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Record W4415046404 · doi:10.1029/2025ef006201

A Stylized Study of the Climate Response to Longwave and Shortwave Forcing at the Altitude of Aviation‐Induced Cirrus

2025· article· en· W4415046404 on OpenAlexaff
Tresa Mary Thomas, Lei Duan, Govindasamy Bala, K. Caldeira

Bibliographic record

VenueEarth s Future · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAdvanced Aircraft Design and Technologies
Canadian institutionsMerck Canada Inc. (Canada)
FundersCarnegie Institution for ScienceGates Ventures
KeywordsLongwaveShortwaveCirrusRadiative forcingCloud forcingShortwave radiationForcing (mathematics)Latitude

Abstract

fetched live from OpenAlex

Abstract Several lines of evidence indicate that aviation‐induced cirrus clouds contribute to global warming. These clouds produce both longwave and shortwave radiative forcing, yet their climate impacts are not well understood. To improve understanding of the climate effects of radiative forcing associated with aviation‐induced cirrus clouds, we use the Community Earth System Model CESM1.2.2 to perform simulations with stylized longwave and shortwave forcing agents in different latitude bands. We find that for the same concentration, longwave absorbers in the sub‐tropics have the largest magnitude of instantaneous radiative forcing but these absorbers in the polar regions show the largest impact on global temperature. In contrast, shortwave scatterers in the low latitudes have the largest magnitude of effective and instantaneous radiative forcing, but the global temperature response is not highly sensitive to the latitude of forcing. Our results suggest that contrail‐induced warming could be reduced most effectively by avoiding aviation‐induced cirrus clouds at night, and at high latitudes during their winters.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.537
Threshold uncertainty score0.207

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.244
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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