Climatology of Lightning Activities over Bandaranaike International Airport in Sri Lanka
Bibliographic record
Abstract
This study reveals the spatiotemporal distribution of lightning activities over Bandaranaike International Airport, the main international airport of Sri Lanka. Lightning flash data was acquired from the Lightning Imaging Sensor (LIS) on Tropical Rainfall Measuring Mission (TRMM) of NASA to investigate lightning activities from 1998 to 2014 covering an area of 30 km×30 km over the airport. Overhead annual flash density was 8.19 flashes km-2 year-1. The maximum lightning activities (57%) with an overhead flash density of 28.83 flashes km-2 year-1 was recorded in the first inter-monsoon season. The overhead flash density of 5.28 flashes km-2 year-1, 16.36 flashes km-2 year-1 and 7.46 flashes km-2 year-1 were recorded in the southwest monsoon season, second inter-monsoon season, and northeast monsoon season respectively. The month of April accounts for the highest number of lightning activities while maximum lightning flashes (22%) had occurred during 19.00-20.00 Local Time. According to the international climate season, maximum lightning activities over the study area have been recorded from March to May and during this seasonal period, the northern hemisphere is in spring and the southern hemisphere is in autumn. Safety guidelines are proposed to minimize lightning accidents in the airport. It is important to concern the regions with high lightning activity and vulnerable time periods to mitigate lightning accidents and to take adequate safety precautions to ensure the safety of passengers and the working crew to achieve environmental goals of sustainable development in the aviation industry.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".