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Record W4229458551 · doi:10.1029/2022pa004419

African Hydroclimate During the Early Eocene From the DeepMIP Simulations

2022· article· en· W4229458551 on OpenAlexaff
Charles J. R. Williams, Daniel J. Lunt, Ulrich Salzmann, Tammo Reichgelt, Gordon N. Inglis, David R. Greenwood, Wing‐Le Chan, Ayako Abe‐Ouchi, Yannick Donnadieu, David K. Hutchinson, Agatha M. de Boer, Jean‐Baptiste Ladant, Polina Morozova, Igor Niezgodzki, Gregor Knorr, Sebastian Steinig, Zhongshi Zhang, Jiang Zhu, Matthew Huber, Bette L. Otto‐Bliesner

Bibliographic record

VenuePaleoceanography and Paleoclimatology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsBrandon University
FundersJapan Agency for Marine-Earth Science and TechnologyVetenskapsrådetJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyGrand Équipement National De Calcul IntensifNational Science CouncilSight Research UKNational Supercomputer Centre, Linköpings UniversitetNatural Environment Research CouncilDeutsches Klimarechenzentrum
KeywordsProxy (statistics)PrecipitationClimatologyGeologyClimate changeClimate modelGeographyOceanographyMeteorology

Abstract

fetched live from OpenAlex

Abstract The early Eocene (∼56–48 Myr ago) is characterized by high CO 2 estimates (1,200–2,500 ppmv) and elevated global temperatures (∼10°C–16°C higher than modern). However, the response of the hydrological cycle during the early Eocene is poorly constrained, especially in regions with sparse data coverage (e.g., Africa). Here, we present a study of African hydroclimate during the early Eocene, as simulated by an ensemble of state‐of‐the‐art climate models in the Deep‐time Model Intercomparison Project (DeepMIP). A comparison between the DeepMIP pre‐industrial simulations and modern observations suggests that model biases are model‐ and geographically dependent, however, these biases are reduced in the model ensemble mean. A comparison between the Eocene simulations and the pre‐industrial suggests that there is no obvious wetting or drying trend as the CO 2 increases. The results suggest that changes to the land sea mask (relative to modern) in the models may be responsible for the simulated increases in precipitation to the north of Eocene Africa. There is an increase in precipitation over equatorial and West Africa and associated drying over northern Africa as CO 2 rises. There are also important dynamical changes, with evidence that anticyclonic low‐level circulation is replaced by increased south‐westerly flow at high CO 2 levels. Lastly, a model‐data comparison using newly compiled quantitative climate estimates from paleobotanical proxy data suggests a marginally better fit with the reconstructions at lower levels of CO 2 .

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.205
Teacher spread0.194 · 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 designObservational
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

Citations18
Published2022
Admission routes1
Has abstractyes

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