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# QBO and ENSO

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551.

Dave, The equivalent of the 60 Hz forcing signal is more complicated in lunisolar terms. The analogy is that there are two strong signals that are nearly balanced but closely spaced at 59 Hz and 61 Hz. These are the fortnightly tropical signal and the monthly anomalistic tidal forces. When amplified by the annual spring barrier, the repeat cycle of just these two signals is at least 130 years(***). Yet, we only have 140 years of monthly resolution ENSO data to deal with (since about 1880).

The equivalent for a tidal signal analysis is someone giving you only 2 weeks worth of tidal gauge data, and then you have to deal with a non-linear fit on top of that. If you want to get the next 2 weeks, you have to wait the equivalent of another 130 years.

You demanding an extrapolated time series without having the slightest idea of how to discriminate tightly spaced signals in the context of a non-linear model is the real issue. Perhaps you want to reconsider what you are asking. That's why I don't care. Perhaps if some other people get involved in the project they can offer up independent projections, and spend the next decade waiting for data to come in.

The bottom-line is that 130 years of data is not nearly enough time to justify punting on the problem and attributing it to a "multi-chaos" mechanism. You and a whole boat-load of climate scientists are apparently not aware of the underlying issue on what otherwise would be a straightforward analysis.

(***) Taking all the orbital cycles into consideration, it may be 1800 years according to Keeling

"The 1,800-year oceanic tidal cycle: A possible cause of rapid climate change" Charles D. Keeling and Timothy P. Whorf https://www.pnas.org/content/97/8/3814

Comment Source:Dave, The equivalent of the 60 Hz forcing signal is more complicated in lunisolar terms. The analogy is that there are two strong signals that are nearly balanced but closely spaced at 59 Hz and 61 Hz. These are the fortnightly tropical signal and the monthly anomalistic tidal forces. When amplified by the annual spring barrier, the repeat cycle of just these two signals is at least 130 years(***). Yet, we only have 140 years of monthly resolution ENSO data to deal with (since about 1880). The equivalent for a tidal signal analysis is someone giving you only 2 weeks worth of tidal gauge data, and then you have to deal with a non-linear fit on top of that. If you want to get the next 2 weeks, you have to wait the equivalent of another 130 years. You demanding an extrapolated time series without having the slightest idea of how to discriminate tightly spaced signals in the context of a non-linear model is the real issue. Perhaps you want to reconsider what you are asking. That's why I don't care. Perhaps if some other people get involved in the project they can offer up independent projections, and spend the next decade waiting for data to come in. The bottom-line is that 130 years of data is not nearly enough time to justify punting on the problem and attributing it to a "multi-chaos" mechanism. You and a whole boat-load of climate scientists are apparently not aware of the underlying issue on what otherwise would be a straightforward analysis. (***) Taking all the orbital cycles into consideration, it may be 1800 years according to Keeling > "The 1,800-year oceanic tidal cycle: A possible cause of rapid climate change" Charles D. Keeling and Timothy P. Whorf https://www.pnas.org/content/97/8/3814 
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552.
edited February 8

Multi-Chaos Science is not "punting" if you sort it out. Stick with it. It helps to care.

You are not addressing the possibility that your 60Hz (or 59-61Hz) analogy is correct in the sense that coherent noise really can corrupt deterministic chaos data. Maybe what we should be doing to understand ENSO-QBO better is filtering out some of the lunisolar noise in sensor data.

"Punting" could instead be now claiming ENSO data is inadequate for any purpose but asserting your thesis, that no proof in geophysics is even ever possible,* that you simply don't care to predict upcoming periods because they might be wrong just "by chance", that Jupiter QQO is not worth weighing as a counter-argument analog, that Coriolis Force is "constant" when its not, and anyway an a priori insufficient geophysical driver by itself, that non-tidal Wind Setup itself is Lunisolar forced, that Chaos Physics cannot be applied rigorously ever since Poincare to this day because geophysicists on the whole are incurious clueless guardians of false orthodoxy, and that your previous writings have resolved all possible alternative hypotheses, like simple Helmholtz resonance overlaid with lunisolar signal; that third-party investigators must care enough to compile your code into executable form and run the Model themselves while you don't care enough yourself to predict upcoming cycles, except "even better", 2280 onward, and so on. Give me some credit; I do not "punt" like these claims, at least.

Your hypothesis really is testable by publishing accurate (or not) near-term predictions like competing models do. You have not studied nor quantified how negligibly Lunisolar sensor-data noise may (or may not) be corrupting the statistics you rely on. You have not mapped out an end-to-end causal sequence of lunisolar forcing, the actual mathematical physics that would be the heart of credible validation of the lunisolar forcing hypothesis.

(*) You concede 1300yrs might settle doubts here. Eratosthenes and peers are credited for proving Earth is round, and even closely calculating circumference, >2000yrs ago. It then took ~1600yrs more for full Wilczek-confirmation. The Science Game here is hardly settled yet. Its 2nd Quarter at most.

Comment Source:Multi-Chaos Science is not "punting" if you sort it out. Stick with it. It helps to care. You are not addressing the possibility that your 60Hz (or 59-61Hz) analogy is correct in the sense that coherent noise really can corrupt deterministic chaos data. Maybe what we should be doing to understand ENSO-QBO better is filtering out some of the lunisolar noise in sensor data. "Punting" could instead be now claiming ENSO data is inadequate for any purpose but asserting your thesis, that no proof in geophysics is even ever possible,* that you simply don't care to predict upcoming periods because they might be wrong just "by chance", that Jupiter QQO is not worth weighing as a counter-argument analog, that Coriolis Force is "constant" when its not, and anyway an a priori insufficient geophysical driver by itself, that non-tidal Wind Setup itself is Lunisolar forced, that Chaos Physics cannot be applied rigorously ever since Poincare to this day because geophysicists on the whole are incurious clueless guardians of false orthodoxy, and that your previous writings have resolved all possible alternative hypotheses, like simple Helmholtz resonance overlaid with lunisolar signal; that third-party investigators must care enough to compile your code into executable form and run the Model themselves while you don't care enough yourself to predict upcoming cycles, except "even better", 2280 onward, and so on. Give me some credit; I do not "punt" like these claims, at least. Your hypothesis really is testable by publishing accurate (or not) near-term predictions like competing models do. You have not studied nor quantified how negligibly Lunisolar sensor-data noise may (or may not) be corrupting the statistics you rely on. You have not mapped out an end-to-end causal sequence of lunisolar forcing, the actual mathematical physics that would be the heart of credible validation of the lunisolar forcing hypothesis. --------- (*) You concede 1300yrs might settle doubts here. Eratosthenes and peers are credited for proving Earth is round, and even closely calculating circumference, >2000yrs ago. It then took ~1600yrs more for full Wilczek-confirmation. The Science Game here is hardly settled yet. Its 2nd Quarter at most.
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553.

that Coriolis Force is "constant" when its not

It's constant by definition as long as the earth's rotation is constant. Earth's rotation varies slightly due to tidal cycles. So any variation is primarily due to tidal cycles.

Comment Source:> that Coriolis Force is "constant" when its not It's constant by definition as long as the earth's rotation is constant. Earth's rotation varies slightly due to tidal cycles. So any variation is primarily due to tidal cycles. 
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554.
edited February 8

Coriolis is complex rather than truly constant because variable geophysical flows interact with constant rotation to comprise the Effect (see below). These flows vary in velocity and direction, and the latent Force itself varies greatly with latitude and altitude (Vertical Coriolis). Only in unphysical approximation is it idealized as a constant waiting to happen. Its also not helpful to cite that its relatively constant overall, on-average, when dealing with subscale cases like ENSO or QBO, one by one. Coriolis is extra variable at the planetary surface, where cloud-mediated solar-driven convection causes increased inertial interaction of flow with rotation.

Gross energy misestimation controversies are still quite common in modern geophysics, like in Wind Energy, where recent total estimates of wildly varying magnitude cannot be all correct ("Coastline of England" fractal-scales uncertainty is a factor). I think Laplace greatly underestimated Coriolis in his Tidal Equations. [Keeling & Whorf 2000] seem to mostly neglect vertical Coriolis Effect energy input as such, in badly overestimating the role of Tidal Energy forcing. They also seem too much to discover what they wish in noisy data.

There may be a Three Jesus Fallacy at work with some of the controversies. Psychologists [Rokeach 64] put together three patients who each claimed to be Jesus, expecting conflict. Instead they got along rather well as their outlier Confirmation Bias was supported; that it was reasonable to claim to be Jesus, even as each demurred as to the other two being mistaken, while seeing themself as the one true Jesus. Beware such a dynamic in the extreme Lunisolar Forcing holdout faction. Let's stop short of asserting "lunacy", as we are all by definition Jesuses to some degree O:-)

Here is an approximate simplified Horizontal Coriolis Force formula for a moving mass. As is evident, there are multiple variables (a, m, v) and one constant (w).

F = 2 * m * v * w * sin(a)

F is force

m is object mass

v is object velocity

w is Earth angular velocity

a is latitude

Comment Source:Coriolis is complex rather than truly constant because variable geophysical flows interact with constant rotation to comprise the Effect (see below). These flows vary in velocity and direction, and the latent Force itself varies greatly with latitude and altitude (Vertical Coriolis). Only in unphysical approximation is it idealized as a constant waiting to happen. Its also not helpful to cite that its relatively constant overall, on-average, when dealing with subscale cases like ENSO or QBO, one by one. Coriolis is extra variable at the planetary surface, where cloud-mediated solar-driven convection causes increased inertial interaction of flow with rotation. Gross energy misestimation controversies are still quite common in modern geophysics, like in Wind Energy, where recent total estimates of wildly varying magnitude cannot be all correct ("Coastline of England" fractal-scales uncertainty is a factor). I think Laplace greatly underestimated Coriolis in his Tidal Equations. [Keeling & Whorf 2000] seem to mostly neglect vertical Coriolis Effect energy input as such, in badly overestimating the role of Tidal Energy forcing. They also seem too much to discover what they wish in noisy data. There may be a Three Jesus Fallacy at work with some of the controversies. Psychologists [Rokeach 64] put together three patients who each claimed to be Jesus, expecting conflict. Instead they got along rather well as their outlier Confirmation Bias was supported; that it was reasonable to claim to be Jesus, even as each demurred as to the other two being mistaken, while seeing themself as the one true Jesus. Beware such a dynamic in the extreme Lunisolar Forcing holdout faction. Let's stop short of asserting "lunacy", as we are all by definition Jesuses to some degree O:-) Here is an approximate simplified Horizontal Coriolis Force formula for a moving mass. As is evident, there are multiple variables (a, m, v) and one constant (w). F = 2 * m * v * w * sin(a) F is force m is object mass v is object velocity w is Earth angular velocity a is latitude
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555.

Dave said:

"I think Laplace greatly underestimated Coriolis in his Tidal Equations."

I know you haven't read the entirety of this thread that has been running for over 5 years now, but Coriolis is included in Laplace's Tidal Equations, and it's the precise cancellation of Coriolis exactly along the equator that allows us to analytically solve LTE as a separable spatio-temporal standing wave formulation.

No one so far has found anything wrong with the derivation, which could fall under the category of a topological insulator or a topologically protected system, as recently described in this article Topological origin of equatorial waves.

You may want to catch up to all the analysis that has gone into the thread.

Comment Source:Dave said: > "I think Laplace greatly underestimated Coriolis in his Tidal Equations." I know you haven't read the entirety of this thread that has been running for over 5 years now, but Coriolis is included in Laplace's Tidal Equations, and it's the precise cancellation of Coriolis **exactly** along the equator that allows us to analytically solve LTE as a separable spatio-temporal standing wave formulation. No one so far has found anything wrong with the derivation, which could fall under the category of a topological insulator or a topologically protected system, as recently described in this article [Topological origin of equatorial waves](https://science.sciencemag.org/content/358/6366/1075). You may want to catch up to all the analysis that has gone into the thread. 
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556.
edited February 8

Have been slowly catching up here, learning a lot. On the other hand, I immediately bring to bear extra applicable background, like topological matter and general geophysics knowledge.

"Precise cancellation of Coriolis along the equator" is a crude rather un-physical assumption, given so many exception factors. That's "(finding something) wrong with (primitive LaPlacian) derivation".

Again, ENSO and QBO Equatorial Belt wave-guides are anything but perfect Topological Insulators. Nor is geophysical topological robustness against perturbations helpful to the hypothesis these Earth-rotation dominated systems are so sensitive to lunisolar tides.

