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Record W2060773099 · doi:10.1029/2000jd000233

Lindenberg Aerosol Characterization Experiment 1998 (LACE 98): Overview

2002· article· en· W2060773099 on OpenAlexaboutno aff
Albert Ansmann, Ulla Wandinger, Alfred Wiedensohler, U. Leiterer

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
Fundersnot available
KeywordsAerosolEnvironmental scienceObservatoryMeteorologyTroposphereRadiative transferRemote sensingAtmospheric sciencesInstrumentation (computer programming)Earth's energy budgetRadiationGeologyGeographyPhysicsComputer science

Abstract

fetched live from OpenAlex

Backscattering and absorption of solar radiation by aerosol particles are an important source of uncertainty in climate predictions. Integrated research on the radiative properties of aerosol may reduce this uncertainty. The Lindenberg Aerosol Characterization Experiment 1998 (LACE 98) contributes to this aim. LACE 98 took place between 13 July and 12 August 1998, near Berlin, Germany. The Lindenberg Meteorological Observatory (52.2°N, 14.1°E) was chosen as the central field site because of its long record with aerosol optical‐depth data. Measurements were performed from three aircraft, with one airborne and four ground‐based lidars, and at a ground station. The meteorological situations in which intensive observations were carried out included clean and polluted air masses as characterized by low and high aerosol optical depths. This introductory paper gives an overview of the LACE 98 goals, instrumentation, meteorological and aerosol properties, and reports on the key findings as a guide to the results presented in the more detailed papers that follow. A very remarkable finding should be mentioned beforehand because of its unique character: on 9–10 August 1998, a free‐tropospheric aerosol layer was observed that originated from forest fires in western Canada.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.567
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0130.003

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 head0.048
GPT teacher head0.315
Teacher spread0.267 · 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; both teacher heads agree on what is shown here.

Study designBench or experimental
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

Citations78
Published2002
Admission routes1
Has abstractyes

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