John Christy

An Oldie But A Goodie: John Christy’s Letter to Lisa Jackson on Fuel Economy Regulation

by Marlo Lewis on April 28, 2010

Well, it’s not really so old. I’m referring to a March 10, 2009 letter by atmospheric scientist John Christy to EPA Administrator Lisa Jackson. I post it on Open Market and GlobalWarming.Org because it is hard to find on the Internet, and Dr. Christy makes a key point that will need to be made again and again in the upcoming Senate battle over the Murkowski resolution of disapproval to veto EPA’s endangerment finding.

The endangerment finding is the statutory prerequisite for the joint greenhouse gas/fuel economy standards rule that EPA and the National Highway Traffic Safety Administration (NHTSA) finalized on April 1, 2010. Veto the endangerment finding, Murkowski foes warn, and NHTSA will have to ”de-couple” its portion of the joint GHG/fuel economy rule, which could delay by a year implementation of model year 2012 fuel economy standards.

Well, boo-hoo! Keeping the model year 2011 standards in place for an extra year would make no perceptible difference in atmospheric CO2 concentrations, average global temperature, weather patterns, or public health, even if one assumes that climate change is a big problem.

Christy’s letter puts this in perspective. For the sake of argument, Christy adopts the IPCC’s warming projections for its mid-range (A1B) emissions scenario. Even if the United States were to adopt immediately a 43 mpg fuel-economy standard, the net reduction in average global temperature would be 0.01°C in 2100. Such a change would be too small to detect. Even more microscopic would be the impact of the 34.1 mpg standard that NHTSA and EPA want to phase in by model year 2016. Whether that standard is delayed for a year or implemented on schedule is climatologically irrelevant.

In contrast, the economic and safety benefits of a one-year delay could be substantial. The distressed auto industry would not have to spend an estimated $5.9 billion in incremental technology investments (Table 4A.5-6) in model year 2012.

In addition, slower implementation of economy standards would slow the pace at which automakers decrease average vehicle size and weight. Reducing vehicle weight and size is a vintage method of improving fuel economy — but it also negatively affects vehicle safety. NHTSA’s 2002 fuel economy report concluded that regulatory-induced vehicle downsizing contributed to 1,300-2,600 fatalities and 13,000 to 26,000 serious injuries in 1993, a typical year.

EPA and NHTSA struggle to belittle the size-safety tradeoff in their joint rule. However, they do include a “worst-case” scenario in which the new standards cause an additional 493 deaths in model year 2016 (see p. 144). Slowing the pace of fuel economy regulation would save lives.

Real Climate Spin

by Marlo Lewis on November 24, 2009 · 2 comments

in Features, Global Warming, Zeitgeist

Real Climate.Org is chief defender of ”consensus” climatology on the Internet. One of its enduring missions has been to defend the dubious, indeed discredited “Hockey Stick” reconstruction of Northern hemisphere temperature history. The Hockey Stick was the basis for the IPCC’s claim in its 2001 report that the 1990s were the warmest decade and 1998 the warmest year of the past millennium.

That Real Climate (RC) should feel special solicitude for the Hockey Stick is no accident, comrade. Two of the five principals at RC — Michael Mann and Raymond Bradley — were among the three researchers (Mann, Bradley, and Malcolm Hughes) who authored the Hockey Stick.

All of the RC principals (Gavin Schmidt, Caspar Ammann, Rasmus Benestad, Mann, and Bradley) are frequent senders and recipients of the thousands of emails and other documents, now posted on many Web sites, that were hacked or leaked last week from the University of East Anglia’s Climate Research Unit (CRU).

The Wall Street Journal today published a selection of the leaked emails and an editorial concluding that the emails ”give every appearance of testifying to concerted and coordinated efforts by leading climatologists to fit the data to their conclusions while attempting to silence and discredit their critics.”

Even eco-radical George Monbiot says he is “dismayed and deeply shaken” by the emails, because, “There appears to be evidence here of attempts to prevent scientific data from being released, and even to destroy material that was subject to a freedom of information request.”

So far, the only email on which RC has seen fit to comment is one from CRU director Phil Jones dated Nov. 16, 1999, 13:31. It’s gotten a lot of buzz on the Internet, because it appears to advocate the use of a “trick” to “hide” a “decline” in global temperatures.

In a post titled “The CRU Hack” (November 20), RC writes:

No doubt, instances of cherry-picked and poorly-worded “gotcha” phrases will be pulled out of context. One example is worth mentioning quickly. Phil Jones in discussing the presentation of temperature reconstructions stated that “I’ve just completed Mike’s Nature trick of adding in the real temps to each series for the last 20 years (ie from 1981 onwards) and from 1961 for Keith’s to hide the decline.” The paper in question is the Mann, Bradley and Hughes (1998) Nature paper on the original multiproxy temperature reconstruction, and the ‘trick’ is just to plot the instrumental records along with reconstruction so that the context of the recent warming is clear. Scientists often use the term “trick” to refer to a “a good way to deal with a problem”, rather than something that is “secret”, and so there is nothing problematic in this at all. As for the ‘decline’, it is well known that Keith Briffa’s maximum latewood tree ring density proxy diverges from the temperature records after 1960 (this is more commonly known as the “divergence problem”–see e.g. the recent discussion in this paper) and has been discussed in the literature since Briffa et al in Nature in 1998 (Nature, 391, 678-682). Those authors have always recommend not using the post 1960 part of their reconstruction, and so while ‘hiding’ is probably a poor choice of words (since it is ‘hidden’ in plain sight), not using the data in the plot is completely appropriate, as is further research to understand why this happens.

So a “trick” is just scientific shorthand for a “good way to deal with a problem,” not something “secret.” But RC ducks the real issue. Is the ”trick” Phil Jones learned from Hockey Stick author Michael Mann a form of trickery? Does it create a false impression, as an illusionist does on stage, right out in the open, in front of an audience?

The trick, according to RC, is to splice onto the end of a temperature reconstruction, built on proxy data going back several centuries, the data from instrumental records starting in 1960 and 1981.

Now this is quite a trick, because it involves comparing apples (proxy data) to oranges (instrumental data) and pretending that the composite forms a continuous record.

As the Center for the Study of Carbon Dioxide and Climate Change observed years ago, researchers attempting to construct long-term (centuries to millennia) temperature records should ”finish the dance” with the (proxy) data they started with.

Grafting instrumental data onto proxy data to produce a seemingly continuous record is trickery, because instrumental data, unlike proxy data, are massively influenced by land-use changes and site-specific quality control issues.

Urban heat islands and irrigated agriculture can inject false warming biases into instrumental data that are absent from proxy data taken from remote forests or sediment cores at the bottom of lakes, for example. Improper placement of temperature sensing equipment near local heat sources (e.g. air conditioning vents, asphalt parking lots, waste water treatment plants) also generates significant false warming signals, as retired meteorologist Anthony Watts documents in gory detail.

