My thanks to talkshop contributor and PRP author R.J. Salvador for sending me an updated prediction for changes in LOD during 2016. This plot has been produced using R.J.s model, which has been developed using the planetary periodicities we have been working on here at the talkshop over the last few years.
R.J. has kindly agreed to send a monthly update showing the progress of the model output against IERS observations as the year progresses. This is real science in progress. Creating a hypothesis, building a model, and testing it against reality.
So far as we know, apart from the model built by talkshoppers Paul Vaughan and Tim Channon a while ago, no-one else in the world has a detailed model predicting LOD.
This is cutting edge science in realtime. If this prediction succeeds, it’s a strong indication we are onto some of the planetary periodicities which affect the Sun’s variation and Earth’s climate as well as its orientation parameters.
Tallbloke's Talkshop 
This is the sort of competition R.J. is up against in the mainstream
http://www.gfz-potsdam.de/en/section/earths-magnetic-field/topics/sources-of-the-earths-magnetic-field/core-field/prediction-of-the-decadal-change-of-length-of-day/
“So far as we know, apart from the model built by talkshoppers Paul Vaughan and Tim Channon a while ago, no-one else in the world has a detailed model predicting LOD.”
As I’ve said many times, that stuff was widely known before Tim & I ever looked at it. For example you can see the exact same periods listed in Gross (2007) (along with dozens of others in a far more detailed model). Everyone working in EOP (earth orientation parameters) knows that stuff.
I was looking at the stuff trying to understand unsound false judgements of the solar-terrestrial weave and solar cycle deceleration. I concluded it was due to deliberate (politically motivated) methodological narrow-mindedness (to deceitfully engineer false public optics). The door was shut on those people long ago. They’re untrustworthy and they will be corrected by Asians with intelligence far superior to theirs. The correction that’s coming for that level of hubris is going to be a schooling in humility that goes to levels and dimensions far above and beyond the mere discussion of climate. The matter is now out of our hands.
For the record:
From 1962 to 2015.857 for all the days
Standard error of estimate = 0.000222644
Average deviation = 0.000176546
Maximum deviation for any observation = 0.00109157
in seconds.
Paul V: Everyone working in EOP (earth orientation parameters) knows that stuff.
I can’t find their predictions online. Got a link?
For example, there is this in the Gross 2007 paper Paul refers to:
But where are the updated plots showing how these models have performed since they were published?
Here’s R.J.s plot for 1962-2015
If they’ve got the “exact same periods”, they don’t seem to be getting the exact same results.
The terms Tim & I included in the minimalist model (not to be confused with what R J is doing) were just the ones listed with the highest weightings in Gross (2007):
Click to access Gross_Geodesy_LpER07.pdf
It wasn’t a new discovery. It was a reproduction of what has been extremely well-known for decades.
The only reason that concise backbone model was presented was to provide the audience with background in the hopes that it would enable them to understand something more advanced.
Context: The goal wasn’t to model LOD, but rather to map out, explore, and understand the adamant distortion artistry I was encountering on decadal volatility in semi-annual LOD. By definition global-width Fourier methods can’t deal with that stuff, so of course I was able to diagnose the distortion agency conclusively.
R J’s work and the Figure 4 models on your illustration are both different entirely, so perhaps we’ve had a miscommunication.
Tim did look at the decadal terms on his own. I’ll leave commentary on that to others.
The time-only decadal models may go along fine at times, but keep in mind that to be fully trustable models in the longer term they need to be spatiotemporal. Until the geometry is understood and accurately represented in models, modelers can expect catastrophic failures where their predictions do things like go anti-phase. This is already known conclusively from the multivariate record, as I stressed near the end of ERSST EOF 1234. It’s still instructive form an exploratory perspective to purse time-only models, as learning about the limitations and phase shifts (e.g. Panama Canal timing as I’ve illustrated elsewhere) informs crucially and inspires the exploration of geometry.
As that great baseball player said, “It’s hard to make predictions, especially about the future”
Paul says “The only reason that concise backbone model was presented was to provide the audience with background in the hopes that it would enable them to understand something more advanced.”
Yes, we know this model will fail. It will fail because work on solar sunspots data suggests we are probably dealing with a geared clockworks. A geared clockworks is not built into this model. But the hope is that the spatiotemperal change is slow enough to gain some insight as to whether the backbone choice is correct.
R.J. Regardless of amplitude or longer term trend, how closely does a long hindcast of your model get the timings of multi-decadal reversals to the Gross 2001 ‘observations’ curve in fig 4 above?
