Congo Basin precipitation: Assessing seasonality, regional interactions, and sources of moisture
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Precipitation in the Congo Basin was examined using a version of the National Center for Atmospheric Research Community Earth System Model (CESM) with water tagging capability. Using regionally defined water tracers, or tags, the moisture contribution from different source regions to Congo Basin precipitation was investigated. We found that the Indian Ocean and evaporation from the Congo Basin were the dominant moisture sources and that the Atlantic Ocean was a comparatively small source of moisture. In both rainy seasons the southwestern Indian Ocean contributed about 21% of the moisture, while the recycling ratio for moisture from the Congo Basin was about 25%. Near the surface, a great deal of moisture is transported from the Atlantic into the Congo Basin, but much of this moisture is recirculated back over the Atlantic in the lower troposphere. Although the southwestern Indian Ocean is a major source of Indian Ocean moisture, it is not associated with the bulk of the variability in precipitation over the Congo Basin. In wet years, more of the precipitation in the Congo Basin is derived from Indian Ocean moisture, but the spatial distribution of the dominant sources is shifted, reflecting changes in the midtropospheric circulation over the Indian Ocean. During wet years there is increased transport of moisture from the equatorial and eastern Indian Ocean. Our results suggest that reliably capturing the linkages between the large‐scale circulation patterns over the Indian Ocean and the local circulation over the Congo Basin is critical for future projections of Congo Basin precipitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it