Trends and variability in extreme precipitation indices over Maghreb countries
Bibliographic record
Abstract
Abstract. Maghreb countries are highly vulnerable to extreme hydrological events, such as floods and droughts, driven by the strong variability of precipitation. While several studies have analyzed the presence of trends in precipitation records for the Euro-Mediterranean basin, this study provides a regional assessment of trends on its southernmost shores. A database of 22 stations located in Algeria, Morocco and Tunisia with between 33 and 59 yr of daily precipitation records is considered. The change points and trends are analyzed for eleven climate indices, describing several features of the precipitation regime. The issue of conducting multiple hypothesis tests is addressed through the implementation of a false discovery rate procedure. The spatial and interannual variability of the precipitation indices at the different stations are analyzed and compared with large-scale atmospheric circulation patterns, including the North Atlantic Oscillation (NAO), western Mediterranean Oscillation (WEMO), Mediterranean Oscillation (MO) and El Niño–Southern Oscillation (ENSO). Results show a strong tendency towards a decrease of precipitation totals and wet days together with an increase in the duration of dry periods, mainly for Morocco and western Algeria. On the other hand, only a few significant trends are detected for heavy precipitation indices. The NAO and MO patterns are well correlated with precipitation indices describing precipitation amounts, the number of dry days and the length of wet and dry periods, whereas heavy precipitation indices exhibit a strong spatial variability and are only moderately correlated with large-scale atmospheric circulation patterns.
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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 | 0.002 |
| 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".