Assessment of Historical and Future Mean and Extreme Precipitation Over Sub‐Saharan Africa Using <scp>NEX</scp> ‐ <scp>GDDP</scp> ‐ <scp>CMIP6</scp> : Part <scp>II</scp> —Future Changes
Bibliographic record
Abstract
ABSTRACT This study utilised a multi‐model ensemble (MME) of 26 NASA Earth Exchange Global Daily Downscaled Projections (NEX‐GDDP) to assess future changes in mean and extreme precipitation over sub‐Saharan Africa at both seasonal and annual scales under three Shared Socioeconomic Pathway scenarios: SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5. The changes are examined for two distinct future periods, specifically the near future (2031–2060) and the far future (2061–2090), relative to 1985–2014. Nine precipitation indices are utilised to characterise extreme precipitation. The results show that mean precipitation is expected to increase in northern sub‐Saharan Africa, while a decrease is expected in the southern region. Additionally, the duration of dry spell (CDD) is expected to decrease, while the duration of wet spell (CWD) and precipitation frequency (RR1) are projected to increase in the northern region. Conversely, CDD is expected to increase, and CWD and RR1 are expected to decrease in the southern region. These trends become more pronounced in the far future compared to the near future, particularly under the high‐emission scenario SSP5‐8.5. However, there are few localised regions where at least 80% of the models agree with the MME on the changes in CDD, CWD and RR1 under all scenarios for both time frames. Precipitation intensity is expected to increase across most of sub‐Saharan Africa in both time frames, regardless of the scenario, leading to more frequent heavy precipitation and extreme wet events. This increase is expected to be more pronounced under the SSP5‐8.5 scenario, particularly in the far future. Specifically, at least 80% of the models project an increase in heavy and extreme wet events across most of northern sub‐Saharan Africa under all scenarios for both time frames. These findings emphasise the urgent need to develop effective adaptation strategies for sub‐Saharan Africa to mitigate the potential impacts of these projected changes in precipitation characteristics.
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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 | 0.001 | 0.001 |
| 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".