Will the Real Hockey Stick Please Stand Up?
Posted by Jeff Condon on October 11, 2008
I won’ t abuse you with my venting today. Mostly pictures. Pretty interesting ones I think.
I used the CPS method today with actual proxies from M08. Instead of the infilled data with the fake hockey stick glued on the end I used the original original 1357 series before processing. I also chopped off the 95 Luterbacher series which aren’t really proxies, they are temperature. It didn’t make any big difference to the shape of graphs in my results but I don’t like em.
There are more pre-deletion Luterbacher series in this data set because they were re-scrambled from 95 into 71 series for M08 most likely using RegEm according to their locations. I previously did a software pattern match for the original 89 Luter to the final 71 and found no match, yet the average was the same.
Anyway, to the fun. I used M08 CPS and r correlation to scale and sort data according to different trends. The point of this article is to show you can produce any trend you want from this method. ANYTHING!
The red line is the temperature trend I am claiming in each graph was true. The blue is the CPS algorithm temperature reconstruction. Since the big claim in M08 was the percentage of series which passed correlation 484 of 1209 take a look at the Percent used in the graphs below.
200 year Hockey stick
200 year Negative HS
100 year Hockey stick
100 year negative hockey stick — NOTE THE HIGH CORRELATION PERCENTAGE
Low r hockey 100 year hockey stick
Low r negative 100 year hockey stick. Note the amazing correlation percentage of 39.43!
Little Ice age
Little warm age
Remember how temps went up then down then up then down.
or was it down then up?
I can’t remember these things didn’t it go up and down 4 times.
Nope, wrong again. It was down then up 4 times.
What happens with an r >0.1. Wow, 495 of the proxies used!
Oh, now I remember it was seven times down and up. That was it.
Alright, you get the idea.
I don’t think Mann had to worry if he would be able to produce a hockey stick, do you?
The strongest correlation I got was for a negative trend in the most recent 100 years with r=0.1 of 39.43 percent of 1357 series (graph 6). Almost as good as Mann08 got with 484 of 1209 series for a value of 40.03%. But wait, I didn’t use luterbacher’s 89 series because they aren’t really proxies so really I had 535 of 1262 series or 42.2 percent. It is better than that though, of Mann’s 484 series 71 were Luterbacher and 90% of the remaining series were infilled with a fake hockey stick. The Schweingruber MXD series represented 105 of the total group but 95 of those passed correlation after 38 YEARS of hockey stick data was pasted on the end TO REPLACE KNOWN DIVERGENCE (down slope). So at best Mann’s percentage is 484 accepted series – 71 Luterbacher – 95 Shweingruber (briffa) series or 318 of 1209 series passed his correlation for 26.3 percent. It’s not fair to give Mann08 1209 because I deleted some for obvious reasons so 1209-71-95 = 1043 starting series. 318/1043 = 30.5% correlation.
Summary — Id percent of proxies correlation to a temp drop r>0.1 - 42.2% Mann08 30.5 temp rise!!
So without manufacturing any data as M08 did, I have achieved a correlation for a drop in temperature in the last 100 years that exceeds the best correlation Mann08 had to offer for a rise in temperature by 42.2/30.5 or 40 percent!!!!
Say what you want about this last calculation but remember I found an equal correlation without the required corrections. I also need to point out that I didn’t spend any time trying to optimize my result, it was without searching around that I achieved this correlation! Note the second to last graph with 36%!!!!