MétaCan
Menu
← Back to cohort
Record W3175958960 · doi:10.5194/egusphere-egu21-1842

Comparing temperature trends and variability over the Holocene in climate models of low and high complexity

2021· article· en· W3175958960 on OpenAlexaff
Christian Wirths, Elisa Ziegler, Matthew Toohey, Julie Schindlbeck-Belo, Steffen Kutterolf, Heather Anders, Kira Rehfeld

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsMemorial University of NewfoundlandUniversity of Saskatchewan
Fundersnot available
KeywordsHoloceneClimate changeGlobal warmingClimatologyClimate modelGreenhouse gasAtmospheric sciencesChemistryEndocrinologyEnvironmental scienceInternal medicineGeologyOceanographyBiologyMedicine

Abstract

fetched live from OpenAlex

Modeled and observed temperature trends over the Holocene disagree. Proxy reconstructions suggest global cooling during the late Holocene. Model simulations, on the other hand, show a warming trend for the entire Holocene, a contradiction known as the Holocene temperature conundrum. A recent study by Bader et. al. (2020) introduced a new approach to the question by proposing the coexistence of a cooling and warming climate mode. While the warming mode is proposed to be related to changes in greenhouse gas concentrations, the physical process behind the cooling mode might be a change in the seasonal cycle of Arctic sea-ice. It’s unclear to what extent this process is responsible for the observed climate response. Depending on their strength and location these modes have strong implications for proxy data interpretation and location selection when calculating global mean temperatures. Here, we investigate if similar modes and temperature trends can be found in models of different complexity. Therefore, we use a 2D Energy Balance Model (EBM), with solar, volcanic, ice-sheet and greenhouse gas forcing, for transient simulations of the Holocene climate. We analyze these Holocene climate simulations in terms of global and regional temperature trends, modes and variability patterns. We conduct sensitivity tests to examine the influence of the forcings on those trends and modes. In particular, we are interested in the influence of volcanic eruptions on the Holocene climate. Furthermore, we compare our model results with temperature reconstructions and simulations from Earth System Models. Altogether, we comprehensively analyze Holocene climate as simulated by a conceptual EBM, a state-of-the-art Earth System Model and proxy reconstructions. The results provide insight into whether models of different complexity produce similar modes and trends and whether these occur due to climate forcing rather than internal processes of the earth system. Finally, we will provide a better understanding of Holocene cooling and warming and the interpretation of differences between Holocene temperature proxy reconstructions and climate model simulations. References: Bader, J., Jungclaus, J., Krivova, N. et al. Global temperature modes shed light on the Holocene temperature conundrum. Nat Commun 11, 4726 (2020). https://doi.org/10.1038/s41467-020-18478-6

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)0.003
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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.230
Teacher spread0.209 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicMethane Hydrates and Related Phenomena→French-language works237,207→