So RC’s “nothing to see here” argument based on the alleged insider meaning of “trick” raises rather than allays suspicion that CRU is attempting to fit data to a predetermined conclusion.

Note also that RC says nothing about Phil Jones’s advice to backdate correspondence (Sept. 12, 2007, 11:30 a.m.), to delete emails related to the 2007 IPCC report (May 29, 2008, 11:04), and to evade FOIA requests, if necessary by deleting files (Feb. 2, 2005, 9:41 a.m.). RC also says nothing about Mann’s call to delegitimize the Journal of Climate for publishing papers critical of his work (March 11, 2003, 8:14).

The Wall Street Journal editorial’s concluding comment is spot on: ”In the department of inconvenient truths, this one surely deserves a closer look by the media, the U.S. Congress and other investigative bodies.”

No data, no science

by Marlo Lewis on September 24, 2009 · 3 comments

in Global Warming, Legal

In “The Dog Ate Global Warming,” published yesterday in National Review Online, Cato Institute scholar and climatologist Patrick J. Michaels delivers a body blow to the “science is settled” dogma.

There are three core issues in climate change science: detection (Is it warming, and if so by how much); attribution (What’s causing the warming we observe?); and, sensitivity (How much warming will a given increase in greenhouse gas concentrations produce?). As I argue in a previous post, all of these issues remain unsettled, and more so today than at any time in the past decade.

Although climate sensitivity is the most important issue (because if climate sensitivity is low, then there is no “planetary emergency,” hence no need for “urgent action”), detection is in a sense primary, because without reliable temperature data it is impossible to resolve the other two issues.

The claim that the latter half of the 20th century was warmer than any comparable period during the past 1300 years is largely based on surface temperature records subject to several well-known warming biases. Urbanization generates artificial “heat islands.” Agriculture and irrigation in places like California’s Central Valley also produce local warming effects. Retired meteorologist Anthony Watts has documented that nearly nine out of every 10 U.S. weather stations fail to meet the U.S. Weather Service’s minimum requirement that temperature sensing equipment be placed at least 30 meters (about 100 feet) away from artificial heat sources such as air conditioner exhaust vents, waste water treatment plants, and parking lot pavements.

Michaels now exposes the shocking fact that the data allegedly underpinning the most influential surface temperature record are missing and apparently have been destroyed. The record is known as Jones-Wigley for its authors, Phil Jones of the University of East Anglia Climate Research Unit (CRU) and Tom Wigley of the National Center for Atmospheric Research (NCAR). The IPCC relied exclusively on this record until its 2001 report.

For years, Jones and Wigley declined to share the raw data from which they constructed their record. Recently, however, Jones told University of Colorado Professor Roger Pielke, Jr. that they could not share their data with him, because the data no longer exist:

Data storage availability in the 1980s meant that we were not able to keep multiple sources for some sites, only the station series after adjustment for homogeneity issues. We, therefore, do not hold the original raw data but only the value-added (quality-controlled and homogenized) data.

Michaels says the “data storage availability” excuse is “balderdash,” since “All the original data could easily fit on the 9-inch tape drives common in the mid-1980s.”

The bigger point, of course, is that if other scientists cannot examine the raw data, they cannot assess the accuracy and objectivity of the “value-adding” adjustments Jones and Wigley made to produce their global temperature record.

In addition to providing another reason to reject the “science is settled” dogma, disappearance of the Jones-Wigley data is of direct relevance to EPA’s pending endangerment finding. The Jones-Wigley temperature record is part of the evidence on which EPA bases its judgment that “air pollution” from greenhouse gas emissions “endangers public health and welfare.”

Use of the Jones-Wigley temperature record in a rulemaking clearly flouts federal data quality standards. Under OMB guidelines implementing the Federal Data Quality Act, data quality consists of four elements: objectivity, utility to users, integrity of information, and reproducibility in the case of “influential scientific or statistical information.”

Now, if the original Jones-Wigely data have been destroyed, then it is impossible to assure “integrity of information.” For all we know, Jones and Wigley goofed in their calculations or choice of methodologies, or even manipulated the data to produce a pre-determined result. By the same token, it is impossible to “reproduce” the Jones-Wigley temperature record, because there are no data to reproduce it from. Yet, as a factual basis of both the IPCC reports and the EPA endangerment finding, Jones-Wigley indisputably qualifies as “influential scientific or statistical information.”

Michaels’s terse conclusion speaks volumes: “No data, no science.” For decades, Jones-Wigley has been a mainstay of the alleged ”scientific consensus” supporting Kyoto-style energy rationing. Warmists have a lot of explaining to do.

PNAS: Peer Review or Old Boy Network?

by Marlo Lewis on September 23, 2009 · 1 comment

in Global Warming

On February 25, 2009, Dr. James Hansen of Columbia University’s Earth Institute and Dr. John Christy of the University of Alabama in Huntsville testified on “Scientific Objectives for Climate Change Legislation,” before the House Ways and Means Committee.

Dr. Hansen is probably the world’s most influential scientist in the climate alarmist camp. His 1988 congressional testimony, which projected significant increases in global temperatures over the next two decades, gave birth to the warming movement.

At the Ways and Means hearing, Christy testified that datasets he and his colleagues have developed contradict the climate model hypotheses and surface temperature records on which alarmism rests. His leading example was the discrepancy between Hansen’s 1988 model forecasts and actual temperatures as measured by two independent satellite monitoring systems.

“GISS” A, B, and C are Hansen’s 1988 global warming model projections. “A” and “B” are model projections assuming business-as-usual emission levels similar to what happened (actually a bit lower than what occurred). ”C” is a model projection assuming drastic CO2 cuts. ”UAH” and “RSS” are, respectively, the University of Alabama in Huntsville and Remote Sensing Systems satellite records.

Christy comments:

All model projections show a high sensitivity to CO2 while the actual atmosphere does not. It is noteworthy that the model projection for drastic CO2 cuts still overshot the observations. This would be considered a failed hypothesis test for the models from 1988.

Ancient history, you say? Maybe, but Christy also compared the IPCC Fourth Assessment Report’s (AR4) climate model warming projections with actual temperature data.

The red and orange lines mark the upper and lower bounds of 95% of the global warming projections calculated by 21 IPCC AR4 models for multi-year segments ending in 2020. The blue and green lines show temperature trends calculated from the UAH satellite record and the U.K. Hadley Center surface temperature record, respectively.

Christy comments:

The two main points here are (1) the observations are much cooler than the mid-range of the model spread and are at the minimum of the model simulations and (2) the satellite adjustment for surface comparisons is exceptionally good. The implication of (1) is that the best estimates of the IPCC models are too warm, or that they are too sensitive to CO2 emissions.

By now you may be wondering what any of this has to do with peer review at the Proceedings of the National Academy of Sciences (PNAS). Patience, grasshopper.

At the hearing, Hansen declined to address Christy’s critique of model sensitivity assumptions on the merits. Rather, he asserted that climate sensitivity is “crystal clear,” and advised the Committee to ask the National Academy of Sciences (NAS) to produce a report and accept its verdict as “authoritative.”

