Iowahawk offers readers “a detailed how-to-guide for replicating the climate reconstruction method used by the so-called “Climategate” scientists. Not a perfect replication, but a pretty faithful facsimile that you can do on your own computer, with some of the same data they used.”

It takes 30-60 minutes, along with modest math & spreadsheet skills, he promises.

My goal was to provide interested people with a hands-on DIY example of the basic statistical methodology underlying temperature reconstruction, at least as practiced by the leading lights of “Climate Science.”

If you’ve followed all this, it should also give you the important glossary terms that should help you decipher the Climategate emails and methodology discussions. For example “instrumental data” means observed temperature; “reconstructions” are the modeled temperatures from the past; “proxy” means the tree ring, ice core, etc. predictors; “PCs” mean the principal components.

Is there anything wrong with this methodology? Not in principle. In fact there’s a lot to recommend it. There’s a strong reason to believe that high resolution proxy variables like tree rings and ice core o-18 are related to temperature. At the very least it’s a more mathematically rigorous approach than the earlier methods for climate reconstruction, which is probably why the hockey stick / AGW conclusion received a lot of endorsements from academic High Society (including the American Statistical Association).

The devil, as they say is in the details. In each of the steps there is some leeway for, shall we say, intervention. …

(If you run a few tests,)

(C)ontrary to Mann’s assertion that the hockey stick is “robust,” you’ll find that the reconstructions tend to be sensitive to the data selection. M&M found, for example, that temperature reconstructions for the 1400s were higher or lower than today, depending on whether bristlecone pine tree rings were included in the proxies.

What the leaked emails reveal, among other things, is some of that bit of principal component sausage making. But more disturbing, they reveal that the actual data going into the reconstruction model — the instrumental temperature data and the proxy variables themselves — were rife for manipulation. In the laughable euphemism of Philip Jones, “value added homogenized data.” The data I provided here was the real, value added global temperature and proxy data, because Phil told me so. Trust me!