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Record W2921025948 · doi:10.1029/2018ms001603

The DOE E3SM Coupled Model Version 1: Overview and Evaluation at Standard Resolution

2019· article· en· W2921025948 on OpenAlexaff
Jean‐Christophe Golaz, Peter Caldwell, Luke Van Roekel, Mark Petersen, Qi Tang, Jonathan D. Wolfe, Guta Wakbulcho Abeshu, Valentine Anantharaj, Xylar Asay‐Davis, David C. Bader, Sterling Baldwin, Gautam Bisht, Peter Bogenschutz, M. L. Branstetter, Michael A. Brunke, Steven Brus, Susannah M. Burrows, Philip Cameron‐Smith, Aaron S. Donahue, Michael Deakin, R. C. Easter, Katherine J. Evans, Yan Feng, M. Flanner, James Foucar, Jeremy Fyke, Brian M. Griffin, Cécile Hannay, Bryce E. Harrop, Mattthew J. Hoffman, Elizabeth Hunke, Robert Jacob, Douglas W. Jacobsen, Nicole Jeffery, Philip W. Jones, Noel D. Keen, Stephen A. Klein, Vincent E. Larson, L. Ruby Leung, Hong‐Yi Li, Wuyin Lin, William H. Lipscomb, Po‐Lun Ma, Salil Mahajan, Mathew Maltrud, Azamat Mametjanov, Julie L. McClean, Renata McCoy, Richard Neale, Stephen Price, Yun Qian, Philip J. Rasch, J. E. Jack Reeves Eyre, W. J. Riley, Todd D. Ringler, Andrew Roberts, Erika Roesler, Andrew G. Salinger, Zeshawn Shaheen, Xiaoying Shi, Balwinder Singh, Jinyun Tang, Mark A. Taylor, Peter Thornton, Adrian K. Turner, Milena Veneziani, Hui Wan, Hailong Wang, Shanlin Wang, D. N. Williams, Phillip Wolfram, Patrick H Worley, Shaocheng Xie, Yang Yang, Jin‐Ho Yoon, Mark D. Zelinka, Charles S. Zender, Xubin Zeng, Chengzhu Zhang, Kai Zhang, Yuying Zhang, Xue Zheng, Tian Zhou, Qing Zhu

Bibliographic record

VenueJournal of Advances in Modeling Earth Systems · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsWorkers Compensation Board of AlbertaUniversity of British Columbia
FundersBiological and Environmental ResearchOffice of ScienceNational Research FoundationU.S. Department of Energy
KeywordsClimatologyClimate modelCoupled model intercomparison projectEnvironmental scienceRadiative forcingForcing (mathematics)Earth system sciencePredictabilityMeteorologyAtmospheric sciencesAerosolGeologyClimate changeGeographyPhysics

Abstract

fetched live from OpenAlex

Abstract This work documents the first version of the U.S. Department of Energy (DOE) new Energy Exascale Earth System Model (E3SMv1). We focus on the standard resolution of the fully coupled physical model designed to address DOE mission‐relevant water cycle questions. Its components include atmosphere and land (110‐km grid spacing), ocean and sea ice (60 km in the midlatitudes and 30 km at the equator and poles), and river transport (55 km) models. This base configuration will also serve as a foundation for additional configurations exploring higher horizontal resolution as well as augmented capabilities in the form of biogeochemistry and cryosphere configurations. The performance of E3SMv1 is evaluated by means of a standard set of Coupled Model Intercomparison Project Phase 6 (CMIP6) Diagnosis, Evaluation, and Characterization of Klima simulations consisting of a long preindustrial control, historical simulations (ensembles of fully coupled and prescribed SSTs) as well as idealized CO 2 forcing simulations. The model performs well overall with biases typical of other CMIP‐class models, although the simulated Atlantic Meridional Overturning Circulation is weaker than many CMIP‐class models. While the E3SMv1 historical ensemble captures the bulk of the observed warming between preindustrial (1850) and present day, the trajectory of the warming diverges from observations in the second half of the twentieth century with a period of delayed warming followed by an excessive warming trend. Using a two‐layer energy balance model, we attribute this divergence to the model's strong aerosol‐related effective radiative forcing (ERF ari+aci = −1.65 W/m 2 ) and high equilibrium climate sensitivity (ECS = 5.3 K).

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.296
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; 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 designSimulation or modeling
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

Citations896
Published2019
Admission routes1
Has abstractyes

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