Now, if you’re like me, you probably assume that the National Academy insists on the most rigorous standards of peer review for PNAS, the organization’s flagship publication. But an article in the current (19 September 2009) issue of Science magazine (subscription required) suggests otherwise.

The article, “PNAS Nixes Special Privileges for (Most) Papers,” reports that:

National Academy members, as elite scientists, could shepherd their own work through peer review with less vetting than at other publications by “contributing” a paper. They could also “communicate” a paper on behalf of colleagues who had not been elected to the academy’s august ranks.

The article goes on to explain that:

In practice, “communicating” a colleague’s paper meant that a member lined up referees to review it before PNAS ever saw it. This increased the chance of a favorable reception — and looked suspiciously like cronyism to outsiders.

Because of that perception, PNAS announced last week that it will end the “communicated” option for submitting papers by July 2010. However, Science reports, “The move will not affect the privileges of academy members to line up reviews before they submit their own papers to PNAS …”

I don’t know about you, but my college GPA would have been higher had I been allowed to ”line up” friends to grade my term papers and tests. And wouldn’t it be nice if, during job performance reviews at work, we could “line up” allies to decide whether we deserve a raise and a bonus?

Science further reports that the “rejection rate for communicated or contributed papers that reach the PNAS is a few percent, whereas the rejection rate for standard submissions is 80%.” Membership doth seem to have its privileges at the National Academy.

Having spent a few years in institutions of higher learning, both as a student and a teacher, I have seen how our alleged bastions of academic freedom breed conformity and group-think.

First, there’s the quest for tenure. A young professor serious about his career dare not challenge the methodological or ideological pieties of his colleagues, lest they deny him the coveted job security he seeks. And if the acolyte makes it into the ranks of the tenured, he will think twice about offending colleagues with whom he may be stuck for decades, and he’ll take care not to jeopardize his department’s research contracts and grants by offending the political pieties of grantmakers in Washington, D.C.

Most people admitted into the august ranks of the National Academy will have been shaped by the conformity mills that our institutions of higher learning have become. Moreover, once ensconced in the club, they will be loathe to offend other members, many of whom may have voted to admit them in the first place.

So it should come as no surprise that “the rejection rate for communicated or contributed papers that reach the PNAS is a few percent, whereas the rejection rate for standard submissions is 80%.”

Even apart from these considerations, cronyism seems to be a significant problem in climate-related research. The IPCC reports are collections of literature reviews in which the lead authors often review their own work. Statistician Edward Wegman noted in his assessment of the infamous “hockey stick“ reconstruction of global temperatures (which allegedly proved that 1998 was the warmest year of the past 1,000 years) that “authors in the area of paleoclimate studies are closely connected and thus ‘independent studies’ may not be as independent as they seem on the surface.”

So when National Academy member James Hansen declines to debate John Christy on the merits, and instead advises Congress to let the NAS decide the scientific basis of climate legislation, he is actually asking Congress to let the old-boy network to which he belongs call the shots.

That Hansen would proffer such self-serving advice rather than debate the core issue on the merits is reason enough to be skeptical of the science he espouses.

Policy Peril Segment 10: It’s a Moral Issue

by Marlo Lewis on August 24, 2009 · 2 comments

in Global Warming

Today’s excerpt from CEI’s film, Policy Peril: Why Global Warming Policies Are More Dangerous Than Global Warming Itself, offers a free-market perspective on Al Gore’s proclamation, at the end of An Inconvenient Truth, that global warming is “a moral issue.”

Considered in the abstract, apart from its context in movie, this is a completely unremarkable statement. Just about all public policy issues can be described as moral issues, because they directly or implicitly ask us to decide whether a proposed course of action is fair or unfair, honorable or dishonorable, good or bad.

However, when Gore says global warming is a “moral issue,” he means something more. He means that combatting global warming is the overriding moral imperative of our time. He implies that if you are decent, self-respecting person, you have no moral choice but to follow his lead and heed his call. He is trying to play a rhetorical trump card.

Gore is clever. In An Inconvenient Truth, he presents himself as an a-political Mr. Science – and then exploits the moral authority so contrived to bash the Bush Administration and other political opponents. Similarly, he presents as a moral imperative a policy agenda that — just by sheer coincidence, we’re supposed to believe – would empower him and his political allies to control the global economy. It’s all a little too convenient.

More importantly, what if the alleged imperative to decarbonize U.S. and global economy conflicts with other, arguably better-established imperatives, such as eradicating poverty? If Gore were a moral leader rather than a moralizing partisan, wouldn’t he at least acknowledge that his ”solutions” might have harmful side-effects?

To watch today’s film excerpt, click here. To watch Policy Peril from start to finish, click here. The text of today’s film clip follows. The footnotes are to additional commentary and supporting information.

Narrator: Now let’s look at the international side of climate policy. Al Gore and the European Union advocate a 50% cut in global emissions by 2050. [1] But most of the growth in global emissions between now and then will come from developing countries. [2] So those countries, too, will have to stop building coal plants. They, too, will have to limit their use of fossil fuel. [3] It would be a humanitarian disaster.
Globally, about 1.6 billion people lack access to electricity. About 2.4 billion still rely on traditional biomass–wood, crop waste, even dung–for cooking and heating. [4]
Tom Tanton (Pacific Research Institute): Look at developing countries. The thing they need most of all is commercial energy and electricity. People in developing countries spend most of their day collecting fuel. They don’t have time to go to school and get an education. It gets dark at night so there’s no studying at night, because there’s no electricity. Electricity is the essential commodity for any kind of growth and improvement in lifestyle. [5]
Narrator: A coal-fired power plant would improve the lives of those villagers in many ways. Women would be freed from backbreaking toil. People would be healthier because indoor air quality would improve. Refrigeration would make food preparation easier and safer. Electric lighting would allow people to read and study at night. The forests and the species dependent on them would be spared. [6]
Myron Ebell (Competitive Enterprise Institute): I agree with former Vice President Gore that global warming is a moral issue. I think it is preeminently a moral issue because we have a billion and a half people in the world who don’t have access to electricity, for example. The world is not energy rich, it’s energy poor. And if we’re going to put energy rationing policies on the backs of the world’s poorest people, they will have very little hope of ever achieving even a fraction of the well-being, the lifestyle that we have.
Narrator: India is an emerging industrial powerhouse. Yet even in India, energy poverty kills. India has the largest incidence of snake bites in the world. About 50,000 Indians die from snake bites each year. Doctors there have developed an anti-venom antidote. So why is the death toll so high?
Barun Mitra (Liberty Institute): The primary reason is that most Indian health centers, primarily in rural areas where the snakebites are more prevalent, have no electricity, no refrigeration, no way to store the anti-venom. The technology is there. We know how to generate electricity. The technology is there. We know how to make the anti-venom. Yet, 95% of Indians, or thereabouts, do not have access to it, because they stay in areas which cannot store anti-venom in a refrigerated environment.
Narrator: Let me state the obvious. Poverty is the number one cause of premature death and preventable disease in the world. [7] Global restrictions on fossil energy use would trap millions of people in poverty.
Al Gore and others don’t say exactly how they would stop poor countries from using coal. But some U.S. and European politicians want to impose carbon tariffs on goods from China and other developing countries that refuse to limit emissions. [8]
Iain Murray (Competitive Enterprise Institute; author The Really Inconvenient Truths): I think the question to ask here is: Can any of the potential effects of climate change be so great as to justify keeping the developing world in poverty. I think to ask that question is to answer it.

