MétaCan
Menu
← Back to cohort
Record W2013318329 · doi:10.1029/2001jd001101

Impact of improved near‐infrared water vapor line data in simulations with the ECHAM4 general circulation model

2002· article· en· W2013318329 on OpenAlexaff
Ulrike Lohmann, Ralf Bennartz

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2002
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsDalhousie University
FundersDeutsches Klimarechenzentrum
KeywordsHITRANWater vaporEnvironmental scienceMeteorologyInfraredAtmospheric sciencesAbsorption (acoustics)Remote sensingAbsorption spectroscopyPhysicsOpticsGeology

Abstract

fetched live from OpenAlex

Recently, two new water vapor line absorption data sets have become available. First, the HITRAN 2000 data set provides updated information on several water vapor absorption lines in the near infrared. Second, an independent study initiated by the European Space Agency (ESA) created a new line data set for the spectral range between 8592 and 20000 cm−1. We investigate the impact of these new data in the near infrared as compared to HITRAN‐92 on the absorption of solar radiation in the ECHAM4 general circulation model. Owing to the increased water vapor absorption in the new parameterizations, the global annual mean atmospheric absorption of solar radiation in ECHAM4 is increased under all skies between 3.2 and 3.7 W m−2 and between 5.0 and 5.7 W m−2 under clear skies for the different data sets. While the dynamics barely change, the hydrological cycle is slightly weaker, the cloud cover has decreased by 0.4% and the precipitation by 0.06 to 0.08 mm d−1 when the new data sets are used.

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)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.329
Teacher spread0.259 · 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 designSimulation or modeling
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

Citations10
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Geophysical Research Atmospheres→Same topicAtmospheric Ozone and Climate→French-language works237,207→