Global Warming BombshellA prime piece of evidence linking human activity to climate change turns out to be an artifact of poor mathematics.
Progress in science is sometimes made by great discoveries. But science also advances when we learn that something we believed to be true isnt. When solving a jigsaw puzzle, the solution can sometimes be stymied by the fact that a wrong piece has been wedged in a key place. In the scientific and political debate over global warming, the latest wrong piece may be the hockey stick, the famous plot (shown below), published by University of Massachusetts geoscientist Michael Mann and colleagues. This plot purports to show that we are now experiencing the warmest climate in a millennium, and that the earth, after remaining cool for centuries during the medieval era, suddenly began to heat up about 100 years ago--just at the time that the burning of coal and oil led to an increase in atmospheric levels of carbon dioxide. I talked about this at length in my December 2003 column. Unfortunately, discussion of this plot has been so polluted by political and activist frenzy that it is hard to dig into it to reach the science. My earlier column was largely a plea to let science proceed unmolested. Unfortunately, the very importance of the issue has made careful science difficult to pursue. But now a shock: Canadian scientists Stephen McIntyre and Ross McKitrick have uncovered a fundamental mathematical flaw in the computer program that was used to produce the hockey stick. In his original publications of the stick, Mann purported to use a standard method known as principal component analysis, or PCA, to find the dominant features in a set of more than 70 different climate records. But it wasnt so. McIntyre and McKitrick obtained part of the program that Mann used, and they found serious problems. Not only does the program not do conventional PCA, but it handles data normalization in a way that can only be described as mistaken. Now comes the real shocker. This improper normalization procedure tends to emphasize any data that do have the hockey stick shape, and to suppress all data that do not. To demonstrate this effect, McIntyre and McKitrick created some meaningless test data that had, on average, no trends. This method of generating random data is called Monte Carlo analysis, after the famous casino, and it is widely used in statistical analysis to test procedures. When McIntyre and McKitrick fed these random data into the Mann procedure, out popped a hockey stick shape! That discovery hit me like a bombshell, and I suspect it is having the same effect on many others. Suddenly the hockey stick, the poster-child of the global warming community, turns out to be an artifact of poor mathematics. How could it happen? What is going on? Let me digress into a short technical discussion of how this incredible error took place.  In PCA and similar techniques, each of the (in this case, typically 70) different data sets have their averages subtracted (so they have a mean of zero), and then are multiplied by a number to make their average variation around that mean to be equal to one; in technical jargon, we say that each data set is normalized to zero mean and unit variance. In standard PCA, each data set is normalized over its complete data period; for key climate data sets that Mann used to create his hockey stick graph, this was the interval 1400-1980. But the computer program Mann used did not do that. Instead, it forced each data set to have zero mean for the time period 1902-1980, and to match the historical records for this interval. This is the time when the historical temperature is well known, so this procedure does guarantee the most accurate temperature scale. But it completely screws up PCA. PCA is mostly concerned with the data sets that have high variance, and the Mann normalization procedure tends to give very high variance to any data set with a hockey stick shape. (Such data sets have zero mean only over the 1902-1980 period, not over the longer 1400-1980 period.) The net result: the principal component will have a hockey stick shape even if most of the data do not. |
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 Massachusetts Institute of Technology |
© 2009 Technology Review. All Rights Reserved. |
Comments
02/08/2006
Posts:1
alex75
01/30/2007
Posts:2
02/09/2006
Posts:1
04/04/2006
Posts:1
roncram
12/11/2006
Posts:1
alex75
01/30/2007
Posts:2
WATCH OUT! now what! storm are coming... sea is rising... abnormal climate oohh my! now they are going to get us alive.. OOOHH! God what have we done!.. WAKE UP! WAKE UP! we are close too late.. make up your mind ... cure the invironment fast..
roldan_sibay...
02/05/2007
Posts:1
"If, on the other hand, we reject the hockey stick, and recognize that natural fluctuations can be large, then we will not be misled by a few years of random cooling."
Thanks for that little editorial comment on "random cooling."
As it appears likely the earth is indeed in a cooling period and may well be for the next ten to twelve years, who says global cooling is at all random?
Pete357
09/08/2008
Posts:1
.....
yyy=reform(compmxd(*,2,1))
;mknormal,yyy,timey,refperiod=[1881,1940]
;
; Apply a VERY ARTIFICAL correction for decline!!
;
yrloc=[1400,findgen(19)*5.+1904]
valadj=[0.,0.,0.,0.,0.,-0.1,-0.25,-0.3,0.,-0.1,0.3,0.8,1.2,1.7,2.5,2.6,2.6,$
2.6,2.6,2.6]*0.75 ; fudge factor
if n_elements(yrloc) ne n_elements(valadj) then message,'Oooops!'
