Comments on: AGU – Day Four

By: EW

EW — Tue, 19 Dec 2006 11:25:39 +0000

#4 The guy from the Ancarett's blog says that the historians don't share the view about reforestation and LIA. Sources quoted in the article.

Well, it's just that most medievalists point to much earlier events than 1347 signalling the start of the Little Ice Age. Glacial advances that were noted in thirteenth century Europe. The two early fourteenth century cold snaps that contributed to the decline of the Greenland colony. The Great Famine of 1315-1317. I could go on and on. And while the Black Death was briefly effective at reducing Europe's population, an agricultural and demographic upswing was well underway by the seventeenth and eighteenth centuries. By 1750, England was home to some 3.7 million people (approximately the same population that had inhabited the country circa 1300) intensively working the land, deforesting the countryside and draining the marshlands to increase the total amount of arable land by some 30% over the previous era.

By: PHE

PHE — Tue, 19 Dec 2006 10:44:07 +0000

I’m sure everyone knows the famous quotation:

“There are three kinds of lies: lies, damned lies, and statistics”.

Statistics, like computer modelling, is a very useful scientific tool. However, like modelling, it can be used very cunningly to present a pre-conceived outcome, whether subconciously, or consciously.

As a modeller myself, I never fully trust the outcome of someone elses model unless I can understand the mathematics and assumptions behind it. It is the duty of a modeller to make these available as a report appendix. I’m sure that statisticians feel the same when they see someone elses work. Saying: “trust me, I’m an expert, I have a degree/PhD, , I know what I’m doing” is not enough for your peers. And its not about distrusting your peers. Its in the spirit of openess and acceptance that scientific interpretation and opinion have many facets.

By: Gary

Gary — Tue, 19 Dec 2006 04:24:42 +0000

#13, agreed. The only time novel techniques should be tried is when they are clearly identified as such. They then should get a double dose of scruteny.

By: Paul Penrose

Paul Penrose — Tue, 19 Dec 2006 01:17:08 +0000

Gary,
The big problem is that novel statistical methods are indeed being utilized in some, if not many, of these temperature reconstructions, however they are not being vetted by professional statisticians first. This is very risky since it’s easy for a layman to get this statistical stuff wrong.

By: PHE

PHE — Mon, 18 Dec 2006 21:20:32 +0000

Steve Bloom says (No. 4):

“This issue is by no means settled”.

… EXACTLY.

By: Steve Bloom

Steve Bloom — Mon, 18 Dec 2006 20:32:44 +0000

Re #5: Bob, my point (agreeing with Sara Chan’s comment) was just that if Scafetta wants to say that the only forcings he needs to account for are volcanoes and solar, he needs to make sure about possible other signals (both forcings and feedbacks) that might convolute the solar signal he’s trying to extract. Milankovitch cycles are obviously a forcing, not a feedback as Sara mentioned (and I would appreciate it if she could indicate what she had in mind for that, although maybe it was Ruddiman’s work), but the point is that Scafetta needs to go through the step of accounting for all such factors. My understanding, BTW, is there is presently a slight overall cooling forcing from Milankovitch cycles.

By: Gary

Gary — Mon, 18 Dec 2006 17:06:29 +0000

#9 – Hard to see how that’s a paraphrase. My post wasn’t snarky at all. The two dozen climate scientists I’ve encountered DO have a clue, DON’T fake their data, and are pretty careful about the statistics and what they claim as results or offer as hypotheses.

The funding process is what it is and has feedbacks that reinforce the convential wisdom. That’s good when it limits the pointless research John A was questioning; it’s bad when it prevents worthwhile projects for political reasons.

Some researchers have taking the alarmist tack doesn’t condemn them all. You paint with too broad a brush. The last thing a responsible researcher wants is to find out that half of his career was wasted on a false hypothesis. Steve M has been right to counter the alarmism with a call for audited results, but I’m sure he doesn’t think that all federally-funded researchers are frauds as you imply.

By: Para Gary

Para Gary — Mon, 18 Dec 2006 16:10:22 +0000

To paraphrase Gary in #7–”Hey folks, we’re drowning here! We haven’t got a clue so we gotta fake it and make up the statistics. Too bad for you, cause the big money funders are on our side. So go back to your video games already and leave us to audit ourselves!”

By: richardT

richardT — Mon, 18 Dec 2006 10:27:22 +0000

I’d be slightly skeptical of dinoflagellate cyst-based reconstructions. The dinocysts transfer functions I’ve seen have some undesirable statistical properties, and many of their results strain credibility.

By: Gary

Gary — Mon, 18 Dec 2006 04:18:11 +0000

#3 – Federal funding, and probably all serious funding for that matter, requires a highly detailed proposal of what will be done, how it will be done, and what the expected outcome should be. In other words, you better have a pretty good line of evidence for what you eventually expect to “prove” by the research in order to get the money. The old joke is that every grant you get is meant to provide the results you need for your next proposal. The trick then is getting your first grant. That usually happens by doing a good doctoral thesis, getting a good post-doc position, and attaching yourself to an already successful group. Getting grants is highly competitive; I’ve heard numbers like 1-in-4 to 1-in-10 proposals being funded depending on the reseach area. With this high stress it’s natural that the data would be milked, often through multiple papers rehashing nearly the same thing. If a project should fail for any reason there also is incentive to make anything out of it so as not to break the funding chain.

OTOH, most people aren’t stupid and hedge their bets by gathering as much data as possible. So much is unknown that speculation isn’t necessarily a bad thing and why not try some new statistics or extrapolating beyond the data when fresh thought just might be needed.