QBO Model Validation

[mathjax]The strongly periodic Quasi-Biennial Oscillation (QBO) of stratospheric winds is externally forced by a cyclic mechanism. This is obvious in spite of what the current scientific literature says about the nature of QBO;  the general consensus being that the QBO emerges as a complex natural resonant response of other atmospheric factors [1]. Yet, an experienced experimental scientist should not consider that as the only plausible premise. It is in fact exceedingly rare for a phenomena of that global a scale to be the result of a natural resonance, and for the QBO to be a resonance is clearly an untenable hypothesis based on historical precedent. There simply aren’t any climate phenomena that behave similarly and are not reliant on lunar or solar periods.

 

What causes the oscillation then?

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Common Origins of Climate Behaviors

I have been on a path to understand ENSO via its relationship to QBO and the Chandler wobble (along with possible TSI contributions, which is fading) for awhile now. Factors such as QBO and CW have all been considered as possible forcing mechanisms, or at least as correlations, to ENSO in the research literature.

Over time, I got sidetracked into trying to figure out the causes of QBO and the Chandler wobble hoping that it might shed light into how they could be driving ENSO.

But now that we see how the QBO and the Chandler wobble both derive from the seasonally aliased lunar Draconic cycle, it may not take as long to piece the individual bits of evidence together.

I am optimistic based on how simple these precursor models are. As far as both QBO and the Chandler wobble are concerned, one can’t ask for a simpler explanation than applying the moon’s Draconic orbital cycle as a common forcing mechanism.

As a possible avenue to pursue, the post on Biennial Connection from QBO to ENSO seems to be the most promising direction, as it allows for a plausible phase reversal mechanism in the ENSO standing wave. I’ll keep on kicking the rocks to see if anything else pops out.

 

If the glove don’t fit …

To finish off that sentence, “If the glove don’t fit, you must acquit”. One of the most common complaints that I’ve received whenever I describe fitting models to data, is that “correlation does not equal causation”. I especially get this at Daily Kos with respect to any comment I make to science posts. One knee jerk follows me around and reminds me of this bit of wisdom like clockwork.  I can’t really argue the assertion out of hand because it’s indeed true that there are plenty of coincidental correlations that don’t imply anything significant in terms of causation.

Fig 1:  Correlation of the QBO 30 hPa time-series data.  Does this excellent correlation of data to a model of aliased tidal periods lead to a causation conclusion?  Or is it just a coincidence of the fit chosen?

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