MétaCan
Menu
Back to cohort
Record W2342205477 · doi:10.5281/zenodo.48902

The Ground-Based Musica Dataset: Tropospheric Water Vapour Isotopologues (H216O, H218O And Hd16O) As Obtained From Ndacc/Ftir Solar Absorption Spectra

2016· dataset· en· W2342205477 on OpenAlexaff
Sabine Barthlott, Matthias Schneider, Frank Hase, Thomas Blumenstock, Gizaw Mengistu Tsidu, Michel Grutter, Kimberly Strong, Justus Notholt, Emmanuel Mahieu, Nicholas Jones, Dan Smale

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2016
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicOceanographic and Atmospheric Processes
Canadian institutionsUniversity of Toronto
FundersEuropean Commission
KeywordsIsotopologueTroposphereWater vaporEnvironmental scienceRadiosondeFourier transform infrared spectroscopyAtmospheric sciencesRemote sensingSpectral lineMeteorologyGeologyPhysics

Abstract

fetched live from OpenAlex

MUSICA (“MUlti-platform remote sensing of Isotopologues for investigating the Cycle of Atmospheric water”, http://www.imk-asf.kit.edu/english/musica.php) is a European Research Council (ERC) project. The project has developed tropospheric water vapour isotopologue retrievals (H2O and H2O-δD pairs) using ground-based FTIR spectra as well as thermal nadir spectra measured by the satellite sensor IASI. H2O-δD pairs allow studying tropospheric water transport pathways and in combination with models they can improve our understanding of important climate feedback mechanisms (see also WCRP Grand Challenges: http://www.wcrp-climate.org/grand-challenges).<br> <br> For MUSICA, the FTIR spectra have been analysed centrally at KIT using uniform and consistent retrieval settings, thereby guaranteeing ultimate consistency of the retrieval products generated for different FTIR stations. The FTIR products are H2O profiles for the lower, middle and upper troposphere as well as H2O-δD pairs for the lower and middle troposphere. The data have been produced for 12 FTIR stations and date back to 1996. The dataset has been extensively characterized and validated (theoretically and empirically). Furthermore, the spectra have been used to perform uniform retrievals of XCO<sub>2</sub>, which is then used for documenting the long-term stability of these kind of FTIR data. The data are provided in the form of two data types. The first type ("ftir.iso.h2o") is best-suited for tropospheric water vapour distribution studies that disregard the different isotopologues (comparison with radiosonde data, analyses of water vapour variability and trends, etc.). The second type ("ftir.iso.post.h2o") is needed for analysing moisture pathways by means of H<sub>2</sub>O-δD pair distribution. The data format is hdf4 and the files have been generated in compliance with GEOMS (Generic Earth Observation Metadata Standard). The complete MUSICA NDACC/FTIR dataset is also publicly available via the NDACC database (ftp://ftp.cpc.ncep.noaa.gov/ndacc/MUSICA). Details on the characteristics of the dataset are described in the paper "Tropospheric water vapour isotopoloque data (H\(_{2}^{16}\)O, H\(_{2}^{18}\)O and HD<sup>16</sup>O) as obtained from NDACC/FTIR solar absorption spectra" that has been prepared for ESSD in the context of the special issue “25th anniversary of NDACC”.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0040.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.014

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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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 designNot applicable
Domainnot available
GenreDataset

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

Citations15
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicOceanographic and Atmospheric ProcessesFrench-language works237,207