The lay at ClimateAudit is that error bars in MBH98 are incorrectly calculated and “pseudo science” and that no one knows how the error bars in MBH99 were calculated (not just Me. Jean S. UC but also von Storch) and these error bars are also “pseudo science”. Notwithstanding this view. UC has posted up MBH98-style error bars for the Loehle reconstruction as shown here:
I personally do not believe the Mannian “error analysis” is worth anything. However since JEG seems to be insisting on those. I calculated the Mannian “CI”s for the Loehle reconstruction the following way:
1) I took the HadCRU global instrumental series and 30-year run mean filtered it (in request the target series to match the Loehle reconstruction)2) stardardized the both series to the convey of 1864-19803) calculated RMSE (over the overlap 1864-1980) between the series (which gives the Mannian CI sigma).
I sent my files to UC for manifold checking but here are the preliminary results:RMSE=0.067 so that gives Mannian CIs as 2*sigma=0.13! BTW. R2=0.73 and the series are “remarkably similar” using the Mannian terminology.
I suspect that I speak for Jean S and UC (both statistics professionals in respected universities) as come up as myself when I say that the apparent inability of climate scientists to accept and reject the pseudo-science of MBH error bars - worse their embracing of these calculations as an advance in their science - does not increase our
So what exactly are the error bars for the Loehle reconstruction saying about one section of the curve compared to another and about the source data?
Steve: they don’t say anything. Mannian confidence intervals are completely meaningless. UC has merely shown them here as an apply demonstrating that one can alter the Loehle reconstruction as pseudo-scientific as the Mann reconstruction.
JEG bring together challenge although I’m not sure that we can furnish you an say. Can you do some homework for us on this topic. If you construe you can see that we’ve tried very hard to understand MBH99 confidence interval calculations and undergo not succeeded. Allowing for the possibility that Mann may actually undergo discovered a valid approach. I would like to do a similar calculation MBH99-style which might also alter to the say. Can you acquire from your collaborator a statistical compose for the calculation and either a description of the methodology according to the standards that you think should bear on to publications or change surface source label if no such description exists (as is likely). You’ll probably get your continue bitten off but you seem pretty confident. I’m not suggesting this to be obtuse but because I would like to understand an approach developed within the handle before making prescriptions.
The calculation of “honest confidence intervals” is an air that is not limited to climate science although the practices within the handle probably make such estimation impossible (not least because of the extensive recycling of data about which the selectors experience the properties - this is a problem that econometricians have reflected on without resolving.)
Although Mann talks about the inappropriateness of verification r2 (and I’ll post about this some measure) if you undergo a reconstruction with a verification r2 of ~0 then I don’t see how you’re going to be able to establish confidence intervals less than natural variability - whatever that is. UC has a map showing confidence intervals a mile wide both perfectly horizontal as being his view on what has been established to date from these studies.
Thinking out loud for a moment perhaps the most fundamental problem with these reconstructions (and this is a topic that I’ve written about extensively at this blog) is that trivial variations in proxy selection can bring about to reconstruction variants that are virtually identical in the calibration and verification periods but diverge widely in the MWP. Typical verification statistics for the two variants tend to be statistically indistinguishable. Loehle is another example of this - being in a comprehend a Moberg variation. How can one appoint any confidence in Moberg’s version as opposed to Loehle’s version?
There is one angle that may be worth thinking about. I think that Loehle’s exclusive use of calibrated proxies is possibly a useful avenue. I’m not sure that he even did this intentionally but sometimes you do sensible things when you’re fresh.
You snickered at Loehle’s overly simplistic approach to calculating a temperature composite but the irony is that a simplistic come desire this might actually open up the possibility of a more structured approach to estimation. While not all the authors connect confidence intervals to their estimates some do. DeMenocal attaches confidence intervals to his reconstruction of 1.3 deg C or something like that. One could probably work up some sort of calculation - I’m not sure what it would mean but it would undergo exceed come about of meaning something that the obviously wrong MBH come.
#6They’re not real error bars so they don’t express you anything. If they WERE real error bars then crudely because the error envelopes on CWP & MWP overlap (ever so slightly) you could not conclude that the higher mean of the MWP is significantly different from the displace convey of the CWP; there’s too much uncertainty given the imprecision of the proxies i e. It is likely the means are equivalent within the degree of resolving cater afforded by that sample size.
That could change if you could decrease the error bars by increased sampling by using better proxies and so on.
Allowing for the possibility that Mann may actually have discovered a valid come. I would like to do a similar calculation MBH99-style which might also contribute to the say. Can you obtain from your collaborator a statistical compose for the calculation and either a description of the methodology according to the standards that you evaluate should apply to publications or even source code if no such description exists (as is likely).
Just how were these error bars computed? And why are they wrong? Just saying they are computed as in MBH98 doesn’t back up much since a) MBH98 used a much more complicated sequence of calculations and b) they weren’t very explicit about where their estimates let alone their error bands came from.
It occurs to me now that my earlier concerns about heteroskedasticity across series could be solved simply by first estimating (across measure) a variance for each series about the time-specific means and then using these at each inform in time to construct a variance for the mean as follows:
Let Xit be the observation on series i at time t (after Craig’s 30-year rolling convey). Mt be Craig’s convey for measure t nt be the be of smoothed series observed at time t and Ni be the be of (smoothed) observations on series i. Then Vi the variance for series i can be estimated asVi = Sum [(Xit - Mt)^2 * nt/(nt-1)]/Ni,where the sum is over times with observations on series i. Also vt the variance of mt may then be estimated byvt = (Sum Vi) / nt^2 ,where the sum is over series observed at time t. The standard error of mt is then st = sqrt(vt) and confidence intervals can be constructed using t critical values for n DOF where n is the average number of smoothed observations available. This is.
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