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Record W4232924093 · doi:10.5194/bg-2019-473

Carbon-concentration and carbon-climate feedbacks in CMIP6 models, and their comparison to CMIP5 models

2019· preprint· en· W4232924093 on OpenAlexaff
Vivek K. Arora, Anna Katavouta, Richard G. Williams, Chris Jones, Victor Brovkin, Pierre Friedlingstein, Jörg Schwinger, Laurent Bopp, Oliviér Boucher, Patricia Cadule, Matthew A. Chamberlain, James R. Christian, Christine Delire, Rosie A. Fisher, Tomohiro Hajima, Tatiana Ilyina, Émilie Joetzjer, Michio Kawamiya, Charles D. Koven, John P. Krasting, R. M. Law, David M. Lawrence, Andrew Lenton, Keith Lindsay, Julia Pongratz, Thomas Raddatz, Roland Séférian, Kaoru Tachiiri, Jerry Tjiputra, Andy Wiltshire, Tongwen Wu, Tilo Ziehn

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Victoria
FundersNatural Environment Research CouncilSight Research UK
KeywordsCoupled model intercomparison projectCarbon cycleEnvironmental scienceEarth system scienceSensitivity (control systems)Climate changeClimate modelClimatologyCarbon fibersAtmospheric sciencesComputer scienceGeologyEcosystemAlgorithm

Abstract

fetched live from OpenAlex

Abstract. Results from the fully-, biogeochemically-, and radiatively-coupled simulations in which CO2 increases at a rate of 1 % per year (1pctCO2) from its pre-industrial value are analyzed to quantify the magnitude of two feedback parameters which characterize the coupled carbon-climate system. These feedback parameters quantify the response of ocean and terrestrial carbon pools to changes in atmospheric CO2 concentration and the resulting change in global climate. The results are based on eight comprehensive Earth system models from the fifth Coupled Model Intercomparison Project (CMIP5) and eleven models from the sixth CMIP (CMIP6). The comparison of model results from two CMIP phases shows that, for both land and ocean, the model mean values of the feedback parameters and their multi-model spread has not changed significantly across the two CMIP phases. The absolute values of feedback parameters are lower for land with models that include a representation of nitrogen cycle. The sensitivity of feedback parameters to the three different ways in which they may be calculated is shown and, consistent with existing studies, the most relevant definition is that calculated using results from the fully- and biogeochemically-coupled configurations. Based on these two simulations simplified expressions for the feedback parameters are obtained when the small temperature change in the biogeochemically-coupled simulation is ignored. Decomposition of the terms of these simplified expressions for the feedback parameters allows identification of the reasons for differing responses among ocean and land carbon cycle models.

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)
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 score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.218
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 teacher head, not a consensus.

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

Citations125
Published2019
Admission routes1
Has abstractyes

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