analytical options.

Team B operated within the professional “community,” making its contributions instantly credible and mandatory for review by Team A and the eventual policy makers.

The Marshall Institute had engendered discussion of this approach for today’s scientific policy issues, as have members of the American Physical Society. In particular, Dr. William Happer, Cyrus Fogg Brackett Professor of Physics at Princeton University, member of the National Academy of Sciences, and Fellow of the American Physical Society (APS), has proposed a Team B approach within the APS. Without question, the APS has enough independent and qualified members to have been able to audit the critical work underlying the IPCC reports and inform journal publisher’s of the important analytical elements to which regular peer-reviewers should give special attention.

A Proposal

I have little confidence in Happer’s approach, however. It stands too far back from the critical scientific process and will make contributions too late in the policy process. Instead, we can take a page from the book of the existing science policy bureaucracy – environmental assessments.

Under the National Environmental Policy Act, a project using significant federal funds cannot move forward until some form of environmental assessment has been completed and approved. These assessments have, of course, been misused to delay and prevent projects. However, at their heart, they have significantly improved proposals with the potential to adversely impact the environment. Correcting to eliminate the pathologies of the process, something similar could be used in other areas.

In the context of science-based policy today, Team B would be the ne plus ultra peer-review group required for any scientific or engineering initiative (including grants and grant programs) that Congress or the Federal bureaucracy planned to fund above a trigger level, or which would have such an impact on the private sector. The trigger might be $500 million, for example.

Before Congress authorized expenditure of such funds, the bill sponsor would need to offer a Team B report that validated the basis otherwise offered to justify the expenditure. An National Science Foundation program manager wishing to fund a subject area that expands high-cost research would need a valid Team B analysis of the science to ensure the area of investigation is justified. The Department of Energy, the Interior Department and the Environmental Protection Agency would need a Team B report on their major research initiatives and regulatory proposals. Any major studies commissioned or conducted by the National Research Council (and its subsidiaries) would require a Team B review.

In every case, a Team B report would involve an independent replication of the analysis, including assumptions, selection and screening of data, logic of computer code, statistical analysis and presentation of data. The Team B report would have to demonstrate its independence, using the tools discussed in the Wegman report. 

This independence is a key aspect of a Team B approach. It would not be helpful to simply pit antagonists against each other; and, of course, one cannot permit the incestuousness observed in the Mann-Jones et al network. Rather, one wants a “one-off” approach.  In nearly every case, one would want a Team B to include a statistician familiar with the statistical methods used, but not familiar with the authors and perhaps only peripherally knowledgeable about the scientific subject. They can obtain the information about the subject from the subject matter specialists on the team. 

The real challenge is selecting subject matter specialists.  In cases where funding opportunities is controlled by cliques, there is even a greater problem. Because all Team B work should be done in the light of day, perhaps all one needs is an honest Team B.  (OK, call me Diogenes.) An open process, one that access the entire planet’s available and experienced scientific community through the internet, may be the guarantor of a quality project.

The Upside of Reform

While Wegman did not believe peer review ought to be through blogs, without question, without McIntyre’s efforts, as recorded on his blog site, Mann’s corrupt hockey stick would never have been exposed. A competent Team B could harvest the intellectual contributions from an engaged web-community to good effect, especially with regard to highly technical issues. Further, the anonymity of the web would allow specialists to provide critical information without having to be worried about being outcast by the specialists’ cliques.

Surely a Team B approach would evolve and mature over time. What is certain, however, is that even the threat of a Team B review would occasion a return to trustworthy science and a fundamental return to the bedrock principles of scientific inquiry. As Wegman, Montford and McIntyre have made unutterably clear, if we need heightened oversight of financial institutions, we surely need such heightened oversight of the science upon which we found science-related policies having large economic consequences.

Of course in the real world, if the politicians and/or EPA starts intervening in the energy sector, their actions will be far from the economist’s theoretical ideal. Then the case for such policy activism falls apart.

Frank’s Pros/Cons of Intervention

Frank’s opening paragraphs nicely summarize his views on climate policy:

FORECASTS involving climate change are highly uncertain, denialists assert — a point that climate researchers themselves readily concede. The denialists view the uncertainty as strengthening their case for inaction, yet a careful weighing of the relevant costs and benefits supports taking exactly the opposite course.

Organizers of the recent climate conference in Copenhagen sought, unsuccessfully, to forge agreements to limit global warming to 3.6 degrees Fahrenheit by the end of the century. But even an increase that small would cause deadly harm. And far greater damage is likely if we do nothing.

