Puͣkiͧte̍

Puͣkiͧte̍

@pukite.com

Earth Sciences 🌏 Mathematical Geoenergy (Wiley/AGU, 2019) 🌊 I think in reciprocal space https://GeoEnergyMath.com https://github.com/orgs/azimuth-project/discussions

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This is a model of sea-level height at Brest, France since 1880, cross-validated in the interval shown. It uses Laplace's tidal equations (LTE) and applies long-period tidal forcing factors over the training interval. Despite being obvious, no one has ever tried doing this in the research lit.

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Puͣkiͧte̍@pukite.com

AMO and PDO With the correct intermediate manifold, those of AMO and PDO are nearly indistinguishable. The ocean response is subtle -- AMO has the basin-wide slow response, whereas PDO doesn't, and both have a similar LTE modulation as shown in… https://geoenergymath.com/2026/10/05/amo-and-pdo/

Revisit Sea Level Pressure paper Revisiting the post An obvious clue from tidal data, which is an analysis of this paper The effect of regional sea level atmospheric pressure on ... At the time, I did not try to duplicate the results, but after coming across it again, curiosity got the best of me.…

geoenergymath.comRevisit Sea Level Pressure paperRevisiting the post An obvious clue from tidal data, which is an analysis of this paper The effect of regional sea level atmospheric pressure on ... At the time, I did not try to duplicate the results, but after coming across it again, curiosity got the best of me. The program to duplicate the results is in this GIST: …

Deep Seek of Wind + ENSO This is a thread with DeepSeek, my prompts in italics bold. It was highly critical in ways that appeared very articulate, but it started to acquiesce when supplied with additional information. Not sure if this is due to a sliding or widening context window. In the past,…

geoenergymath.comDeep Seek of Wind + ENSOThis is a thread with DeepSeek, my prompts in italics bold. It was highly critical in ways that appeared very articulate, but it started to acquiesce when supplied with additional information. Not sure if this is due to a sliding or widening context window. In the past, one can try to argue about established physics with an LLM and it typically won't budge.

Forcing of NAO and MSL in the Baltic Modeling LTE solutions from pukpr/GEM-LTE: GeoEnergyMath Laplaces Tidal Equation modeling and fitting software Warnemunde Mean Sea Level (#11 from PSMSL.org). Dashed lines are cross-validation intervals. North Atlantic Oscillation NAO (top) and Warnemunde MSL…

geoenergymath.comForcing of NAO and MSL in the BalticModeling LTE solutions from pukpr/GEM-LTE: GeoEnergyMath Laplaces Tidal Equation modeling and fitting software Warnemunde Mean Sea Level (#11 from PSMSL.org). Dashed lines are cross-validation intervals. North Atlantic Oscillation NAO (top) and Warnemunde MSL (bottom) latent forcing layer

Spectral details in Chandler Wobble and QBO Using LLMs as peer-review devil's advocates for research findings can't hurt and can only help strengthen an argument. One of the common criticisms an LLM makes is that it will claim that a factor is "too weak" or insignificant to serve as a mechanism…

geoenergymath.comSpectral details in Chandler Wobble and QBOUsing LLMs as peer-review devil's advocates for research findings can't hurt and can only help strengthen an argument. One of the common criticisms an LLM makes is that it will claim that a factor is "too weak" or insignificant to serve as a mechanism for some observed behavior. This has almost turned into a cliche since it caters to the consensus bias of "

Wind Distribution I prompted the Gemini LLM with the following to see how well it would summarize with so little context: Familiar with the BesselK wind distribution model pioneered by Pukite et al in Mathematical GeoEnergy? The BesselK Wind Model: A Maximum Entropy Derivation In the study of wind…

geoenergymath.comWind DistributionI prompted the Gemini LLM with the following to see how well it would summarize with so little context: Familiar with the BesselK wind distribution model pioneered by Pukite et al in Mathematical GeoEnergy? The BesselK Wind Model: A Maximum Entropy Derivation In the study of wind energy, the Weibull distribution is the industry standard. However, as Pukite et al. argue in…

When are #LLM, #ChatGPT, #Claude, #OpenAI, #Anthropic, #DeepSeek, #Grok, #Gemini, #Perplexity, #ML, #AI, #CoPilot, #Antigravity , #GammaAI, #Llama, #Mistral, #xAI, #Google, #Kimi, #Meta going to take this challenge on? It will be a breakthrough in science discovery. github.com/pukpr/Chandl...

