Empiric Forecasting of Dominant Modes to Summer Precipitation Anomaly of Northeast Brazil
Bibliographic record
Abstract
The main economic activities of the Brazilian Northeast (NEB) are affected by the region's highly variable climate, requiring research into seasonal climate forecasting. In a work we show the results obtained after analysing the relationship between the main modes of NEB rainfall variability and lagged oceanic and atmospheric variable fields, that is, preceding rainfall. Consistent relationships were found between sea surface temperature (SST) in the Equatorial Pacific, Equatorial Atlantic and South Atlantic with NEB rainfall. Rossby wave patterns over the North Pacific that propagate from west to east to the Intertropical Convergence Zone (ITCZ), Walker Cell and Upper Bolivia have also been identified. In this research, the main objective was to identify the physical basis for the construction of linear regression models capable of predicting seasonal summer rainfall in the NEB, from the relationships between predictor-predictor. The adjusted regression model performed well between simulations and observations based on validation metrics and can be reliably indicated for operational climate forecasting systems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".