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Record W2042482931 · doi:10.1002/2014ms000346

The Specified Chemistry Whole Atmosphere Community Climate Model (SC‐WACCM)

2014· article· en· W2042482931 on OpenAlexfundaboutno aff
Karen L. Smith, Ryan R. Neely, D. R. Marsh, Lorenzo M. Polvani

Bibliographic record

VenueJournal of Advances in Modeling Earth Systems · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersNOAA ResearchNatural Sciences and Engineering Research Council of CanadaU.S. Department of EnergyOffice of ScienceNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsAtmosphere (unit)ClimatologyEnvironmental scienceClimate modelOzone layerAtmospheric sciencesMontreal ProtocolStratosphereClimate changeMeteorologyOceanographyGeographyGeology

Abstract

fetched live from OpenAlex

Abstract We here present, document and validate a new atmospheric component of the Community Earth System Model (CESM1): the Specified Chemistry Whole Atmosphere Community Climate Model (SC‐WACCM). As the name implies, SC‐WACCM is a middle atmosphere‐resolving model with prescribed, rather than interactive chemistry. Ozone concentrations are specified throughout the atmosphere, using zonal and monthly mean climatologies computed by a companion integration with the Whole Atmosphere Community Climate Model (WACCM). Above 65 km, in addition, the climatological chemical and shortwave heating, nitrogen oxide, atomic and molecular oxygen and carbon dioxide are also prescribed from the companion WACCM integration. We carefully compare the climatology and the climate variability of preindustrial integrations of SC‐WACCM and WACCM each coupled with active land, ocean and sea‐ice components. We note some differences in upper stratospheric and lower mesospheric temperature, just below the 65 km transition level, due to the diurnal ozone cycle that is not captured when monthly mean ozone is used. Nonetheless, we find that the climatology and variability of the stratosphere, the troposphere and surface climate are nearly identical in SC‐WACCM and WACCM. Notably, the frequency and amplitude of Northern Hemisphere stratospheric sudden warmings in the two integrations are not significantly different. Also, we compare WACCM and SC‐WACCM to CCSM4, the “low‐top” version of CESM1, and we find very significant differences in the stratospheric climatology and variability. The removal of the chemistry reduces the computational cost of SC‐WACCM to approximately one half of WACCM: in fact, SC‐WACCM is only 2.5 times more expensive than CCSM4 at the same horizontal resolution. This considerable reduction in computational cost makes the new SC‐WACCM component of CESM1 ideally suited for studies of stratosphere‐troposphere dynamical coupling and, more generally, the role of the stratosphere in the climate system.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0040.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.017
GPT teacher head0.237
Teacher spread0.219 · 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

Citations112
Published2014
Admission routes2
Has abstractyes

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