Rainfall Characteristics Over Kenyir Dam Catchment Under AR5 Climate Change Scenarios
Bibliographic record
Abstract
In this study, the Coupled Model Intercomparison Project Phase 5 (CMIP5) dataset namely CanESM2, a Canadian Earth System Model was used to assess the potential changes of rainfall characteristics over the Kenyir dam catchment. The changes were computed for two future time slices (2025–2055 and 2056–2085) relative to the reference period (1988–2017) under three Representative Concentration Pathways (RCPs; RCP2.6, RCP4.5 and RCP8.5). For comparison purposes, climate change data was also obtained from National Hydraulic Research Institute of Malaysia (NAHRIM). NAHRIM climate data are based on GCMs adopting the Special Report on Emission Scenarios (SRE) scenarios in the AR4. The three selected GCMs were CCSM3, ECHAM5 and MRI-CGCM2.3.2. The simulated rainfall patterns generally resemble those in the historical observations. However, the CCSM, ECHAM and MRI produce lower monthly rainfall, while generally CanESM2 simulations produce monthly rainfall that are more consistent with the historical observations for RCP2.6, RCP4.5 and RCP8.5. The projected future climate rainfall by the CanESM2 suggest slightly decreasing of total rainfall over the Kenyir dam catchment due to the global warming. The largest decrement appears to be in January and February. The analysis of historical daily rainfall characteristic has suggested remarkable changes in the hydroclimatic regimes over this catchment. Understanding of such changes allow better risk assessment and mitigation planning for water security.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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".