The Power of Darwin

Using the LTE model on the NINO4 ENSO time-series, I excluded the interval between 1870-1875 for cross-validation. The fit below is from scratch on a dLOD-calibrated initial forcing, then allowing the values to vary slightly but the dLOD remains at 0.9999668 of the initial calibration.

The cross-validation doesn’t look good and actually is anti-correlated to a CC = -0.5 over that interval. But the region before 1875 appears suspiciously flat in any case, see the data on the KNMI site — it’s only a certainty that the El Nino peak at 1877-1878 is real and not estimated.

So, the next step is to take the fit to NINO4 and apply it to the Darwin (SOI) time-series, applying the same fitting interval from 1875-present. Immediately, it captures the 3 positive excursions in the interval 1870 to 1875. And then letting the fit proceed to a high CC, the result is shown below:

The resultant fit in the excluded cross-validation region reaches 0.58, thus reversing the anti-correlation and confirming that the NINO4 time-series data prior to 1875 is likely incorrect.

The fit data is at https://gist.github.com/pukpr/c26f1da00337e92dbb47671ca48af2cf?permalink_comment_id=4639783#gistcomment-4639783. The main modifications to tidal factors are in the very long periods — these values start small due to the dLOD calibration (the differential filters out low frequencies) but the 4.42 year amplitude is nearly tripled after the fit, the 8.85 & 9.3 year up by 50%. The 18.6 year is only up 14%, and the 3rd order 6 year and 15.9 year are down 63% and up 45% respectively. All the fortnightly and monthly values are stable. This is perhaps reasonable considering how much the LOD drifts over time at low frequency, and that the calibration is restricted to post-1962.

Heuristics

In the book Mathematical GeoEnergy, I mention the word heuristic or heuristics 82 times. In scientific research, it’s an important signpost because it identifies where a physical understanding is lacking, which is the point I was trying to make in a recent online discussion.

In the preface, I specifically cite the sunspot cycle as a heuristic, which I commented on:

For example, the 11 -year sunspot cycle is considered a heuristic but not the annual or daily cycles, which are trivially explained. Tried to get ChatGPT to agree with me:
https://chat.openai.com/share/2706730c-2767-4060-b65e-08549b538d0e

chatGPT is correct.

whats your problem

I responded with two examples of heuristics that can conceivably be replaced by plausible and parsimonious physics.

Chandler wobble.

Heuristic: The wobble is approximately 433 days, thought to be excited by fluctuations of mass on Earth achieving a natural resonance condition.
Physics: The wobble of precisely 433 days is a frequency side-band of the lunar draconic cycle interacting with the annual cycle. Not resonant just as the annual wobble is not resonant, and due to a forced angular momentum response.

QBO.

Heuristic: The oscillation is approximately 2+ years, thus the name “quasi-biennial”, thought to be excited by atmospheric waves.
Physics: The oscillation of 2.37 years period follows from the semi-annual oscillation at higher altitudes locked to the longer period by the lunar tidal forcing at lower altitudes of the stratosphere. The cycle is commensurate with simultaneous nodal crossings of both the moon and sun across the ecliptic plane.

In both these cases, the heuristic could be discarded and the description of the behaviors updated. Another example may be Milankovitch cycles, which replaces the heuristic of glacial cycles with a plausible physical mechanism that matches the observations. Whether Chandler, QBO, or Milankovitch will stand the test of time is another question, but these new models aren’t considered heuristics because they predict precise values for the observations. Discovering replacements for heuristics are rare nowadays as most of the heuristics (such as ocean tidal cycles) were resolved long ago. Circadian rhythms were a heuristic replaced by an encoded mechanism 20-30 years ago. Explaining predator-prey population cycles are at the heuristic stage still, IMO and may not get resolved as humans modify the environment.

The suggestion is that an unresolved heuristic is always a good candidate for a thesis topic.

NEW

Discussing relatively recent discoveries that replaced a heuristic, one that also came up is the Quantum Hall Effect. This is a subtle one because although the effect was experimentally discovered by von Klitzing, a Japanese team did roughly predict it a few years earlier, but added a caveat that they did not believe their own calculations! They also did not predict the quantization was in exact integer multiples. So that remained a heuristic for only a short time until it was physically explained (I remember giving a talk on this derivation for my solid-state physics class, which the instructor was very happy about). But then the experimental discovery of a fractional Quantum Hall Effect occurred, which apparently is still a heuristic because a strong consensus has yet to emerge on the physics behind it. Over the years, there have been at least 3 Nobel Prizes shared among 7 physicists to topological QHE research.

I bring this up because there’s a recent Quanta Magazine article dated July 18 titled “How Quantum Physicists Explained Earth’s Oscillating Weather Patterns” which describes how the QHE math can be conceivably applied to making predictions for equatorial patterns, and thus removing at least some of the heuristic nature. Geoffrey Vallis, who is an expert on geophysical fluid dynamics, is quoted in the article saying that the new result is a significant advance that will provide a “foundational understanding” of Earth’s fluid systems. The intriguing aspect is that this did not require the periodic order of a lattice — quoting from the article:

“I was surprised to see that topology could be defined in fluid systems without periodic order,” said Anton Souslov, a theoretical physicist at the University of Bath

Curry has a tweet on this, a reply tweet here because I am blocked

The Big 10 Climate Indices

The above diagram courtesy of Karnauskus

These correspond to the geographically defined climate indices

Overall I’m confident with the status of the published analysis of Laplace’s Tidal Equations in Mathematical Geoenergy, as I can model each of these climate indices with precisely the same (save one ***) tidal forcing, all calibrated by LOD. The following Threads allow interested people to contribute thoughts

  1. ENSO – https://www.threads.net/@paulpukite/post/CuWS8MFu8Jc
  2. AMO – https://www.threads.net/@paulpukite/post/Cuh4krjJTLN
  3. PDO – https://www.threads.net/@paulpukite/post/Cuu0VCypIi5
  4. QBO – https://www.threads.net/@paulpukite/post/CuiKQ5tsXCQ
  5. SOI (Darwin & Tahiti) – https://www.threads.net/@paulpukite/post/Cuu2IkBJh55 => MJO
  6. IOD (East & West) – https://www.threads.net/@paulpukite/post/Cuu9PYvJAG2
  7. PNA – https://www.threads.net/@paulpukite/post/CuvAVR7JN7R
  8. AO – https://www.threads.net/@paulpukite/post/CuvEz37JPFV
  9. SAM – https://www.threads.net/@paulpukite/post/CuvLZ2CMt1X
  10. NAO – https://www.threads.net/@paulpukite/post/CuvNnwns2la

(*** The odd-one out is QBO, which is a global longitudinally-invariant behavior, which means that only a couple of tidal factors are important.)

Is the utility of this LTE modeling a groundbreaking achievement? => https://www.threads.net/@paulpukite/post/CuvNnwns2la