Three-Dimensional Modelling of Precipitation Enhancement by Cloud Seeding in Three Different Climate Zones
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study numerically investigates precipitation enhancement from cumuliform clouds in three different climate regions: (1) Arid climate of the United Arab Emirates (UAE); (2) maritime climate of Thailand; and (3) continental climate of Serbia. Recently developed core/shell sodium chloride (NaCl)/titanium dioxide (TiO2) nanostructure (CSNT) aerosol was tested as a precipitation enhancer in all three climate regions. Previous experimental studies in cloud chambers and idealized numerical simulations demonstrated that CSNT is a significantly more effective precipitation enhancer than the traditional NaCl. Here, CSNT and NaCl seeding agents are incorporated into the WRF (Weather Research and Forecasting) model microphysics with explicate treatment of aerosol. Our results show that CSNT is a profoundly more effective precipitation enhancer in the case of arid climate characterized with low humidity. The accumulated surface precipitation in the arid test was 1.4 times larger if CSNT seeding agent was used instead of NaCl. The smallest difference in the effectiveness between CSNT and NaCl was observed in the maritime case due to their similar activation properties at high values of relative humidity.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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