Commentary

[1] The goal of cutting global CO2 emissions 50%-85% by 2050 has become canonical for the global warming movement. Proponents of this viewpoint include the IPCC, the European Union, the G-8 (U.S., UK, France, Italy, Canada, Germany, Japan, Canada), and just about every environmental group. Supposedly, a 50%-85% cut would likely limit 21st century global warming to 2ºC (3.6ºF), which in turn would likely “avoid some of the worst effects” of climate change. All of this assumes that the climate is moderately-to-highly sensitive to increases in CO2 concentrations. Recent research contradicts that assumption.

[2] 80-90% of the increase in greenhouse gas emissions between now and 2050 is expected to come from developing countries, chiefly India, China, and SE Asia.

Figure source: James Connaughton, Chairman, White House Council on Environmental Quality (CEQ), Energy and Climate Policy, December 2007.

Figure source: Stephen Eule, U.S. Chamber of Commerce Institute for 21st Century Energy, Scale & Scope of the Challenge of Reducing Greenhouse Gas Emissions, February 2009

[3] Global CO2 emissions are projected to increase from 24 gigatons a year in 2000 to 50.6 gigatons a year in 2050. Thus, to achieve a 50% reduction, global emissions in 2050 will have decline to 12.3 gigatons — 76% below the baseline projection.

Figure source: Stephen Eule, Scale & Scope of the Challenge, Feb. 2009

This means that even if developed countries miraculously reduce their CO2 emissions to zero, global emissions cannot be cut by 50% unless developing countries cut their emissions 62% below baseline. Their per capita CO2 emissions will have to decline to 1.7 metric tons per year — less than current per-capita CO2 emissions in Central and South America.

If developed countries reduce their emissions by “only” 84% — approximately the Waxman-Markey target for 2050 — then developing countries will have to reduce their emissions 71% below baseline. They’ll have to hold their emissions almost flat between now and 2050. Their per-capita emissions will have to decline to 1.3 metric tons per year. That’s about what per-capita emissions are today in Africa, the most energy-starved continent on the planet.

Figure source: Stephen Eule, Scope & Scale of the Challenge, February 2009

Absent spectacular breakthroughs in the cost and performance of zero-emission energy, the minimal EU/UN/Al Gore goal of a 50% reduction in global CO2 emissions by 2050 cannot be achieved without dramatically limiting developing countries’ energy consumption and economic growth.

[4] 1.6 billion people have never flipped a light switch and 2.4 billion people depend on primitive biomass for heat and light — these figures come from chapter 13 (“Energy and Poverty”) of the International Energy Agency’s World Energy Outlook 2002.

[5] That electrification is a prerequisite for continual improvement in the human condition is obvious. Nonetheless, some scholars attempt via statistical techniques to demonstrate the importance of electricity to the physical quality of life. An October 2000 study by Alan Pasternak of the Lawrence Livermore Laboratory finds a strong association between per capita electricity consumption and the United Nation’s Human Development Index (HDI), a composite measure of human welfare taking into account GDP, life expectancy, and educational attainment.

Figure source: Alan Pasternak, Global Energy Futures and Human Development: A Framework of Analysis, Lawrence Livermore Laboratory, October 2000.

Although in 1997 four countries (South Korea, Russia, Saudi Arabia, and South Africa) with per capita annual electricity consumption somewhat above 4,000 kWh had an HDI below 0.9, no country with per capita annual electricity consumption below 4,000 kWh had an HDI of 0.9 or higher. Pasternak concludes that there is a “compelling need for increased energy and electricity supplies in the developing countries,” and that, “Neither the Human Development Index nor the Gross Domestic Product of developing countries will increase without an increase in electricity use.”

[6] For this formulation, I am indebted to University of Alabama-in-Huntsville atmospheric scientist John Christy. A former African missionary, Christy has seen first-hand the hardship and perils of life in an energy-poor country. When Christy testifies before Congress, he often includes a plea not to demonize energy, because “life without energy is brutal and short.”

[7] “A large proportion of illnesses in low-income countries are entirely avoidable or treatable with existing medicines or interventions,” observes Philip Stevens, Health Director for the International Policy Network (see p. 4 of this report). Such illnesses include tuberculosis, malaria, HIV/AIDS, childhood diseases (polio, measles, tetanus), diarrhoeal diseases from poor sanitation, respiratory infections from indoor air pollution, and malnutrition such as vitamin A deficiency. These eminently preventable and treatable illnesses kill millions people — a high proportion of them children — in developing countries each year. Although vaccines or treatments are inexpensive, poor countries lack the infrastructure to make them widely available.

[8] Cap-and-trade and protectionism are joined at the hip. You might not think so, judging from the oft-repeated assurances that Kyoto-style policies will spur innovation, efficiency, and “green job” creation, making us more competitive in the “economy of the future.” Yet European politicians warn (see here, here, and here) that they will impose border taxes (carbon tariffs) on goods from countries — chiefly China but also the United States — that refuse to limit emissions.

Most “trade-exposed, energy-intensive” firms call for additional free emission allowances to “level the playing field” rather than for carbon tariffs (see here, here, and here). However, the Sierra Club argues that carbon border taxes may be needed as a “backstop,” particularly as emission caps tighten and the supply of free allowances shrinks. It is telling that some experts are making the case that carbon tariffs are legal under WTO trade rules. (Other experts, however, warn that unilateral imposition of border taxes or counterveiling duties on carbon-intensive imports would violate WTO rules, engendering a long period of trade friction and uncertainty.)

Both free allowances and carbon tariffs are also touted as a cure for “carbon leakage” — the flight of capital, jobs, and emissions to developing countries in order to escape the high energy costs stemming from carbon controls in developed countries.

But beyond concerns about unfair competition and carbon leakage, there are more basic reasons why cap-and-trade depends on protectionism. First, how do you enforce a treaty like Kyoto over the long term? It’s a typical collective action problem. Even if one assumes it is in the common interest of all nations to mitigate global warming, it is in the individual interest of each nation to bear less than its negotiated share of the burden — to reap the climate benefits (if any) of other nations’ sacrifices and employ creative accounting on behalf of one’s own industries to give them a competitive edge. If cheating isn’t credibly punished, the number of “free riders” will grow, and the system will collapse.