It seems as if the major geophysical oscillations are all only metastable Helmholtz resonances, that start to go chaotically haywire when they drift near a major state transition. This is a very different kind of theory (dynamical-chaos) from long period forcing conjunctions by multi-orbital periodicity.

Comment Source:Have been slowly catching up here, learning a lot. On the other hand, I immediately bring to bear extra applicable background, like topological matter and general geophysics knowledge. "Precise cancellation of Coriolis along the equator" is a crude rather un-physical assumption, given so many exception factors. That's "(finding something) wrong with (primitive LaPlacian) derivation". Again, ENSO and QBO Equatorial Belt wave-guides are anything but perfect Topological Insulators. Nor is geophysical topological robustness against perturbations helpful to the hypothesis these Earth-rotation dominated systems are so sensitive to lunisolar tides. It seems as if the major geophysical oscillations are all only metastable Helmholtz resonances, that start to go chaotically haywire when they drift near a major state transition. This is a very different kind of theory (dynamical-chaos) from long period forcing conjunctions by multi-orbital periodicity.
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557.

Again, ENSO and QBO Equatorial Belt wave-guides are anything but perfect Topological Insulators.

That's a contradiction. The flow properties of topological insulator are robust against imperfections so an imperfect structure (up to a point) would still show these properties.

Comment Source:> Again, ENSO and QBO Equatorial Belt wave-guides are anything but perfect Topological Insulators. That's a contradiction. The flow properties of topological insulator are robust against imperfections so an imperfect structure (up to a point) would still show these properties. 
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558.
edited February 9

It is not a real contradiction. Insulators are indeed imperfect. One can almost as easily highlight the extent to which these waveguides are Topological Conductors. Call them Topological Semiconductors, if you will. "Robust against imperfections" is not perfect either.

What is cool is extreme-scale geophysics meaningfully interpreted as Quantum Analogs. ENSO and QBO can be modeled as Phonon Physics, using Feynman Diagrams. Planetary Tidal Phonons (wave packets) are at the cutting edge of current geoscience. In a sense, a Tidal Bulge traveling around the world is the same ancient Phonon that daily tunnels across the North and South American barrier. There was objection over such avant-garde interpretation of hurricanes crossing Central America, earlier...

Comment Source:It is not a real contradiction. Insulators are indeed imperfect. One can almost as easily highlight the extent to which these waveguides are Topological Conductors. Call them Topological Semiconductors, if you will. "Robust against imperfections" is not perfect either. What is cool is extreme-scale geophysics meaningfully interpreted as Quantum Analogs. ENSO and QBO can be modeled as Phonon Physics, using Feynman Diagrams. Planetary Tidal Phonons (wave packets) are at the cutting edge of current geoscience. In a sense, a Tidal Bulge traveling around the world is the same ancient Phonon that daily tunnels across the North and South American barrier. There was objection over such avant-garde interpretation of hurricanes crossing Central America, earlier...
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559.

It's called a topological insulator because the flow is restricted to a surface, boundary, or interface instead of the bulk. So in the sense of a topological insulator, equatorial waves are topological boundary states, similar to those emerging in various topological insulating media according to Delplace et al. It's ok that they make these physical analogies, while I just as soon work directly with the equations and then evaluate with respect to the data.

One of the saddest correlations I have observed is the emergence of MJO cycles as traveling wave offshoots of the equatorial ENSO, delayed by about 21 days

I have inferred from reading the literature that climate scientists consider MJO as being an independent behavior, but this essentially shows the direct connection. (it's sad if no one else has observed this direct time-series correlation until now).

So ENSO is the standing wave but it has an impact off the equator either through these traveling waves or via a common-mode forcing mechanism which synchronizes standing wave dipoles away from the equator. The buzzword is teleconnection, which implies causation at a distance.

Comment Source:It's called a topological insulator because the flow is restricted to a surface, boundary, or interface instead of the bulk. So in the sense of a topological insulator, equatorial waves are topological boundary states, similar to those emerging in various topological insulating media according to Delplace et al. It's ok that they make these physical analogies, while I just as soon work directly with the equations and then evaluate with respect to the data. One of the saddest correlations I have observed is the emergence of MJO cycles as traveling wave offshoots of the equatorial ENSO, delayed by about 21 days ![](https://imagizer.imageshack.com/img921/7305/bXNFwm.png) I have inferred from reading the literature that climate scientists consider MJO as being an independent behavior, but this essentially shows the direct connection. (it's sad if no one else has observed this direct time-series correlation until now). So ENSO is the standing wave but it has an impact off the equator either through these traveling waves or via a common-mode forcing mechanism which synchronizes standing wave dipoles away from the equator. The buzzword is teleconnection, which implies causation at a distance. ![](https://www.climate.gov/sites/default/files/ENSOMJO_Ships2_620.png) from https://www.climate.gov/news-features/blogs/enso/catch-wave-how-waves-mjo-and-enso-impact-us-rainfall 
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560.
edited February 9

PaulP:"It's called a topological insulator because the flow is restricted to a surface, boundary, or interface instead of the bulk."

However, the Equatorial Kelvin Wave travels within the bulk of the Equatorial Belt between North and South Boundaries, which themselves could be accounted as insulating here. Metamaterial scientists tend to omit Galilean Invariance. Its great that geophysicists are applying concepts from Topological Metamaterials, but its a very early stage of cross-analysis. The conventional equations and existing data are also not fully definitive.

Of course ENSO and MJO interact quasi-harmonically, as any two interacting quasi-periodic systems would. We need not be "sad" when hardly anyone belabors the obvious.

Like weather prediction has slowly advanced, ENSO predictions will slowly improve, until predicting a few cycles ahead should be possible, but not much better. Lunisolar Tides must mostly play a marginal role compared to the dramatic daily and seasonal oscillations of Earth rotation and inclination, interacting with solar radiation, and the complex crustal geology of oceans, coasts, and continents.

Lunisolar noise in ENSO-QBO data needs to be accounted for in your Model. It can't be all or even mostly pure coherent forcing, but also some major degree of chaotic interference to identify and quantify. Your science will be all the better not to "punt" (arm-wave) the chaos aspect, but take it on with the rigor now possible. Once its accepted that Lunisolar inputs do have their place in the mix, accurate quantification can follow, even if strong prediction remains elusive.

A basic quantification is to compare the High Q of Lunisolar statistics to the Low Q of them in the thicket ENSO-QBO data. We could call this the non-dimensional Pukite Number.

Comment Source:PaulP:"It's called a topological insulator because the flow is restricted to a surface, boundary, or interface instead of the bulk." However, the Equatorial Kelvin Wave travels within the bulk of the Equatorial Belt between North and South Boundaries, which themselves could be accounted as insulating here. Metamaterial scientists tend to omit Galilean Invariance. Its great that geophysicists are applying concepts from Topological Metamaterials, but its a very early stage of cross-analysis. The conventional equations and existing data are also not fully definitive. Of course ENSO and MJO interact quasi-harmonically, as any two interacting quasi-periodic systems would. We need not be "sad" when hardly anyone belabors the obvious. Like weather prediction has slowly advanced, ENSO predictions will slowly improve, until predicting a few cycles ahead should be possible, but not much better. Lunisolar Tides must mostly play a marginal role compared to the dramatic daily and seasonal oscillations of Earth rotation and inclination, interacting with solar radiation, and the complex crustal geology of oceans, coasts, and continents. Lunisolar noise in ENSO-QBO data needs to be accounted for in your Model. It can't be all or even mostly pure coherent forcing, but also some major degree of chaotic interference to identify and quantify. Your science will be all the better not to "punt" (arm-wave) the chaos aspect, but take it on with the rigor now possible. Once its accepted that Lunisolar inputs do have their place in the mix, accurate quantification can follow, even if strong prediction remains elusive. A basic quantification is to compare the High Q of Lunisolar statistics to the Low Q of them in the thicket ENSO-QBO data. We could call this the non-dimensional Pukite Number.
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561.

"ENSO predictions will slowly improve, until predicting a few cycles ahead should be possible, but not much better"

It's not about the predictions, but about the physics. No one makes any progress in science by throwing darts while blindfolded. There are many kinds of analyses one can do without relying on predictions as the only means to further understanding.

This was tweeted yesterday by the NASA climate science chief Gavin Schmidt

I responded

One mention in the ENSO literature on double-sideband modulation https://inis.iaea.org/collection/NCLCollectionStore/_Public/22/055/22055016.pdf

Got some discussion going last year on Gavin's blog: http://www.realclimate.org/index.php/archives/2020/03/why-are-so-many-solar-climate-papers-flawed/

Comment Source:> "ENSO predictions will slowly improve, until predicting a few cycles ahead should be possible, but not much better" It's not about the predictions, but about the physics. No one makes any progress in science by throwing darts while blindfolded. There are many kinds of analyses one can do without relying on predictions as the only means to further understanding. This was tweeted yesterday by the NASA climate science chief Gavin Schmidt <blockquote class="twitter-tweet"><p lang="en" dir="ltr">Checks to see whether these are comparable:<br>- seasonal cycle - visible in the forcing, but not the obs ❎<br>- interannual variability - ENSO doesn’t affect the forcing line, but is changing the obs ❎<br><br>We want the trend comparison but this depends on T/q changes (not included?)</p>&mdash; Gavin Schmidt (@ClimateOfGavin) <a href="https://twitter.com/ClimateOfGavin/status/1358391689275183107?ref_src=twsrc%5Etfw">February 7, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> I responded <blockquote class="twitter-tweet"><p lang="en" dir="ltr">The annual component isn&#39;t directly observed because of a property of signal processing called double-sideband suppressed carrier modulation. The annual carrier splits into sidebands modulated by the external forcing. Mirror symmetry of spectra about the Nyquist freq reveals it <a href="https://t.co/2aIasgHgtK">pic.twitter.com/2aIasgHgtK</a></p>&mdash; Puͣkiͧte̍ (@WHUT) <a href="https://twitter.com/WHUT/status/1359177109130928130?ref_src=twsrc%5Etfw">February 9, 2021</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> ![](https://pbs.twimg.com/media/EtzDsCAXYAAi-HZ.jpg) One mention in the ENSO literature on double-sideband modulation https://inis.iaea.org/collection/NCLCollectionStore/_Public/22/055/22055016.pdf Got some discussion going last year on Gavin's blog: http://www.realclimate.org/index.php/archives/2020/03/why-are-so-many-solar-climate-papers-flawed/ 
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562.
edited February 10

More broadly, ENSO prediction geophysics are much the same physics as weather prediction. There is a lot human life and assets riding on the best physics-based predictive models. Technical forecasters look at multiple physical models to make the best predictions.

You seem also to speak to the concern your model might not be predictive "by chance", yet still be physically correct. But what about being studiously uninterested in how much Lunisolar noise is directly picked up by ENSO sensor networks, to contaminate the data? Its not about that either?

An alternative Topological Insulator identification of the Equatorial Kelvin Wave is the major insulated bulks being Doldrum zones North and South of the narrow waveguide, and the wave itself being rather ballistic, not so much statically insulated. Once again, its the ontological Elephant Problem. At least we can predict some of the physics easily- Kelvin-Helmholtz Instabilities at the interface surfaces of the topological bulks.

Comment Source:PaulP: "It's not about the predictions, but about the physics." More broadly, ENSO prediction geophysics are much the same physics as weather prediction. There is a lot human life and assets riding on the best physics-based predictive models. Technical forecasters look at multiple physical models to make the best predictions. You seem also to speak to the concern your model might not be predictive "by chance", yet still be physically correct. But what about being studiously uninterested in how much Lunisolar noise is directly picked up by ENSO sensor networks, to contaminate the data? Its not about that either? An alternative Topological Insulator identification of the Equatorial Kelvin Wave is the major insulated bulks being Doldrum zones North and South of the narrow waveguide, and the wave itself being rather ballistic, not so much statically insulated. Once again, its the ontological Elephant Problem. At least we can predict some of the physics easily- Kelvin-Helmholtz Instabilities at the interface surfaces of the topological bulks. 
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563.

"There is a lot human life and assets riding on the best physics-based predictive models"

Yes, many people, including farmers and others, have a lot riding on minimizing loss due to droughts, floods, and heat waves. I'm all for supporting research that improves the quality of the models, perhaps ultimately to make them as practically useful as tidal tables.