Frank goes on to quote a new MIT study, which paints an alarming scenario of damages from warming if world governments sit on their hands. In contrast, Frank argues that the cost to the economy of limiting greenhouse gases is not in the same ballpark. He sums up with, “In short, the cost of preventing catastrophic climate change is astonishingly small, and it involves just a few simple changes in behavior.”

So if the risks of inaction are potentially catastrophic, while the costs of preventive government measures are relatively trivial, then who but a fool or a stooge for Big Oil would question the need for immediate intervention?

Why Aren’t We Consulting the  “Scientific Consensus”?

The funny thing is, in order for me to present a less frightening scenario, I don’t have to dig up a paper from Richard Lindzen or a speech by James Inhofe. All I need to do is quote from the recent Economic Report of the President and the IPCC AR4.

From the Obama administration’s Economic Report, in a chapter ominously entitled, “TRANSFORMING THE ENERGY SECTOR AND ADDRESSING CLIMATE CHANGE” [.pdf], we learn:

[T]he projected losses for the most likely range of temperature changes are relatively modest. For example, at the Intergovernmental Panel on Climate Change’s most likely temperature increase of 3?C for a doubling of CO₂ concentration (concentrations in 2100 are likely to be higher), the projected decline is 1.5 percent of GDP. (Box 9-2, page 242, emphasis added)

To put that projected decline of 1.5 percent of GDP in context, note that the CBO puts the high-end estimate for the economic cost of Waxman-Markey above this figure (at 3.5 percent of GDP) for the year 2050. (Note that the two figures are measuring slightly different things, but the general point remains.)

In other words, we have the Obama administration’s own report admitting that the projected damages from “doing nothing” are lower than the high-end estimates of the cost of “doing something.” Granted, that might present a prima facie case for doing something, but it’s not nearly as open-and-shut as Frank would have you believe. Using the government’s own estimates, it’s entirely possible that government intervention would cause more damage than benefits, and that’s even with textbook policy implementation!

“Fat Tails”: The Small Chance of Catastrophe

Perhaps realizing that its admission of a likely 1.5 percent decline in the share of consumption in GDP would not inspire the public to gladly hand over the energy sector to the politicians, the president’s report went on to say:

The projected relationship between temperature changes and consumption losses is nonlinear—that is, the projected losses grow more rapidly as temperature increases. For example, while the projected loss for the first 3?C is 1.5 percent, the loss at 6?C is five times higher. And the estimated loss associated with an increase of 9?C is about 20 percent [of consumption’s share of GDP]…Overall, it is evident that policy based on the most likely outcomes may not adequately protect society because such estimates fail to reflect the harms at higher temperatures. (ibid, bold added)

Now we’re getting somewhere. A potential 20 percent hit to consumption is indeed frightening. But how likely is this outcome?

If we turn to the IPCC AR4, we have our answer, at least according to a suite of modeling teams across different emission scenarios:

To read the above chart, technically you need to integrate the curve over a range of temperature increases to find the probability that the actual warming will occur in that range. But simply eyeballing the chart shows that the Economic Report’s catastrophic 9C warming scenario has a virtually zero change of occurring.

Conclusion

I am not arguing that the MIT study is wrong, or that the CBO has correctly quantified the likely economic impacts of a cap-and-trade program. All I am pointing out is that the standard alarmist claims–as typified by Robert Frank–do not enjoy nearly as much evidence as their most vocal proponents would have us believe.

To take apart the case for climate alarmism, we don’t need to embrace the research of the “denialists.” We only need to look at the government and IPCC’s own reports.

While not an issue for estimates of future sea level rise (sea ice is floating ice which does not influence sea level), a significant expansion of Antarctic sea ice runs counter to climate model projections. As the errors in the climate change “assessment” reports from the IPCC mount, its aura of scientific authority erodes, and with it, the justification for using their findings to underpin national and international efforts to regulate greenhouse gases.

Some climate scientists have distanced themselves from the IPCC Working Group II’s (WGII’s) Fourth Assessment Report (AR4), Impacts, Adaptation, and Vulnerability, prefering instead  the stronger hard science in the Working Group I (WGI) Report—The Physical Science Basis. Some folks have even gone as far as saying that no errors have been found in the WGI Report and the process in creating it was exemplary.

Such folks are in denial.

As I document below, WGI did a poor job in regard to Antarctic sea ice trends. Somehow, the IPCC specialists assessed away a plethora of evidence showing that the sea ice around Antarctica has been significantly increasing—a behavior that runs counter to climate model projections of sea ice declines—and instead documented only a slight, statistically insignificant rise.

How did this happen? The evidence suggests that IPCC authors were either being territorial in defending and promoting their own work in lieu of other equally legitimate (and ultimately more correct) findings, were being guided by IPCC brass to produce a specific IPCC point-of-view, or both.