How will the world’s nations punish cheaters? If military force is not an option, then trade penalties — carbon tariffs — are pretty much the only remedy.

Furthermore, how do you persuade major developing countries to get on board? They repeatedly refuse to accept binding limits on their emissions. Yet, as explained above, developing countries must make heroic efforts to decarbonize their economies if the world is to cut emissions 50%-85% by 2050, as demanded by Vice President Gore, the EU, and the UN.

One option is to bribe them with massive wealth and technology transfers. But building hundreds of new nuclear power plants or hundreds of futuristic zero-emission coal power plants in China, India, Brazil, and other developing countries would cost trillions of dollars. In the midst of a global financial crisis and high unemployment, it is unlikely that U.S. and EU taxpayers will agree export more jobs to China.

If carrots are out as an inducement to decarbonize, then sticks are what’s left. It would need to be a big stick — for example, a coordinated campaign of trade sanctions by the United States, the EU, Canada, Russia, and Japan.

More than likely, though, such a campaign would fail because developing countries would retaliate with trade sanctions of their own. We would get trade war, not compliance.

Nonetheless, if the major-emitting developing countries — China, India, Brazil, and Indonesia — continue to reject binding emission limits, advocates of CO2 controls will be continually tempted to rattle the trade sabers and demand carbon tariffs. Indeed, earlier this month, 10 Democratic U.S. Senators, in a letter to President Obama, indicated they would not support a cap-and-trade bill lacking a “border adjustment mechanism” (a.k.a. carbon tariff) to create a level playing field and pressure nations like China into adopting carbon controls.

Conclusion

Yes, global warming is a moral issue, but not for the reasons Al Gore supposes. As John Christy reminds us, human life without energy is brutal and short. Yet Gore would suppress the 85% of the world’s energy that comes from fossil fuels.

But there’s more to it than that. In a recent video commentary on CO2Science.Org, Christy offers both a personal insight and an analyst’s perspective on why abundant, affordable energy is one of the great blessings of modern civilization. I’ll conclude this blog post — the last in my series of posts on Policy Peril – with the text of Christy’s remarks.

John Christy: When people talk about the moral issue of controlling carbon dioxide emissions, I say yes, that’s right, it is a moral issue. In 1900, the energy technology of the day supported 56 billion human life years. Okay. That’s 1.6 billion people times 35 years’ life expectancy. 56 billion human life years. The average person lived to 35. Now, the energy technology supports about 450 billion human life years. That is an eight-fold increase in the experience of human life, and that is a spectacular achievement.
I am a grandfather now. And when my little grandson runs up and hugs me around the knees, I am experiencing something in human life that, a hundred years ago, the average person could not, at all. So this experience of human life that’s been granted to us by energy technology is tremendous and wonderful.
Therefore, the moral issue here is that we should provide people, who do not have it, energy, so that they can experience life that is safer, that is healthier, and that is longer. That’s the moral issue.

To read previous posts in this series, click on the links below:

Policy Peril: Looking for antidote to An Inconvenient Truth? Your search is over.

Policy Peril Segment 1: Heat Waves

Policy Peril Segment 2: Air Pollution

Policy Peril Segment 3: Hurricanes

Policy Peril Segment 4: Sea-Level Rise

Policy Peril Segment 5: Is the Science Debate Over?

Policy Peril Segment 6: Cap and Trade

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Policy Peril Segment 5: Is the Science Debate “Over”? Updated 08/17/09

by Marlo Lewis on August 5, 2009 · 1 comment

in Global Warming

Today’s post in my series of commentaries on excerpts from CEI’s film, Policy Peril: Why Global Warming Policies Are More Dangerous Than Global Warming Itself, challenges the Gorethodox dogma that the science debate on global warming is “over.”

There are three basic issues in the climate change science debate:

Detection – Has the world warmed, and if so, by how much?
Attribution – How much of the observed warming (especially since the mid-1970s) is due to increases in atmospheric greenhouse gas concentrations?
Sensitivity – How much additional warming should we expect from continuing increases in greenhouse gas concentrations?

Despite what you’ve heard over and over again, these basic issues are unsettled, and more so now than at any time in the past decade. The science debate is not “over.” Reports of the death of climate skepticism have been greatly exaggerated.

Because of time constraints (Policy Peril runs under 40 minutes), the film briefly explores only the most important of the three basic issues: climate sensitivity. Today’s clip comes from that part of the film: an interview with University of Alabama in Huntsville atmospheric scientist Dr. Roy Spencer. To watch the Spencer interview, click here. To watch the entire movie, click here.

Here’s how this post is organized. First, I’ll reproduce the text of Spencer’s interview. Then, I’ll review some recent research bearing on the three fundamental science issues: detection, attribution, and sensitivity.

Text of today’s film clip:

Narrator: All the IPCC models assume that a CO2-induced warming will produce more high-altitude cirrus clouds, which then trap even more heat in the atmosphere. This is what’s called a positive climate feedback. Roy Spencer and his colleagues use satellites to study cirrus cloud behavior.
Dr. Roy Spencer (University of Alabama in Huntsville): Last August, August of 2007, we published research which showed from a whole bunch of satellite data that when the tropical atmosphere heats up–there are these periods when the atmosphere heats up from more rain activity or cools down from less rain activity–that when it heats up, the skies actually open up. The cirrus clouds that are up high, in the troposphere, in the upper atmosphere, open up and let more cooling infrared radiation escape to space. And it was a very strong effect.
Narrator: Spencer says that if climate models incorporated the negative feedback his team discovered, the models might forecast 75% less warming.

This is definitely not the Al Gore view of climate sensitivity. In fact, in An Inconvenient Truth (p. 67), Gore suggests we could get “three times as much” warming by mid-century as has occurred since the “depth of the last ice age.” That would mean a warming of 10ºC-12ºC by mid-century! Gore’s implicit warming forecast goes way beyond the IPCC best-estimate forecast range of 1.8ºC to 4.0ºC (IPCC WWI AR4, Summary for Policymakers, p. 13). As we’ll see below, several strands of evidence suggest that the IPCC models are also too “hot.”

Detection

The world has warmed overall during the past 130 years, as evidenced by melting glaciers, longer growing seasons, and both proxy and instrumental data. However, the main era of “anthropogenic” global warming supposedly began in the mid-1970s, and ongoing research by retired meteorologist Anthony Watts leaves no doubt that in recent decades, the U.S. surface temperature record–reputed to be the best in the world–is unreliable and riddled with false warming biases.

Watts and a team of more than 650 volunteers have visually inspected and photographically documented 1003, or 82%, of the 1,221 climate monitoring stations overseen by the U.S. Weather Service. In a report summarizing an earlier phase of the team’s investigation (a survey of 860+ stations), Watts says, “We were shocked by what we found.” He explains:

We found stations located next to exhaust fans of air conditioning units, surrounded by asphalt parking lots and roads, on blistering-hot rooftops, and near sidewalks and buildings that absorb and radiate heat. We found 68 stations located at wastewater treatment plants, where the process of waste digestion causes temperatures to be higher than in surrounding areas.