OTOH, just listen to yourself. All you seem to be doing is marginalizing any analysis that I am posting to the forum. It actually sounds like you don't want to see any progress being made, perhaps because it doesn't conform to your own opinion on how to do research?

In practice, science advances by pitting one model against another model, so if you have a better model, maybe it's about time for you to present it here so we can do a comparison?

Comment Source:> "There is a lot human life and assets riding on the best physics-based predictive models" Yes, many people, including farmers and others, have a lot riding on minimizing loss due to droughts, floods, and heat waves. I'm all for supporting research that improves the quality of the models, perhaps ultimately to make them as practically useful as tidal tables. OTOH, just listen to yourself. All you seem to be doing is marginalizing any analysis that I am posting to the forum. It actually sounds like you don't want to see any progress being made, perhaps because it doesn't conform to your own opinion on how to do research? In practice, science advances by pitting one model against another model, so if you have a better model, maybe it's about time for you to present it here so we can do a comparison? ![](https://theysaidso.com/quote/image/Z_wuq3rRn9tffDZRGzvB8QeF) 
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564.

"You seem also to speak to the concern your model might not be predictive "by chance", yet still be physically correct."

That's not what I said at all. I stated that even if my model made a correct prediction of the next El Nino, an informed statistician will claim that that can happen just by chance, because even a random guess can be correct a fraction of the time. So then I will be asked to make another prediction, and then another, ... until somebody deems that an adequate significance level is achieved.

If, as you say that "There is a lot human life and assets riding on the best physics-based predictive models" then we should not wait 20 years to get several correct El Nino predictions under our belt, and instead try to use all the best cross-validation tools available that will work on the historical data. Using your own words, that sounds like a much more socially responsible approach to take, right?

Comment Source:> "You seem also to speak to the concern your model might not be predictive "by chance", yet still be physically correct." That's not what I said at all. I stated that even if my model made a correct prediction of the next El Nino, **an informed statistician** will claim that that can happen just by chance, because even a random guess can be correct a fraction of the time. So then I will be asked to make another prediction, and then another, ... until somebody deems that an adequate significance level is achieved. If, as you say that *"There is a lot human life and assets riding on the best physics-based predictive models"* then we should not wait 20 years to get several correct El Nino predictions under our belt, and instead try to use all the best cross-validation tools available that will work on the historical data. Using your own words, that sounds like a much more socially responsible approach to take, right? 
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565.
edited February 10

PaulP:"All you seem to be doing is marginalizing any analysis that I am posting to the forum."

Sorry if it seems so. Your analysis here stands or falls on its own merits; its not for anyone to change that. From the start, I readily agreed with you there must be (at least weak) Lunisolar Forcing to geophysical oscillations. If here and there analysis divergent from yours occurs, no worry about you somehow "marginalizing" it apart from inherent (de)merits.

You are specially invited to challenge the role of Lunisolar Noise on ENSO sensor data. The more I review the various sensor data sources, like sea-surface data, the more I find Lunisolar signals really are mixed-in, in real-time. These are not necessarily Forcings of overall ENSO Periodicity, and correction factors will filter out much of the spurious content. I am not sure yet how much sensor data defects currently skews your Model's output, but the "Pukite Number" proposed begins to bear rigorously on that question.

You rightly ask for a better predictive model here to compare with yours, and I have presented one. Again, with analogy to the best weather prediction, composite prediction is proposed based on the leading ENSO-QBO Models, including yours; to the extent these Models first singly show significant predictive validation. Am currently reviewing the field of ENSO Models. No doubt you deeply know many of these, and that their strengths could prove synergistic. As sensor data for training improves, there will increasingly be powerful Connectionist ENSO Models, that are semantic Black Boxes; so its not just classic equations and geophysical heuristics in play.

This is a sound plan of yours- "if my model made a correct prediction of the next El Nino, an informed statistician will claim that that can happen just by chance, because even a random guess can be correct a fraction of the time. So then I will be asked to make another prediction, and then another, ... until somebody deems that an adequate significance level is achieved." Let that "somebody" be understood to be the "informed statistician".

Accurately predicting just a few ENSO cycles in advance would indeed achieve "an adequate significance level", especially if there are no major mispredictions and the Model nicely catches outlier events longer and shorter than average. Not just cycle-periods need prediction, but also the amplitude of events, and identifying emerging multi-typed El Niño classifications.

A new conjecture here- that if the Earth was sufficiently uniform geophysically, Lunisolar Forcing, in combination with inherent geophysical harmonics, would generate specific Chladni Patterns. Partial heuristic evidence is the striking polar hexagon on Saturn.

Finally, regarding how better to apply the Topological Insulator concept to Equatorial Kelvin Waves, the equatorial waveguide effectively acts as a quasi 1D line case, often topologically identified as an Edge, ergo an Edge-Wave medium for Edge-Modes, ie Anyons under Sonic Relativity-

1D anyons in relativistic field theory, Yamamoto, 2018.

The topological insulator medium to EKW is effectively all the surrounding space and matter around the confined waveguide (edge); North, South, above (atmosphere), and below (sea-bottom).

Comment Source:PaulP:"All you seem to be doing is marginalizing any analysis that I am posting to the forum." Sorry if it seems so. Your analysis here stands or falls on its own merits; its not for anyone to change that. From the start, I readily agreed with you there must be (at least weak) Lunisolar Forcing to geophysical oscillations. If here and there analysis divergent from yours occurs, no worry about you somehow "marginalizing" it apart from inherent (de)merits. You are specially invited to challenge the role of Lunisolar Noise on ENSO sensor data. The more I review the various sensor data sources, like sea-surface data, the more I find Lunisolar signals really are mixed-in, in real-time. These are not necessarily Forcings of overall ENSO Periodicity, and correction factors will filter out much of the spurious content. I am not sure yet how much sensor data defects currently skews your Model's output, but the "Pukite Number" proposed begins to bear rigorously on that question. You rightly ask for a better predictive model here to compare with yours, and I have presented one. Again, with analogy to the best weather prediction, composite prediction is proposed based on the leading ENSO-QBO Models, including yours; to the extent these Models first singly show significant predictive validation. Am currently reviewing the field of ENSO Models. No doubt you deeply know many of these, and that their strengths could prove synergistic. As sensor data for training improves, there will increasingly be powerful Connectionist ENSO Models, that are semantic Black Boxes; so its not just classic equations and geophysical heuristics in play. This is a sound plan of yours- "if my model made a correct prediction of the next El Nino, an informed statistician will claim that that can happen just by chance, because even a random guess can be correct a fraction of the time. So then I will be asked to make another prediction, and then another, ... until somebody deems that an adequate significance level is achieved." Let that "somebody" be understood to be the "informed statistician". Accurately predicting just a few ENSO cycles in advance would indeed achieve "an adequate significance level", especially if there are no major mispredictions and the Model nicely catches outlier events longer and shorter than average. Not just cycle-periods need prediction, but also the amplitude of events, and identifying emerging multi-typed El Niño classifications. A new conjecture here- that if the Earth was sufficiently uniform geophysically, Lunisolar Forcing, in combination with inherent geophysical harmonics, would generate specific Chladni Patterns. Partial heuristic evidence is the striking polar hexagon on Saturn. Finally, regarding how better to apply the Topological Insulator concept to Equatorial Kelvin Waves, the equatorial waveguide effectively acts as a quasi 1D line case, often topologically identified as an Edge, ergo an Edge-Wave medium for Edge-Modes, ie Anyons under Sonic Relativity- 1D anyons in relativistic field theory, Yamamoto, 2018. The topological insulator medium to EKW is effectively all the surrounding space and matter around the confined waveguide (edge); North, South, above (atmosphere), and below (sea-bottom).
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566.

"The more I review the various sensor data sources, like sea-surface data, the more I see Lunisolar signals are mixed-in, in real-time."

You talk as if you have done the data analysis. Where is it? It's not possible to hand-wave the agreement as the lunisolar cycles are precisely fixed and therefore the analysis has to be quantifiable and not just a qualitative match.

"You rightly ask me to present a better predictive model here to compare with yours, and I have. "

Where is it? It's easy to post charts to this forum.

So you say that you "have" a "better predictive model" than mine.

Consider this passage from a recent paper called "Quantification and interpretation of the climate variability record"

This passage demonstrates that climate scientists have little confidence as to the fundamental mechanism behind ENSO. They hedge by saying "thought to be", providing an "or", and then waffling with an "on the other hand". The charge-recharge oscillator model has never come close to matching the data in any quantifiable fashion, since it is chaotically unstable as they even admit.

So where is your predictive model of chaos?

Comment Source:> "The more I review the various sensor data sources, like sea-surface data, the more I see Lunisolar signals are mixed-in, in real-time." You talk as if you have done the data analysis. Where is it? It's not possible to hand-wave the agreement as the lunisolar cycles are precisely fixed and therefore the analysis has to be quantifiable and not just a qualitative match. > "You rightly ask me to present a better predictive model here to compare with yours, and I have. " Where is it? It's easy to post charts to this forum. --- So you say that you "have" a "better predictive model" than mine. Consider this passage from a recent paper called ["Quantification and interpretation of the climate variability record"](https://arxiv.org/ftp/arxiv/papers/2101/2101.08050.pdf) > ![](https://pbs.twimg.com/media/Et3psQHXMAEqKK6.png) This passage demonstrates that climate scientists have little confidence as to the fundamental mechanism behind ENSO. They hedge by saying "thought to be", providing an "or", and then waffling with an "on the other hand". The charge-recharge oscillator model has never come close to matching the data in any quantifiable fashion, since it is chaotically unstable as they even admit. So where is your predictive model of chaos? 
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567.
edited February 11

PaulP: "So where is your predictive model of chaos?"

Again, our best example of a "predictive model of chaos" is modern weather prediction, now fairly accurate out to 10 days. Weather is chaotic, but because its also deterministic, we diligently improve forecasting.

Its not an original idea to combine predictive models, but quite standard in professional Weather Prediction. Since that is further along than us here, look at this page for an idea how ENSO could soon enough aggregate models and learn to synergize them. For now, you need only keep open to the idea that combining ENSO Models is a reasonable approach. I proposing that a Combined Model may be better predictive than yours alone.

https://www.theweather.com/models/

Be patient, let me get to work better describing a Combined ENSO Model in the weeks to come. TIA if you have helpful links to any existing up-to-date ENSO model lists. I have seen a handful of Models, mentioned here and there, ranging from major geophysical institutions with many researchers, now running multi-physics solvers on supercomputers for decades, to your own model as offered, needing to be compiled.

It won't be hard to take basic predictions, to average them, or have models "vote", and tweak the combining algorithm over time. Of course, there may be emerge some dominant single model that is right more often than any combination of discrete models, but that model itself will likely be the most broadly comprehensive internally, combining and accounting for the most critical factors.

As for the ENSO sensor data sets, I have only just begun to validate (or not) the Lunisolar Noise Hypothesis. I start from the heuristic that a buoy or satellite sensor picks up a constant churn of tidal and wave sea states, plus sensor noise, as it also seeks imperfectly to detect desired long period state information. You also speculate over this same noisy data, and no analysis is yet final. You are ideally prepared to pivot and filter Lunisolar Noise from the data, should that prove to be helpful.

Here is starting information of Lunisolar Third Body Effect on orbiting satellites; 0.7m variation per orbit, comparable or greater than open ocean sea-surface tide range.

Perturbations in orbital elements of a low earth orbiting satellite

Eshagh and Najafi Alamdari 2005

[Heydt et al 2021] as quoted, is in good agreement with what I have been asserting about ENSO here.