The handling of Antarctic sea ice is, unfortunately, not an isolated incident in the IPCC reports, but is simply one of many examples in which portions of the peer-reviewed scientific literature were cast aside, or ignored, so that a particular point of view—the preconceived IPCC point of view—could be either maintained or forwarded.

Background

The problems with the IPCC’s handling of the trends in Antarctic sea ice was first uncovered and presented a week or two ago in an article posted over at the World Climate Report—another blog with which I have been involved with for a long time.

In this MasterResource article, I have dug a bit deeper into what lies behind the IPCC’s “assessment” of the trends in Antarctic sea ice that is presented in its WGI Fourth Assessment Report. What I’ve uncovered clearly illustrates the difference between a “review” of the literature and an “assessment” of the literature. The former would include as much of the literature on the topic under consideration as possible, while the latter carefully selects from the literature to make a particular case. As such, the results of a “review” would be pretty constant across different assemblages of folks doing the reviewing, while the results of an “assessment” strongly depend on just who is doing the assessing. Case in point, compare the IPCC’s Fourth Assessment Report with the equally glossy and thick Assessment Report from the Nongovernmental International Panel on Climate Change (NIPCC). Both start with the same body of literature, and yet they arrive at completely different conclusions.

Getting into the Detail

This is clearly evident in the section on recent sea ice trends in Antarctica. The IPCC dedicates part of one paragraph to the topic (IPCC AR4 Chapter 4, Section 4.4.2.2, p. 350-351) incorporating one reference (“Comiso (2003)”) which turns out to be a book chapter (i.e. not part of the peer-reviewed literature). The NIPCC on the other hand dedicates two full pages to the subject and incorporates 14 citations from the peer-reviewed literature (NIPCC, Chapter 4, Section 4.2.1, p 152–154).

The IPCC concludes, after its brief analysis, that while there has been an apparent increase in the sea ice extent around Antarctica from 1979 through 2005, that the increase has been slight and not statistically significant.

The NIPCC, on the other hand, finds that the trend in Antarctic sea ice has been about 2 to 3 times as great as the IPCC reported and, in fact, is quite statistically significant.

True, the NIPCC Report was published after the IPCC Assessment, so it includes a few citations that were published in the literature subsequent to the IPCC inclusion deadline, but still, there were plenty of publications that were extant at the time of the IPCC preparation that should have better guided the IPCC finding.

For some reason, the IPCC opted to ignore the vast majority those papers (and associated datasets). Consequently, as we shall see, the NIPCC’s assessment turns out to be superior to the IPCC’s.

The fact that the IPCC’s assessment was extremely limited and narrow did not go unnoticed in the IPCC review process (the set of expert and government reviews for various drafts of the IPCC AR4 can be found here).

One commenter (Ola Johannessen, who himself has published on sea ice trends) complained about the First Order Draft of the AR4 Chapter 4 that:

Section 4.4.2.2 [the section on sea ice trends]: The presentation of hemispheric, regional and seasonal trends is also incomplete, misleading and biased to NASA work (Comiso).

To which the IPCC replied:

Taken into account in the revised text.

A look at the final, published version of Section 4.4.2.2 shows that, in fact, there is only one reference to data on sea ice trends, that to Comiso (2003). The only other reference in the section (Belchansky et al., 2005) is to explain reasons for interannual variability and the Belchansky et al. reference was already present in the First Order Draft. So it hardly seems like Johannessen’s comments were “taken into account,” instead it seems like they were ignored.

Johannessen further complains about IPCC’s use of only one sea ice dataset, commenting “There should be a sentence added before ‘An updated version of the analysis done by Comiso…’ (which, by the way, appears to an update that is not a published or accepted paper)” and then going on to suggest many additional references that should be added to this section. The IPCC responds:

“Taken into account with the inclusion of Johannessen et al. (2004) work. But AR4 is meant to be the most recent assessment, not a history of prior assessments. Updates of data sets using previously published methodology is acceptable for IPCC.”

Interesting. First, in the published version of Chapter 4, the reference to Johannessen et al. (2004) does not appear in the section of the Chapter 4 under discussion—so apparently the IPCC was just bluffing about including it. Second, the IPCC affirms that being an “assessment” doesn’t mean having to include all relevant literature (i.e., it includes only literature that it deems to be relevant). And third, that using updates of previously published datasets is acceptable in the IPCC process.

In this case, points 2 and 3 seem opposed to each other. For the IPCC has deemed one particular dataset, that of Comiso (2003), to be most relevant, despite the fact that several other “recent” datasets existed.

Let’s look into the IPCC’s reliance on Comiso (2003) a bit further (Comiso by the way was a contributing author to IPCC AR4 Chapter 4).

