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Record W4281287433 · doi:10.1080/07055900.2022.2077170

Modulation of the Atmospheric Heat Source Over the Tibetan Plateau on the Intra-seasonal Oscillation of Summer Precipitation in the Yangtze-Huaihe River Basin

2022· article· en· W4281287433 on OpenAlexvenueno aff
Shanshan Zhong, Hao Wang, Bing Chen, Hua Chen

Bibliographic record

VenueATMOSPHERE-OCEAN · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsTropospherePrecipitationEnvironmental scienceTrough (economics)ClimatologyWater vaporAtmospheric sciencesPlateau (mathematics)GeologyMeteorologyGeography

Abstract

fetched live from OpenAlex

Based on the daily precipitation from China Meteorological Administration and the daily atmospheric circulation data from the Japanese 55-year Reanalysis (JRA-55) from 1979 to 2018, this paper analyzes the evolution of 10-30-day intra-seasonal oscillation (ISO) of the precipitation in the Yangtze-Huaihe River Basin (YHRB) and the modulation of the atmospheric heat source over the Tibetan Plateau (TP) with different intensity on the peak and trough values of the precipitation in the YHRB. When the atmospheric heating is strong on the southern flank of TP (STP), the lower-level anomalous low strengthens on the STP, which leads to convergence of airflow in the lower troposphere, ascent and divergence in the upper troposphere. Thus, the intense pumping action on the STP results in the convergence of water vapour from the Bay of Bengal to the STP. Due to the high altitude of TP, the water vapour turns eastward and increases the convergence and ascent of water vapour in the YHRB, which is conductive to enhancement of the peak values or weakening of trough values of the ISO of precipitation in the YHRB. When the STP heating is weak, the lower-level anomalous low decreases on the STP, leading to divergence in the lower troposphere, descent and convergence in the upper troposphere. Then the convergence of water vapour from the Bay of Bengal to the STP is suppressed and the transport of water vapour to the YHRB is interrupted, thus the peak values of precipitation are weakened or the trough are enhanced.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.219
Teacher spread0.205 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueATMOSPHERE-OCEANSame topicClimate variability and modelsFrench-language works237,207