A Satellite-Based Climatic Description of Jet Aircraft Contrails and Associations with Atmospheric Conditions, 1977–79
Bibliographic record
Abstract
The possible contribution of jet aircraft condensation trails (contrails) to recent observed increases in high cloudiness constitutes a potentially important human effect on climate that has received relatively little attention. Very high resolution (0.6 km) thermal-infrared imagery from the Defense Meteorological Satellite Program polar orbiters, concentrated in the nighttime and morning hours, is interpreted to derive a climatic description of contrails over the United States and adjacent areas for the midseason months (April, July, October, and January) of 1977–79. A manual technique of identifying contrails on the imagery is validated by comparison with more recent ground-based observations. Contrail spatial distributions are mapped at a 1° lat × 1° long resolution for monthly and multimonth time periods. Contrail incidence is widespread over the United States and adjacent areas, with highest frequencies occurring over the following regions: the extreme Southwest (particularly southern California), the Southeast (especially southeast Georgia and northeast Florida), the west coast of British Columbia and Vancouver Island, and the eastern Midwest centered on southeast Indiana and western Kentucky. Contrails are most frequent during the transition-season months (April and October), and are least frequent in July. Latitudinally, contrail incidence peaks over the northern (southern) regions in July (January), suggesting a first-order association with the seasonal variation of upper-tropospheric westerly winds. Analysis of synoptic-scale midtropospheric circulation patterns confirms that the highest contrail frequencies occur in association with baroclinic phenomena, particularly cyclone waves and jet streams. Moreover, contrails tend frequently to occur in conjunction with other clouds, including the cirrus associated with jet-stream and frontal systems. Analyses of rawinsonde data for three representative contrail “outbreak” (multiple occurrence) events during the study months confirm some earlier studies that suggest contrails form below a cold, elevated tropopause (i.e., around ridgelines in the geopotential height field), in contrast with noncontrail days. Accordingly, the temperature advection in the troposphere accompanying the contrail outbreaks is positive, or warm, and relatively weak. This contrail climatic description provides a context within which recent surface climate changes at regional and subregional scales may be cast.
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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 | 0.000 |
| 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) | 0.001 | 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".