The IPCC reference of their sea ice data is to Comiso (2003) which is the following book chapter (available here):

Comiso, J.C., 2003: Large scale characteristics and variability of the global sea ice cover. In: Sea Ice – An Introduction to its Physics, Biology, Chemistry, and Geology [Thomas, D. and G.S. Dieckmann (eds.)]. Blackwell Science, Oxford, UK, pp. 112–142.

The analyses in this book chapter use a sea ice algorithm developed and improved by Dr. Josefino Comiso during the 1980s and 1990s (Comiso’s technique was known as the “Bootstrap” algorithm). At the same time, there was another algorithm to derive sea ice from satellite observations that had been developed and improved by Dr. Donald Cavalieri and colleagues during the same span (Cavalieri et al.’s technique was known as the “NASA Team” algorithm). Both algorithms produced pretty similar results when deriving sea ice extent in the Arctic, but in the Antarctic regions, the results—especially the trend results—differed rather significantly. This difference was well-recognized in the peer-reviewed scientific literature (e.g. Zwally et al., 2002; Comiso and Steffen, 2001). Comiso’s Bootstrap method produced a much smaller and insignificant increase in Antarctic sea ice while the NASA Team algorithm produced a larger, statistically significant increase. Another analysis, by Watkins and Simmonds (2000) produced a trend that agreed better with the NASA Team results than Comiso’s Bootstrap results.

All these facts were acknowledged by the researchers involved as evidenced by discussions in Zwally et al. (2002) and Comiso and Steffen (2001), with each group more or less showing more reliance on their own methodology.

Further, an update to the NASA Team algorithm (known as NASA Team version 2) was published by Markus and Cavalieri in 2000. This update had the impact of producing an even greater trend in the extent of Antarctic sea ice (over the original NASA Team algorithm) and enlarging the discrepancy with Comiso’s Bootstrap algorithm.

All of this was extant in the peer-reviewed literature at the time of the IPCC AR4 production and yet the IPCC “assessed” things this way:

Most analyses of variability and trend in ice extent using the satellite record have focused on the period after 1978 when the satellite sensors have been relatively constant. Different estimates, obtained using different retrieval algorithms, produce very similar results for hemispheric extent, and all show an asymmetry between changes in the Arctic and the Antarctic. As an example, an updated analysis done by Comiso (2003) spanning the period November 1987 through December 2005, is shown in Figure 4.8. [emphasis added]

The statement in bold above was well-established at the time to be wrong, at least as it applied to the Southern Hemisphere. So obviously, even at this point, it is clear that the IPCC had conducted an inaccurate “assessment” of the literature.

Not surprisingly, of the existing “retrieval algorithms,” the one which showed the smallest (and statistically insignificant) trend in the Southern Hemisphere was the one used in “Comiso (2003)” which was selected as the example used by the IPCC.

How convenient.

It is even somewhat debatable whether even the “updated analysis done by Comiso (2003)” showed an insignificant trend.

The First Order Draft of Chapter 4 contained the following illustration of Southern Hemisphere sea ice, along with the caption “Sea Ice extent anomalies … the Southern Hemisphere based on passive microwave satellite data… [l]inear trend lines are indicated for each hemisphere….the small positive trend in the Southern Hemisphere is not significant. (Updated from Comiso, 2003).”

Figure 1. Figure 4.4.1b from the IPCC AR4 Chapter 4 First Order Draft.

Notice two things, 1) the figure depicts monthly ice extent anomalies from November 1978 through October 2004, and 2) the trend through them seems to be statistically significant (i.e. the confidence range does not include zero), given in the illustration as 9089.2 +/- 2970.7 km²/year or 0.735 +/- 0.240%/dec.

Yet, for some reason, the accompanying text claims that the trend in Figure 4.4.1b is insignificant (AR4 First Order Draft, page 4-14, lines 9-10):

The Antarctic results show a slight but insignificant positive trend of 0.7 ± 0.2% per decade.

This inconsistency was brought to the IPCC Chapter 4 authors’ attention by several IPCC commenters. Commentor John Church wrote “I do not understand why this trend is insignificant – it is more than three times the quoted error estimates” and Stefan Rahmstorf wrote “How can a trend of 0.7 +/- 0.2 be ‘insignificant’? Is not 0.2 the confidence interval, so it is significantly positive?” The IPCC responded to both in the same manner “Taken into account in revised text.”

And boy did they ever!

The Second Order Draft of Chapter 4 included the following figure (which ultimately was the one included in the final publication):

Figure 2. Figure 4.4.1b from the IPCC AR4 Chapter 4 Second Order Draft (this graphic was Figure 4.8 in the IPCC AR4 published version of Chapter 4).

