High‐resolution modeling of atmospheric dynamics in the Nepalese Himalaya
Bibliographic record
Abstract
Abstract High‐altitude meteorological processes in the Himalaya are influenced by complex interactions between the topography and the monsoon and westerly circulation systems. In this study, we use the Weather Research and Forecasting model configured with high spatial resolution to understand seasonal patterns of near‐surface meteorological fields and precipitation processes in the Langtang catchment in the central Himalaya. Using a unique high‐altitude observational network, we evaluate a simulation from 17 June 2012 to 16 June 2013 and conclude that, at 1 km horizontal grid spacing, the model captures the main features of observed meteorological variability in the catchment. The finer representation of the complex terrain and explicit simulation of convection at this grid spacing give strong improvements in near‐surface air temperature and small improvements in precipitation, in particular in the magnitudes of daytime convective precipitation and at higher elevations. The seasonal differences are noteworthy, including a reversal in the vertical and along‐valley distributions of precipitation between the monsoon and winter seasons, with peak values simulated at lower altitudes (~3000 m above sea level (asl)) and in the upper regions (above 5000 m asl) in each season, respectively. We conclude that there is great potential for improving the local accuracy of climate change impact studies in the Himalaya by using high‐resolution atmospheric models to generate the forcing for such studies.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".