TB. This is a comparison of Gross and the Gas Giant back bone hind cast to 1890.
On the optimistic side this model could track for about 100 years.
Thanks R.J.
I’ve taken the liberty of scaling the plots to match timescales and added some lines in red to think about. Maybe there’s an extra modulation we’re missing, unless the Gross and other obs reconstructions are somehow time-distorted? Can anyone remember the longer term envelope of variation in the Chandler wobble?
My Z-axis version is time lagged, but not distorted in the same way.
It’s almost as if we need to somehow integrate R.J’s X-Y based jovian periods with my Z-axis approach to get the best fit. Thinking about mechanism for a moment, it does seem easier to conceive of a gyroscopic effect on LOD from the Giants via their Z positions above and below Earth’s orbital plane, where they can spend years/decades, rather than from their X-Y positions, where Earth meets them all near annually.
Opinions?
Just so we are all on the same page notice that Gross plotted his data in reverse order and so did I to make a comparison. I got the plot from wuwt. A longer term plot of the historical data to 1833 not reversed is here but I don’t know if this is by Gross.
Point of clarification:
That quote was about the work Tim & I did, not about R J’s work. (Lots of misunderstandings unfortunately…)
Let me try again…
What I’m trying to get at is what Bill Illis cautions about — e.g. Drake Passage opening Antarctic circumpolar current, Isthmus of Panama closure, Florida current off/on switch with sea level to change Gulf Stream pumping to arctic, Fram Strait ice export, etc.
Once again here’s a classic lesson Bill Illis gave us on geography & flow:
The circulatory topology changes. It does that on FAST timescales too and so you get these relations that in the extreme look like this…
…but the example I had in mind when I wrote above was:
One of my favorites is the way the polar motion group wave amplitude reverses its phase relationship with IPO (interdecadal pacific oscillation) in the early 1960s. It’s a clean phase reversal. I illustrated that in ERSST EOF 1234 and I’m still waiting for people to get real about what it implies. There’s no need to react to such observation as if it’s a threat. It tells us something really simple about the FLOW geometry. This is about knotted circulatory topology and the shifting of braiding patterns over time. You don’t have to limit perspective to the atmosphere and/or ocean currents; there’s also what’s going on under the crust.
An important piece of work will be for someone thorough and careful to CATALOG ALL examples of flows that can change or have changed to stick in different configurations that have SERIOUS effects. These really are tipping points. The system goes over a hill into another basin of attraction. That’s what Bill Illis is showing. It happens at other scales. And the bounds on aggregation is an area of deep ignorance in climate science. For example they have nothing like the “lower bounds” in mathematical statistics. One of my favorites is Chebyshev’s inequality:
“The inequality has great utility because it can be applied to completely arbitrary distributions (unknown except for mean and variance). For example, it can be used to prove the weak law of large numbers.” — https://en.wikipedia.org/wiki/Chebyshev's_inequality
That’s why climate enthusiasts show ZERO appreciation for volatility envelopes. (I think the majority of them don’t even know what that is. I’m not trying to put them down. Rather I’m pointing out that it’s one of many communication obstacles.)
There are at least 2 layers to this:
the changing braided circulatory topology (at times changing in discrete steps)
and
aggregation bounds.
I hope this comment won’t be misunderstood as somehow being about R J’s model specifically. It’s about a more general class of exploratory challenges that never gets discussed sensibly by climate enthusiasts.
There’s no reason to always assume 1:1 correspondence. The coupling and shifting geometry may mean many:1. And why wouldn’t it? One can think of endless examples just from watching the smoke coming off of a cigarette …but if one lets the smoke go up a tube, THEN THERE ARE BOUNDS on smoke pattern. What if the tube is invisible to the observer (e.g. jet stream in the sky, mantle flow beneath, Antarctic Circumpolar Current, etc.)? What if the tubes braid and the braiding pattern changes with seasons, Milankovitch, etc?
Some of the aggregate structures are well-bounded and we needn’t limit our attention to means; we can explore limits on variance. Why so many limit focus to the mean I’ve never understood. Where the variance supplies an easier constraint to isolate, this can be exploited to simplify other puzzle pieces. I don’t think many people sufficiently appreciate the power of aggregates to constrain sets.
Maybe that’s enough to get across at least Bill Illis’ main point about circulatory topology flipping aggregate switches.
Please keep exploring and sharing models R J.
Cheers
Btw the 13.68 number has come up 4 more times in the past 1 day alone as I further exploration of both the geometry & observations.
RJ: That looks like the Gross reconstruction reversed.
