Study of Moisture Budget of Meteorological Droughts over Indian Region
Bibliographic record
Abstract
The study mainly focuses on heat and moisture budget components and its variations during meteorological drought conditions over India for the period 1951-2013. IITM sub-divisional summer monsoon standardized rainfall anomaly is considered to identify the meteorological drought where the standardized summer monsoon rainfall anomaly is less than one. From the analysis, there are thirteen meteorological droughts are identified, and the rainfall decreased on spatial and temporal scales with significant changes in the frequency, duration and total amount of rainfall. Mainly, anticyclonic circulation is observed along 60⁰-70⁰E with weak westerlies at lower levels. At the upper level, the intensity of easterly jet stream is decreased and shifted southward during drought years.Anomalous variations in relative humidity and vertical velocity induce the maximum reduction in the moisture amount (15%) at lower and upper levels leads to weakening of the strength of local Hadley circulation. Next, the heat budget components are decreased over Bay of Bengal and coastal regions with a magnitude of 40 to 200 W/m2 in drought years. It is observed that more moisture is transported to the equatorial region producing below average rainfall over the Indian subcontinent during weak monsoon periods. Hence, this study will help to identify the quantitative and qualitative estimation of drought conditions for long-range prediction of rainfall forecasting.
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) | 0.000 | 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 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".