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Record W2945744074 · doi:10.5281/zenodo.1194490

Idealized Single-Forcing Gcm Simulations With Ncar Cesm

2018· dataset· en· W2945744074 on OpenAlexaboutno aff
Michael P. Erb, C. S. Jackson, Pedro DiNezio

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typedataset
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsnot available
Fundersnot available
KeywordsGCM transcription factorsForcing (mathematics)ClimatologyEnvironmental scienceGeneral Circulation ModelMeteorologyGeologyPhysicsClimate change

Abstract

fetched live from OpenAlex

This repository contains a set of single-forcing general circulation model (GCM) simulations run with the National Center for Atmospheric Research (NCAR) Community Earth System Model version 1.2 (CESM1.2). In each of these equilibrium simulations, one climate forcing was altered while all others were held constant at preindustrial levels, modeling the climate response to individual climate forcings. Simulations were run for obliquity (low and high obliquity), precession (four phases of the precession cycle with high eccentricity, and one simulation with eccentricity set to zero), half CO<sub>2</sub>, and LGM-sized ice sheets. The values chosen for the orbital simulations represent the extreme values of the past 900 thousand years. Simulations were run for at least 500 years, and forcings do not change from year to year. The uploaded files are 100 year (or longer) monthly climatologies. For most simulations, variables are presented for the atmosphere (atm), sea ice (cice), land (clm2), and river runoff (rtm). For the ice sheets simulation and its corresponding preindustrial simulation (0ka), only atmospheric output is presented; to inquire about other fields for those simulations, please contact Pedro DiNezio at pdn@ig.utexas.edu. Ocean files are not currently available; please contact Michael Erb at michael.p.erb@gmail.com if you are interested in those results. === FORCINGS === Preindustrial climate forcings for the 0ka_0urb simulation were set to the following values: - Obliquity: 23.44107° - Longitude of perihelion: 102.7242° - Eccentricity: 0.01670772 - CO<sub>2</sub>: 284.7 ppm - Ice sheets: 0 ka BP The remaining simulations explore the climate response to a change in one of these forcings, with all other forcings set to preindustrial levels. Forcings are specified as follows: - lo_obliq and hi_obliq: Obliquity is set to 22.079° or 24.480°, respectively. - 0_AEQ, 90_WSOL, 180_VEQ, and 270_SSOL: Perihelion occurs at the NH autumnal equinox, winter solstice, vernal equinox, or summer solstice, respectively, with eccentricity set to 0.0493. This corresponds to a longitude of perihelion of 0°, 90°, 180°, or 270°, respectively. - ECC_0: Eccentricity is set to 0. - half_CO2: CO<sub>2</sub> is set to 142.35 ppm. - 21kaGlac: Ice sheets and sea level are set to Last Glacial Maximum (LGM) levels. Ice sheets come from the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3) reconstruction, with ice shelves added in the western Labrador Sea. A note about preindustrial simulations: Some details of the model setup differ between the ice sheet simulation and the other simulations. Because of this, if a preindustrial control simulation is wanted for analysis, it is recommended that you use certain preindustrial simulations for certain comparisons, as follows: - 0ka_0urb (BG1850C5CN): Control simulation for all simulations except ice sheets. - 0ka (B1850C5): Control simulation for ice sheets (21kaGlac) simulation. === NOTES === More detailed description of these simulations, as well as results, can be found in the following papers: Erb, M. P., C. S. Jackson, A. J. Broccoli, D. W. Lea, P. J. Valdes, M. Crucifix, and P. N. DiNezio, in press: Model evidence for a seasonal bias in Antarctic ice cores. <em>Nature Communications.</em> Bosmans, J. H. C., M. P. Erb, A. M. Dolan, S. S. Drijfhout, E. Tuenter, F. J. Hilgen, D. Edge, J. O. Pope, and L. J. Lourens, in press: Response of the Asian summer monsoons to idealized precession and obliquity forcing in a set of GCMs. <em>Quat. Sci. Rev.</em> Bhattacharya, T., J. E. Tierney, and P. DiNezio, 2017: Glacial reduction of the North American Monsoon via surface cooling and atmospheric ventilation. <em>Geophys. Res. Lett.</em>, <strong>44</strong>, 5113-5122, doi:10.1002/2017GL073632. DiNezio, P. N., J. E. Tierney, B. L. Otto-Bliesner, A. Timmermann, T. Bhattacharya, N. Rosenbloom, and E. Brady, in review: Glacial changes in tropical climate amplified by the Indian Ocean. Note that the monthly data analyzed in these papers is sometimes converted to a common fixed-angular calendar in which every "month" corresponds to a 30° arc of Earth's orbit. This was done because changes in precession affect the speed at which Earth travels through different parts of its orbit according to Kepler's second law, complicating the comparison of months in different precession experiments. However, the results provided in this repository use the model's original fixed-day calendar. Computing resources (ark:/85065/d7wd3xhc) were provided by the Climate Simulation Laboratory at NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation and other agencies. If you use these simulations for research, please let the authors know. For a similar set of experiments using another model (GFDL CM2.1), see doi:10.5281/zenodo.1194480. Contact:<br> Michael Erb<br> Postdoctoral Scholar at Northern Arizona University<br> michael.p.erb@gmail.com

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.016
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.006

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 head0.030
GPT teacher head0.227
Teacher spread0.197 · 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 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

Citations2
Published2018
Admission routes1
Has abstractyes

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