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Record W4220920828 · doi:10.5194/egusphere-egu22-2891

On the potential impact of the Great Green Wall on the West African Monsoon 

2022· preprint· en· W4220920828 on OpenAlexaff
Roberto Ingrosso, Francesco Rocco Salvatore Pausata

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicClimate change impacts on agriculture
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsClimatologyPrecipitationTropical monsoon climateMonsoonDesertificationClimate changeEnvironmental scienceAtmospheric circulationClimate modelGeographyGeneral Circulation ModelOceanographyMeteorologyGeologyEcology

Abstract

fetched live from OpenAlex

The Great GreenWall (GGW) is a multibillion-dollar African initiative to combat desertification and drought in the Sahel. In Western Africa, the most important climate feature is the West African Monsoon (WAM), which brings rainfall over the Sahel during the Northern Hemisphere summer. Changes in WAM strength and length could impact climate both regionally and far afield, such as the tropical Atlantic, equatorial Pacific or the Arctic, Potential climatic system response to a greener Sahel are investigated, by means of an atmospheric climate model, looking at changes in the regional atmospheric circulation and climate indices aimed at providing information about changes in extreme events. The analysis shows significant changes in temperature, precipitation and atmopsheric circulation and in the climate indices considered related to the presence of the GGW for the end of this century.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.068
GPT teacher head0.268
Teacher spread0.200 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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