"Is the ENSO/QBO index from literature reference [5]? Usually I have no access to nature articles."

nad,
Yes that is from reference 5. I can dig this up for you when I get a chance.

I agree looking at the waveform in the third chart is a lot like trying to read an EKG, where the extra little features and the exact timing is crucial, i.e long QT, etc.

The QBO details also change with altitude but that maintains the overall mean period, as it must otherwise the behavior would gradually get out of phase.

I have a link for QBO data from the official repository as given in the 6th paragraph, but I don't know what kind of filtering was involved in getting the third chart. When I plot from the source data, it ends up looking more like a noisy full-wave rectified sine wave, with the valleys sharper than the peaks, as shown below.

![QBO plot](http://imageshack.com/a/img905/7240/F3Gam7.gif)

That's why I was intrigued by this other one. As nad observed, I was also curious about all the “extrasystole” features that emerged. The main peaks don't really line up with my QBO chart and so perhaps the one I plotted is a derivative of QBO? As long as the noise is not too great, derivatives are a great way of revealing extra features, as shown with edge detection algorithms. Or it more likely is just QBO data taken at a different altitude.

The one I plotted was from the lowest altitude, which I figured would have the greatest influence on ENSO. By using the data from the handful of altitudes, it may be possible to further discriminate these features. From what I understand, some QBO research uses the different altitudes to arrive at an empirical orthogonal function ( [EOF](http://en.wikipedia.org/wiki/Empirical_orthogonal_functions) ) representation of the data. I have to admit that I don't completely "get" EOFs other than assuming that they are similar to a Fourier series of various fixed frequency sine waves and to principle components analysis -- but with the sinusoids replaced with functions that are combinations of other data sources. I am OK with this as long as the other sources are isolated as in a multiple regression, but when they get combined I start losing intuition. But as I said, my understanding is not complete as I have yet to experiment with EOFs on my own and I use multiple regression spectral decomposition more than PCAs. I hope someone can help clarify if this is a possible route.

The other point by nad is important, and that is whether we could actually pick up a pattern and predict the extrasystole peaks in the future. If you can't do this for QBO, then it must be even harder for ENSO and El Ninos, where the fundamental frequency is even less well-defined.

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Incidentally, the way I came across the Ref 5 article was thanks to a fierce climate skeptic who seemed a little confused. After he found out that I was working on an ENSO & QBO correlation, he dug up this article and acted like it was no big deal and that anybody could see the connection. And then he wrapped it up by saying that I was wasting my time pursuing this angle (?!?!)

I don't know what's up with these climate skeptical people, but all I can say is Thank You.