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Record W2162403566 · doi:10.5194/cp-3-355-2007

Historical droughts in Mediterranean regions during the last 500 years: a data/model approach

2007· article· en· W2162403566 on OpenAlexaff
Simon Brewer, Samuel Alleaume, Joël Guiot, Antoine Nicault

Bibliographic record

VenueClimate of the past · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsClimatologyEnvironmental scienceMediterranean climateWesterliesForcing (mathematics)Atmospheric circulationClimate modelGeneral Circulation ModelCommon spatial patternGreenhouse gasIrradianceClimate changeProxy (statistics)Atmospheric sciencesGeologyGeographyMathematicsStatistics

Abstract

fetched live from OpenAlex

Abstract. We present here a new method for comparing the output of General Circulation Models (GCMs) with proxy-based reconstructions, using time series of reconstructed and simulated climate parameters. The method uses k-means clustering to allow comparison between different periods that have similar spatial patterns, and a fuzzy logic-based distance measure in order to take reconstruction errors into account. The method has been used to test two coupled ocean-atmosphere GCMs over the Mediterranean region for the last 500 years, using an index of drought stress, the Palmer Drought Severity Index. The results showed that, whilst no model exactly simulated the reconstructed changes, all simulations were an improvement over using the mean climate, and a good match was found after 1650 with a model run that took into account changes in volcanic forcing, solar irradiance, and greenhouse gases. A more detailed investigation of the output of this model showed the existence of a set of atmospheric circulation patterns linked to the patterns of drought stress: 1) a blocking pattern over northern Europe linked to dry conditions in the south prior to the Little Ice Age (LIA) and during the 20th century; 2) a NAO-positive like pattern with increased westerlies during the LIA; 3) a NAO-negative like period shown in the model prior to the LIA, but that occurs most frequently in the data during the LIA. The results of the comparison show the improvement in simulated climate as various forcings are included and help to understand the atmospheric changes that are linked to the observed reconstructed climate changes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.308

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.053
GPT teacher head0.255
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations39
Published2007
Admission routes1
Has abstractyes

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