The 18.6‐year lunar nodal cycle and surface temperature variability in the northeast Pacific
Bibliographic record
Abstract
The 18.6‐year lunar nodal cycle (LNC) is a significant feature of winter (January) air and sea temperatures along the North American west coast over a 400‐year period. Yet much of the recent temperature variation can also be explained by wind patterns associated with the PNA teleconnection. At Sitka, Alaska, (57°N) and nearby stations in northern British Columbia, the January PNA index accounts for over 70% of average January air temperatures in lengthy meteorological records. It appears that the LNC signal in January air temperatures in this region is not independent of the PNA, but is a component of it. The Sitka air temperature record, along with SSTs along the British Columbia coast and the PNA index have significant cross‐correlations with the LNC that appear at a 2‐year lag, LNC leading. The influence of the PNA pattern declines in winter with decreasing latitude but the LNC component does not. It appears as a significant feature of long‐term SST variation at Scripps Pier and the California Current System. The LNC also appears over centennial‐scales in proxy temperatures along western North America. The linkage of LNC‐moderated surface temperatures to processes involving basin‐scale teleconnections expands the possibility that the proximate mechanism may be located remotely from its expression in the northeast Pacific. Some of the largest potential sources of a diurnal tidal signal in the atmosphere are located in the western Pacific; the Sea of Okhotsk and the Indonesian archipelago.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".