Teleconnected tide gauges record the 20th century enhancement of decadal climate variability
Bibliographic record
Abstract
Changes in the amplitude of decadal climate variability over the 20th century have been noted, with most evidence derived from tropical Pacific sea surface temperature records. However, the length, spatial coverage, and stability of most instrumental records are insufficient to robustly identify such non-stationarity, or resolve its global spatial structure. Here, I find that the long-term, stable, observing platform provided by tide gauges reveals a dramatic increase in the amplitude and spatial coherence of decadal (11-14 year period) coastal sea level (𝜁) variability between 1960 and 2000. During this epoch, western North American 𝜁 was approximately out of phase with 𝜁 in Sydney, Australia, and led northeastern United States 𝜁 by approximately 1-2 years. The amplitude and timing of changes in decadal 𝜁 variability are consistent with changes in the spatial structure of atmospheric variability. In particular, central equatorial Pacific wind stress (𝜏 𝐶 𝑃) and Labrador sea heat flux (𝑄 𝐿𝑆) are highly coherent with 𝜁 and exhibit contemporaneous, order-of-magnitude increases in decadal power. These statistical relationships have a mechanistic underpinning: along the western North American coastline, 𝜏 𝐶 𝑃 variability is known to drive rapidly propagating 𝜁 signals along equatorial and coastal waveguides; while a 1-2 year lag between 𝑄 𝐿𝑆 and northeastern United States 𝜁 , is consistent with a remotely-forced, buoyancy-driven, mechanism. Tide gauges thus provide strong independent support for an increase in inter-basin coherence on decadal timescales over the second half of the 20th century, with implications for both the interpretation and prediction of climate and sea level variability. SIGNIFICANCE STATEMENT: Decadal climate variability influences the frequency and severity of many natural hazards (e.g., drought), with considerable human and ecological impacts. Understanding observed changes and predicting future impacts relies upon an understanding of the physical processes and any changes in their variability and relationship over time. However, identifying such changes requires very long observational records. This paper leverages a large set of tide gauge records to show that global decadal-timescale coastal sea level variability increased dramatically in the second half of the 20th century in many locations. The increase was driven by a shift in the amplitude, spatial pattern, and inter-basin coherence, of atmospheric pressure, wind, and sea surface temperature variability.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".