;
yearlyadj=interpol(valadj,yrloc,timey)
......
Please note the remark in the code :'Apply a VERY ARTIFICAL correction for decline!!'
Note also:
valadj=[0.,0.,0.,0.,0.,-0.1,-0.25,-0.3,0.,-0.1,0.3,0.8,1.2,1.7,2.5,2.6,2.6,$
2.6,2.6,2.6]*0.75 ; fudge factor
This lines might seem cryptic but they clearly indicate that the program used to analyse the temperatures has been modified in order to produce results showing temperature increases instead of declines. Basically a fudge factor is applied to temperatures that do not agree with the global warming religion.
It is clear that this demonstrates a total lack of ethic.
Gross!
branwenn
12/01/2009
Posts:1
The simple truth about climate change is that it is due to our use of energy of all sorts, from Coal and hydrocarbons, hydro electricity, nuclear fission, solar panels for electricity or heating, wind power, hybrid cars, electric cars, battery operated devices. All forms of energy used by man , eventually put that energy into the atmosphere and heat it.
The most used energy sources are coal and hydrocarbons , about 80 percent , all the other forms make up the rest.
If one does simple calculations, as I have done , one finds that the hydrocarbon usage has heated the atmosphere by 1.68 deg K, over the past 210 years. If we divide the 1.68 by 0.8 we get a temperature rise of 2.1 deg K. (Which is the claimed rise experienced to date)
Now if one subtracts that value from the rise in temperature experienced over the same time period the result is 0 .
What this means for climate modelers and alarmists is truly devastating as it means all their modeling work is incorrect, as there is no " greenhouse " effect.; rather it is just a purely chemical effect due to the release of energy.
The earth's atmosphere can be considered a closed system to a great extent.
The atmosphere has an average temperature, which is contained in the bulk of the gases.
The only way for the earth to lose heat is by radiation from the top of the atmosphere.
Now if the top of the atmosphere consists of only 1 percent of the atmosphere and is quite cold it radiates heat based on its temperature .
Now if the bulk atmosphere temperature rises by 2. 1 degree K this does not mean that the temperature rises by 2.1 deg K everywhere.
The bulk will contain enough energy to give an average temperature which is 2.1 degrees higher, however the cold radiative surface temperature will only increase slightly.
Without doing any mass and heat transfer equations , my estimate is that the radiative surface temperature will only rise by 0.01 deg. K.
The heat loss will merely increase by 0.14 percent., which is within the error of measurement for heat loss.
This therefore means that while there is a climate warming effect, it is due simply to the combustion / energy use values and to a radiative altering "greenhouse" effect.
The current heating rate works out to be 0.8 deg. K per century. So it will take another 200 years before we get to a level of 4 deg. k higher than it was in 1800.
Sure the ice cap in the arctic is melting and polar bears are threatened in some locations, but there is very little we can do about the heating process other than to stop using any form of energy, which means going back to pre- industrial revolution activities, and which of us , especially the elite of Hollywood and Congress , is willing to do that.
There are some benefits of more CO2 in the atmosphere. Better crop yields, faster tree growth, a shorter route to Europe from Asia, therefore less energy expended shipping goods, lower heating costs offset by high cooling costs, although to feel cool we only need to lower the temp by 10 deg K in the summer, but to feel warm we need to raise the temp by 20 deg K in the winter.
Here are the numbers I have used in my calculations.
It's our lifestyle not a Greenhouse effect
Some scientists do not take the time to do the basic science related to climate heating.
I have and this is the result
I use
C = 7 Gigatonnes of Carbon/year = 7e12 kg Carbon/year burned to CO2
E = 678kJ/(0.014kg of (Carbon + H2))=56500000 J/(kg of Carbon) energy released to heat the atmosphere.
C_p = 1000 J/(K * kg of dry air)
M = 5e18 (kg of dry air) (total mass of atmosphere; you can also use (area of earth)*(surface pressure)/(gravity))
so
(dT/dt)=[(7e12 kg Carbon/year)*56500000 J/(kg carbon)]/[1000 J/(K * kg of dry air)*5e18 (kg of dry air)]=8e-2 K/year=0.008 K/year=0.8 K/century. so over 2.1 centuries this is 1.68 K
Simply put this means that for every kg of coal or oil burned we heat 56,500 kgs( about 56 tons) of air 1 degree Kelvin / centigrade or 1.8 degrees F. This and this alone can account for the rise in temperature that has occurred over the past 210 years.
Selwyn Firth
Toronto.
Dec 1, 2009.
ZAPHBEEBLEBR...
12/01/2009
Posts:1