The caption still read “the small positive trend in the Southern Hemisphere is not significant” but now the trend had become “5.6 +/- 11 x 10³ km² per year.”

Note two things 1) the monthly sea ice anomalies were replaced by annual anomalies, and 2) the trend shrunk by 38% and now actually was statistically insignificant.

So how did this come about?

First off, the IPCC used a well known statistical trick to lower the significance of the increase—that is, switch from monthly values to annual values. This trick generally has little impact on the trend value, but can have a sizeable impact on the statistical confidence of the trend. A trend that is supported by a larger amount of individual data points (in this case, monthly values) has more statistical confidence than the same trend supported by fewer data point (in this case annual data values). So, by using annual data instead of monthly data, the IPCC effectively lowered the perceived confidence of the Southern Hemisphere sea ice trend.

Secondly, just how did the trend drop by 38% when adding another 13 months’ worth of observations? Well, it is not because of the influence of those extra months, as they fell very near the established trend line (in other words, they had little direct influence on the trend). And switching from monthly to annual data also wouldn’t do it. So it had to be something else. One possible explanation is that the figure from the First Order Draft was actually (mistakenly) depicting Comiso’s determination of the area of sea ice, rather than the extent of sea ice. There is a difference in definition between these terms. The sea ice extent is taken to mean the area which is covered by sea ice with a concentration of at least 15% (i.e. this includes regions that are 85% open water), while sea ice area is taken to be the actual area of sea ice itself (so the sea ice area is less than the sea ice extent). Under general circumstances, the two measurements are highly correlated, and their trends are very similar. However, in the case of the Comiso’s Bootstrap algorithm, the trends in Southern Hemisphere sea ice extent and sea ice area were largely different. This fact raised some flags of concern at the time. Zwally et al. (2002) noted that the Bootstrap sea ice extent trends were the odd man out of all datasets. The area trends were similar across retrieval algorithms (all were significantly positive, including Comiso’s Bootstrap) and the extent trends were similar to the area trends in all algorithms except Comiso’s Bootstrap algorithm. Zwally et al. (2002) took this to mean that something was likely wrong with the Bootstrap determinations of Southern Hemispheric sea ice extent (probably involving how data from two satellites was stitched together). Comiso and Steffen (2001) also noted the difference in the trend between sea ice area and extent produced by the Bootstrap algorithm, they attributed most of the difference to changes in how tightly the sea ice was packed together (a mechanism dismissed by Zwally et al.) but admitted that inter-satellite issues may also play a part in the trend differences.

Bottom line is that not only did the IPCC Chapter 4 authors have to carefully choose which sea ice retrieval algorithm to use, but they also had to be careful to use sea ice extent rather than sea ice area (somthing they quite possibly forgot that they needed to do in the First Order Draft of Chapter 4).

The IPCC justifies these decisions as being the result of their “assessment” of the topic and the literature—decisions that just so happen to minimize the apparent increase in Southern Hemispheric sea ice concentration. The result of the inclusion of any other then-extant dataset on Southern Hemispheric sea ice would have been to counter the IPCC’s “assessment” that the sea ice increase there was statistically insignificant.

Oh yeah, an “assessment” of a significant rise in Southern Hemispheric sea ice would have been quite inconvenient to another IPCC “assessment” that “[s]ea ice is projected to shrink in both the Arctic and the Antarctic under all SRES scenarios.” So, no doubt the IPCC Chapter 4 Coordinating Lead Authors got a big slap on the back from the IPCC brass for avoiding that potentially embarrassing problem.

Parenthetically, I bet it would be fun to see the emails associated with the production of AR4 Chapter 4!

One last thing.

Less than a year after the IPCC AR4 was published, Comiso reported that indeed there was a problem with the Bootstrap algorithm as it concerned Southern Hemispheric sea ice extent (Comiso and Nishio, 2008). Correcting that problem increased the observed trend in Antarctic sea ice extent from November 1978 to December 2005 to 14,645 km²/year—a highly statistically significant value that is 2.6 times higher than reported by the IPCC and virtually identical to the trend from the updated NASA Team algorithm, described by Markus and Cavalieri in 2000 but completely ignored by the IPCC. Basically, everyone but Comiso (and the IPCC) was right all along.

Figure 3. Annual Antarctic sea ice anomalies from three datasets: the one used by the IPCC (Comiso, 2003; red); another extant at the time of the IPCC production (Markus and Cavalieri, 2000; blue); and the update to the IPCC analysis (Comiso and Nishio, 2008; cyan). The trend in the latter two datsets are more than 2.5 times larger than the IPCC trend and both are statistically significant (the IPCC trend is not).

