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A study by Joel Schwartz challenges the scientific basis of both the Bush Administrations Clear Skies Initiative and Senator Jim Jeffordss (I-Vt.) Clean Power Act. The analysis has implications for climate policy because Jeffordss legislation includes regulation of carbon dioxide emissions and Bushs plan could serve as a proxy climate policy by forcing utilities to close coal-fired power plants in order to reach the limits on mercury emissions.

Clear Skies and Clean Power would impose tough new controls on power plants to reduce levels of fine particle (PM_2.5) pollution, which both sides claim kills tens of thousands of people per year. Supporters of these bills promise substantial benefits from additional PM reductions.

Schwartzs new study, published by the Competitive Enterprise Institute, argues that Clear Skies and Clean Power rest on a weak scientific foundation. The U.S. Environmental Protection Agency (EPA) based its new annual fine PM (PM_2.5) standard on a study known as the American Cancer Society (ACS) study of PM and mortality, which assessed the association between the risk of death between 1982 and 1998 with PM_2.5 levels in dozens of American cities.

Although the ACS study reported an association between PM and mortality, some odd features of the ACS results suggest that PM is not the culprit. For example, higher PM levels increased mortality in men, but not women; in those with no more than a high school degree, but not those with at least some college; in former-smokers, but not current- or never-smokers; and in those who said they were moderately active, but not those who said they were very active or sedentary.

These odd variations in the relationship between PM_2.5 and mortality seem biologically implausible. Even more surprising, the ACS study reported that higher PM_2.5 levels were not associated with an increased risk of mortality due to respiratory disease; a surprising finding, given that PM would be expected to exert its effects through the respiratory system.

EPA also ignored the results of another epidemiological study that found no effect of PM_2.5 on mortality in a cohort of veterans with high blood pressure, even though this relatively unhealthy cohort should have been more susceptible to the effects of pollution than the general population. The evidence therefore suggests that EPAs annual standard for PM_2.5 is unnecessarily stringent. Attaining the standard will be expensive, but is unlikely to improve public health.

Air pollution has declined dramatically over the past 30 years, and will continue to decline, both because more recent vehicle models start out cleaner and stay cleaner as they age than earlier ones, and also because already-adopted standards for new vehicles and existing power plants will come into effect in the next few years.

If policymakers feel they must do something to speed up PM reductions, Schwartz advises they offer people tax incentives to scrap high-polluting older vehicles that account for a substantial portion of ambient PM levels in metropolitan areas. This flexible, cost-effective approach is more likely to result in net public health benefits than either Clear Skies or Clean Power.

The study is available at http://www.cei.org/gencon/025,03452.cfm.

Announcement

The Cooler Heads Coalition and the George C. Marshall Institute will host a congressional staff and media briefing on Friday, May 16, from Noon to 1:30 PM in Room G-50 of the Senate Dirksen Office Building. Dr. Willie Soon, a research physicist with the Harvard-Smithsonian Center for Astrophysics, will speak on, “Was the Twentieth Century Climate Unusual? Exploring the Lessons and Limits of Climate History.”

Lunch will be provided, and reservations are required. To register, please telephone the Marshall Institute at (202) 296-9655 or e-mail them at info@marshall.org.

Soons talk will be based on a recent major review article of which he was the lead author. See the April 16 issue for more details. The article has been posted on the web at http://cfa-www.harvard.edu/~wsoon/1000yrclimatehistory-d/. A less technical version is available on the Marshall Institutes web site at www.marshall.org/pdf/materials/136.pdf.

Evidence Confirms Existence of Naturally-Occurring, Large-Scale Climate Change

A new study reviewing over 240 climate studies shows that the 20^th century is neither the warmest century nor the century with the most extreme weather over the last 1000 years as has been argued by some scientists. Michael Mann and his collaborators, for example, have published studies using proxy data to reconstruct past global temperatures suggesting that the Medieval Warm Period never existed and that the Little Ice Age was not a global phenomenon. They also argued that the 20^th century was the warmest in the last 1000 years. Their research and the resulting “hockey stick” graph showing significant and anomalous 20^th century warming were featured prominently in the IPCCs Third Assessment Report.

The new study, conducted by Willie Soon and Sallie Baliunas with the Harvard-Smithsonian Center for Astrophysics, Craig and Sherwood Idso with the Center for the Study of Carbon Dioxide and Global Change, and David Legates with the Center for Climatic Research at the University of Delaware, sets out to answer three questions.

