Trend Analysis of Climate Variability over the West Bank - East London Area, South Africa (1975-2011)
Bibliographic record
Abstract
In recent years, climate change has received considerable attention by the scientific community at different scales concerning its potential impacts on Earth system processes. This study focused at local scale by analysing trends in rainfall and temperature data for the West Bank–East London area in South Africa, spanning 36 years from 1975–2011. Sen’s and Man-Kendall non-parametric tests were performed on derived mean observed rainfall and temperature data to establish trends for monthly, seasonal, annual, and 30 year (1975–2005 and 1980–2011) climatic regimes. Results revealed that, 1977 recorded the highest annual rainfall (2272.9 mm) while the month of August received the highest total rainfall (493.8 mm) in 2002, whereas it never had rain in 1995. Seasonal and annual rainfall showed statistically no significant trend (at a = 0.10) while the magnitude of change varied between 1.87 mm (January) and -1.67 mm (September) across the study period. Rainfall decreased by 13.99 mm within the two climatic regimes. On the other hand, maximum and minimum annual mean temperature experienced an increasingly statistically significant trend (at a < 0.05) at 95% confidence level. February recorded the highest mean monthly temperature (21.8 °C) while July with the lowest (12.6 °C). Seasonal mean maximum temperature trends were statistically not significant (a = 0.10) while autumn minimum temperatures revealed a statistically significant trend (at a < 0.1). However, the period 1990-1999 predominantly experienced numerous extreme events. The seasonal trends showed substantial variability across the months and years during the study period. The significance of these findings lies in the linkage of rainfall and temperature to climate change and its potential impacts on vegetation in particular and changes in the ecology in general.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.018 | 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 teacher head, 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".