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10y ago JS Wettlaufer wrote in a PRL editorial : “Climate Science: An Invitation for Physicists” “New ideas will emerge from perspectives that come from the range of approaches used across all areas of physics. “ journals.aps.org/prl/abstract... AI can create an open world from which to draw from

amo.dat.p AMO trained on region outside of dashed line, so that's the cross-validated region, using Descent optimized LTE annual time-series, Python python3 ts_lte.py amo.dat --cc --plot --low 1930 --high 1960 using the following JSON parameters file amo.dat.p { "Aliased": [ 0.422362756,…

geoenergymath.comamo.dat.pAMO trained on region outside of dashed line, so that's the cross-validated region, using Descent optimized LTE annual time-series, Python python3 ts_lte.py amo.dat --cc --plot --low 1930 --high 1960 using the following JSON parameters file amo.dat.p { "Aliased": [ 0.422362756, 0.38861749700000003, 0.23562139699999995, 0.259019747, 0.33201584700000003, 0.165274488, 0.262765007, 0.385761106, 0.07374525999999999, 0.215992198, 0.192246939, 0.528757205, 0.112996099, 0.03714361, 0.10034691, 0.07660165, 0.501613596, 2.0, 1.0 ], "AliasedAmp": [ 0.03557922624939592, 0.09988731513671248, 0.07106292426402241, 0.1202147059011645, -0.16310647366824904, -0.21099766009700224, 0.3178250739779875, -0.034763054040409205, -0.26973831298426476, -0.13417117453373803, 0.33741450649520405, 0.14844747522132112, 0.38176481941684715, -0.24512757533159843, 0.17007002069621968, -0.3175673142831867, -0.0801663078936891, 0.0410641305028224, 0.15648561320675802 ], "AliasedPhase": [ 12.907437383830702, 9.791011963532627, 20.894959747239227, 11.230932614457465, 24.106215317177334, 14.921596063027563, 11.928445369162157, 14.76066439534825, 9.307516552468496, 6.238399781667854, 4.78878496205605, 19.328424226102666, 4.1510957254818255, 24.986414787848002, 3.764292351659264, 7.899565162852414, 10.701455186458222, 6.575719630634085, 4.603123916071089 ], "DeltaTime": 7.217156366226141e-06, "Hold": 0.001560890374528988, "Imp_Amp": 36.03147961053978, "Imp_Stride": 1, "Initial": 0.023119471463386495, "LTE_Amp": 1.2149052076222568, "LTE_Freq": 232.0780473685175, "LTE_Phase": -1.98155204056087, "Periods": [ 27.2122, 27.3216, 27.564500000000002, 13.63339513, 13.69114014, 13.5961, 13.6708, 13.72877789, 6795.015773000002, 1616.2951719999999, 2120.013852999989, 13.78725, 3232.690344000001, 9.142931547, 9.108450374, 9.120674533, 27.0926041 ], "PeriodsAmp": [ 0.22791356815287772, 0.03599719419115529, 0.18676833431961723, 0.03956128728097599, -0.2649706920257545, 0.10022074474351093, 0.10436992221139457, 0.14430534046016136, 0.07102249228279979, 0.11758452315976271, 0.04510213195702457, 0.06361160068822835, 0.05674788795284906, -0.043657524764462274, 0.07791151774412787, 0.019631216465477552, -0.14009026634971397 ], "PeriodsPhase": [ 13.451016651034463, 7.371101643819357, 18.44011357432109, 6.802030606034782, 21.120997888353294, 9.616514380782336, 5.715489866748063, 10.809731364754402, 9.031554832315345, 7.401459819968337, 5.9383444499771105, 14.60402121854254, 5.541215399062276, 8.44043335583645, 1.6019323722385819, 7.500513005887212, 7.860442540394975 ], "Year": 365.2520198, "final_state": { "D_prev": 0.04294 } }

Taylor series expansion is a key to multiple harmonics in non-linear wave formulation pukite.substack.com/p/mean-sea-l...

pukite.substack.comMean Sea Level modelsThe monthly-to-decadal extremes in local sea level are not understood.
arXiv cs.LG Machine Learning@cslg-bot.bsky.social

Yunpeng Gong, Sihan Lan, Can Yang, Kunpeng Xu, Min Jiang: StruSR: Structure-Aware Symbolic Regression with Physics-Informed Taylor Guidance https://arxiv.org/abs/2510.06635 https://arxiv.org/pdf/2510.06635 https://arxiv.org/html/2510.06635