Aircraft Takeoff Performance in a Changing Climate for Canadian Airports
Bibliographic record
Abstract
Temperature and wind are major meteorological factors that affect the takeoff and landing performance of aircraft. Warmer temperatures and the associated decrease in air density in future climate, and changes to crosswind and tailwind, can potentially impact aircraft performance. This study evaluates projected changes to aircraft takeoff performance, in terms of weight restriction days and strong tailwind and crosswind occurrences, for 13 major airports across Canada, for three categories of aircraft used for long-, medium- and short-haul flights. To this end, two five-member ensembles of transient climate change simulations performed with a regional climate model, for Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios, respectively, are analyzed. Results suggest that the projected increases in weight restriction days associated with the increases in daily maximum temperatures vary with aircraft category and airfield location, with larger increases noted for airfields in the south central regions of Canada. Although avoiding takeoff during the warmest period of the day could be a potential solution, analysis focused on the warmest and coolest periods of the day suggests more weight restriction hours even during the coolest period of the day, for these airfields. Though RCP8.5 in general suggests larger changes to weight restriction hours compared to RCP4.5, the differences between the two scenarios are more prominent for the coolest part of the day, as projected changes to daily minimum temperatures occur at a much faster rate for RCP8.5 compared to RCP4.5, and also due to the higher increases in daily minimum temperatures compared to maximum temperatures. Both increases and decreases to crosswind and tailwind are projected, which suggest the need for detailed case studies, especially for those airfields that suggest increases. This study provides useful preliminary insights related to aircraft performance in a warmer climate, which will be beneficial to the aviation sector in developing additional analysis and to support climate change adaptation-related decision-making.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".