Posted on 02/01/2012 6:19:45 PM PST by Ernest_at_the_Beach
That letter signed by 16 scientists saying theres No Need to Panic About Global Warming to the Wall Street Journal has caused a great disturbance in the farce. At last count there were no less than 19 blog rebuttals plus one new WSJ op ed piece trying to convince the alliance that all is well. It didnt work.
But, they know the AGW Alliance Death Star has been compromised before its mission can be completed, the Rebellion has seen the plans and the Alliance knows it is only a matter of time before the consensus blows apart. Reports are that Michael Mann has been tweeting furiously, but the reinforcements hes bringing in may not be able to stop the Rebellion as its ranks swell with ordinary people.
Here at WUWT, we had our best day ever on January 31st with 229,000 views from ordinary people, exceeding the heady days just after Climategate 1 and Copenhagen. People are coming in out of the cold to embrace the warmth and declare it good, while laughing at the folly of the alliance.
Meanwhile, the Bad Astronomer (Phil Plait er, not Jim Hansen) has been spinning in low orbit trying tell alliance forces that the past 10-15 years of stalled temperature rise are just a statistical illusion.
William Briggs, Statistician to the Stars, schools Plait on what statistics really is and writes:
Remember when I said how you shouldnt draw straight lines in time series and then speak of the line as if the line was the data itself? About how the starting point made a big difference in the slope of the line, and how not accounting for uncertainty in the starting date translates into over-certainty in the results?
If you cant recall, refresh your memory: How To Cheat, Or Fool Yourself, With Time Series: Climate Example.
Well, not everybody read those warnings. As an example of somebody who didnt do his homework, I give you Phil Plait, a fellow who prides himself on exposing bad astronomy and blogs at Discover magazine. Well, Phil, old boy, I am the Statistician to the Starsget it? get it?1and Im here to set you right.
The Wall Street Journal on 27 January 2012 published a letter from sixteen scientists entitled, No Need to Panic About Global Warming, the punchline of which was:
Every candidate should support rational measures to protect and improve our environment, but it makes no sense at all to back expensive programs that divert resources from real needs and are based on alarming but untenable claims of incontrovertible evidence.
Plait in response to these seemingly ho-hum words took the approach apoplectic, and fretted that denialists were reaching lower. Reaching where he never said. He never did say what a denialist was, either; but we can guess it is defined as Whoever disagrees with Phil Plait.
The WSJs crew said, Perhaps the most inconvenient fact is the lack of global warming for well over 10 years now. This allowed Plait to break out the italics and respond, What the what? I wouldve guessed that the scientists statement was fairly clear and even true. But Plait said, That statement, to put it bluntly, is dead wrong. Was it?
Plait then slipped in a picture, one which he thought was a devastating touché. He was so exercised by his effort that he broke out into triumphal clichés like crushed to dust and scraping the bottom of the barrel. You know what they say about astronomers. Anyway, heres the picture:
See that red line? Its drawn on a time serieswait! No it isnt. Those dots are not what Plait thinks they are. They are notthey most certainly are notglobal temperatures.
Read the whole rebuttal here, well worth your time.
Maybe Our Republican candidates will hear about all of the Uproar...and get a clue!
No Need to Panic About Global Warming
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Editor's Note: The following has been signed by the 16 scientists listed at the end of the article:
A candidate for public office in any contemporary democracy may have to consider what, if anything, to do about "global warming." Candidates should understand that the oft-repeated claim that nearly all scientists demand that something dramatic be done to stop global warming is not true. In fact, a large and growing number of distinguished scientists and engineers do not agree that drastic actions on global warming are needed.
In September, Nobel Prize-winning physicist Ivar Giaever, a supporter of President Obama in the last election, publicly resigned from the American Physical Society (APS) with a letter that begins: "I did not renew [my membership] because I cannot live with the [APS policy] statement: 'The evidence is incontrovertible: Global warming is occurring. If no mitigating actions are taken, significant disruptions in the Earth's physical and ecological systems, social systems, security and human health are likely to occur. We must reduce emissions of greenhouse gases beginning now.' In the APS it is OK to discuss whether the mass of the proton changes over time and how a multi-universe behaves, but the evidence of global warming is incontrovertible?"
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The fact is that CO2 is not a pollutant. CO2 is a colorless and odorless gas, exhaled at high concentrations by each of us, and a key component of the biosphere's life cycle. Plants do so much better with more CO2 that greenhouse operators often increase the CO2 concentrations by factors of three or four to get better growth. This is no surprise since plants and animals evolved when CO2 concentrations were about 10 times larger than they are today.