In fact, we found that 89 percent of the stations–nearly 9 of every 10–fail to meet the National Weather Services’s own siting requirements that stations must be 30 meters (about 100 feet) or more away from an artificial heating or radiating/reflecting heat source. In other words, 9 or every 10 stations are likely reporting higher or rising temperatures because they are badly sited.

“It gets worse,” Watts continues:

We observed that changes in the technology of temperature stations over time also have caused them to report a false warming trend. We found gaps in the data record that were filled in with data from nearby sites, a practice that propagates and compounds errors. We found adjustments to the data by both NOAA and another government agency, NASA, cause recent temperatures to look even higher.

How big a problem is this? According to Watts, “The errors in the record exceed by a wide margin the purported rise in temperature of 0.7ºC (about 1.2ºF) during the twentieth century.” Based on analysis of 948 stations rated as of May 31, 2009, Watts estimates that 22% of stations have an expected error of 1ºC, 61% have an expected error of 2ºC, and 8% have an expected error of 5ºC.

watts_fig23

Watts concludes that, “this record should not be cited as evidence of any trend in temperature that may have occurred across the U.S. during the past century.” He further concludes: “Since the U.S. record is thought to be ‘the best in the world,’ it follows that the global database is likely similarly compromised and unreliable.”

A related issue is the influence of urban heat islands on long-term temperature records. Climate Change Reconsidered, a report by the Nongovernmental International Panel on Climate Change (NIPCC), written by Drs. Craig Idso and S. Fred Singer with 35 contributors and reviewers, reviews more than 40 studies on urban heat islands. For example, a study by Oke (1973) of the urban heat island strength of 10 settlements in the St. Lawrence Lowlands of Canada found that a population as small as 1,000 people could generate a heat island effect of 2ºC-2.5ºC. From this study and the others reviewed, the NIPCC concludes:

It appears almost certain that surface-based temperature histories of the globe contain a significant warming bias introduced by insufficient corrections for the non-greenhouse-gas-induced urban heat island effect. Furthermore, it may well be impossible to make proper corrections for the deficiency, as the urban heat island of even small towns dwarfs any concommitant augmented greenhouse effect that may be present [p. 95; emphasis in original].

In a comment submitted to EPA regarding its proposed endangerment finding, University of Alabama in Huntsville (UAH) atmospheric scientist John Christy notes two additional reasons to conclude that the IPCC surface data records exaggerate warming trends:

As a culmination of several papers and years of work, Christy et al. (2009) demonstrates that popular surface datasets overstate the warming that is assumed to be greenhouse related for two reasons. First, these datasets use only stations that are electronically (i.e. easily) available, which means the unused, vast majority of stations (usually more rural and representative of actual trends but harder to find) are not included. Secondly, these popular datasets use the daily mean surface temerpature (TMean) which is the average of the daytime high (TMax) and nighttime low (TMin). In this study (and its predecessors, Christy 2002, Christy et al. 2006, Pielke Sr. et al. 2008, Walters et al. 2007 and others) we show that TMin is seriously impacted by surface development, and thus its rise is not an indicator of greenhouse gas forcing. Some have called this the Urban Heat Island effect, but, as described in Christy et al. 2009, it is much more than this and encompasses any development of the surface (e.g. irrigated agriculture).

For example, the UK Hadley Center, relying on two electronic surface stations, computed a TMax temperature trend in East Africa of 0.14ºC per decade during 1905-2004. Christy, using data from 45 stations, found a trend of only 0.02ºC per decade.

In California, Christy found that the only significant warming trend is for TMin in the irrigated San Joaquin Valley. Note, in the non-irrigated Sierra mountains, where models project a greenhouse gas-induced warming should occur, there is actually a decreasing temperature trend.

Obviously, temperature data are the starting point of any analysis of global warming. But if we can’t trust the U.S. and IPCC temperature records, how do we know how much global warming has actually occurred?

Satellite observations are not influenced by heat islands and irrigation, or subject to the quality control problems detailed by Watts. Moreover, satellite records tally well with weather balloon observations–an independent database. So maybe detection should be based solely on satellite data, which do show some warming over the past 30 years. However, the “debate is over” crowd is unlikely to embrace this solution. The satellite record shows a relatively slow rate of warming–about 0.13ºC per decade–hence a relatively insensitive climate.

uah-temperature-anomalies-jan-1979-june-20093

Moreover, as can be seen in the above chart of the University of Alabama-Huntsville (UAH) satellite record, some of the 0.13ºC/decade ”trend” comes from the 1998 El Nino warming pulse. Remove 1998, and the 30-year satellite record trend drops to 0.12ºC/decade.

Attribution

The IPCC, the leading spokesman for the alleged scientific consensus, claims that, “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.” How does the IPCC know this? The IPCC offers three main reasons.

First, according to the IPCC, “Paleoclimate reconstructions show that the second half of the 20th century was likely the warmest 50-year period in the Northern hemisphere in 1300 years” (IPPC AR4, WGI, Chapt. 9, p. 702). The warmth of recent decades coincided with a rapid increase in GHG concentrations. Therefore, the IPCC reasons, most of the recent warming is likely due to anthropogenic GHG emissions.

This argument is unconvincing if the warming of recent decades is not unusual or unprecedented in the past 1300 years. As it happens, numerous studies indicate that the Medieval Warm Period (MWP)–roughly the period from AD 800 to 1300, with peak warmth occurring about AD 1050–was as warm as or warmer than the Current Warm Period (CWP).

The Center for the Study of Carbon Dioxide and Global Change has analyzed more than 200 peer-reviewed MWP studies produced by more than 660 individual scientists working in 385 separate institutions from 40 countries. The Center divides these studies into three categories–those with quantitative data enabling one to infer the degree to which the peak of the MWP differs from the peak of the CWP (Level 1), those with qualitative data enabling one to infer which period was warmer (Level 2), although not by how much, and those with data enabling one to infer the existence of a MWP in the region studied (Level 3). An interactive map showing the sites of these studies is available at CO2Science.org.

Only a few Level 1 studies determined the MWP to have been cooler than the CWP; the vast majority indicate a warmer MWP. On average, the studies indicate that the MWP was 1.01ºC warmer than the CWP.

mwpquantitative

Figure Description: The distribution, in 0.5ºC increments, of Level 1 studies that allow one to identify the degree to which peak MWP temperatures either exceeded (positive values, red) or fell short of (negative values, blue) peak CWP temperatures.

Similarly, the vast majority of Level 2 studies indicate a warmer MWP:

mwpqualitative

Figure Description: The distribution of Level 2 studies that allow one to determine whether peak MWP temperatures were warmer than (red), equivalent to (green), or cooler than (blue), peak CWP temperatures.

