Rainfall Characteristics during the Years of Significant Departures from Normal in the Sudano-Sahelian Ecological Zone of Nigeria
Bibliographic record
Abstract
The rationale examining the rainfall characteristics during the years of significant departures from normal in the Sudano-Sahelian Ecological Zone (SSEZ) of Nigeria is based on the devastating effects of extreme weather events and their subsequent implications for agriculture and food security in sub-Saharan Africa. This study designated Significant Years of Positive Departure (SYPD) and Negative Departure (SYND) of rainfall from normal using a Z-score analysis on 39 years of rainfall data (1980-2018) for Sokoto, Kano, Maiduguri, and Nguru. The results show that nine years possessed significant positive departures in rainfall versus six years of negative departures significant at α = 0.05. The frequency of occurrence of intra-seasonal dry spells outweighed that of wet spells in all the years except in 2000 (Maiduguri), 2012 (Kano and Nguru), and 2016 in Sokoto. Light rainfall contributed almost 60% of the total annual rainfall in the zone with heavy rains comprising 17.6% of the total in SYPD versus only 3% in SYND. The average length of the growing season (106 days) was higher during the SYND than the SYPD with an average of 99 days. Onset and retreat days were mostly recorded during June and September respectively in SSEZ. This study found that SYPD in Sudano-Sahelian Ecological Zone possessed more wet occurrences than dry periods resulting from below-normal rainfall. These wetter occurrences also possess food security concerns because of their timing, while the SYND years portend to drought and possible famine.
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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) | 0.000 | 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".