I know for a fact that the CFC known as R-12, the primary existing refrigerant before some professor at UC California Irvine got a Noble prize for saying that CFCs were destroying the upper atmosphere ozone layer, weighs more than air... about six times more than air. That means that R-12 released into the atmosphere drops like a rock.
Shipyard workers need to know this because refrigerants released inside a ships hull would push out - replace - air held inside the hull and kill anyone not equipped with breathing apparatus.
This guy calls himself a mathematician? He is either incompetent or lying. When fitting a straight line to data the most common approach is to use a least-squared-error method. When using this algorithm over even a modest number of data points the value of any one (eg. the starting point) makes little difference - there is no particular significance to that value over the second, third, nth...
My take, lying POS. Counting on most people not being familiar with math, and their eyes glazing over when they hear one of the anointed speak... Well, I don't buy it, the Emperor has no clothes.
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Alarmism over climate is of great benefit to many, providing government funding for academic research and a reason for government bureaucracies to grow. Alarmism also offers an excuse for governments to raise taxes, taxpayer-funded subsidies for businesses that understand how to work the political system, and a lure for big donations to charitable foundations promising to save the planet.
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Claude Allegre, former director of the Institute for the Study of the Earth, University of Paris; J. Scott Armstrong, cofounder of the Journal of Forecasting and the International Journal of Forecasting; Jan Breslow, head of the Laboratory of Biochemical Genetics and Metabolism, Rockefeller University; Roger Cohen, fellow, American Physical Society; Edward David, member, National Academy of Engineering and National Academy of Sciences; William Happer, professor of physics, Princeton; Michael Kelly, professor of technology, University of Cambridge, U.K.; William Kininmonth, former head of climate research at the Australian Bureau of Meteorology; Richard Lindzen, professor of atmospheric sciences, MIT; James McGrath, professor of chemistry, Virginia Technical University; Rodney Nichols, former president and CEO of the New York Academy of Sciences; Burt Rutan, aerospace engineer, designer of Voyager and SpaceShipOne; Harrison H. Schmitt, Apollo 17 astronaut and former U.S. senator; Nir Shaviv, professor of astrophysics, Hebrew University, Jerusalem; Henk Tennekes, former director, Royal Dutch Meteorological Service; Antonio Zichichi, president of the World Federation of Scientists, Geneva.
Defining CO2 as a “pollutant” was a gimmick perpetrated to give the EPA the power to regulate fossil fuel emissions.
Thanks for reminding me how irritating I find this ‘bad astronomy’ guy. He seems like an arrogant twerp to me.
You’re critiquing on the basis of having heard part of the discussion. Briggs was referring to an older post on his blog in which he gives examples of real time-series data in which choosing a starting point radically changes the slope of the regression line, not by omitting a data point at one end, but by choosing only to analyse a tail of the time-series: we have estimated surface temperatures going back into the 19th century. Why start at 1973? Why not 1980? or 1960? or 1940? In the older post he linked, he had a real data set in which omitting the first eighth or so of the data gave a radically different regression model. (Even changing by one year would be adding or dropping 12 data points in the example.)
Briggs is not lying and is definitely not incompetent. I am a mathematician, and I’m consistently impressed by Briggs’s insights into his own area (which is not mine, though I have a reasonable grasp of elementary applied statistics and even some non-elementary topics in statistics gleaned from helping my wife who’s in psychology with statistical analyses).
You’re also wrong about a single data point not making much of a difference in OLS regression with a modest number of data points: consider the two data sets
(1,1.1), (2,0.9), (3,1.0), (4,1.0), (5, 0.9), (6, 1.1)
and
(0, 0.0), (1,1.1), (2,0.9), (3,1.0), (4,1.0), (5, 0.9), (6, 1.1)
In the first, the regression line is y = 1
In the second, it has positive slope and a y-intercept less than 1.
In fact, this is a baby example of the phenomenon for which Briggs gave a more realistic example.
And, where the errant point is, does matter. If it had been (3.5, 0.0) inserted into the first data set to get the second,
the regression slope would still have been 0 and only the intercept (or rather the height of the whole horizontal regression line) would have changed.
Of course for less modest numbers, the outlier would need to be more extreme.
In the case of a hundred or so data points, for any reasonably self-consistent data set (eg. surface temperature) that isn't likely to see wild data points then any one does not have much of a chance of drastically influencing slope of the line.
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