The IPCC’s second main reason for attributing most recent warming to the increase in GHG concentrations is that climate models “cannot reproduce the rapid warming observed in recent decades when they only take into account variations in solar output and volcanic activity. However . . . models are able to simulate observed 20th century changes when they include all of the most important external factors, including human influences from sources such as greenhouse gases and natural external factors” (IPCC, AR4, WGI, Chapt. 9, p. 702).

This would be decisive if today’s models accurately simulate all important modes of natural variability. In fact, models do not accurately simulate the behavior of clouds and ocean cycles. They may also ignore important interactions between the Sun, cosmic rays, and cloud formation.

Richard Lindzen of MIT spoke to this point at the Heartland Institute’s recent (June 2, 2009) Third International Conference on Climate Change:

What was done [by the IPCC], was to take a large number of models that could not reasonably simulate known patterns of natural behavior (such as ENSO, the Pacific Decadal Oscillation, the Atlantic Multi-Decadal Oscillation), claim that such models nonetheless adequately depicted natural internal climate variability, and use the fact that models could not replicate the warming episode from the mid seventies through the mid nineties, to argue that forcing was necessary and that the forcing must have been due to man. The argument makes arguments in support of intelligent design seem rigorous by comparison.

“Fingerprint” studies are the third basis on which the IPCC attributes most recent warming to anthropogenic greenhouse gases. Climate models project a specific pattern of warming through the vertical profile of the atmosphere–a greenhouse “fingerprint.” If the observed warming pattern matches the model-projected fingerprint, that would be strong evidence that recent warming is anthropogenic. Conversely, notes the NIPCC, “A mismatch would argue strongly against any signficant contribution from greenhouse gas (GHG) forcing and support the conclusion that the observed warming is mostly of natural origin” (NPICC, p. 106).

Douglass et al. (2007) compared model-projected and observed warming patterns in the tropical troposphere. The observed pattern is based on three compilations of surface temperature records, four balloon-based records of the surface and lower troposphere, and three satellite-based records of various atmospheric layers–10 independent datasets in all.

“While all greenhouse models show an increasing warming trend with altitude, peaking around 10 km at roughly two times the surface value,” observes the NIPCC, “the temperature data from balloons give the opposite result; no increasing warming, but rather a slight cooling with altitude” (p. 107). See the figures below.

hot-spot

The mismatch between the model-predicted greenhouse fingerprint and the observed pattern is profound. As the Douglass team explains: “Model results and observed temperature trends are in disagreement in most of the tropical troposphere, being separated by more than twice the uncertainty of the model mean. In layers near 5 km, the modeled trend is 100% to 300% higher than observed, and above 8 km, modeled and observed trends have opposite signs.”

douglass

Figure description: Temperature trends for statellite era (ºC/decade). HadCRUT, GHCH and GISS are compilations of surface temperature observations. IGRA, RATPAC, HadAT2, and RAOBCORE are balloon-based observations of surface and lower troposphere. UAH, RSS, UMD are satellite-based data for various layers of the atmosphere. The 22-model average comes from an ensemble of 22 model simulations from the most widely used models worldwide. The red lines are the +2 and -2 standard errors of the mean from the 22 models. Source: Douglass et al. 2007.

The NIPCC concludes that the mismatch of observed and model-calculated fingerprints “clearly falsifies the hypothesis of anthropogenic global warming (AGW)” (p. 108). I would put the state of affairs more cautiously. In view of (1) significant evidence that the MWP was as warm as or warmer than the CWP, (2) the inability of climate models to simulate important modes of natural variability, and (3) the failure of observations to confirm a greenhouse fingerprint in the tropical trosophere, the IPCC claim that “most” recent warming is “very likely” anthropogenic should be considered a boast rather than a balanced assessment of the evidence.

Climate Sensitivity

The most important unresolved scientific issue in the global warming debate is how sensitive (reactive) the climate is to increases in GHG concentrations.

Climate sensitivity is typically defined as the global average surface warming following a doubling of carbon dioxide (CO2) concentrations above pre-industrial levels. The IPCC says a doubling is likely to produce warming in the range of 2ºC to 4.5ºC, with a most likely value of about 3ºC (IPCC, AR4, WGI, Chapt. 10, p. 749). The IPCC presents a range rather than a specific value because of uncertainty regarding the strength of the relevant feedbacks.

In a hypothetical climate with no feedbacks, positive or negative, a CO2 doubling would produce 1.2ºC of warming (IPCC, AR4, WGI, Chapt. 8, p. 631). In most climate models, the dominant feedbacks are positive, meaning that the warmth from rising GHG levels causes other changes (in water vapor, clouds, or surface reflectivity, for example) that either increase the retention of outgoing long-wave radiation (OLR) or decrease the reflection of incoming short-wave radiation (SWR).

In his speech at the June 2 Heartland Institute conference, Professor Lindzen summarized his research on climate sensitivity, which has since been accepted for publication by Geophysical Research Letters. Lindzen argues that climate feedbacks and sensitivity can be inferred from observed changes in OLR and SWR following observed changes in sea-surface temperatures. For fluctuations in OLR and SWR, Lindzen and his colleagues used the 16-year record (1985-1999) from the Earth Radiation Budget Experiment (ERBE), as corrected for altitude variations associated with satellite orbital decay. For sea surface temperatures, they used data from the National Centers for Environmental Prediction. For climate model simulations, they used 11 IPCC models forced with the observed sea-surface temperature changes.

The results are striking. All 11 IPCC models show positive feedback, “while ERBE unambiguously shows a strong negative feedback.”

Figure description: ERBE data show increasing top-of-the-atmosphere radiative flux (OLR plus reflected SWR) as sea surface temperatures rise whereas models forecast decreasing radiative flux. Source: Lindzen and Choi 2009.

The ERBE data indicate that the sensitivity of the actual climate system “is narrowly constrained to about 0.5ºC,” Lindzen estimates. ”This analysis,” says Lindzen in a recent commentary, “makes clear that even when all models agree, they can be wrong, and that this is the situation for the all important question of climate sensitivity.”

erbe-v-model-sensitivity4

At the Heartland Institute’s Second International Conference on Climate Change (March 2009), Dr. William Gray of Colorado State University presented satellite-based research that may explain the low climate sensitivity the Lindzen team infers from the ERBE data.

The IPCC climate models assume that CO2-induced warming significantly increases upper troposphere clouds and water vapor, trapping still more OLR that would otherwise escape to space. Most of the projected warming in the models comes from this positive water vapor/cloud feedback, not from the CO2. Satellite observations do not support this hypothesis, Gray contends:

Observations of upper tropospheric water vapor over the last 3-4 decades from the National Centers of Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data and the International Satellite Cloud Climatology Project (ISCCP) data show that upper tropospheric water vapor appears to undergo a small decrease while Outgoing Longwave Radiation (OLR) undergoes a small increase. This is the opposite of what has been programmed into the GCMs [General Circulation Models] due to water vapor feedback.

