Characteristics and Mechanisms of Heavy Precipitation in Spring of Eastern Himalayas
Bibliographic record
Abstract
Abstract In spring, eastern Himalayas (EH) receives the largest amount of rainfall in South Asia. However, the characteristics and formation mechanisms of spring precipitation, especially heavy precipitation (HP), in this region remain poorly understood. Based on 10-yr IMERG precipitation and the clustering approach of the self-organizing map, two types of HP are revealed with the rainfall center located at the northern coast of the Bay of Bengal (BOB) and the Gangetic Plain near the foot of EH, respectively. Despite low occurrence frequency, HP contributes importantly to the total rainfall, especially after the onset of South Asian summer monsoon. The coastal HP and inland HP are of opposite diurnal cycles, which peak in the early afternoon and midnight, respectively. Composite analyses are conducted for the synoptic circulation patterns using ERA5 reanalysis. The occurrence of HP is promoted by the moisture transport and uplifting of southwesterly boundary layer jet (BLJ) associated with an anomalous lower-tropospheric cyclonic circulation over BOB, which is dynamically induced by the excessive surface sensible heating (SH) over the Indian subcontinent. When the surface SH is enhanced in northwestern-central India, BLJ terminates near the northern coast of BOB, resulting in coastal-type HP. By contrast, when the enhanced surface SH mainly occurs in northwestern India, BLJ penetrates further northward to the foot of EH and thus produces inland HP. In the latter case, the interaction between BLJ and EH topography helps increase the water vapor convergence and dynamical lifting, leading to heavier precipitation than the former.
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 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) | 0.000 | 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".