1) “Is there an objectively discernible climatic anomaly occurring during the Little Ice Age, defined as 1300-1900 A.D.?”

2) “Is there an objectively discernible climatic anomaly occurring during the Medieval Warm Period, defined as 800-1300 A.D.?”

3) “Is there an objectively discernible climatic anomaly occurring within the 20^th century that may validly be considered the most extreme (i.e., the warmest) period in the record?”

To answer these questions, the researchers reviewed the extensive scientific literature on the available climate proxy data. “Many true research advances in reconstructing ancient climates have occurred over the past two decades,” said Soon, “so we felt it was time to pull together a large sample of recent studies from the last 5-10 years and look for patterns of variability and change.”

The researchers analyzed numerous climate indicators including: borehole data; cultural data; glacier advances or retreats; geomorphology; isotopic analyses from lake sediments or ice cores, tree or peat celluloses (carbohydrates), corals, stalagmite or biological fossils; net ice accumulation rates, including dust or chemical counts; lake fossils and sediments; river sediments; melt layers in ice cores; phenological (recurring natural phenomena in relation to climate) and paleontological fossils; pollen; seafloor sediments; luminescent analysis; tree ring growth, including either ring width or maximum late-wood density; and shifting tree line positions plus tree stumps in lakes, marshes and streams.

What they found from analyzing many more proxy records than did Mann flatly contradicts his conclusions. “Climate proxy research does yield an aggregate and broad perspective on questions regarding the reality of the Little Ice Age, the Medieval Warm Period and the 20^th century surface thermometer global warming. The picture emerges from many localities that both the Little Ice Age and Medieval Warm Period are widespread…. [and] are worthy of their respective labels. Furthermore, thermometer warming of the 20^th century across the world seems neither unusual nor unprecedented within the more extended view of the last 1000 years. Overall, the 20^th century does not contain the warmest or most extreme anomaly of the past millennium in most of the proxy records” (Energy and Environment, March 2003).

Urban Heat in Houston

The urban heat island (UHI) effect is a well known phenomenon that causes an upward bias in the temperature records used to determine whether the earth is warming up. Because concrete, asphalt and steel retain heat better than natural landscapes, cities are warmer than their surrounding areas. As cities grow this temperature bias grows also, making it difficult to determine whether global temperatures are increasing due to greenhouse gases or urbanization. Attempts have been made to account for these biases, but there is simply no way to know whether the methods used are adequate.

New research appearing in the March issue of Remote Sensing of Environment, suggests that the UHI can have a large influence on temperatures. David Streutker with the Department of Physics and Astronomy at Rice University, used satellite remote sensing to determine the effect of urban growth on temperatures in Houston, Texas. Data was collected from two discrete time periods, March 1985 to February 1987 and July 1999 to June 2001. Eighty-two relatively cloud free images were obtained from the first period and 125 were obtained for the second period.

What Streutker found upon analyzing the data is that the temperature from rural areas around Houston experienced no change in temperature. But for the Houston metropolitan area, “Over the course of 12 years, between 1987 and 1999, the mean nighttime surface temperature heat island of Houston increased 0.82 0.10 [degrees C] in magnitude.” This is a rather striking increase, especially when compared to the general belief that global temperatures have only risen about 0.6 degrees C over the last 100 years. Streutker also noted that, “The growth in UHI, both in magnitude and spatial extent, scales roughly with the increase in population, at approximately 30 percent.” World population has increased 280 percent over the last century.

Irrigation Blamed for Warming San Joaquin Valley

A new study funded by the National Science Foundation suggests that the warming experienced in the San Joaquin Valley in California is due to increasing amounts of irrigated land rather than carbon dioxide emissions. One of the researchers, John Christy, director of the Earth System Science Center at the University of Alabama in Huntsville, said that increases in humidity from irrigation may be the culprit in rising temperatures.

“One of the big issues right now is human-induced climate change from carbon dioxide,” said Christy. “Temperatures in the valley are used to assess climate change, and the typical view has been that if there is warming, it must be due to carbon dioxide, therefore we must reduce the use of fossil fuels. Actually, it appears temperature in the valley could be due to a different human factor, and that is irrigation.”

Night-time temperatures in the valley have risen by about 4 degrees over the past 70 years, according to Christy. The study area contains two million irrigated acres and the resulting increases in humidity may be preventing nighttime air from cooling off. “The evidence shows that if this were a large scale climate change caused by carbon dioxide, it would affect the valley, the foothills and the mountains. But we have not seen these changes in the higher elevations,” said Christy.

