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Record W4393538523 · doi:10.5281/zenodo.3967596

CORE inter-annual forced ocean ice simulation using E3SMv0-HiLAT-tx0.3v2 (HiLAT03)

2020· dataset· en· W4393538523 on OpenAlexaboutno aff
Jiaxu Zhang, Wilbert Weijer

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsMeteorologyCore (optical fiber)ClimatologyEnvironmental scienceIce coreGeologyOceanographyComputer scienceGeographyTelecommunications

Abstract

fetched live from OpenAlex

This data set supports the analysis presented in the manuscript: “Labrador Sea freshening linked to Beaufort Gyre freshwater release” (LA-UR-20-20936), which is under review for publication by Nature Communications. The model output is from a 186-year long simulation with the E3SMv0-HiLAT code that was described in the technical report: “An eddy-permitting ocean-sea ice general circulation model (E3SMv0-HiLAT03): Description and evaluation” (LA-UR-19-25177; doi: 10.2172/1542803), by Zhang et al.. The ocean and sea ice components are active, and their grid is configured with a nominal 0.3 degree horizontal resolution. The model is forced by an atmospheric data set that represents the atmospheric state from 1948 through 2009, and is repeated for 3 cycles. #---------------------------------------------------------------------------------------------------------- # Data description # Fri Jul 24 16:55:12 MDT 2020 # Contacts: Jiaxu Zhang (jiaxuzh@uw.edu) and Wilbert Weijer (wilbert@lanl.gov) #---------------------------------------------------------------------------------------------------------- Simulation length: 186 years Simulation machine: LANL HPC facility, on Grizzly Case name: t32_GIAF_woa13rest_deepenNares_Griz Time range: 012101-018612 (corresponding to Jan 1948 to Dec 2009) Grid file: gridFile/tx0.3v2_grid.nc In the post-processed files: pop = ocean output from POP2 mon = monthly ann = annual mean clim = monthly climatology ltm = long-term annual mean dec = decadal mean YYYYMM-YYYYMM = time range FastRel = Fast release case, corresponding to the 016001-017212 period FastAcc = Fast accumulation case, corresponding to the 017301-018512 period NH = data only contain the Northern Hemisphere Similarly, there are files for "BG" (Beaufort Gyre), "Davis_Strait", "Fram_Strait", "Labrador_Sea", "Labrador_Sea_Outflow", "Lancaster_Sound", and "Nares_Strait". These regions are illustrated in Figure 1 of the manuscript. Variable names: SALT = salinity UES = East flux of SALT UVEL = Zonal Velocity VNS = North flux of SALT VVEL = Meridional velocity DYE01 = dye tracer that tags the Beaufort Gyre freshwater (from surface to the reference salinity of 34.6) DSALT01 = salt tracer that tags the Beaufort Gyre salinity (from surface to the reference salinity of 34.6) UE_DSALT01 = East flux of DSALT01 VN_DSALT01 = North flux of DSALT01 In the transport folder: File names: transport.[StraitName].012101-018612.txt Content: Diagnosed transport at a specific strait. Structure: 4 columns are 1. Model time (days since 0001-01) 2. Volume transport (Sv) 3. Heat transport (PW) 4. Liquid freshwater transport (mSv) For all the transports, positive is poleward, negative is equatorward. File names: [CaseName].transport.BG_portion.[StraitName].txt Content: Diagnosed BG-sourced transport at a specific strait for either FastRel or FastAcc case. Structure: 8 columes are 1. Model time (days since 0001-01) 2. Volume transport (Sv) 3. Liquid freshwater transport (mSv) 4. Validation data, please ignore 5. Validation data, please ignore 6. Volume transport sourced from BG alone (Sv) 7. Liquid freshwater transport sourced from BG alone (mSv) 8. Validation data, please ignore

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)0.001
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: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.049
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.061
GPT teacher head0.264
Teacher spread0.203 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)→Same topicArctic and Antarctic ice dynamics→French-language works237,207→