MétaCan
Menu
Back to cohort
Record W1587345599 · doi:10.1002/jgrd.50752

SPARC Data Initiative: Comparison of water vapor climatologies from international satellite limb sounders

2013· article· en· W1587345599 on OpenAlexafffund
Michaela I. Hegglin, Susann Tegtmeier, J. G. Anderson, L. Froidevaux, R. Fuller, B. Funke, A. Jones, G. Lingenfelser, J. D. Lumpe, Diane Pendlebury, Ellis E. Remsberg, Alexei Rozanov, Matthew Toohey, J. Urban, T. von Clarmann, Kaley A. Walker, R. Wang, Katja Weigel

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of Toronto
FundersNational Oceanic and Atmospheric AdministrationUniversität BremenCore Research for Evolutional Science and TechnologyScheme for Promotion of Academic and Research CollaborationTekesCanadian Foundation for Climate and Atmospheric SciencesNational Aeronautics and Space AdministrationCalifornia Institute of TechnologyJet Propulsion LaboratoryDeutsche Forschungsgemeinschaft
KeywordsStratosphereSCIAMACHYWater vaporTroposphereEnvironmental scienceMiddle latitudesAtmospheric sciencesPolar vortexClimatologyMicrowave Limb SounderSatelliteExtratropical cycloneLatitudeMeteorologyGeographyGeology

Abstract

fetched live from OpenAlex

Within the SPARC Data Initiative, the first comprehensive assessment of the quality of 13 water vapor products from 11 limb‐viewing satellite instruments (LIMS, SAGE II, UARS‐MLS, HALOE, POAM III, SMR, SAGE III, MIPAS, SCIAMACHY, ACE‐FTS, and Aura‐MLS) obtained within the time period 1978–2010 has been performed. Each instrument's water vapor profile measurements were compiled into monthly zonal mean time series on a common latitude‐pressure grid. These time series serve as basis for the “climatological” validation approach used within the project. The evaluations include comparisons of monthly or annual zonal mean cross sections and seasonal cycles in the tropical and extratropical upper troposphere and lower stratosphere averaged over one or more years, comparisons of interannual variability, and a study of the time evolution of physical features in water vapor such as the tropical tape recorder and polar vortex dehydration. Our knowledge of the atmospheric mean state in water vapor is best in the lower and middle stratosphere of the tropics and midlatitudes, with a relative uncertainty of ±2–6% (as quantified by the standard deviation of the instruments' multiannual means). The uncertainty increases toward the polar regions (±10–15%), the mesosphere (±15%), and the upper troposphere/lower stratosphere below 100 hPa (±30–50%), where sampling issues add uncertainty due to large gradients and high natural variability in water vapor. The minimum found in multiannual (1998–2008) mean water vapor in the tropical lower stratosphere is 3.5 ppmv (±14%), with slightly larger uncertainties for monthly mean values. The frequently used HALOE water vapor data set shows consistently lower values than most other data sets throughout the atmosphere, with increasing deviations from the multi‐instrument mean below 100 hPa in both the tropics and extratropics. The knowledge gained from these comparisons and regarding the quality of the individual data sets in different regions of the atmosphere will help to improve model‐measurement comparisons (e.g., for diagnostics such as the tropical tape recorder or seasonal cycles), data merging activities, and studies of climate variability.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.132
GPT teacher head0.367
Teacher spread0.235 · 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 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

Citations120
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Geophysical Research AtmospheresSame topicAtmospheric Ozone and ClimateFrench-language works237,207