Conclusion

On the topic of Antarctic sea ice trends, the “consensus of scientists”—as the IPCC likes to call itself—was wrong, led astray by the extremely poor “assessment” of the scientific knowledge-base made by a very few people who were directly involved in preparing that section—people who were either being territorial in defending and promoting their own work, were being guided by higher-ups to produce a specific IPCC point-of-view, or both.

From all I have been able to find out about this so far (including enlightenment gained from the Climategate emails into how other sections of the AR4 were carefully constructed), I would rate it “extremely unlikely” (in IPCC parlance, less than 5% chance) that what transpired was dumb luck, born of the IPCC authors’ unfamiliarity with the peer-reviewed literature—the very thing they were supposed to be assessing.

I am not sure which case is the most embarrassing.

References:

Comiso, J.C., 2001. Studies of Antarctic sea ice concentrations from satellite data and their applications. Journal of Geophysical Research, 106, C12, 31361-31385.

Comiso, J. C., and F. Nishio, 2008. Trends in the sea ice cover using enhanced and compatible AMSR-E, SSM/I, and SMMR data. Journal of Geophysical Research, 113, C02S07, doi:10.1029/2007JC004257.

Cavalieri, D. J., P. Gloersen, C. L. Parkinson, J. C. Comiso, and H. J. Zwally, 1997. Observed hemispheric asymmetry in global sea ice changes. Science, 278, 1104–1106.

Cavalieri, D. J., C. L. Parkinson, P. Gloersen, J. C. Comiso, and H. J. Zwally, 1999. Deriving long-term time series of sea ice cover from satellite passive microwave multisensor data sets. Journal of Geophysical Research, 104, 15803–15814.

Markus, T., and D. Cavalieri, 2000. An enhancement of the NASA Team sea ice algorithm. IEEE Transactions on Geoscience and Remote Sensing, 38, 1387-1398.

Watkins, A. B., and I. Simmonds, Current trends in Antarctic sea ice: The 1990s impact on a short climatology, 2000. Journal of Climate, 13, 4441–4451.

Zwally, H.J., J. C. Comiso, C. L. Parkinson, D. J. Cavalieri, 2002. Variability of Antarctic sea ice 1979-1998. Journal of Geophysical Research, 107, C5, 3041, doi:10.1029/2000JC000733.

[Editor note: The author has added an update at the end showing why it can be reasonably argued that anthropogenic greenhouse gases may be responsible for less than half of the observed warming since the mid-20th century]

Back in December, the EPA announced that it had determined that greenhouse gases released by human activities “threaten the public health and welfare of current and future generations.” This “Endangerment Finding” is the first step toward EPA’s issuing regulations aimed at restricting GHG emissions in the U.S.

Unfortunately for the EPA, a major pillar of support of the Endangerment Finding—that “most” of the “observed warming” since the mid-20th century is from greenhouse gas emissions from human activities—has been shown by recent scientific research in major peer-reviewed scientific journals to be largely in doubt.

Add this result to the list of problems that seems to grow longer with each passing day as more IPCC gaffes are uncovered and Climategate emails are parsed. One has to wonder just how long it will be until the EPA is challenged to reconsider its Endangerment Finding.

The basis for the Engangerment Finding is contained in the EPA’s Technical Support Document for Endangerment and Cause or Contribute Findings for Greenhouse Gases under Section 202(a) of the Clean Air Act (TSD). The TSD does not describe any new, independent research carried out by the EPA (because they did not undertake any), but instead largely summarizes the findings of the Intergovernmental Panel on Climate Change (IPCC).

One of the key statements (from page 2 of the Executive Summary of the EPA’s TSD) is this—a simple mimic the IPCC AR4 finding:

Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic GHG [greenhouse gas] concentrations.

As I shall show, this statement is no longer tenable.

Background

First off, here is my take on what the EPA/IPCC is claiming.

For “most” I’ll assume “more than half.” For “observed increase in global temperature” I’ll assume the linear least-squares regression trend through the most recent version of the global temperature dataset compiled jointly by the U.K.’s Hadley Center and Climate Research Unit (dataset HadCRUT3). There are other global temperature compilations (most notably from NASA and NOAA) and while there are certainly notable differences over the short run, over the longer term, they are very similar. “Since the mid-20th century” I’ll take as 1950. The EPA defines what it means by “very likely” in the Table I reproduced below—they mean “with a 90-99% probability.” And for “observed increase in GHG concentrations”, I’ll assume the greenhouse gases explicitly mentioned by the EPA (CO2, CH2, N2O, HFCs, PFCs, SF6).

