http://www.ipcc.ch/publications_and_data/ar4/wg1/en/contents...
(There are doubtlessly a couple people queueing up to say the IPCC's part of some grand socialist conspiracy or had some minor error that's since been corrected in the errata section.)
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/contents...
(There are doubtlessly a couple people queueing up to say the IPCC's part of some grand socialist conspiracy or had some minor error that's since been corrected in the errata section.)
1) Compare your collected data series to each other to determine a "reliability" index for each data series.
2) Construct a series as a weighted average on this reliability index.
3) Iterate, using your new series to calculate the reliability index.
There are substantial issues with the above approach, having to do with sensitivity to particular kinds of signals. For a while, the Climate Audit folks got a lot of mileage over a data set that was put in "upside down" in one of the reconstructions. Rather than claiming "data error," the author defended it based on the idea that the above process would just give it a negative weighting!
Regardless, you should see why the above could easily be susceptible to issues. Further, the disagreement between these reconstructions and what our limited historical sources tell us about the MWP, etc., makes them further suspect.
This is a problem for the global warming model because it means that we don't know what the historical standard deviation for temperature is. So we can't say whether the last 3 decades warming is "within normal deviations" or "unprecedented."
I would just point out that scientific debate occurs through published papers and conference presentations, not programming message boards. I hope that you are publishing in those channels if you feel you have substantive contributions to this kind of research.
And happily, informal communication and message boards matter more than you would think!
Also, the published papers reporting these studies are all easily available. I highly advise reading them for yourself.
edit: misspelling
I stand by the importance of published work in scientific discourse, but I apologize to schoper for taking a personal shot that was not called for.
I don't have direct experience with climatology, but from what I understand it's somewhat similar: conferences like AGU are really important to climatologists for that reason.
Edit to acknowledge: obviously a lot of work gets done informally during conferences as well.
But it's in the service of publishable research, is it not? I don't think many scientists are going to say, "I'm changing my research program based on something I read on Hacker News yesterday." There's a bar for serious consideration.
The stick all but vanishes when you look at a long term climate projection, rather than the last 500 years or so.
The thing about this process is, if you feed in completely random red-noise time series you will get a hockey stick. The reason is simple, the selection period will mirror the instrumental temperature (mental check: it has to, after all we only selected the proxies that matched the instrumental temperature). You have your blade. But none of those red noise proxies actually reflect past temperature do they? They just happened to be selected by random chance. So in the time before the selection period, the noise cancels out and you have a flat line. There is your stick.
This is the core of how these "proxy reconstructions" work, and it is nonsense.
Outside of that, it gets even better. The stories are comical and numerous. Mann famously fed a contaminated Finnish lake sediment series into his algo, which happily regressed it against temperature and found that it passed significance if it was used upside down (in the opposite orientation to that suggested by the author in the original source paper). So in it went. GIGO. Or how about the question of which temperature series to regress against? You'd think you'd regress against local temperature right? Or maybe at least the same continent? Oh ye optimistic fool, go and google "teleconnection" and "non-local statistical relationship". This is what passes as "climate science".
Paleoclimatology isn't any worse than some other soft sciences I guess - the difference is that there isn't so much riding on them being right.
There are countless arguments and rebuttals to be found on both sides of the debate, but I've found the ones below to be particularly helpful:
Pro Hockey Stick:
[1] Original MBH98 paper (PDF): http://stephenschneider.stanford.edu/Publications/PDF_Papers...
[2] Wahl and Ammann 2007 (PDF): http://www.cgd.ucar.edu/ccr/ammann/millennium/refs/Wahl_Clim...
[3] Wikipedia article: http://en.wikipedia.org/wiki/Hockey_stick_controversy
[4] Real Climate Hockey Stick "Dummies Guide" (PDF): http://www.realclimate.org/dummies.pdf
Skeptical of Hockey Stick:
[5] Skeptic blog post "Casper and the Jesus Paper": http://bishophill.squarespace.com/blog/2008/8/11/caspar-and-...
[6] "The Hockey Stick Illusions" book (same skeptic author): http://www.amazon.com/The-Hockey-Stick-Illusion-Climategate/...
[7] McIntyre & McKitrick 2003 (PDF): http://climateaudit.files.wordpress.com/2005/09/mcintyre.mck...
By the way, are you a climate scientist?
I don't even get what you're getting at: scientific arguments are also not decided by someone spouting off something they read off of Climate Audit and pretending to be an expert when they don't even have a passing familiarity with the scientific literature. Asking an open question "well, what would make you change your mind" is a perfectly reasonable response, especially when the answer is, expectedly, "nothing."
No, I'm not a climate scientist, though an immediate family member is.
Your second paragraph is an ad hominem, where you make various assumptions about the OP. Yet there is still not a single coherent argument why the OP was actually wrong.
If you ran this experiment numerous times I would expect to see the "average" line prior to the instrument record vary as a random walk.
Of course you don't have to take my word for all this, thanks to Climategate we have all the behind-the-scenes dirty laundry:
http://foia2011.org/index.php?id=4191
Here Rob Wilson does just the test I'm describing and seems a little concerned about the results.
The cousin refers to the obvious long-term temperature variability. Nobody doubts the major ice ages. But the long-term reconstructions use very different techniques.