Comment Source:PaulP: "So where is your predictive model of chaos?" Again, our best example of a "predictive model of chaos" is modern weather prediction, now fairly accurate out to 10 days. Weather is chaotic, but because its also deterministic, we diligently improve forecasting. Its not an original idea to combine predictive models, but quite standard in professional Weather Prediction. Since that is further along than us here, look at this page for an idea how ENSO could soon enough aggregate models and learn to synergize them. For now, you need only keep open to the idea that combining ENSO Models is a reasonable approach. I proposing that a Combined Model may be better predictive than yours alone. https://www.theweather.com/models/ Be patient, let me get to work better describing a Combined ENSO Model in the weeks to come. TIA if you have helpful links to any existing up-to-date ENSO model lists. I have seen a handful of Models, mentioned here and there, ranging from major geophysical institutions with many researchers, now running multi-physics solvers on supercomputers for decades, to your own model as offered, needing to be compiled. It won't be hard to take basic predictions, to average them, or have models "vote", and tweak the combining algorithm over time. Of course, there may be emerge some dominant single model that is right more often than any combination of discrete models, but that model itself will likely be the most broadly comprehensive internally, combining and accounting for the most critical factors. As for the ENSO sensor data sets, I have only just begun to validate (or not) the Lunisolar Noise Hypothesis. I start from the heuristic that a buoy or satellite sensor picks up a constant churn of tidal and wave sea states, plus sensor noise, as it also seeks imperfectly to detect desired long period state information. You also speculate over this same noisy data, and no analysis is yet final. You are ideally prepared to pivot and filter Lunisolar Noise from the data, should that prove to be helpful. Here is starting information of Lunisolar Third Body Effect on orbiting satellites; 0.7m variation per orbit, comparable or greater than open ocean sea-surface tide range. Perturbations in orbital elements of a low earth orbiting satellite Eshagh and Najafi Alamdari 2005 https://jesphys.ut.ac.ir/article_18539_a2b54fd7d0f5b087bf3ead7555637f8f.pdf [Heydt et al 2021] as quoted, is in good agreement with what I have been asserting about ENSO here.
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568.

I don't see your ENSO model results yet, just some links to weather and an orbiting satellite.

Comment Source:I don't see your ENSO model results yet, just some links to weather and an orbiting satellite.
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569.
edited February 11

Don't give up yet. There is more shared here than you are allowing.

You are farther along than me in showing your ENSO model results, after so many years head-start. Anyone needs the sort of time it took you to be ready. Give me time to satisfy your requests for even more, until you can fairly concede some value. I have at least posed my starting hypotheses.

Chaos science does not "punt", but meets its dynamics head on. Weather science is a brilliant success story. Sensor noise is no blind spot not to be spoken of. If your model is merely memorizing the noisy data, to seemingly recreate it accurately, then predicting the next few years will show gross mismatch. If your model is true, actual and predicted wave forms will match closely. If the Lunisolar Noise Hypothesis is true, your model will well predict that signal.

We'll see if a combined model, with better sensor-noise filtering, does better. Fortunately its not all on me. We will accept anyone's multi-physics model and better data validated by superior predictive power. In particular, solar radiation, seasonal variance, and geological harmonics in a model seem essential to best predictive performance, apart from any Lunisolar components.

Demanding immediate third-party validations here, while invoking 2280 as "even better", is wide of the mark on both ends. I devote to diligent study on a reasonable timescale. Thanks for any encouragement.

Comment Source:Don't give up yet. There is more shared here than you are allowing. You are farther along than me in showing your ENSO model results, after so many years head-start. Anyone needs the sort of time it took you to be ready. Give me time to satisfy your requests for even more, until you can fairly concede some value. I have at least posed my starting hypotheses. Chaos science does not "punt", but meets its dynamics head on. Weather science is a brilliant success story. Sensor noise is no blind spot not to be spoken of. If your model is merely memorizing the noisy data, to seemingly recreate it accurately, then predicting the next few years will show gross mismatch. If your model is true, actual and predicted wave forms will match closely. If the Lunisolar Noise Hypothesis is true, your model will well predict that signal. We'll see if a combined model, with better sensor-noise filtering, does better. Fortunately its not all on me. We will accept anyone's multi-physics model and better data validated by superior predictive power. In particular, solar radiation, seasonal variance, and geological harmonics in a model seem essential to best predictive performance, apart from any Lunisolar components. Demanding immediate third-party validations here, while invoking 2280 as "even better", is wide of the mark on both ends. I devote to diligent study on a reasonable timescale. Thanks for any encouragement. 
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570.

The lunisolar gravitational forces control the variation in the earth's rotation speed (dLOD) as a direct solid body inertial response. With the correct accounting of the tidal factor strengths it makes perfect sense assuming a linear transfer function.

OTOH, that same force applied to a stratified liquid will cause that liquid to slosh with a nonlinear response. The only nonlinear response that seems to work is the one that I mathematically derived from analytically solving Laplace's Tidal Equations along the equator.

In the figure below, the lower panel shows the model fit to dLOD using the known tidal factors, while the upper panel shows an ENSO fit applying the LTE transfer function to the same dLOD forcing, i.e. a scaled linear to nonlinear mapping.

(note the difference in the time-series range, thus requiring an extrapolation of the modeled LOD forcing to all dates prior to 1962)

This is all one needs to validate the ENSO model, as it is statistically impossible to match each of the peaks and valleys in the data, while being tightly constrained by a stationary cyclic tidal forcing. There is very little noise in the data because the inertial response of that large a mass will filter out everything but the strongest forcing -- which just happens to be the tidal forces.

Conclusion: If one doesn’t know how to solve the geophysical fluid dynamics problem, one will never be able to fit ENSO to a known forcing.

BTW, as a challenge, there is no need for me to provide any more validation than this as a starting point -- what is needed next is someone to either debunk this model (perhaps by finding a flaw in the fitting algorithm) or having someone devise a better model in terms of fit, plausibility, and parsimony.

This group apparently claims a decent ENSO model fit using a machine learning training algorithm written in R.

https://blogs.rstudio.com/ai/posts/2021-02-02-enso-prediction

Their prediction extends to the next time step

"However, we need to keep in mind that we’re predicting just a single time step ahead. We probably should not overestimate the results."

So, which is a better ENSO model? Mine or this ML version?

Comment Source:The lunisolar gravitational forces control the variation in the earth's rotation speed (dLOD) as a direct solid body inertial response. With the correct accounting of the tidal factor strengths it makes perfect sense assuming a linear transfer function. OTOH, that same force applied to a stratified liquid will cause that liquid to slosh with a nonlinear response. The only nonlinear response that seems to work is the one that I mathematically derived from analytically solving Laplace's Tidal Equations along the equator. In the figure below, the lower panel shows the model fit to dLOD using the known tidal factors, while the upper panel shows an ENSO fit applying the LTE transfer function to the same dLOD forcing, i.e. a scaled linear to nonlinear mapping. ![](https://imagizer.imageshack.com/img923/4420/MjEtGA.png) (note the difference in the time-series range, thus requiring an extrapolation of the modeled LOD forcing to all dates prior to 1962) This is all one needs to validate the ENSO model, as it is statistically impossible to match each of the peaks and valleys in the data, while being tightly constrained by a stationary cyclic tidal forcing. There is very little noise in the data because the inertial response of that large a mass will filter out everything but the strongest forcing -- which just happens to be the tidal forces. Conclusion: If one doesn’t know how to solve the geophysical fluid dynamics problem, one will never be able to fit ENSO to a known forcing. BTW, as a challenge, there is no need for me to provide any more validation than this as a starting point -- what is needed next is someone to either debunk this model (perhaps by finding a flaw in the fitting algorithm) or having someone devise a better model in terms of fit, [plausibility, and parsimony](https://imagizer.imageshack.com/img924/4444/uEUOGo.png). This group apparently claims a decent ENSO model fit using a machine learning training algorithm written in **R**. https://blogs.rstudio.com/ai/posts/2021-02-02-enso-prediction Their prediction extends to the next time step > ![](https://blogs.rstudio.com/ai/posts/2021-02-02-enso-prediction/images/preds.png) > "However, we need to keep in mind that we’re predicting just a single time step ahead. We probably should not overestimate the results." So, which is a better ENSO model? Mine or this ML version? 
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571.
edited February 12

PaulP: "So, which is a better ENSO model? Mine or this ML version?"

Let measured predictive success decide the question. I agree with you below.

PaulP on ML Version: "a great addition to open-source climate science. "

Caution: Machine Learning is also susceptible to overfitting and underfitting, caused by imperfect data.

Here is NOAA prediction as reference-model. They seem to avoid overfitting and underfitting risk better than simple models dependent on narrower data-sets.

https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf

Comment Source:PaulP: "So, which is a better ENSO model? Mine or this ML version?" Let measured predictive success decide the question. I agree with you below. PaulP on ML Version: "a great addition to open-source climate science. " Caution: Machine Learning is also susceptible to overfitting and underfitting, caused by imperfect data. Here is NOAA prediction as reference-model. They seem to avoid overfitting and underfitting risk better than simple models dependent on narrower data-sets. https://www.cpc.ncep.noaa.gov/products/analysis_monitoring/lanina/enso_evolution-status-fcsts-web.pdf
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572.

LOL, those predictions are for 6 only months in advance! Basically dead-reckoning forecasts

Comment Source:LOL, those predictions are for 6 only months in advance! Basically dead-reckoning forecasts 
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573.
edited February 13

True. With six month forecasts NOAA is betting on Chaos. With "even better" 260yr-plus predictions, you are betting against Chaos. All you have to do is beat NOAA six months at a time for a few years. Even better, beat them a few years out.

Comment Source:True. With six month forecasts NOAA is betting on Chaos. With "even better" 260yr-plus predictions, you are betting against Chaos. All you have to do is beat NOAA six months at a time for a few years. Even better, beat them a few years out.
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574.

No, it only means that they don't understand the pattern.

Comment Source:No, it only means that they don't understand the pattern.
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575.
edited February 13

Unclear what proposition "No" relates to above. NOAA understands patterns of tides and strengths and limitations of LaPlace's Equations to an expert degree better than blanket denial suggests.

Continuing review of Lunisolar effects on data collection, tidal currents affect seasurface temperatures in complex ways. There is the internal sloshing. Shoals and other features promote mixing. Coasts, seamounts and islands have a sort of plunger effect. Given Chaos, there is both some coherent forcing, and highly chaotic outcomes. Some of this tidal churn will express as noise in sea-surface temperature data in the false guise of bulk forcing.

Surface Gravity Wave mixing is a huge source of seasurface temperature noise. A data buoy in heavy seas will read a different temperature than calm seas, in the same place and ENSO state. A data buoy will read a different temperature on a sunny day than cloudy day. As we dig down into the sensor dynamics, we'll get a truer picture.

Again, we see a pattern NOAA well knows, that ENSO identification and ENSO data is significantly uncertain. Lunisolar noise adds to the uncertainty, as well as having at best a weak theoretic (not well quantified) forcing effect. If ENSO Lunisolar Forcing was a strong effect, it would be long ago recognized and widely agreed. Training ML from inherently uncertain data is very imperfect.

Plate Tectonics is a clue. If Lunsolar tides where a source of harmonic order rather than noise, why are the continental plates so screwed up? It can't just be three-body chaos in vacuo, as a gross simplification, given Earth rotation as the first-order driver, not the incidental position of the three bodies. It really looks like seething multi-chaos, with a clean Lunsolar signal at most only superficially overlaid on the data.

Even if the 60Hz noise analogy is recast as a 59-61Hz dual beat cycle, it would not be forcing the music, only perhaps appear so, superposed.

Comment Source:Unclear what proposition "No" relates to above. NOAA understands patterns of tides and strengths and limitations of LaPlace's Equations to an expert degree better than blanket denial suggests. Continuing review of Lunisolar effects on data collection, tidal currents affect seasurface temperatures in complex ways. There is the internal sloshing. Shoals and other features promote mixing. Coasts, seamounts and islands have a sort of plunger effect. Given Chaos, there is both some coherent forcing, and highly chaotic outcomes. Some of this tidal churn will express as noise in sea-surface temperature data in the false guise of bulk forcing. Surface Gravity Wave mixing is a huge source of seasurface temperature noise. A data buoy in heavy seas will read a different temperature than calm seas, in the same place and ENSO state. A data buoy will read a different temperature on a sunny day than cloudy day. As we dig down into the sensor dynamics, we'll get a truer picture. Again, we see a pattern NOAA well knows, that ENSO identification and ENSO data is significantly uncertain. Lunisolar noise adds to the uncertainty, as well as having at best a weak theoretic (not well quantified) forcing effect. If ENSO Lunisolar Forcing was a strong effect, it would be long ago recognized and widely agreed. Training ML from inherently uncertain data is very imperfect. Plate Tectonics is a clue. If Lunsolar tides where a source of harmonic order rather than noise, why are the continental plates so screwed up? It can't just be three-body chaos in vacuo, as a gross simplification, given Earth rotation as the first-order driver, not the incidental position of the three bodies. It really looks like seething multi-chaos, with a clean Lunsolar signal at most only superficially overlaid on the data. Even if the 60Hz noise analogy is recast as a 59-61Hz dual beat cycle, it would not be forcing the music, only perhaps appear so, superposed.
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576.