TABLE 1. EPA’s “Description of likelihood”

Likelihood refers to a probabilistic assessment of some well defined outcome having occurred or occurring in the future, and may be based on quantitative analysis or an elicitation of expert views. When authors evaluate the likelihood of certain outcomes, the associated meanings are:

Virtually certain ………. >99% probability of occurrence

Very likely ………. 90 to 99% probability

Likely ………. 66 to 90% probability

About as likely as not ……….. 33 to 66% probability

Unlikely ……… 10 to 33% probability

Very unlikely ……… 1 to 10% probability

Exceptionally unlikely ………. <1% probability

As to what the “observed increase in global average temperature since the mid-20th century” has been, I present Figure 1—the annual HadCRUT3 global temperature record from 1950 to 2009. The trend line has value of 0.117°C/decade which amounts to a total temperature increase of 0.702C over the 60 years from 1950.

Figure 1. Observed global temperature history, 1950-2009 (data source: Hadley Center).

So that’s what we are starting with. The EPA is 90 to 99% certain that at least 0.35°C of warming in the extant (“observed”) record is from GHG emissions from human activity.

Now, let’s see what happens when we start to factor in recent findings.

Corrections to the “Observed” Record

First off, about a year after the IPCC released its AR4 report (from which the EPA took its statement), David Thompson and colleagues published a paper in Nature magazine titled “A large discontinuity in the mid-twentieth century in observed global-mean surface temperature.” In it, they documented how a change in observing practices before and after World War II produced a cold bias in the sea surface temperatures that were incorporated into the compilations of global average temperatures (see here and here for more details). Thompson et al. were unable to correct this bias (so it remains in the extant “observed” global temperature histories) but suggested that:

The adjustments immediately after 1945 are expected to be as large as those made to the pre-war data (~0.3°C), and smaller adjustments are likely to be required in SSTs through at least the mid-1960s, by which time the observing fleet was relatively diverse and less susceptible to changes in the data supply from a single country of origin.

The U.K.’s The Independent newspaper reproduced a graphic (from by the Climate Research Unit) that generally illustrated what the correction to the dataset may look like when it is finally applied.

The Independent’s chart basically shows what the Thompson et al. paper described—about a +0.3°C correction after about 1945 slowly declining to zero by the mid-1960s.

Figure 2 shows what happens when I apply this correction to the “observed” data in Figure 1 and then re-calculate the temperature change. The overall warming trend declines from the “observed” rate of 0.116°C/decade to a “corrected” rate of 0.092°C/decade. So EPA’s “observed increase in global average temperatures since the mid-20th century” has now dropped from 0.702°C to a “corrected” value of 0.552°C and 21% of EPA’s increase from “anthropogenic GHG” increases has now vanished, lost to errors in the observed data.

Figure 2. Observed global temperature history, 1950-2009 (black). “Corrected” global temperature history (following to Thompson et al., 2008) (red line).

Stratospheric Water Vapor

Now consider the results of a paper published just a few weeks ago in Science magazine by Susan Solomon and colleagues. They report that variations in the water vapor content in the lower stratosphere (apparently largely unrelated to GHG changes) have a large influence on the rate of global temperature change for periods of a decade or more. In fact, since 1980 (the start of the data analyzed), an overall increase in stratospheric water vapor content as been responsible for perhaps 15% of the overall temperature increase.

It is impossible from Solomon et al.’s analysis to know what went on prior to 1980, so, for lack of any other guidance, I’ll assume that no changes took place (or, that the net change was zero) from 1950 to 1980. I’ll then back the 15% warming influence from stratospheric water vapor changes since 1980 out of the “corrected” data in Figure 2. The warming I am left with is shown in Figure 3.

The overall trend declines to 0.081°C/decade (or a total rise of 0.486°C).

Now the EPA’s “observed increase in global average temperatures since the mid-20th century” has dropped from 0.702°C down to 0.486°C—and about 31% of increase from anthropogenic GHGs is gone.

Figure 3. Observed global temperature history, 1950-2009 (black). “Corrected” global temperature history (red line). “Corrected” temperature history with general influence of stratospheric water vapor (according to Solomon et al., 2010) removed (green line).

Influence of Black Carbon

Finally, consider the results from Ramanathan and Carmichael published in Nature Geoscience last year. These researchers reviewed the scientific understanding of how black carbon aerosols (aka soot) warm the earth’s climate. Black carbon is not a GHG. Black carbon warms the earth by directly absorbing reflected solar radiation and also by darkening the surface of snow and ice when it is deposited there (and enhances melting). Ramanathan and Carmichael determined that in toto black carbon has been responsible for about 25% of the overall warming.

The result of factoring out this non-GHG warming is illustrated in Figure 4. The 1950-2009 trend drops to 0.061°C/decade.