Environmentalists questioned the usefulness of the research. Bernadette Del Chiaro, a spokeswoman for Environment California worried that this might derail efforts to suppress energy usage. “There may be multiple factors causing climate change,” said Del Chiaro. “But regardless, there is still the larger problem, which is our dependence on fossil fuels.”

When the United Nations Intergovernmental Panel on Climate Change released its Third Assessment Report (TAR) in 2001, many were surprised that its projections for temperature increases had risen substantially. The IPCCs 1996 Second Assessment Report (SAR) predicted that the earths temperature could increase by as much as 0.9 to 3.5 degrees Celsius. The TAR, however predicted a rise of 1.4 to 5.8 degrees C. In a paper published in the Journal of Climate (October 15, 2002), Thomas Wigley with the National Center for Atmospheric Research and Sarah Raper with the Climatic Research Unit at the University of East Anglia, ask the question, “Why are the more recent projections so much larger?”

The authors attempt to quantify how much of the change in projections was due to the new emissions scenarios presented in the IPCCs Special Report on Emissions Scenarios, and how much was due to differences in the science used in the climate models. To determine this, the authors plugged the emissions scenarios responsible for the high and low ends of the temperature projections into the models used for the TAR, what Wigley and Raper call the “TAR science.”

For the TARs high end, coal-intensive scenario, the “CO2 concentrations are remarkably similar” to those used for the high-end scenario in the SAR. The biggest differences between the two high-end scenarios are the assumptions about sulfate aerosol concentrations, which are thought to offset warming. “The large aerosol forcing differences arise because the SRES scenarios account for likely policy responses to sulfur pollution…. This leads to substantially lower SO2 emissions than for the [SAR scenarios].” There are also some differences in methane forcing and tropospheric ozone forcing. This exercise revealed a difference in forcing from changes in the TAR greenhouse gas cycle from 0.5 Watts per meter squared (W/m2) at the low end to 2 W/m2 at the high end.

The differences in science between the two reports refer to changes in the way the models handle complex climate processes. So it is not so much a change in science as a change in modeling. To determine how these changes affect the projections, Wigley and Raper compare the low and high-end scenarios using SAR science and TAR science. What they found was that “the effects on concentration projections for any give emission scenario are relatively small.”

In fact, there was actually a reduction in CO2 forcing combined with increased warming. This was due primarily to two thingsa change in a parameter that defines the relationship between CO2 concentrations and forcing and a change in how the thermohaline circulation (THC) was modeled. A slowdown in the THC, for example, would offset some of the projected warming due to higher greenhouse gas concentrations. In the TAR, the THC will not slow down as much as assumed in the SAR.

The result of these exercises reveals that very little of the change in temperature projections is due to changes in scientific understanding or better modeling, but due almost entirely to different emissions scenarios. “At the low warming limit, TAR science inflates the 1990-2100 warming for the [low-end SAR scenario] by around 34 percent,” says Wigley and Raper. “At the high end, TAR science inflates the 1990-2100 warming for the [high-end SAR scenario] by around 4 percent.” The rest of the high-end alarmist projection comes from changes in the worst-case storyline, which has little basis in reality. A full 79 percent of the change at the high-end projection came from the changed assumptions about sulfate aerosols alone, about which we know very little.

The history of science and politics explains a lot about the manifold distortions, exaggerations, and outright hokum that regularly appear in some of our major journals on the subject of global warming.

Specifically, Thomas Kuhn’s landmark book The Structure of Scientific Revolutions (first published in 1967 and reprinted about a zillion times) demonstrates that scientists have a herd mentality in which almost everyone believes in some reigning “paradigm” (in this case, disastrous global warming). Careers are spent proving that paradigm and discounting anything that disagrees with prevailing theory. That’s “science.”

As for “politics,” the two intersect, writes James Buchanan, when researchers find they can sell their ideas to policymakers for mutual gain: If a little distortion is required, so be it. That’s a powerful prism through which we must view so-called “facts”: a throng of scientists acting in concert with the political process.

Prism in hand, we can’t say we were surprised when the science community’s weekly lobbying newsletter, Science magazine, couldn’t stop gushing about recent research purportedly demonstrating that climate models of gloom and doom are right after all and the satellite temperature records reporting precious little warming were wrong.

Don’t misunderstand: Science does also report on scientific research. But anyone who thinks it isn’t lobbying hasn’t read the news or editorial sections and just about anything else in it that isn’t hard science. And any idea that Science is fair and balanced on the subject of global warming can be thrown into the trash along with previous issues.