Someone said:

"I avoid people who have a tendency to capitalize words that shouldn’t be."

"One of King's least favorite Twitter users, Donald Trump, also loves to capitalize words in tweets — though his capitalizations can often come across as random and nonsensical."

Just a thought

Comment Source:Someone said: > "I avoid people who have a tendency to capitalize words that shouldn’t be." [A look at the Ubiquitous Habit of capitalizing letters to make A Point](https://mashable.com/article/capitalizing-first-letter-words-trend/) (from Mashable) > "One of King's least favorite Twitter users, Donald Trump, also loves to capitalize words in tweets — though his capitalizations can often come across as random and nonsensical." Just a thought 
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577.
edited February 13

Again, what amount of Lunisolar Noise do you think is in the ENSO data? Do you think its only "forcing" expressed in the data? No contribution to chaos?

As Earth rotates, the Moon's pull goes on way, then the other. Does this to-and-fro not considerably cancel overall, by elastic response?

Anyway, open ENSO questions continue piling up. Please take due time and care addressing them rigorously.

Regarding CAPS use as ad hominem red-herring "punting" with regard to ENSO Topic; which words were wrongly capitalized, so they can be fixed, removing the objection? Look at Newton's PRINCIPIA, as first printed. Feynman's Notebooks have more CAPS than Trump-

https://physicstoday.scitation.org/do/10.1063/PT.5.9099/full/

Search on , "I avoid people who have a tendency to capitalize words that shouldn’t be," delivered a clown at top of results- https://withoutbullshit.com/blog/dont-capitalize-random-crap

That's "BS" and "crap" in one URL. Avoid THAT person, not Newton or Feynman.

Citing NOAA (bad), v citing Mashable (good)?

Your Mashable link to "Ubiquitous (CAPS) Habit" by "NICOLE GALLUCCI" (sic), who herself reasonably writes with CAPS as she sees fit (like "Extremely Self-Aware"):

"...capitalized words in texts or tweets not only highlight an original idea, but give off an extra sense of pride one has in that idea...as an indicator of sorts...they alert readers that the altered text is the most important part of a thought, but also that the writer has a certain sense of humor...Every single Extremely Self-Aware person who replied (to CAPS use query) made sure to lightheartedly own their capitalization habit in their responses, fully embracing the technique as part of their personality."

CAPs is a "technique" to "fully embrace", according to your source.

This topic is about ENSO and QBO, regardless of who shuns Newton for CAPS. Lets focus on Geophysics Content.

Getting back to serious ENSO science questions posed, but still unaddressed by you. Is Lunisolar Sensor Data Noise not a legitimate open ENSO Modeling question in your view? Until refuted, its a plausible alternative hypothesis to explain the Lunisolar Signal apparent in ENSO-QBO data.

Comment Source:Again, what amount of Lunisolar Noise do you think is in the ENSO data? Do you think its only "forcing" expressed in the data? No contribution to chaos? As Earth rotates, the Moon's pull goes on way, then the other. Does this to-and-fro not considerably cancel overall, by elastic response? Anyway, open ENSO questions continue piling up. Please take due time and care addressing them rigorously. Regarding CAPS use as ad hominem red-herring "punting" with regard to ENSO Topic; which words were wrongly capitalized, so they can be fixed, removing the objection? Look at Newton's PRINCIPIA, as first printed. Feynman's Notebooks have more CAPS than Trump- https://physicstoday.scitation.org/do/10.1063/PT.5.9099/full/ Search on , "I avoid people who have a tendency to capitalize words that shouldn’t be," delivered a clown at top of results- https://withoutbullshit.com/blog/dont-capitalize-random-crap That's "BS" and "crap" in one URL. Avoid THAT person, not Newton or Feynman. Citing NOAA (bad), v citing Mashable (good)? Your Mashable link to "Ubiquitous (CAPS) Habit" by "NICOLE GALLUCCI" (sic), who herself reasonably writes with CAPS as she sees fit (like "Extremely Self-Aware"): "...capitalized words in texts or tweets not only highlight an original idea, but give off an extra sense of pride one has in that idea...as an indicator of sorts...they alert readers that the altered text is the most important part of a thought, but also that the writer has a certain sense of humor...Every single Extremely Self-Aware person who replied (to CAPS use query) made sure to lightheartedly own their capitalization habit in their responses, fully embracing the technique as part of their personality." CAPs is a "technique" to "fully embrace", according to your source. This topic is about ENSO and QBO, regardless of who shuns Newton for CAPS. Lets focus on Geophysics Content. Getting back to serious ENSO science questions posed, but still unaddressed by you. Is Lunisolar Sensor Data Noise not a legitimate open ENSO Modeling question in your view? Until refuted, its a plausible alternative hypothesis to explain the Lunisolar Signal apparent in ENSO-QBO data. 
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578.

I'm getting a bit sick and tired of this stuff. Today I find that Trump gets acquitted of charges of insurrection, and my 2-page Ideas paper gets rejected from the Earth System Dynamics journal (yes, 2 pages is the page limit).

The two are definitely related as there are cowards among us in both politics and science.

Dave, so you say that NOAA has all the answers, eh?

This reviewer of my paper, Billy Kessler of NOAA, wrote this:

I am a physical oceanographer who knows nothing about the Chandler wobble, is only slightly familiar with the QBO, but is a longtime expert on ENSO. To be blunt, trying to shoehorn ENSO into a periodic tidal framework stretches reality to fit someone’s preconceived theory. Only the most motivated reasoning can believe this.

(more stuff that you can read)

I am sorry to have wasted an hour on this.

Billy Kessler, NOAA/PMEL, Seattle

interactive comment on earth syst. dynam. discuss., https://doi.org/10.5194/esd-2020-74

That last line is a pathetic insult. And suggesting "preconceived theory" and "motivated reasoning" is a slam at anyone that is testing out a theory or hypothesis by actually showing some persistence in doing an involved computational analysis.

"shoehorn ENSO into a periodic tidal framework"

Umm, like duh. Way back in 1776, Laplace developed the now-referred-to Laplace's Tidal Equations to attempt to model tidal flows, including the effects of Coriolis and lateral forcing. They proved so successful that they were enhanced to form the so-called primitive equations used to approximate atmospheric flow in global atmospheric models. So they are essentially GCMs. So what I did is to derive a compact analytical solution for the LTE along the equator and applied that theoretical model to evaluating the ENSO while using tidal forces as input.

And Billy from NOAA calls that motivated reasoning ? I would give up if they weren't so laughably ignorant about how to do physics.

Comment Source:I'm getting a bit sick and tired of this stuff. Today I find that Trump gets acquitted of charges of insurrection, and my 2-page Ideas paper gets rejected from the Earth System Dynamics journal (yes, 2 pages is the page limit). The two are definitely related as there are cowards among us in both politics and science. Dave, so you say that NOAA has all the answers, eh? This reviewer of my paper, Billy Kessler of NOAA, [wrote this](https://esd.copernicus.org/preprints/esd-2020-74/esd-2020-74-RC1.pdf): > I am a physical oceanographer who knows nothing about the Chandler wobble, is only slightly familiar with the QBO, but is a longtime expert on ENSO. To be blunt, trying to shoehorn ENSO into a periodic tidal framework stretches reality to fit someone’s preconceived theory. Only the most **motivated reasoning** can believe this. > … *(more stuff that you can read)* > **I am sorry to have wasted an hour on this.** > Billy Kessler, NOAA/PMEL, Seattle >interactive comment on earth syst. dynam. discuss., https://doi.org/10.5194/esd-2020-74 That last line is a pathetic insult. And suggesting "preconceived theory" and "motivated reasoning" is a slam at anyone that is testing out a theory or hypothesis by actually showing some persistence in doing an involved computational analysis. > **"shoehorn ENSO into a periodic tidal framework"** Umm, like duh. Way back in 1776, Laplace developed the now-referred-to **Laplace's Tidal Equations** to attempt to model tidal flows, including the effects of Coriolis and lateral forcing. They proved so successful that they were enhanced to form the so-called [primitive equations](https://en.wikipedia.org/wiki/Primitive_equations) used to approximate atmospheric flow in global atmospheric models. So they are essentially GCMs. So what I did is to derive a compact analytical solution for the LTE along the equator and applied that theoretical model to evaluating the ENSO while using tidal forces as input. And Billy from NOAA calls that *motivated reasoning* ? I would give up if they weren't so laughably ignorant about how to do physics. 
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579.
edited February 14

PaulP:"Dave, so you say that NOAA has all the answers, eh?"

No, NOAA only has some ENSO answers, not all. I continue insisting its a long game, like progress in Weather Modeling and Prediction.

I disagree with Billy too. He did not waste that hour pouring out his skepticism, but diligently provided an honorably contrasting interpretation to yours, in accord with the "Elephant" analogy. "Motivated reasoning" is only bad if one is wrong; then its a rather gentlemanly let-down. NOAA is not "laughably ignorant about how to do (ENSO) physics", except perhaps to the most pitiably ignorant. Rejection by Copernicus Publications means little, even if they use less CAPS than me. Keep trying.

There is a way forward by asserting ENSO Lunisolar Forcing is weak but probable. As a Chaotic System, ENSO is sensitive to initial conditions, therefore occasionally susceptible to Tidal Forcing. As a Quantum Analog System, there must be greater-than-zero entanglement of Lunisolar and ENSO statistics. These are not easy "proofs" of the rigor Wilczek demands, but if you do the homework, you can prevail. Then you might teach NOAA a thing or two.

The winner of ENSO Modeling controversy will be whoever bends from crude starting assumptions (eg. Laplace) to first fit the final validated truths. Best of Luck to You and Billy both, to arrive at that same true science together.

Comment Source:PaulP:"Dave, so you say that NOAA has all the answers, eh?" No, NOAA only has some ENSO answers, not all. I continue insisting its a long game, like progress in Weather Modeling and Prediction. I disagree with Billy too. He did not waste that hour pouring out his skepticism, but diligently provided an honorably contrasting interpretation to yours, in accord with the "Elephant" analogy. "Motivated reasoning" is only bad if one is wrong; then its a rather gentlemanly let-down. NOAA is not "laughably ignorant about how to do (ENSO) physics", except perhaps to the most pitiably ignorant. Rejection by Copernicus Publications means little, even if they use less CAPS than me. Keep trying. There is a way forward by asserting ENSO Lunisolar Forcing is weak but probable. As a Chaotic System, ENSO is sensitive to initial conditions, therefore occasionally susceptible to Tidal Forcing. As a Quantum Analog System, there must be greater-than-zero entanglement of Lunisolar and ENSO statistics. These are not easy "proofs" of the rigor Wilczek demands, but if you do the homework, you can prevail. Then you might teach NOAA a thing or two. The winner of ENSO Modeling controversy will be whoever bends from crude starting assumptions (eg. Laplace) to first fit the final validated truths. Best of Luck to You and Billy both, to arrive at that same true science together. 
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580.

"As a Chaotic System, ENSO is sensitive to initial conditions, therefore occasionally susceptible to Tidal Forcing. "

Not chaotic implies the converse. None of the model behaviors (ENSO, QBO, or Chandler wobble) are dependent on initial conditions -- instead they are sensitive to continuous (including annual) forcing, with any perturbations quickly damping out.

Is having a winter season sensitive to initial conditions? Is having a daily warming sensitive to initial conditions? Thought not.

Comment Source:> "As a Chaotic System, ENSO is sensitive to initial conditions, therefore occasionally susceptible to Tidal Forcing. " Not chaotic implies the converse. None of the model behaviors (ENSO, QBO, or Chandler wobble) are dependent on initial conditions -- instead they are sensitive to continuous (including annual) forcing, with any perturbations quickly damping out. Is having a winter season sensitive to initial conditions? Is having a daily warming sensitive to initial conditions? Thought not. 
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581.
edited February 14

PaulP:"Is having a winter season sensitive to initial conditions? Is having a daily warming sensitive to initial conditions?"

Yes, the slight declination of the Earth had to be set up, or there would be no seasons, and the Earth had to rotate, rather than be tidally locked to the Sun, or there would be no daily warming cycle. Even the Laws of Physics in this Universe may have been exquisitely sensitive to initial conditions.

Comment Source:PaulP:"Is having a winter season sensitive to initial conditions? Is having a daily warming sensitive to initial conditions?" Yes, the slight declination of the Earth had to be set up, or there would be no seasons, and the Earth had to rotate, rather than be tidally locked to the Sun, or there would be no daily warming cycle. Even the Laws of Physics in this Universe may have been exquisitely sensitive to initial conditions.
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582.

