I’m looking at side-band variants of the lunisolar orbital forcing because that’s where the data is empirically taking us. I had originally proposed solving Laplace’s Tidal Equations (LTE) using a novel analytical derivation published several years ago (see Mathematical Geoenergy, Wiley/AG, 2019). The takeaway from the math results — given that LTEs form the primitive basis of the GCM-specific shallow-water approximation to oceanic fluid dynamics — was that my solution involved a specific type of non-linear modulation or amplification of the input tidal. However, this isn’t the typical diurnal/semi-diurnal tidal forcing, but because of the slower inertial response of the ocean volume, the targeted tidal cycles are the longer period monthly and annual. Moreover, as very few climate scientists are proficient at signal processing and all the details of aliasing and side-bands, this is an aspect that has remained hidden (again thank Richard Lindzen for opening the book on tidal influences and then slamming it shut for decades).
Continue readingAMO
Bay of Fundy subbands
With the recent total solar eclipse, it revived lots of thought of Earth’s ecliptic plane. In terms of forcing, having the Moon temporarily in the ecliptic plane and also blocking the sun is not only a rare and (to some people) an exciting event, it’s also an extreme regime wrt to the Earth as the combined reinforcement is maximized.
In fact this is not just any tidal forcing — rather it’s in the class of tidal forcing that has been overlooked over time in preference to the conventional diurnal tides. As many of those that tracked the eclipse as it traced a path from Texas to Nova Scotia, they may have noted that the moon covers lots of ground in a day. But that’s mainly because of the earth’s rotation. To remove that rotation and isolate the mean orbital path is tricky. And that’s the time-span duration where long-period tidal effects and inertial motion can build up and show extremes in sea-level change. Consider the 4.53 year extreme tidal cycle observed at the Bay of Fundy (see Desplanque et al) located in Nova Scotia. This is predicted if the long-period lunar perigee anomaly (27.554 days and the 8.85 absidal precessional return cycle) amplifies the long period lunar ecliptic nodal cycle, as every 9.3 years the lunar path intersects the ecliptic plane, one ascending and the other descending as the moon’s gravitational pull directly aligns with the sun’s. The predicted frequencies are 1/8.85 ± 2/18.6 = 1/4.53 & 1/182, the latter identified by Keeling in 2000. The other oft-mentioned tidal extreme is at 18.6 years, which is identified as the other long period extreme at the Bay of Fundy by Desplanque, and that was also identified by NASA as an extreme nuisance tide via a press release and a spate of “Moon wobble” news articles 3 years ago.
What I find troubling is that I can’t find a scholarly citation where the 4.53 year extreme tidal cycle is explained in this way. It’s only reported as an empirical observation by Desplanque in several articles studying the Bay of Fundy tides.
Continue readingDynamic Time Warping
Useful to note that the majority of the posts written for this blog are in support of the mathematical analysis formulated in Mathematical Geoenergy (Wiley/AGU, 2018). As both new data becomes available and new techniques for model fitting & parameter estimation — aka inverse modeling (predominantly from the machine learning community) — are suggested, an iterative process of validation, fueled by the latest advancements, ensures that the GeoEnergyMath models remain robust and accurately reflective of the underlying observed behaviors. This of course should be done in conjunction with submitting significant findings to the research literature pipeline. However, as publication is pricey, my goal is to make the cross-validation so obvious that I can get an invitation for a review paper — with submission costs waived. Perhaps this post will be the deal-maker — certainly not the deal-breaker, but you can be the judge.
Continue readingFull Wave Forcing
MSet
Global Models of Sea Surface Temperature
These are a set of 6 EOFs that describe the global SST in terms of a set of orthogonal time-series — essentially non-overlapping, each having a cross-correlation of ~0.0 with the others, like a sine/cosine pair, but in both spatial and temporal dimensions.
Continue readingUnified Model of Earth Dynamics
Lorenz turned out to be a chaotic dead-end in understanding Earth dynamics. Instead we need a new unified model of solid liquid dynamics focusing on symmetries of the rotating earth, applying equations of solid bodies & fluid dynamics. See Mathematical Geoenergy (Wiley, 2018).
Should have made this diagram long ago: here’s the ChatGPT4 prompt with the diagramming plugin.
Graph
Ocean Tides and dLOD have always been well-understood, largely because the mapping to lunar+solar cycles is so obvious. And the latter is getting better all the time — consider recent hi-res LOD measurements with a ring laser interferometer, pulling in diurnal tidal cycles with much better temporal resolution.
That’s the first stage of unification (yellow boxes above) — next do the other boxes (CW, QBO, ENSO, AMO, PDO, etc) as described in the book and on this blog, while calibrating to tides and LOD, and that becomes a cross-validated unified model.
Annotated 10/11/2023
ontological classification according to wavenumber kx, ky, kz and fluid/solid.
Added so would not lose it — highlighted tidal factor is non-standard
Annual vs Semi-annual
ENSO models best with alternating sign semi-annual pulses. Operating on the Mf tidal factor this generates a tight forcing with average period 3.8 years.
AMO models best with an annual pulse. Because of the Mt tidal factor the forcing slowly wanders with a period of ~120 years.
PDO models best with an annual pulse but fast decay. Because of the Mt tidal factor the forcing would wander like AMO, but instead it makes biased excursions.
To summarize, the models of ENSO, AMO, and PDO depend on the specific forcing character while keeping the LOD tidal calibration fixed. ENSO likely requires this alternating semi-annual because it is aligned along the equator and so alternates with northern and southern nodal swings. AMO and PDO may require an annual impulse because it’s essentially a northern hemisphere behavior. Why the decay is faster for PDO, or what exactly sets the decay rate after an integrating impulse, is not clear. Perhaps the larger the inertial push the slower the response.
The Big 10 Climate Indices
The above diagram courtesy of Karnauskus
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
- ENSO – https://www.threads.net/@paulpukite/post/CuWS8MFu8Jc
- AMO – https://www.threads.net/@paulpukite/post/Cuh4krjJTLN
- PDO – https://www.threads.net/@paulpukite/post/Cuu0VCypIi5
- QBO – https://www.threads.net/@paulpukite/post/CuiKQ5tsXCQ
- SOI (Darwin & Tahiti) – https://www.threads.net/@paulpukite/post/Cuu2IkBJh55 => MJO
- IOD (East & West) – https://www.threads.net/@paulpukite/post/Cuu9PYvJAG2
- PNA – https://www.threads.net/@paulpukite/post/CuvAVR7JN7R
- AO – https://www.threads.net/@paulpukite/post/CuvEz37JPFV
- SAM – https://www.threads.net/@paulpukite/post/CuvLZ2CMt1X
- 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
Canonical Cross-Validation
The only hope for a non-controlled-experiment-verified model to gain acceptance is either by (1) showing repeated success in predictions, or, precluding that due to long cycle time (2) producing rock-solid cross-validation results. Why? Let ChatGPT-4 answer:
Gist Evaluation
The Gist site on GitHub allows you to comment on posts very easily. For example, images of charts can be pasted in the discussion area. Also snippets of code can be added and updated, which is useful for neural net evaluation. The following is a link to an initial Gist area for evaluating LTE models.
GeoEnergy Math 