Comments on: Decoding Juckes SI Figure 1

By: Willis on “Getting authors to respond to questions” « Climate Audit

Sat, 04 Dec 2010 18:13:26 +0000

[...] (Decoding Juckes SI Figure 1) [...]

By: UC

UC — Fri, 08 Dec 2006 05:47:33 +0000

Maybe I should try to say it differently:

Our recent findings show that the equivalent local-level proxy noise variance is , or even more. This level of SNR appears unprecedented in the context of at least the past 2000 scientific publications. This anomalous finding can only be explained by modern anthropogenic forcing of subjective human-induced components into the research results. Unless urgent and strenuous mitigation actions are taken immediately, a whole branch of science will lose its credibility for decades ahead.

(Sorry, just trying to learn how to write like a pro scientist;) )

By: UC

UC — Thu, 07 Dec 2006 20:23:05 +0000

#69 cont.

model

proxy=A(local_temp+noise)

i.i.d (spatial and temporal) Gaussian noise , would explain the last figure, A is the unknown scale.

By: Mark T

Mark T — Thu, 07 Dec 2006 15:44:51 +0000

My world as dictated by “Detection, Estimation and Modulation Theory, Part I” by Harry L. VanTrees.

Man that was a tough class. The third in his series is for radar, btw.

Mark

By: Jean S

Jean S — Thu, 07 Dec 2006 12:49:19 +0000

#62
Sinan, in signal processing Decision Theory is known (for historical reasons) as Detection Theory. Much of the terminology comes from the radar engineering (think airplane in a radar). The null hypothesis is that the signal is absent from the data (noise only), and the probability of a Type I error (level of significance) is called “false alarm probability”

And to all nitpickers out there: I do understand that the intended meaning of Juckes’ “99.98% significant” is 1 minus the ordinary meaning of significant.

By: Steve McIntyre

Steve McIntyre — Thu, 07 Dec 2006 12:07:57 +0000

Jean S, if it’s a beauty contest between cherry picking and flippping, I’d put more weight on cherry picking as a Team technique. Using Yamal rather than Polar Urals Update or Yakutia/Indigirka is more characteristic of Team CVM methods, as opposed to flipping the Chesapeake series, which is a bit of a one-off. Although as soon as I say this, I think about the G Bulloides coldwater series. Had the percentage of coldwater diatoms declined in the 20th century, yielding an upside down HS, would the Team have used this as evidence of warming? and inverted the graphic? Of course they would.

By: Chris H

Chris H — Thu, 07 Dec 2006 11:32:47 +0000

#68 Yes I should have been careful about using the word flipped. I meant flips based on physical arguments prior to data analysis.

I should have dropped the last three sentences because this argument is incomplete. Instead, I should have added that finding a signal is neccassary but not sufficient. You still need to demonstrate that this model has some sort of validity.

By: Jean S

Jean S — Thu, 07 Dec 2006 11:27:58 +0000

no one would make estimates from a regression equation unless he were convinced, either by theoretical argument or the statistical significance of b itself, that he knew the sign

That was 1969, but now we are much more advanced

By: UC

UC — Thu, 07 Dec 2006 11:19:18 +0000

One should know (from physical considerations) if each proxy is responding positively or negatively to the temperature.

Williams (1969) A Note on Regression Methods in Calibration, Technometrics Vol. 11, No. 9:

The fact that we need to know the sign of before choosing the estimator is only a minor objection to its use, since no one would make estimates from a regression equation unless he were convinced, either by theoretical argument or the statistical significance of b itself, that he knew the sign of .

By: UC

UC — Thu, 07 Dec 2006 10:56:44 +0000

corrigendum:

Corrected my CVM computations and included past climate reconstruction using univariate classical calibration estimator. same url http://www.geocities.com/uc_edit/cvm.html

None of my errors affect my previously published (#66) results.