Not in the sense of the behavior under investigation.

Comment Source:Not in the sense of the behavior under investigation.
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583.
edited February 14

True, our investigation here is about ENSO-QBO behavior. The predicted sensitivity is of a nature that a slight difference now in conditions can completely alter future quasi-periodicity inflection, the longer the time-frame, the more divergent. Indirect evidence of ENSO chaos is NOAA's limited prediction capability, which you take as evidence they are "laughably ignorant about how to do physics".

This is an ENSO Chaos view-

Published: 26 March 2014 Climate science

A high bar for decadal forecasts of El Niño Pedro DiNezio Nature volume 507, pages437–439(2014)

"Climate simulations suggest that multi-decadal periods of high and low variability in the phenomenon known as the El Niño-Southern Oscillation in the tropical Pacific Ocean may be entirely unpredictable."

https://www.nature.com/articles/507437a

Comment Source:True, our investigation here is about ENSO-QBO behavior. The predicted sensitivity is of a nature that a slight difference now in conditions can completely alter future quasi-periodicity inflection, the longer the time-frame, the more divergent. Indirect evidence of ENSO chaos is NOAA's limited prediction capability, which you take as evidence they are "laughably ignorant about how to do physics". This is an ENSO Chaos view- Published: 26 March 2014 Climate science A high bar for decadal forecasts of El Niño Pedro DiNezio Nature volume 507, pages437–439(2014) "Climate simulations suggest that multi-decadal periods of high and low variability in the phenomenon known as the El Niño-Southern Oscillation in the tropical Pacific Ocean may be entirely unpredictable." https://www.nature.com/articles/507437a
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584.

"The predicted sensitivity is of a nature that a slight difference now in conditions can completely alter future quasi-periodicity inflection, the longer the time-frame, the more divergent. "

Nope. Doesn't work that way. For example, all indications are that the more the QBO measurements accumulate over time, the closer they converge (NOT diverge) to the theoretically predicted asymptotic value.

That's the definition of a boundary-value problem, not an initial-conditions problem.

ENSO is even more rigid in following a boundary-value problem since the greater inertia of the Pacific ocean volume is less susceptible to perturbations. Same for seasonal cycle. Same for daily cycle. None of these diverge over time,

Comment Source:> "The predicted sensitivity is of a nature that a slight difference now in conditions can completely alter future quasi-periodicity inflection, the longer the time-frame, the more divergent. " Nope. Doesn't work that way. For example, all indications are that the more the QBO measurements accumulate over time, the closer they converge (NOT diverge) to the theoretically predicted asymptotic value. ![](https://imageshack.com/a/img923/2528/Y240Dt.png) That's the definition of a boundary-value problem, not an initial-conditions problem. ENSO is even more rigid in following a boundary-value problem since the greater inertia of the Pacific ocean volume is less susceptible to perturbations. Same for seasonal cycle. Same for daily cycle. None of these diverge over time, 
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585.
edited February 14

Do not confuse inherent chaotic unpredictability with converging averages of larger samplings. These are quite different things!

Its possible to develop an ever more precise estimation of average ENSO-QBO periodicity, and still not be able to precisely predict inflections. Of course QBO is more periodic, but still seen to express chaotic statistics.

Here is a mother lode of ENSO Chaos science with a mention of "forcings from ... orbital variations", without specifiying a reference from the vast bibliography:

"Previous studies have revealed a wide range of ENSO responses to forcings from greenhouse gases, aerosols, and orbital variations, but they have also shown that interdecadal modulation of ENSO can arise even without such forcings."

ENSO Modulation: Is It Decadally Predictable?

Wittenberg et al 2014

https://journals.ametsoc.org/view/journals/clim/27/7/jcli-d-13-00577.1.xml

Comment Source:Do not confuse inherent chaotic unpredictability with converging averages of larger samplings. These are quite different things! Its possible to develop an ever more precise estimation of average ENSO-QBO periodicity, and still not be able to precisely predict inflections. Of course QBO is more periodic, but still seen to express chaotic statistics. Here is a mother lode of ENSO Chaos science with a mention of "forcings from ... orbital variations", without specifiying a reference from the vast bibliography: "Previous studies have revealed a wide range of ENSO responses to forcings from greenhouse gases, aerosols, and orbital variations, but they have also shown that interdecadal modulation of ENSO can arise even without such forcings." ENSO Modulation: Is It Decadally Predictable? Wittenberg et al 2014 https://journals.ametsoc.org/view/journals/clim/27/7/jcli-d-13-00577.1.xml 
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586.

Another substantiation that ENSO is not chaotic. The scientists at NOAA filter out the annualized signal from the ENSO NINO34 index. Below is the part of the time series that they remove, labelled "ClimAdjust"

One can assert this is just a remnant of the well-known annual signal, but it is actually pulse-shaped and close to what I apply to modulate the tidal-signal to create a "spring-barrier" forcing that carries on to the next year.

What NOAA did was not proper signal processing. One shouldn't remove what may be considered nuisance parameters in a time-series by assuming that they relate to known (in this case seasonal) factors and so can be safely filtered out and ignored. In fact, that may be safe only IF those factors form an independent process and so don't cause non-linear interactions with the rest of the data. So if a model predicts a linear component and a non-linear component, it's not helping to hide the linear portion from the analysis. But that's not the only problem, as the filtering is over-zealous in that it removes all annual harmonics as well. Worse yet, the weighting of these harmonics changes over time, which means that they are removing other parts of the spectrum not related to the annual signal. This is all found in an "ensostuff" subdirectory:

https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/detrend.nino34.ascii.txt

Comment Source:Another substantiation that ENSO is not chaotic. The scientists at NOAA filter out the annualized signal from the ENSO NINO34 index. Below is the part of the time series that they remove, labelled "ClimAdjust" ![](http://imageshack.com/a/img921/8803/GKja1e.png) One can assert this is just a remnant of the well-known annual signal, but it is actually pulse-shaped and close to what I apply to modulate the tidal-signal to create a "spring-barrier" forcing that carries on to the next year. ![](http://imageshack.com/a/img921/192/JPiLyf.png) What NOAA did was not proper signal processing. One shouldn't remove what may be considered nuisance parameters in a time-series by assuming that they relate to known (in this case seasonal) factors and so can be safely filtered out and ignored. In fact, that may be safe only **IF** those factors form an independent process and so don't cause non-linear interactions with the rest of the data. So if a model predicts a linear component and a non-linear component, it's not helping to hide the linear portion from the analysis. But that's not the only problem, as the filtering is over-zealous in that it removes all annual harmonics as well. Worse yet, the weighting of these harmonics changes over time, which means that they are removing other parts of the spectrum not related to the annual signal. This is all found in an "ensostuff" subdirectory: https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/detrend.nino34.ascii.txt 
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587.
edited February 16

PaulP: "substantiation that ENSO is not chaotic."

Even a basic double-pendulum or the square-root of 2 decimal integer sequence is quite chaotic. Any complexity is inherently chaotic. ENSO is clearly multi-chaotic. How is the plate tectonics constraining ENSO not chaotic? Roaming crustal plates do not produce crystal-order.

Another physics lens into Lunisolar ENSO-QBO is thermodynamics. The Earth-Moon-Sun three-body system is thermodynamically "hot", full of "non-thermalized" energy. If Earth and Moon collided with the kinetic energy of their relative motion, they would melt. Instead, thermodynamic temperature exists rather independently at multiple scales. At the human scale of molecular heat, Earth and Moon are "cold to the touch", closer to absolute zero than not.

This "near-absolute-zero" state allows delicate effects like ENSO and QBO to exist. Once again a Quantum Analog applies, in this instance Analog Quantum Thermodynamics, where before we touched on Analog Quantum Chaos. Make no mistake, these analogs are mathematically equivalent to classical microscopic QM, even though we are careful to distinguish them physically. They do combine in symphonic grand synthesis.

We give up a provincial bias toward our own timescale (and space-scale) in the science here, embracing the geologic timescale of Plate Tectonics and cosmic timescale of Solar System formation, to better grasp what is going on. These alternative framings allow us to evaluate the Lunsolar Forcing hypothesis from added perspectives. One prediction of the thermodynamics is that Lunisolar tidal energy and ENSO-QBO energy mostly exist at different spacetime scales, and therefore interact weakly. This allows ENSO-QBO mostly do its own chaos thing, free of strong tidal forcing.

Here is WP's LaPlace Article citing well accepted modern science [Celletti et Perozzi 2007] 200yrs after the great man's time-

"It is now generally regarded that Laplace's methods on their own, though vital to the development of (orbital mechanics), are not sufficiently precise to demonstrate the stability of the Solar System, and indeed, the Solar System is understood to be chaotic, although it happens to be fairly stable."

Comment Source:PaulP: "substantiation that ENSO is not chaotic." Even a basic double-pendulum or the square-root of 2 decimal integer sequence is quite chaotic. Any complexity is inherently chaotic. ENSO is clearly multi-chaotic. How is the plate tectonics constraining ENSO not chaotic? Roaming crustal plates do not produce crystal-order. Another physics lens into Lunisolar ENSO-QBO is thermodynamics. The Earth-Moon-Sun three-body system is thermodynamically "hot", full of "non-thermalized" energy. If Earth and Moon collided with the kinetic energy of their relative motion, they would melt. Instead, thermodynamic temperature exists rather independently at multiple scales. At the human scale of molecular heat, Earth and Moon are "cold to the touch", closer to absolute zero than not. This "near-absolute-zero" state allows delicate effects like ENSO and QBO to exist. Once again a Quantum Analog applies, in this instance Analog Quantum Thermodynamics, where before we touched on Analog Quantum Chaos. Make no mistake, these analogs are mathematically equivalent to classical microscopic QM, even though we are careful to distinguish them physically. They do combine in symphonic grand synthesis. We give up a provincial bias toward our own timescale (and space-scale) in the science here, embracing the geologic timescale of Plate Tectonics and cosmic timescale of Solar System formation, to better grasp what is going on. These alternative framings allow us to evaluate the Lunsolar Forcing hypothesis from added perspectives. One prediction of the thermodynamics is that Lunisolar tidal energy and ENSO-QBO energy mostly exist at different spacetime scales, and therefore interact weakly. This allows ENSO-QBO mostly do its own chaos thing, free of strong tidal forcing. Here is WP's LaPlace Article citing well accepted modern science [Celletti et Perozzi 2007] 200yrs after the great man's time- "It is now generally regarded that Laplace's methods on their own, though vital to the development of (orbital mechanics), are not sufficiently precise to demonstrate the stability of the Solar System, and indeed, the Solar System is understood to be chaotic, although it happens to be fairly stable."
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588.

I don't think you understand the bad science that NOAA perpetrated by removing the annual signal from the ENSO time-series. It would be OK if they filtered the A=Annual portion of the time-series if it was composed as linearly independent factors $$f(t) = A + B$$

Yet, when a non-linear mechanism enters in the picture, such as $$f(t) = (A + B)^2$$

then by removing the A term (and its harmonics), it will leave the cross-term AB sitting by itself $$f(t) = A^2 + 2AB + B^2$$ but with no way to estimate what the missing causal term was.

No wonder that scientists have had a hard time deconvolving the behavior of time-series such as ENSO when they aren't given a complete starting data picture. When the filtered-out annual term is factored back in, one can easily see I guessed 100% dead-on what the missing deterministic forcing term was. As I said, this is further substantiation that ENSO is not chaotic, but rather non-linear deterministic.

As far solving Laplace's Tidal Equations in analytical terms, which creates the nonlinear but non-chaotic solution, the key ansatz that I applied was to create a partial derivative decomposition $$\frac{d \zeta}{d \phi} = \frac{d \zeta}{dt} \frac{dt}{d \phi}$$ that I then reinserted into the equations, resulting in an elegantly simple final formulation.

BTW, the physical reason that this works is because the greatest tidal force acts horizontally to the surface, and the partial derivative expansion captures that topological mechanism.

I have no idea why it took 200+ years for someone like me to come up with such an obvious (in hindsight) ansatz.

"It is now generally regarded that Laplace's methods on their own, though vital to the development of (orbital mechanics), are not sufficiently precise to demonstrate the stability of the Solar System, and indeed, the Solar System is understood to be chaotic, although it happens to be fairly stable."