Paul: good points well taken. I’m not sure what difference the Panama canal would make to flow though, since it has locks at both ends.
Here’s Gross LOD vs Sun relative to SSB in Z-axis with no lag, no detrending, smoothed at 20y ~J-S.
The amplitude doesn’t say much but the phase coherence isn’t too bad.
TB wrote: “Paul: good points well taken. I’m not sure what difference the Panama canal would make to flow though, since it has locks at both ends.”
Spatial aliasing.
The sampling regime changed.
The ships were crossing the ENSO butterfly on different paths with different frequencies (mid-pacific to central america rather than antarctic circumpolar current (southern ocean).
Aggregation aggregation aggregation…
TB: If this model can forecast for 5 years that would be amazing. We will see if it can do just one year. I liked your post of Fenyman describing the scientific method. This model is an example, a wild ass guess. Without phase modulation it will drift off but how soon? Fun eh!
What you record depends on what you sample and how you aggregate.
The difference can be day & night.
Falling victim to nature’s mirror tricks is the answer to none of our quests.
Here’s another example of a mirror trick in the record right where there was a harsh change to the sampling regime:
This one is my favorite. Look what happens exactly coincident with a MAJOR change to the sampling regime:
NASA JPL STILL has not answered my question about that. The question was intended as a deliberate challenge to provoke clearer thinking about aggregation.
Frankly I think people are being TOTALLY ridiculous about aggregation.
I can’t understand why people JUST ASSUME the same thing is always being recorded. If you sample and aggregate DIFFERENTLY beginning at some point, you’re measuring SOMETHING DIFFERENT.
Why do people pretend it’s the same thing?
To me this indicates an intellectual deficiency and at some point in time this needs to be confronted squarely because what is gained by being timid about pointing it out? Nothing. On the contrary, just forever is getting wasted in discussion BASED ON FALSE ASSUMPTIONS ABOUT AGGREGATION.
It appears it is my role to be the one hated for pointing it out. I have more insights on this that I’ve never shared. I’ve never bothered because it’s just so clear that the community is loathed to go that level philosophically.
If people start showing a more open mind about sampling and aggregation, I’ll prepare a graphic that should open some eyes. It has implications for the NOAA ERSSTv4 controversy. I haven’t bothered because people are being so incredibly (reprehensibly) obtuse about that so just why bother? sort of thing…
…but I’ll be watching for a shift towards the more open-mindedness TB wisely promotes. If I see a shift towards Eastern-Style open-mindedness, you can be sure I’ll share the graphic that will make people stop and go “oh! sh*t …we didn’t notice that”… But will Lamar Smith understand? I doubt it…
Before we even consider going there let me put forward a black-&-white question that’s sure to provoke in the right direction philosophically.
First, context:
MAJOR sampling regime changes occurred in 1900 & 1962.
The question:
Which of the 2 thick curves (BLUE OR RED) are we supposed to model?
Both sample the SAME thing IN DIFFERENT WAYS.
Each will give a different model …so which is the right model? …and what if you model one of the curves in ignorance of the other curve? …with it’s phase reversal after 1962 & amplitude shift before 1900.
Like I say, I’ve got another graph on this aggregation issue that will open up a very serious can of worms. It actually makes me doubt whether IPO even exists. It has MAJOR implications for ENSO modeling. It may make anyone trying model ENSO pause for painful sober reflection to ask “OMG, what have I even been doing? Is it possible that I’ve been chasing aliasing? modeling changes to the sampling regime rather than something physical?!!… OMG I feel sick that I’ve wasted so much time on this…” It could be very depressing for some people when they realize… There’s a reason I’ve never spent more than a few minutes at a time on ENSO modeling.
Let’s start with deliberately provocative dichotomy:
Blue or red?
i.e. which of the blue & red curves is the one that should be modeled? And if you get a different model for each of the 2 curves, what does that tell you about the sampling? about the physics? about variance aliasing into mean estimates? about your ignorance? about your conceptualization of what you’ve measured? and what you’re doing? and whether you can possibly succeed if you don’t learn a lesson about mirroring of nature’s braids… etc.
I have an upsetting graphic prepared. But before sharing I want to know:
Blue or red?
Cheers!
