A study that could show that you know fuck-all? Forget Popper and don't do that study!

Without trying to prejudice this work, but also because of what I almost think I know to be the case, the results of this study will show that we can probably say a fair bit about <100 year extra-tropical NH temperature variability (at least as far as we believe the proxy estimates), but honestly know fuck-all about what the >100 year variability was like with any certainty (i.e. we know with certainty that we know fuck-all).

Now that is quite a bombshell of an email. It is more serious than the ‘hide the decline’ situation because it gets to the heart of all of the paleo-hockeystick plots.  If you consider that they are saying any change in temps greater than 100 years in length are a complete unknown, how is it that we “know” that recent years are the warmest in history?  The very clear answer is – we don’t.

A possible study that might show that climate science might know fuck-all? And they know it before hand?  So they don't do it! There you have Popper's Principle Of Falsifiability! To qualify to be a scientific inquiry, to have a scientific theory (and not something pseudo-scientific), one postulates something that can be falsified, and then tests it (or better has it tested by independent parties). To know of such a test and avoid it, now that is truly unscientific.

"The reconstructions clearly show a ‘hockey-stick’ trend."

Therefore, I thought I’d play around with some randomly generated time-series and see if I could ‘reconstruct’ northern hemisphere temperatures.

I first generated 1000 random time-series in Excel – I did not try and approximate the persistence structure in tree-ring data. The autocorrelation therefore of the time-series was close to zero, although it did vary between each time-series.

Playing around therefore with the AR persistent structure of these time-series would make a difference. However, as these series are generally random white noise processes, I thought this would be a conservative test of any potential bias.
…
The reconstructions clearly show a ‘hockey-stick’ trend. I guess this is precisely the phenomenon that Macintyre has been going on about.

The problems with the "consensus science" in the field of climate change

Two clear videos on the topic of Climate Change, and the problems with the "consensus science" behind it.


The first one by Prof. Dr. Vincent Courtillot (via)

And the second by Michael Chrichton (Part 1 is MIA use this and this, here are Part 2 and Part 3):

The planed destruction of a scientific journal and a scientific career

Now the most interesting point of note here is that the article in question refutes the infamous hockey stick chart developed by Mann, in which the Medieval Warm Period disappears. What we have here is Mann, and other members of the team trying to get the editors of a journal to discredit the entire journal, simply for publishing a paper which refutes his own [Mann's] work! Note in this that the stakes are being raised again. Mann seeks to have the entire journal tarnished as a result of the publication of the offending papers. Note also his offer to re-review the manuscripts, which is disingenuous, to say the least (bearing in mind he is calling it crap). The aim appears to be to find out who did the review (which becomes quite and obsession, see earlier Pittock email). Finally, see how the consensus (highlighted) apparently trumps peer review! So the pressure is building against the journal…..

And you should read all the quotes:

Yes, read it again. There can be no doubt that they are trying to get Chris de Freitas sacked from the University of Auckland. Re-read it if you have any doubts. When the team object to a person, they really, really object. And if that means seeking to destroy a reputation and career, so be it. If you look at Pittock’s email with the options for action, you can see the final option was to address critiques with science. Instead, the proposed course of action is to gang up on an individual, and trash their career and reputation.

[Update] And one more:

Now even if the paper was bad, you can see the extremeness of the team response to it. I can tell readers from my own experience in publication that even papers with ‘less’ global warming message are forcefully resisted by some. I have also been privy to other paper’s reviews which suffer the forceful gatekeeping as is implied above. If the authors truly did make an honest attempt at publishing as DeFreitas wrote, and it truly was accepted by four reviewers, even if it had a mistake, can you imagine the difficulty they will now have in promotions or acceptance of future work in their field? I wonder if the huge climate funds will still find their way to them or if their proposals will fall on deaf ears?

Confirmation bias at its worst - Climategate 2.0 edition

Phil Jones worries about "impact", not about scientific soundness, when choosing what goes into his publications:

I’m in discussion with AGU and Ellen about co-ordination as this should increase the impact of both pieces. 

And well, he (and Mike Mann) get called out for it by Bradley.

You just shouldn’t grab anything that’s in print and just use it ‘cos it’s there—that just perpetuates rubbish.

Alas, it has no lasting effect on Phil Jones.

And this by Tom Wigley is revealing:

It seems that there was a misunderstanding about what I suggested re Yang. To be more specific, I suggest adding the following to the end of the Figure 2 caption:

“….. Note that individual series are weighted according to their quality in forming a composite hemispheric-scale time series.”

The word ‘quality’ here has been chosen carefully — as something that is deliberately a bit ambiguous.

The point here is to have something that we can fall back on if anyone criticizes *any* specific input series (*not* just Yang).

These emails are amazing:

I too have expressed my concern to Phil (and Ray) over the logic that you leave all series you want in but just weight them according to some (sometimes low) correlation (in this case based on decadal values). I also believe some of the series that make up the Chinese record are dubious or obscure, but the same is true of other records Mann and Jones have used (e.g. how do you handle a series in New Zealand that has a -0.25 correlation?) .

IT IS A DIFFICULT CALL — WHETHER TO DUMP SERIES THAT HAVE NO SIGNIFICANT LINK TO TEMPERATURE AND WHICH ARE, AS WELL, DUBIOUS ON A PRIORI GROUNDS; OR TO USE A WEIGHTING SCHEME. IF ONE DID THIS BY SIMPLE MULTIPLE REGRESSION, THEN THINGS WOULD BE WEIGHTED AUTOMATICALLY. HOWEVER, STATISTICALLY ONE SHOULD STILL DUMP THE LOW CORRELATION ONES. I HAVE RESERVATIONS ABOUT WHAT MIKE AND PHIL HAVE DONE — BUT THIS IS SOMETHING WE SHOULD TALK ABOUT FACE TO FACE SOME DAY.

And suggesting to let the Mann-O-Matic fix it "AUTOMATICALLY" – nice. How would that help when:

There are problems (and limitations ) with ALL series used.

Does Capital add "value"

At face value, these trends would be consistent with large productivity gains in finance. Pre-crisis, that is what the bald numbers implied. Measured total factor productivity growth in the financial sector exceeded that in the rest of the economy (Figure 1). Financial innovation was said to have allowed the banking system to better manage risk and allocate capital. These efficiency gains in turn allowed the factors of banking production (labour and capital) to reap the benefits through high returns (wages and dividends).

But crisis experience has challenged this narrative. High pre-crisis returns in the financial sector proved temporary. … In what sense is increased risk-taking by banks a value-added service for the economy at large? In short, it is not.

(via)

Avoid doorways

New research suggests the mere act of walking through a doorway helps people forget, which could explain many millions of confusing moments that happen each day around the world. A study published recently in The Quarterly Journal of Experimental Psychology found that participants who walked through doorways in a virtual reality environment were significantly more likely to forget memories formed in another room, compared with those who traveled the same distance but crossed no thresholds.

Notre Dame University researcher Gabriel Radvansky says doorways serve as a type of “event boundary” that the brain uses to separate and store memories. When you enter a new room, your brain updates its understanding of what’s going on in the new environment, which takes some mental effort. This parsing of memory, albeit subtle, leaves the information encoded in the other room (i.e. “Now I’m going to my room to fetch some knickers”) less available in your new location.

Recognizing this tendency could help you avoid future lapses. Or you could take Radvansky’s advice, as (jokingly—I think) told to Postmedia News: ”Doorways are bad. Avoid them at all costs.”

Justus, this one is for you.