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Record W4254856432 · doi:10.5194/acp-2021-154

Impacts of tropical cyclones on the thermodynamic conditions in the tropical tropopause layer observed by A-train satellites

2021· preprint· en· W4254856432 on OpenAlexafffund
Jing Feng, Yi Huang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsMcGill University
FundersCanadian Space AgencyNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsEnvironmental scienceTroposphereTropopauseAtmospheric sciencesWater vaporTropical cycloneCirrusCyclone (programming language)LongwaveRadiative transferClimatologyOutgoing longwave radiationTropical cyclogenesisMeteorologyConvectionGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. The tropical tropopause layer (TTL) is the transition layer between the troposphere and the stratosphere. Tropical cyclones may impact the TTL by perturbing the vertical distributions of cloud, temperature, and water vapor, although this impact is poorly quantified due to the lack of collocated data. To address this problem, we implement a synergistic retrieval approach to obtain the thermodynamic profiles and ice water content above thick high-level clouds using the A-Train satellite measurements that pass over the tropical cyclones. This study detects the signature of cyclone impact on the distribution patterns of cloud, water vapor, temperature, and radiation by compositing these thermodynamic fields with respect to cyclone center locations. It is found that tropical cyclone events considerably increase the occurrence of TTL clouds, in the form of cirrus clouds above a clear troposphere. The amount of TTL cloud ice, however, is found to be mostly contributed by overshooting deep convections that penetrate the bottom of TTL. Using the synergistic retrieval method, we find a vertically oscillating pattern of temperature anomalies above tropical cyclones, with warming beneath the cloud top (around 16 km) and cooling above. The atmospheric column above 16 km is generally hydrated by overshooting convections, although dehydration is detected above non-overshooting TTL clouds. Above overshooting deep convections, the column-integrated water vapor is found to be on average 40 % higher than the climatology. Moreover, the TTL above tropical cyclones is cooled due to longwave radiative cooling. The radiative heating rates above cyclones are well differentiated by the brightness temperature of a satellite infrared channel in the window band. Using radiative calculations, it is found that TTL hydration is usually associated with radiative cooling of the TTL, which inhibits the diabatic ascent of moist air. The radiative balance of the TTL under the impact of the cyclone, therefore, is not in favor of maintaining the moist anomalies in the TTL or transporting water vertically to the stratosphere.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.032
GPT teacher head0.251
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes2
Has abstractyes

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