North Atlantic wave height trends as reconstructed from the 20th century reanalysis
Bibliographic record
Abstract
This study reports on the 1871–2010 trends in significant wave heights ( H s ) in the North Atlantic, as statistically reconstructed from the 20th century reanalysis (20CR) ensemble of mean sea level pressure (SLP) fields. The 20CR SLP data set for the North Atlantic has been reported to be homogeneous since 1871, although it has discontinuities before 1949 in other regions. A multivariate regression model with lagged dependent variable is used to represent the SLP‐ H s relationship. It is calibrated and validated using the ERA‐Interim reanalysis of H s and SLP for the period 1981–2010.Trends in the reconstructed annual mean and maximum H s are found to be consistent with those derived from two dynamical wave reanalysis data sets (MSC50 and ERA40), which indicates robustness of the trend estimates. The trend patterns of extreme H s generally feature increases in the northeast North Atlantic with decreases in the mid‐latitudes; but there are seasonal variations. The main features of the patterns of trends over the last half century or so are also seen in the last 140‐yr period (1871–2010). However, the trend magnitudes are much greater in the last half century than in the 140 years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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".