As damaging the leaked CRU emails are to the Global Warmists, the real truth lies in the code. The computer program that “massages” the raw data into legible graphs and charts. That computer program isn’t written by scientists. It is not even written by anyone closely related to weather or climates: It is written by computer programmers (such as myself) FOR the climatologists. And as a computer programmer, I know that first and foremost the output of your program has to be what the client wants to see. They hired you: they have to be pleased.
I, and a large number of other people along with me, have examined the code leaked by the CRU hacks and I am astonished by the generous amounts of fudging, making up for missing data and adjustments that are mare to the raw input data to result in the now famous hockey stick graph, showing a sharp increase in global temperatures in the past century. I always knew that there were inconsistencies between temperature readings over the years, simply because the thermometers were moved, or temperatures were taken at different times of day. I can understand adjusting, slightly, temperatures to make up for physical differences between readings, but there are a large number of comments in the code, written in there by programmers FOR programmers, that show that programmers just made up “adjustment factors” and “fudge the numbers to hide decline” simply because they were given such inconclusive data, with large holes in it, that generating a graph from that data was simply impossible. And, I suspect, one of the programmers’ parameters must have been to clearly show an increase in temperature over the past 100 years.
This brings us to this piece of code, taken from now famous leaked CRU files:
;
; 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) ;
(Anything following a ‘;’ is a comment from the programmers. As seemingly damning as “Apply a VERY ARTIFICAL correction for decline!!” is, it is just a comment, nothing more).
This code takes years from 1904 to 1999 in 5-year intervals, and assigns a ‘fudge factor’ to them, ranging from -0.1 to 0 in the first half of the century, and a factor of 0 to +2.6 for the latter half. This ‘fudge factors’ will later be applied to the raw data from these years, clearly skewing the numbers to be showing an increase as time goes on.
To make it clearer, I have put the years and their corresponding ‘fudge factors’ in a table, and added a column for a “base temp” and a “fudge factored temp” which takes the base temp and adds the fudge factor for the corresponding year:
| Year: |
‘Fudge factor’ |
Base Temp |
Fudge factored “base temp” |
| 1904 |
0 |
10 |
10 |
| 1909 |
0 |
10 |
10 |
| 1914 |
0 |
10 |
10 |
| 1919 |
0 |
10 |
10 |
| 1924 |
0 |
10 |
10 |
| 1929 |
-0.1 |
10 |
9.9 |
| 1934 |
-0.25 |
10 |
9.75 |
| 1939 |
-0.3 |
10 |
9.7 |
| 1944 |
0 |
10 |
10 |
| 1949 |
-0.1 |
10 |
9.9 |
| 1954 |
0.3 |
10 |
10.3 |
| 1959 |
0.8 |
10 |
10.8 |
| 1964 |
1.2 |
10 |
11.2 |
| 1969 |
1.7 |
10 |
11.7 |
| 1974 |
2.5 |
10 |
12.5 |
| 1979 |
2.6 |
10 |
12.6 |
| 1984 |
2.6 |
10 |
12.6 |
| 1989 |
2.6 |
10 |
12.6 |
| 1994 |
2.6 |
10 |
12.6 |
| 1999 |
2.6 |
10 |
12.6 |
In other words, if we take a steady temperature of 10 C from 1904 to 1999 and apply their ‘fudge factor’, all of a sudden the temperatures show a total increase of 2.6 degrees, rising sharply from 1964 onwards. If plotted on a graph, it would result in the famous hockey stick graph from Micheal Mann.
These ‘fudge factors’ are used by programmers all the time. Take a simple business model: products in a database. These products have a ‘cost price’ stored with them. Now, if the cost of manufacturing goes up by 10%, instead of going into the database and add 10% to every product’s ‘cost price’, it is much easier and more flexible to simply add10% to the price every time the “cost price” gets fetched from the database. That way, we can also vary the increase depending on how expensive the product is, or when or where it was purchased.
Of course, we can’t be sure that this particular piece of code was use to produce the figures that the IPCC used for their reports, however, if anything, it does show clear intent and willingness to fudge the numbers so that they would fall in line with their agenda: climbing temperatures world wide.
If we find out that this piece of code was used on any of the numbers given to the IPCC, clearly, the IPCC reports have to be dismissed as faulty data and all resulting decisions based on those faulty numbers will have to be revisited.
Copyright 2010 ERWIN GERRITS. All Rights Reserved.