The figure below comes from the NCEP/NCAR reanalysis of upper troposphere water vapor and OLR.

reanalysis-olr-and-water-vapor-50

Figure description: NCEP/NCAR renalysis of standardized anomalies at 400 mb (~7.5 km altitude) water vapor content (i.e. specific humidity — in blue) and OLR (in red) from 1950 to 2008. Note the downward trend in moisture and upward trend in OLR.

Gray’s paper deals with water vapor in the upper troposphere. What about high-altitude cirrus clouds, which climate models also predict will increase and trap more OLR as GHG concentrations increase?

Spencer et al. (2007), the study Dr. Spencer spoke about in today’s Policy Peril film clip, found a strong negative cirrus cloud feedback mechanism in the tropical troposphere. Instead of steadily building up as the tropical oceans warm, cirrus cloud cover suddenly contracts, allowing more OLR to escape. As mentioned, Spencer estimates that if this mechanism operates on decadal time scales, it would reduce model estimates of global warming by 75%.

A 2008 study by Spencer and colleague William D. Braswell examines the issue of climate feedbacks related to low-level clouds. Lower troposphere clouds tend to cool the Earth by reflecting incoming SWR. Observations indicate that warmer years have less cloud cover compared to cooler years. Modelers have interpreted this correlation as positive feedback effect in which warming reduces low-level cloud cover, which then produces more warming.

Spencer and Braswell found that climate modelers could be mixing up cause and effect. Random variations in cloudiness can cause substantial decadal variations in ocean temperatures. So it is equally plausible that the causality runs the other way, and increases in sea-surface temperature are an effect of natural cloud variations. If so, then climate models forecast too much warming. For more on this, visit Spencer’s Web site.

In a study now in peer review for possible publication in the Journal of Geophysical Research, Spencer and colleagues analyzed 7.5 years of NASA satellite data and “discovered,” he reports on his Web site, “that, when the effects of clouds-causing-temperature-change is accounted for, cloud feedbacks in the real climate system are strongly negative.” “In fact,” he continues, “the resulting net negative feedback was so strong that, if it exists on the long time scales associated with global warming, it would result in only 0.6ºC of warming by late in this century.”

In related ongoing satellite research, Spencer finds new evidence that “most” warming of the past century “could be the result of a natural cycle in cloud cover forced by a well-known mode of natural climate variability: the Pacific Decadal Oscillation (PDO).”

Whether or not the PDO proves to be a major player in climate change, Spencer has identified a potentially serious error in all IPCC modeling efforts:

Even though they never say so, the IPCC has simply assumed that the average cloud cover of the Earth does not change, century after century. This is a totally arbitrary assumption, and given the chaotic variations that the ocean and atmosphere circulations are capable of, it is probably wrong. Little more than a 1% change in cloud cover up or down, and sustained over many decades, could cause events such as the Medieval Warm Period or the Little Ice Age.

Finally, recent temperature history also suggests that most climate models are too “hot.” Dr. Patrick Michaels touched on this topic in Policy Peril (albeit not in today’s excerpt).

Carbon dioxide emissions and concentrations are increasing at an accelerating rate (Canadell, J.G. et al. 2008). Yet, there has been no net warming since 2001 and no year was as warm as 1998.

Figure description: Observed monthly global temperature anomalies, January 2001 through April 2009, as compiled by the Climate Research Unit. Source: Paul C. Knappenberger.

Paul C. Knappenberger (“Chip” to his friends) quite reasonably wonders, “[H]ow long a period of no warming can be tolerated before the forecasts of the total warming by century’s end have to be lowered?” After all, he continues, “We’re already into the nineth year of the 100 year forecast and we have no global warming to speak of.” It is instructive to compare these data with climate model projections.

A good place to start is with the climate model projections that NASA scientist James Hansen presented in his 1988 congressional testimony, which launched the modern global warming movement.

The figure below, from congressional testimony by Dr. John Christy, a colleague of Roy Spencer at the University of Alabama in Huntsville, shows how Hanesn’s model and reality diverge.

Figure description: The red, orange, and purple lines are Hansen’s model forecasts of global temperatures under different emission scenarios. The green and blue lines are actual temperatures from two independent satellite records. Source: John Christy.

“All model projections show high sensitivity to CO2 while the actual atmosphere does not,” Christy notes. “It is noteworthy,” he adds, “that the model projection for drastic CO2 cuts still overshot the observations. This would be considered a failed hypothesis test for the models from 1988.”

What about the models used by the IPCC in its 2007 Fourth Assessment Report (AR4)? How well are they replicating global temperatures?

This figure, also from Dr. Christy’s testimony, is adapted from Dr. Patrick Michaels’s testimony of February 12, 2009. The red and orange lines show the upper and lower significant range (95% of all model runs are between the lines) of global temperature trends calculated by 21 IPCC AR4 models for multi-year segments ending in 2020. The blue and green lines show observed temperatures ending in 2008 from satellite (University of Alabama in Huntsville) and surface (U.K. Hadley Center for Climate Change) records.

Christy comments:

The two main points here are (1) the observations are much cooler than the mid-range of the model spread and are at the minimum of the model simulations and (2) the satellite adjustment for surface comparisons is exceptionally good. The implication of (1) is that the best estimates of the IPCC models are too warm, or that they are too sensitive to CO2 emissions.

Christy illustrates this another way in his comment on EPA’s endangerment proposal.

Figure description: Mean and standard error of 22 IPCC AR4 model temperature projections in the mid-range (A1B) emissions scenario. From 1979 to 2008, the mean projection of the models is a warming of 0.22ºC per decade. HADCRUT3v (green) is a surface dataset, UAH (blue) and RSS (purple) are satellite data sets.

Christy comments:

. . . even with these likely spurious warming effects in HADCRUT3v and RSS, the mean model trends are still significantly warmer than the observations at all time scales examined here. Thus, the model mean sensitivity, a quantity utilized by the IPCC as about 2.6ºC per doubled CO2, is essentially contradicted in these comparisons.

Michaels, in his testimony, shows that if year 2008 temperatures persist through 2009, then the observed temperature trend will fall below the 95% confidence range of model projections. In other words, the models will have less than a 5% probability of being correct.

Although the IPCC AR4 models have not failed yet, they are, in Michaels’s words, “in the process of failing,” and the longer the current temperature regime persists, the worse the models will perform.

Conclusion

The climate science debate is not “over.” In fact, it is just starting to get very, very interesting. All the basic issues–detection, attribution, and sensitivity–are unsettled and more so today than at any time in the past decade.

A final thought–anyone who wants further convincing that the debate is not over should read the marvelous NIPCC report. On a wide range of issues (nine main topics and 60 sub-topics), the report demonstrates that the scientific literature allows, and even favors, reasonable alternative assessments to those presented by the IPCC.

P.S. Previous posts in this series are available below:

Policy Peril: Looking for an antidote to An Inconvenient Truth? Your search is over

Policy Peril Segment 1: Heat Waves

Policy Peril Segment 2: Air Pollution

Policy Peril Segment 3: Hurricanes

Policy Peril Segment 4: Sea-Level Rise