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Record W4220946147 · doi:10.1038/s41467-022-29386-2

Northwestern Pacific tropical cyclone activity enhanced by increased Asian dust emissions during the Little Ice Age

2022· article· en· W4220946147 on OpenAlexaff
Yang Yang, David J. W. Piper, Min Xu, Jianhua Gao, Jianjun Jia, Alexandre Normandeau, Dongdong Chu, Liang Zhou, Ya Ping Wang, Shu Gao

Bibliographic record

VenueNature Communications · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTropical and Extratropical Cyclones Research
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaBedford Institute of Oceanography
FundersGovernment of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsTropical cycloneAsian DustEnvironmental scienceClimatologyOceanographyAtmospheric sciencesGeographyMeteorologyGeologyAerosol

Abstract

fetched live from OpenAlex

Instrumental records reveal that intense tropical cyclone (TC) activity varies with tropical sea surface temperature (SST) on annual-decadal scales. Drivers of intense TC activity at the centennial-millennial scale are less clear, due to the sparseness of pre-observational reconstructions. Here, we present a new 2 kyr continuous activity record of intense TCs from offshore eastern China. Our reconstruction indicates that this site witnessed enhanced TC activity during relatively warm periods, with a widespread increase in TC activity during the later part of the Little Ice Age. This latter observation reveals that enhanced TC activity was synchronized with increased Asian dust emissions during the Little Ice Age. TC activity was also lower in the late Roman Warm Period, when SST was higher but Asian dust emissions were lower than in the early phase. Such patterns suggest a centennial-millennial link between TC climatology and a combination of SST changes and Asian dust levels.

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, Research integrity, 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 score0.097
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.003
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 head0.014
GPT teacher head0.261
Teacher spread0.246 · 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

Citations37
Published2022
Admission routes1
Has abstractyes

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