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Record W2007426147 · doi:10.1029/2000gl012067

Cloud optical depths and TOA fluxes: Comparison between satellite and surface retrievals from multiple platforms

2001· article· en· W2007426147 on OpenAlexaff
Alexander P. Trishchenko, Zhanqing Li, Fu‐Lung Chang, Howard W. Barker

Bibliographic record

VenueGeophysical Research Letters · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsEnvironment and Climate Change CanadaNatural Resources Canada
FundersCentre National d’Etudes SpatialesLangley Research CenterU.S. Department of Energy
KeywordsRadiative transferEnvironmental scienceRemote sensingInversion (geology)ShortwaveCloud computingSatelliteBroadbandMeteorologyAtmospheric radiative transfer codesCloud topCloud fractionFlux (metallurgy)Cloud coverComputer scienceGeologyPhysicsOpticsTelecommunicationsMaterials scienceAstronomy

Abstract

fetched live from OpenAlex

Performances of two cloud property retrieval schemes are assessed by comparison with each other. The study is limited to liquid phase clouds. Two parameters are assessed: cloud optical depth in the visible band and broadband shortwave (SW) flux at the top‐of‐atmosphere (TOA). Retrievals are based on look‐up tables for a variety of conditions using an adding‐doubling code coupled with LOWTRAN‐7 transmittance models. Comparisons of cloud optical depths retrieved from ground measurements with those from ISCCP DX data agree better than previously reported comparisons with the original ISCCP CX data. Likewise, good agreement is obtained between retrieved and inferred TOA SW fluxes. Differences fall within uncertainties of input parameters, as well as shortcomings in the use of a plane‐parallel radiative transfer model and in the inversion schemes themselves.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.687

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.042
GPT teacher head0.310
Teacher spread0.268 · 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

Citations22
Published2001
Admission routes1
Has abstractyes

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