Tropical pacific forcing of a 1998–1999 climate shift: observational analysis and climate model results for the boreal spring season
Bibliographic record
Abstract
Observational data and climate model simulations and experiments are utilized to document an abrupt shift in Pacific sea surface temperatures (SSTs) and associated atmospheric conditions, which occurred in 1998–1999. Emphasis is placed on the March–May (MAM) season, as the motivation for the work is to extend a recent study that reported an abrupt decline in East African MAM rainfall at that time. An empirical orthogonal function analysis of MAM SSTs over the last century following the removal of the concurrent influence of the El Niño-Southern Oscillation and global warming trend by linear regression reveals a pattern of multidecadal variability in the Pacific similar to the Pacific Decadal Oscillation. Examination of MAM precipitation variations since 1940 indicates, among other findings, that recurrent drought events since 1999 in East Africa, central-southwest Asia, parts of eastern Australia and the southwestern US are all regional manifestations of a global scale multidecadal pattern. Associated shifts in the low-level wind field and upper-level stationary waves are discussed. Simulations using an atmospheric climate model forced with observed, global SSTs capture many of the salient precipitation and atmospheric circulation features associated with the observed shift. Further, when the model is forced only with observed SSTs from the tropical Pacific it also captures many of the observed atmospheric changes, including the abrupt shift in 1999. The results point to the fundamental role played by the tropical Pacific in driving the response to multidecadal variability of SSTs in the basin and provide important context for recent seasonal climate extremes in several regions of the globe.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".