PV says: ‘Btw the 13.68 number has come up 4 more times in the past 1 day alone as I further exploration of both the geometry & observations’
J+S x phi = 13.68233y
13 x 13.68233y = 177.8703y
15 Jupiter = 177.939y
21 x J+S = 177.579y
6 Saturn is about one year less, 9 J-S about one year more.
Paul, no doubt that the validity of continuity of certain data sets is highly questionable given when, where and how they were collected. It’s hard to imagine that data taken in the middle of the pacific ocean in 1890 and the vast expanses of Russia in the time of the Tsar can considered to be representative of only one continuous process with data taken in New York and London in 2015. I take your point that there are many processes going on at the same time and what phase one takes the data for one process may not and probably does not match another over the large expanse of the earth’s surface and time. The certainty with which some speak of their findings based on such data is astounding. (IPCC)
We, who are more humble in the face of nature, need to believe that what we do is like building a cathedral in the year 1200, knowing it will not be done in our life time and many life times to come. But even if we only carried blocks to the site we may have helped.
R J, I believe it’s possible to nail the braided coupling in the here & now. The symmetry is cross-dimensional in aggregate and that is a profound simple point that’s slow to register for many. That’s why as you point out it’s more important to enjoy the process of exploration. Best Regards!
The establishment needs to be able to clearly explain the amplitude and phase difference between the blue & red curves in order to earn sufficient trust to be taken seriously on climate. Similarly, full disclosure on the exact nature of the ~1930 Chandler Wobble phase reversal is a prerequisite for trust. Sincerely.
Just imagine the model R J would come up with (perhaps including phase modulation) if even more detailed top-notch data (say faster than hourly) went back to 1750.
Maybe we could instantly solve topological aggregate flow puzzles with such insights.
Seeing what time-alone can model is a useful aid in identifying what’s tied to trivial factors like spatial asymmetry. I welcome ongoing contributions.
I sure hope some careful, patient, thorough researcher(s) pursue(s) the flow-switch cataloging exercise I outlined above. Such a catalog would be powerful enough to erode mainstream misconceptions and efficiently focus bright minds on a helpfully concise statement of the flow geometry puzzle.
R J, have you tried modeling earth orientation parameters multivariately?
For example I chose to put Panama Canal on that graph to provoke attention to sampling regime changes with shipping route changes, but of course I was thinking about The Chandler Wobble Phase Reversal (…and solar cycle length differintegral).
Have you explored non-sinusoidal phase modulations?
PV: I have looked at some response surfaces but no, I have not looked at earth orientation parameters or looked at non-sinusoidal phase modulation.
What I’m thinking of is insights that might be gained by modeling polar motion & LOD jointly. With sufficient inclination one could extend the modeling to include nutation in obliquity & longitude residuals. This would force attention onto the geometric roots of the phase relation shifts.
I suspect the roots are really simple. I would expect for example NASA JPL experts to fully understand the geometric roots of the phase relations shifts. The fact that with all the talent they have they don’t suggests an important deficiency of human intellectual capacity.
Of course another possibility is that it’s classified information because of defense applications in intercontinental ballistic navigation & guidance (or nuclear submarine stealth or whatever) and the nuclear threat to the security of human civilization. My thinking goes like this: How could they not know? With all of their background knowledge and how clean the phase reversals are: how could they possibly not be able to figure it out?
The important thing to realize is that if they have to keep it classified then they can never make a convincing argument about climate. If they could reveal what they know, it would establish their superiority clearly and therefore earn and warrant public trust. However, if they must not, then there is no basis for trust but rather only basis for suspecting secrecy &/or incompetence.
It may be that if they must defend security then they must sacrifice trustworthiness on climate. This policy of trying to force the populace to believe experts who apparently can’t even explain a simple phase reversal is based on malice. It must be frustrating for them facing such unintended consequences. Surely they must realize that long-term maintenance of such strategy is untenable.
Thanks for helping shine a light. Fear of enlightenment may not be in the best interest of everyone.
If they can’t whether due to intellectual deficiency or secrecy explain these simple phase reversals, then we have no sensible reason to believe they are sufficiently expert to grasp simple climate geometry & aggregation. The optics are that they can’t tell right-side-up from upside-down even though they are supposedly the experts. That isn’t sufficiently reassuring. The appearance is that they either don’t know or can’t say something simple & important about climate.
I don’t see any reason to blindly assume the administration is acting in the best interest of our well-being, as no basis has been established for such trust. Quite the contrary.
The challenge I would put forward to the admins controlling the researchers: Prioritize letting them explain the geometric roots of the phase reversals or alternatively accept that you’ll never have a basis for public trust on climate and cease the malicious campaign being waged to control public thought without having established the most basic prerequisites for moral authority.
This an update of the actual LOD from December 1st 2015 to March 1st 2016 compared to the Models prediction
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