... What's your point? It's stable on any time scale we would be interested in.

Keep at it, you may catch up at some point.

Comment Source:I don't think you understand the bad science that NOAA perpetrated by removing the annual signal from the ENSO time-series. It would be OK if they filtered the *A=Annual* portion of the time-series if it was composed as linearly independent factors $$f(t) = A + B$$ Yet, when a non-linear mechanism enters in the picture, such as $$f(t) = (A + B)^2$$ then by removing the *A* term (and its harmonics), it will leave the cross-term *AB* sitting by itself $$f(t) = A^2 + 2AB + B^2$$ but with no way to estimate what the missing causal term was. No wonder that scientists have had a hard time deconvolving the behavior of time-series such as ENSO when they aren't given a complete starting data picture. When the filtered-out annual term is factored back in, one can easily see I guessed 100% dead-on what the missing deterministic forcing term was. As I said, this is further substantiation that ENSO is not chaotic, but rather non-linear deterministic. As far solving Laplace's Tidal Equations in analytical terms, which creates the nonlinear but non-chaotic solution, the key *ansatz* that [I applied](https://imagizer.imageshack.com/img923/6538/yRorrd.png) was to create a partial derivative decomposition $$\frac{d \zeta}{d \phi} = \frac{d \zeta}{dt} \frac{dt}{d \phi}$$ that I then reinserted into the equations, resulting in an elegantly simple final formulation. BTW, the physical reason that this works is because the greatest tidal force acts horizontally to the surface, and the partial derivative expansion captures that topological mechanism. >>> ![](https://imagizer.imageshack.com/img924/5656/pgzegj.png) I have no idea why it took 200+ years for someone like me to come up with such an obvious (in hindsight) ansatz. > "It is now generally regarded that Laplace's methods on their own, though vital to the development of (orbital mechanics), are not sufficiently precise to demonstrate the stability of the Solar System, and indeed, the Solar System is understood to be chaotic, although it happens to be fairly stable." ... What's your point? It's stable on any time scale we would be interested in. Keep at it, you may catch up at some point. 
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589.
edited February 17

PaulP: "any time scale we would be interested in"

All time scales are scientifically interesting. You objected to lack of curiosity recently, only to now profess your own disinterest (?) ENSO was set up by plate tectonics and many other long period factors. Chaos occurs at all scales.

PaulP: "bad science that NOAA perpetrated by removing the annual signal from the ENSO time-series."

What reference for this bad science? NOAA has thousands of scientists and many models. NOAA can't be all "bad science" and "laughable ignorance" anymore than if you were unfairly dissed so.

PaulP: "ENSO is not chaotic, but rather non-linear deterministic"

ENSO is both; deterministic chaos is non-linear. You have your work cut out proving ENSO is not chaotic without knowing chaos science in depth.

You continue to ignore the need to quantify and filter-out real-time Lunisolar tidal noise in ENSO sensor array data. That's good science to "catch up at some point"; to accurately resolve ENSO Lunisolar Forcing versus ENSO Chaos.

Lets take a close look at NOAA's buoy networks, and the tidal noise they are subject to. Here is a start-

https://www.ndbc.noaa.gov/

Lets consider at your latest factor of interest- horizontal pull of Lunar Tide; specifically on an ENSO data-collection sea-buoy anchored several kilometers deep. Regardless of what wind and current otherwise does, the buoy will experience a definite tidal yanking captured by the multi-sensor data streams. This superposed yanking sequence will indeed encode Lunisolar cycle complexities. Here is part of the appearance in data of ENSO Tidal forcing and noise, but how much of which? I guess its mostly noise, but nobody knows for sure.

Comment Source:PaulP: "any time scale we would be interested in" All time scales are scientifically interesting. You objected to lack of curiosity recently, only to now profess your own disinterest (?) ENSO was set up by plate tectonics and many other long period factors. Chaos occurs at all scales. PaulP: "bad science that NOAA perpetrated by removing the annual signal from the ENSO time-series." What reference for this bad science? NOAA has thousands of scientists and many models. NOAA can't be all "bad science" and "laughable ignorance" anymore than if you were unfairly dissed so. PaulP: "ENSO is not chaotic, but rather non-linear deterministic" ENSO is both; deterministic chaos is non-linear. You have your work cut out proving ENSO is not chaotic without knowing chaos science in depth. You continue to ignore the need to quantify and filter-out real-time Lunisolar tidal noise in ENSO sensor array data. That's good science to "catch up at some point"; to accurately resolve ENSO Lunisolar Forcing versus ENSO Chaos. Lets take a close look at NOAA's buoy networks, and the tidal noise they are subject to. Here is a start- https://www.ndbc.noaa.gov/ Lets consider at your latest factor of interest- horizontal pull of Lunar Tide; specifically on an ENSO data-collection sea-buoy anchored several kilometers deep. Regardless of what wind and current otherwise does, the buoy will experience a definite tidal yanking captured by the multi-sensor data streams. This superposed yanking sequence will indeed encode Lunisolar cycle complexities. Here is part of the appearance in data of ENSO Tidal forcing and noise, but how much of which? I guess its mostly noise, but nobody knows for sure. Thanks for your patience addressing the loose ends. 
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590.

It's like this. In the following DiffEq profile, both the periodic impulse (LHS) and the response (RHS) is provided:

If you don't have the impulse and only have the response, one can try to guess what the impulse is. For ENSO, I had to guess what it is because the geniuses at NOAA filtered it out. No matter ... since when I added the filtered impulse back in (found as an analysis artifact in the "ensostuff" directory), it exactly matched my guess anyways.

The scientists at NASA JPL warn about doing this kind of thing. Perigaud et al have pointed out how reckless it is to remove what are considered errors (or nuisance parameters) in time-series by assuming that they relate to known tidal or seasonal factors and so can be safely filtered out and ignored.

" ... real-time Lunisolar tidal noise ... " "... and the tidal noise they are subject to ..."

"One man's noise is another man's signal", which was a well-known saying from the space program LOL

Comment Source:It's like this. In the following DiffEq profile, both the periodic impulse (LHS) and the response (RHS) is provided: ![](https://imagizer.imageshack.com/img922/3951/JDKHzz.png) If you don't have the impulse and only have the response, one can try to guess what the impulse is. For ENSO, I had to guess what it is because the geniuses at NOAA filtered it out. No matter ... since when I added the filtered impulse back in (found as an analysis artifact in the "ensostuff" directory), it *exactly* matched my guess anyways. The scientists at NASA JPL warn about doing this kind of thing. [Perigaud et al](https://archimer.ifremer.fr/doc/00101/21178/18795.pdf) have pointed out how reckless it is to remove what are considered errors (or nuisance parameters) in time-series by assuming that they relate to known tidal or seasonal factors and so can be safely filtered out and ignored. > " ... real-time Lunisolar tidal noise ... " "... and the tidal noise they are subject to ..." "One man's noise is another man's signal", which was a [well-known saying from the space program](https://en.wikipedia.org/wiki/Edward_Ng) LOL 
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591.
edited February 17

PaulP: "One man's noise is another man's signal"

MDL (male dominant language) is worse than too many CAPS. "One's noise is another's signal," is better. The science of signal and noise is only begun by quoting this truism.

Your choice of noise in the ENSO data case is all the squiggles in the data that do not fit your Lunisolar Forcing hypothesis. In deterministic chaos science, these are deterministic signals you have not identified. ENSO data from mid-ocean sea-buoys, with kilometers of anchor rode, in fact encode lunisolar noise that you are presume without rigorous diligence to only consist of ENSO forcing signals.

Of course NOAA filters noise, or puts it back in, as seen fit. To their credit, they identify both annual noise and signal in sensor data, where you seemingly can only see signal. Ideally, both signal and noise are accounted for. Only you seem adverse to identifying any tidal noise in ENSO sensor array data, as "marginalizing" to your thesis. Everyone else cited here, including NOAA and me, accepts BOTH Lunisolar Signal and Noise in geophysical data. Your thesis is not well-posed as an all-or-nothing question. Diligently identifying and filtering tidal noise from ENSO data will refine your results.

QBO Data seems to be mostly daily Sonde samplings (plus incidental volcano aerosols, and other clues). Atmospheric-Tide would therefore be a noise factor to the Sonde data, inviting misinterpretation as QBO forcing. Again, the Lunisolar signal is quite sharp semi-cancelling pulses (daily peaks and troughs), but the long period ENSO and QBO states are very fuzzy blobs. You claim these sharp events line up with the fuzzy states, with a precision that is not possible for blobs.

This is a fantastic interactive QBO data presentation-

https://acd-ext.gsfc.nasa.gov/Data_services/met/qbo/anim.html

It looks like there must hidden vertical convections that segment QBO, not just a monolithic ring over the equator. Sure enough, Jupiter QQO photos show discontinuities. The cross-equatorial line vortices assume a herring-bone pattern, with vortices anchored in adjoining circulation bands, just as I suggested early in my discussion here of QBO.

Comment Source:PaulP: "One man's noise is another man's signal" MDL (male dominant language) is worse than too many CAPS. "One's noise is another's signal," is better. The science of signal and noise is only begun by quoting this truism. Your choice of noise in the ENSO data case is all the squiggles in the data that do not fit your Lunisolar Forcing hypothesis. In deterministic chaos science, these are deterministic signals you have not identified. ENSO data from mid-ocean sea-buoys, with kilometers of anchor rode, in fact encode lunisolar noise that you are presume without rigorous diligence to only consist of ENSO forcing signals. Of course NOAA filters noise, or puts it back in, as seen fit. To their credit, they identify both annual noise and signal in sensor data, where you seemingly can only see signal. Ideally, both signal and noise are accounted for. Only you seem adverse to identifying any tidal noise in ENSO sensor array data, as "marginalizing" to your thesis. Everyone else cited here, including NOAA and me, accepts BOTH Lunisolar Signal and Noise in geophysical data. Your thesis is not well-posed as an all-or-nothing question. Diligently identifying and filtering tidal noise from ENSO data will refine your results. QBO Data seems to be mostly daily Sonde samplings (plus incidental volcano aerosols, and other clues). Atmospheric-Tide would therefore be a noise factor to the Sonde data, inviting misinterpretation as QBO forcing. Again, the Lunisolar signal is quite sharp semi-cancelling pulses (daily peaks and troughs), but the long period ENSO and QBO states are very fuzzy blobs. You claim these sharp events line up with the fuzzy states, with a precision that is not possible for blobs. This is a fantastic interactive QBO data presentation- https://acd-ext.gsfc.nasa.gov/Data_services/met/qbo/anim.html It looks like there must hidden vertical convections that segment QBO, not just a monolithic ring over the equator. Sure enough, Jupiter QQO photos show discontinuities. The cross-equatorial line vortices assume a herring-bone pattern, with vortices anchored in adjoining circulation bands, just as I suggested early in my discussion here of QBO. 
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592.
edited February 18

This is a fantastic interactive QBO data presentation-

https://acd-ext.gsfc.nasa.gov/Data_services/met/qbo/anim.html

No it's not. It only gives one the impression that they have control over the data. In this case, the interactive control makes it seem as if the movement is downward, as if the wind itself is sinking. Yet, that's just the definition of a traveling wave, which only means that there's a slight imbalance between the + and - solutions to a standing wave, with some of it due to a change in phase due to stratification properties of the stratosphere, like duh.

https://youtu.be/wGP65xm9jZs

The amount of "moment transfer" over time that this is implying may be so small as to be insignificant -- the "sinking" takes place over the course of a few years for wind that itself that has a fairly high speed -- yet they seem to enjoy making a huge deal about this. In other words, the reversing of direction of the QBO wind speed is the primary behavior and any variations in height are more to do with stratification properties such as density than anything else.

In fact, the only way to understand the data is by doing quantitative signal processing along with modeling the fluid dynamics via realistic forcing -- which is something that you just don't seem to get, instead opting for massive hand-waving.

