Watts Up With That continues to dig through data. Someone really needs to tell him that data integrity is way overrated in climate science, what with all the settling of science and all.

Yikes again, double yikes! What on earth justifies that adjustment? How can they do that? We have five different records covering Darwin from 1941 on. They all agree almost exactly. Why adjust them at all? They’ve just added a huge artificial totally imaginary trend to the last half of the raw data! Now it looks like the IPCC diagram in Figure 1, all right … but a six degree per century trend? And in the shape of a regular stepped pyramid climbing to heaven? What’s up with that?

Follow the link and check out the graphs. Short version: the adjusted data goes in the exact opposite direction of the raw data with no discernable reason for the adjustment.

I got the link from Megan McCardle, who, as one of her commenters points out, continues to give the benefit of the doubt to the wrong side. That said, McCardle has a great breakdown on the concept of selection bias and how you don’t need a grand conspiracy or actual fakery of data to get a biased result.

That is the actual worrying question about CRU, and GISS, and the other scientists working on paleoclimate reconstruction:  that they may all be calibrating their findings to each other.  That when you get a number that looks like CRU, you don’t look so hard to figure out whether it’s incorrect as you do when you get a number that doesn’t look like CRU–and maybe you adjust the numbers you have to look more like the other “known” datasets.  There is always a way to find what you’re expecting to find if you look hard enough.

There are other issues:  selection bias in the grant process, papers with large results being much more likely to be published than papers with equivocal results, professors preferring students who agree with them, and so forth.  I doubt that could amount to faking the entire thing.  But it could amplify the magnitude.

Read her entire post as well as she quotes from another useful article that gets into the weeds of the possible biases.

A friend of mine asked me if I really thought these scientist would have faked their data (my quick answer was no) but then he went on to say that the skeptics are more likely to fake data because they are the ones who’d be impacted by the regulations. Leaving aside the fact that many of the skeptics do not actually work for Exxon and the like, I shot back that the idea that greed for money is worse than greed for power was willfully naive. I neglected to add that greed for money COULD also apply to the AGW scientists.

The fact is that many climate scientists make their living off government grants or university grants. Environment bureaucrats and university professors are overwhelmingly populated by people with agendas that are left wing, though I know that isn’t really the best adjective but I can’t think of a better one (its not merely liberalism, or marxism, but an anti-capatilist luddism at play). The bureaucrats have agendas. Let’s not kid ourselves. And they control the grant purse strings. Why is a scientists whose funding comes from Exxon less credible than a scientist whose funding comes from an agenda driver bureaucrat? Both funding sources could easily turn off the spiggot if they feel the research no longer fits their agenda. So, while I still say that I don’t THINK the scientists willfully faked data, I do think there is a very real possibility that they used their theory about what they think should happen to adjust observations that didn’t match the theory. In other words, they see the adjustments as logical because they’ve decide their theory is sound. The observations that don’t conform to that sound (or settled) theory are just inconvenient truths.