Figure 4. Observed global temperature history, 1950-2009 (black). “Corrected” global temperature history (red line). “Corrected” temperature history with general influence of stratospheric water vapor (according to Solomon et al., 2010) removed (green line). “Corrected” temperature history with general influence of stratospheric water vapor (according to Solomon et al., 2010) removed and the influence of black carbon (according to Ramanathan and Carmichael, 2009) removed (blue line).

The remaining warming—that which possibly could be caused by anthropogenic GHG increases—now stands at about 0.366°C—or just 52% of the EPA’s “observed” increase.

Conclusion—The EPA is Wrong

And I have only included the best estimates from Solomon et al. and Ramanathan and Carmichael. In fact, both studies include a range of estimates. Had I used the low end of the ranges, the remaining warming from GHGs would have been quite a bit less than 50% of the “observed” warming.

Also, I used a pretty conservative “correction” based on Thompson et al. Others contend that the “correction” should be larger, and in and of itself could invalidate the EPA/IPCC “most likely” description.

And, I didn’t include any warming from things such as urbanization, land-use change, site changes, or other natural variability—which have been by some studies to have a detectable (warming) impact.

So, if we take what the best science gives us, we find that pretty close to half of the warming that is currently indicated by the extant global temperature datasets may be from influences other than anthropogenic greenhouse gas increases—perhaps a bit less, perhaps a bit more.

Heading back to the EPA’s Description of Likelihood Table (above) we find that instead of “very likely,” probably the most apropos descriptor is found a couple of lines down, the one that encompasses a 33 to 66% probability—or “about as likely as not.”

Somehow, I think that if the EPA had written:

It is about as likely as not that most of the observed increase in global average temperatures since the mid-20th century is due to the observed increase in anthropogenic GHG concentrations.

that EPA’s justification for their Endangerment Finding would “very likely” have been considerably less compelling.

IPCC mistakes, Climategate perversions, and now new major scientific findings all demand the same thing—that EPA reconsider its Endangerment Finding as the validity of its scientific underpinnings is badly in need of update and reappraisal.

Update: Febuary 12, 2010

I have had several inquiries into what the remaining warming would look like if I incorporated the potential effect of non-climatic warming influences (e.g., urbanization, other landscape changes, instrument changes, network quality, etc.). I ran through a middle-of-the road estimate in Comment#6, that I’ll now move up into the post.

It goes something like this:

It is hard to know what a middle-of-the-road estimate from non-climatic influences on the land surface temperature observations may be. Brohan et al. (who developed the HadCRUT3 record) estimate the influence to be 0.005°C/decade. McKitrick and Michaels (2007) on the other hand, estimate it to be nearly 50% of the trend in the land record. This probably defines the range on influence.

Since the land only makes of 30% of the planet, each of the above estimates must be roughly reduced by 70% to be applied to the global record (details may vary). Or, respectively, 0.002°C/decade and 15%.

Applying each to the “corrected” decadal rate from 1950 to 2009 (which is 0.092°C/decade), yields 0.090°C/dec (from Brohan et al.) and 0.078°C/dec (from McKitrick and Michaels).
So, erring on the conservative side, let’s take 0.085°C/decade as the observed rate after correcting for the Thompson et al. error and non-climatic warming.

Working through the rest of my calculations (i.e., stratospheric water vapor and then black carbon) using the new 0.085°C/decade baseline leaves a trend of 0.056°C/decade that could potentially be from anthropogenic GHGs, or a total potential temperature rise of 0.337°C—which is 48% of the current “observed” value—or less than half of the current “observed” warming from the mid-20th century.

I’ve created a new, simplified chart to show the total effect of all the non-GHG adjustments (that I considered, perhaps there are others) to the “observed” temperature history. The black red line in the Figure below is the original warming trend as contained in the most-up-to-date “observed” temperature record, and the red blue line is the remaining (“adjusted”) trend after all non-GHG influences have been removed. The remaining trend is just 48% of the original trend. In other words, it can be reasonably argued that anthropogenic GHGs could be responsible for a minority of the observed warming since the mid-20th century.

Update Figure. Global temperature history, 1950-2009. The black red line in the Figure is the original warming trend as contained in the most-up-to-date “observed” temperature record (HadCRUT3), and the red blue line is the remaining (“adjusted”) trend after non-GHG influences have been removed.

References:

Ramanathan V., and G. Carmichael, 2009. Global and regional climate changes due to black carbon. Nature GeoScience, 1, 221-227.

Solomon, S., et al. 2010. Contributions of stratospheric water vapor to decadal changes in the rate of global warming. Science, published on-line January 28, 2010.

Thompson, D., et al., 2008. A large discontinuity in the mid-twentieth century in observed global-mean surface temperature. Nature, 453, 646-649.