Comment Source:> This is a fantastic interactive QBO data presentation- > https://acd-ext.gsfc.nasa.gov/Data_services/met/qbo/anim.html No it's not. It only gives one the impression that they have control over the data. In this case, the interactive control makes it seem as if the movement is downward, as if the wind itself is sinking. Yet, that's just the definition of a traveling wave, which only means that there's a slight imbalance between the + and - solutions to a standing wave, with some of it due to a change in phase due to stratification properties of the *stratosphere*, like duh. https://youtu.be/wGP65xm9jZs The amount of "moment transfer" over time that this is implying may be so small as to be insignificant -- the "sinking" takes place over the course of a few years for wind that itself that has a fairly high speed -- yet they seem to enjoy making a huge deal about this. In other words, the reversing of direction of the QBO wind speed is the primary behavior and any variations in height are more to do with stratification properties such as density than anything else. ![](https://imagizer.imageshack.com/img921/1654/dLwB8A.png) In fact, the only way to understand the data is by doing quantitative signal processing along with modeling the fluid dynamics via realistic forcing -- which is something that you just don't seem to get, instead opting for massive hand-waving. 
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593.
edited February 18

PaulP:"It only gives one the impression that they have control over the data. In this case, the interactive control makes it seem as if the movement is downward, as if the wind itself is sinking."

It did not seem that way to me nor, no doubt, to the scientists who created the presentation. Its a straw-man to suggest otherwise. If "control over the data" is what you claim to have, you must account for and filter Lunisolar Tidal Noise on the sensors. This is no mere "hand-waving" issue, but a specific figure-of-merit (the proposed "Pukite Number") to rigorously validate your ENSO-QBO Models over others.

Here is another specific prediction- That daily Tidal Noise, in the sense that its not a quasi-periodic long-period forcing, will show up in ENSO-jet velocity data. This excitation is akin to LLJ acceleration above a nocturnal surface inversion layer. The increasing number of testable predictions on offer here are thankfully not "massive hand-waving". Mainstream geophysical deterministic chaos science is not as bad as you make out.

Comment Source:PaulP:"It only gives one the impression that they have control over the data. In this case, the interactive control makes it seem as if the movement is downward, as if the wind itself is sinking." It did not seem that way to me nor, no doubt, to the scientists who created the presentation. Its a straw-man to suggest otherwise. If "control over the data" is what you claim to have, you must account for and filter Lunisolar Tidal Noise on the sensors. This is no mere "hand-waving" issue, but a specific figure-of-merit (the proposed "Pukite Number") to rigorously validate your ENSO-QBO Models over others. Here is another specific prediction- That daily Tidal Noise, in the sense that its not a quasi-periodic long-period forcing, will show up in ENSO-jet velocity data. This excitation is akin to LLJ acceleration above a nocturnal surface inversion layer. The increasing number of testable predictions on offer here are thankfully not "massive hand-waving". Mainstream geophysical deterministic chaos science is not as bad as you make out.
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594.

"That daily Tidal Noise"

It's not noise. It's the signal. It's the forcing, just like the daily or annual signal

See those sideband satellites highlighted in yellow about the daily harmonics (marked by red)? That's clearly a fortnightly tidal modulation.

" Mainstream geophysical deterministic chaos science is not as bad as you make out."

It's not that. They may be OK, but apparently not as proficient as me. This stuff is simple compared to 3-D inverse diffraction tomography.

Comment Source:> "That daily Tidal Noise" It's not noise. It's the signal. It's the forcing, just like the daily or annual signal ![](https://imagizer.imageshack.com/img923/4194/EP8Hq7.png) See those sideband satellites highlighted in yellow about the daily harmonics (marked by red)? That's clearly a fortnightly tidal modulation. ![](https://imagizer.imageshack.com/img924/1039/560kq5.png) > " Mainstream geophysical deterministic chaos science is not as bad as you make out." It's not that. They may be OK, but apparently not as proficient as me. This stuff is simple compared to 3-D inverse diffraction tomography.
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595.
edited February 18

ENSO-QBO themselves are not forced in real time by daily tides, but data-buoys and data-sondes are. This is noise with regard to your hypothesis. It can't be waved away.

Showing the tidal signal clearly in non-ENSO atmospheric data does not address ENSO forcing as such. Its a red herring if argued so. Obviously the High-Q Tidal Signal is degraded in actual ENSO data, whether we distinguish or not what part is signal or noise.

Mainstream geoscience is hardly, " not as proficient as (You)". Take 100,000 geoscientists; even if each was only 1% as proficient as you, that community would still be 1000x more proficient in aggregate.

Its unphysical to claim ENSO sensor data is pure tidal signal and no tidal noise. You know this, as a proficient scientist.

The Pukite Number is essentially a Lunisolar Tidal Signal to Noise Ratio in geophysical sensor data, with Noise >0.

Comment Source:ENSO-QBO themselves are not forced in real time by daily tides, but data-buoys and data-sondes are. This is noise with regard to your hypothesis. It can't be waved away. Showing the tidal signal clearly in non-ENSO atmospheric data does not address ENSO forcing as such. Its a red herring if argued so. Obviously the High-Q Tidal Signal is degraded in actual ENSO data, whether we distinguish or not what part is signal or noise. Mainstream geoscience is hardly, " not as proficient as (You)". Take 100,000 geoscientists; even if each was only 1% as proficient as you, that community would still be 1000x more proficient in aggregate. Its unphysical to claim ENSO sensor data is pure tidal signal and no tidal noise. You know this, as a proficient scientist. The Pukite Number is essentially a Lunisolar Tidal Signal to Noise Ratio in geophysical sensor data, with Noise >0.
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596.

"ENSO-QBO themselves are not forced in real time by daily tides, but data-buoys and data-sondes are. This is noise with regard to your hypothesis. It can't be waved away."

woah. ENSO is not always measured at sea as a temperature, but can be measured as an atmospheric pressure, referred to as the SOI. The QBO wind can get to 60 MPH, and that's essentially what the radiosonde is picking up. Cool if the lunar gravitational force is battering the radiosonde around to that degree, but I really doubt it.

".... that community would still be 1000x more proficient in aggregate."

Yes, one would think that. So why even try? :-/

Comment Source:> "ENSO-QBO themselves are not forced in real time by daily tides, but data-buoys and data-sondes are. This is noise with regard to your hypothesis. It can't be waved away." woah. ENSO is not always measured at sea as a temperature, but can be measured as an atmospheric pressure, referred to as the SOI. The QBO wind can get to 60 MPH, and that's essentially what the radiosonde is picking up. Cool if the lunar gravitational force is battering the radiosonde around to that degree, but I really doubt it. > ".... that community would still be 1000x more proficient in aggregate." Yes, one would think that. So why even try? :-/ 
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597.
edited February 19

ENSO is measured many ways; including current, wind, atmospheric-pressure, sea-surface height, and sea and air temperature. Lunisolar tidal noise is predicted here in all of these data sets, as well as weak long-period harmonic forcings buried in the chaos. Its not all noise nor all signal. Its a ratio to properly quantify.

Again, Jupiter QQO strongly suggests Earth QBO would blow even if there was no Moon. Its not the Moon that drives QBO, but mostly Vertical Coriolis with an aeroelastic spring-mass dynamic (clock balance-wheel analogy). Atmospheric Tides therefore modulate QBO velocity a bit, and thus Lunisolar noise shows up in real-time QBO sonde data.

That's several predictions for geoscience to confirm or falsify.

Comment Source:ENSO is measured many ways; including current, wind, atmospheric-pressure, sea-surface height, and sea and air temperature. Lunisolar tidal noise is predicted here in all of these data sets, as well as weak long-period harmonic forcings buried in the chaos. Its not all noise nor all signal. Its a ratio to properly quantify. Again, Jupiter QQO strongly suggests Earth QBO would blow even if there was no Moon. Its not the Moon that drives QBO, but mostly Vertical Coriolis with an aeroelastic spring-mass dynamic (clock balance-wheel analogy). Atmospheric Tides therefore modulate QBO velocity a bit, and thus Lunisolar noise shows up in real-time QBO sonde data. That's several predictions for geoscience to confirm or falsify.
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598.

What's your infatuation with Jupiter QQO? Show that it has nothing to do with Jupiter's moons. Shouldn't be difficult given your certainty.

Comment Source:What's your infatuation with Jupiter QQO? Show that it has nothing to do with Jupiter's moons. Shouldn't be difficult given your certainty.
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599.
edited February 19

"Strongly suggests" should not be confused with "certainty" by a sloppy reading. Indeed, its not hard to repeat the QQO explanation already on the table.

Jupiter's moons are comparatively tiny compared to its mass, and numerous compared to our Moon. So any tidal forcing would be even smaller and less coherent. "Show (QQO) has nothing to do with Jupiter's moons," is again a red herring demand. There will always be >0 effect between masses, even if quite insignificant as tidal forcing or excitation.

Geophysical "infatuation" (curiosity) with QQO case is in large part for its direct mapping to QBO case, for comparison's sake (Case-Based Reasoning (CBR)). As noted before, geophysical similarity cases are reasoned over like natural Controlled Experiments.

QQO literature typically invokes QBO for direct comparison, as you surely understand as rational. Vertical Coriolis, and related dynamics, are sufficient basis for a hypothesis that a modified ENSO-QBO would prevail even without the Moon. For all we know, such Moonless theoretic ENSO-QBO cases might even be less chaotic.

Comment Source:"Strongly suggests" should not be confused with "certainty" by a sloppy reading. Indeed, its not hard to repeat the QQO explanation already on the table. Jupiter's moons are comparatively tiny compared to its mass, and numerous compared to our Moon. So any tidal forcing would be even smaller and less coherent. "Show (QQO) has nothing to do with Jupiter's moons," is again a red herring demand. There will always be >0 effect between masses, even if quite insignificant as tidal forcing or excitation. Geophysical "infatuation" (curiosity) with QQO case is in large part for its direct mapping to QBO case, for comparison's sake (Case-Based Reasoning (CBR)). As noted before, geophysical similarity cases are reasoned over like natural Controlled Experiments. QQO literature typically invokes QBO for direct comparison, as you surely understand as rational. Vertical Coriolis, and related dynamics, are sufficient basis for a hypothesis that a modified ENSO-QBO would prevail even without the Moon. For all we know, such Moonless theoretic ENSO-QBO cases might even be less chaotic.
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600.

This discussion is delusional in terms of not seeing the obvious. A little upthread, I displayed this chart of the QBO winds in the context of adjacent stratospheric winds.

Directly above the QBO in altitude lies the SAO winds of the upper stratosphere. Not surprisingly given the acronym, these are Semi-Annual Oscillations in wind speed whereby the wind reverses twice each year, which means either the sun passing nodally over the equator is the trigger for reversal, or it could be that the trigger is the sun at its maximal absolute declination to the equatorial plane. So whatever the detailed mechanism of the trigger is, it's certainly not some resonant behavior caused by a "aeroelastic spring-mass dynamic" as you suggest. Rather, it's obviously an orbital trigger -- which is obvious in the sense that you wouldn't be able to show even a slight long-term divergence from a semi-annual synchronization, if you wanted to try to debunk the model.

Thus the QBO is just the SAO with the added trigger of the lunar nodal cycle becoming stronger for the higher air density at lower altitudes. Taken together, the two models are both plausible and parsimonious.

I could argue this extremely quantitative model until the cows came home and it still won't become accepted because it apparently diverges from the script that climate researchers must follow, which is to assertively ascribe a resonant mechanism to a behavior and never mention a lunar mechanism (perhaps so as not to embarrass colleagues?)

Comment Source:This discussion is delusional in terms of not seeing the obvious. A little upthread, I displayed this chart of the QBO winds in the context of adjacent stratospheric winds. ![](https://imagizer.imageshack.com/img921/1654/dLwB8A.png) Directly above the QBO in altitude lies the SAO winds of the upper stratosphere. Not surprisingly given the acronym, these are **S**emi-**A**nnual **O**scillations in wind speed whereby the wind reverses *twice* each year, which means either the sun passing nodally over the equator is the trigger for reversal, or it could be that the trigger is the sun at its maximal absolute declination to the equatorial plane. So whatever the detailed mechanism of the trigger is, it's **certainly** not some resonant behavior caused by a "aeroelastic spring-mass dynamic" as you suggest. Rather, it's obviously an orbital trigger -- which is obvious in the sense that you wouldn't be able to show even a slight long-term divergence from a semi-annual synchronization, if you wanted to try to debunk the model. Thus the QBO is just the SAO with the added trigger of the lunar nodal cycle becoming stronger for the higher air density at lower altitudes. Taken together, the two models are both plausible and parsimonious. I could argue this **extremely** quantitative model until the cows came home and it still won't become accepted because it apparently diverges from the script that climate researchers must follow, which is to assertively ascribe a resonant mechanism to a behavior and never mention a lunar mechanism (perhaps so as not to embarrass colleagues?) 
This discussion has been closed.