At least that’s all we can take from their most recent handling of a new take on satellite-measured global temperature data. On May 1, Sciencexpress (a web page where the magazine posts “selected” paperschosen for their “timeliness and importance”before they actually appear in print) featured research led by Lawrence Livermore’s Ben Santer showing that climate models were in better agreement with a newly produced, and as yet unpublished, version of the satellite-measured temperature history that includes a warming trend about three times that of the oft-peer reviewed satellite-temperature history constructed by John Christy and Roy Spencer.

Although the paper itself does not come right out and say it, a between-the-lines read suggests that because the new satellite dataset is in closer agreement with model results, it is likely the more accurate reflection of the actual state of the lower atmosphere. And just in case you didn’t get that message from the paper itself, the accompanying Science press release makes it clear: “A stubborn argument against global warming may be discredited by a reanalysis of the raw data central to its claims.”

Santer used a climate model to discriminate between two versions of the satellite datathe one published by Christy that shows very little warming, and a modified, unpublished version by Frank Wentz that shows much more heating. That was certainly a novel approach because it wasn’t science. In science, we don’t bend data to fit models and then pronounce those models correct. Rather, we bend models to accommodate datathat is, reality.

If Science had any intent to be fair and balanced, it would have noted that John Christy and colleagues published a paper at the exact same time that checked the satellite data the old-fashioned (i.e., scientific) way. He and Roy Spencer compared their record with a totally independent measurement of lower-atmosphere temperature, taken from daily weather balloons, and found the two to be in strong agreement.

Weather balloons are launched twice daily from sites around the world; as they ascend through the atmosphere, they radio back observations of temperature, humidity, and pressure that are used to initialize models of daily weather forecasts. Balloon observations can be compiled into a record of lower-atmospheric temperatures that can then be compared with the satellite measurements.

It is important to realize that the way the weather-balloon data are collected is completely different from how we obtain satellite observations, and thus represents an independent measurement of the same quantity (atmospheric temperature). Of course, as is the case with any measurement, there are complications that must be considered when compiling the raw data.

For that reason, there are several different research groups that have released their own versions of the weather-balloon temperature history. To protect against any accusation of picking only the particular data set that best matches their satellite observations, Christy and Spencer compared the temperature trend during the past 24 years derived from their observations with the trend during the same period as calculated from four different manifestations of the global weather-balloon history.

Figure 1 shows what they found. The trend in their satellite record is 0.06C per decade. The trends from the various weather-balloon records range from 0.02C per decade to 0.05C per decade. In each case, the trend in the satellite record was slightly greater than that in the weather-balloon records, and the match with the two weather-balloon records with the most complete coverage of the globe was within 0.02C. That close correspondence is remarkable: Remember, these are independent observations.

 

Figure 1. A comparison of trends in satellite-measured temperatures (two columns on left) and weather balloonmeasured temperatures (four columns on right, including one equal to zero).

How does the Wentz and Schabel data set compare with the weather balloons? In a word, poorly. So poorly, in fact, that Santer and colleagues, instead of performing such a comparison themselves (as Christy and Spencer did), obviously anticipated the results and instead simply resorted to taking a swipe at the veracity of the weather-balloon data, saying that “As with [satellite] data, however, there is evidence that the choice of the ‘adjustment pathway’ for radiosonde data markedly influences the size and even the sign of the estimated global-scale trend.” The need to crash the satellite data is as obvious. As Tom Wigley stated in the press release from the U.S. National Center for Atmospheric research concerning the Santer paper: “The real issue is the trend in the satellite data from 1979 onward. If the original analysis of the satellite data were right, then something must be missing in the models.”

Obviously, the global warming community as a whole cannot take such a possibility lightly. Still, it is behaving in a much more predictable fashion than the climateprecisely, in fact, as Kuhn’s and Buchanan would predict. Faced with mounting evidence, it resorts to increasingly bizarre excuses as to why the models are still right, even to the point of disparaging actual real-world observations when necessary.

The question remains, and since they didn’t ask it, we will: Which do you believe, models or reality?

We’ll take reality every time.

References

Christy, J.R., et al., 2003. Error estimates of version 5.0 of MSUAMSU bulk atmospheric temperatures. Journal of Atmospheric and Oceanic Technology, 20, 613629.

Santer, B.D., et al., 2003. Influence of satellite data uncertainties on the detection of externally forced climate change, Sciencexpress,1 May.