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Record W3184098272 · doi:10.1175/jcli-d-20-0547.1

Projections of South Asian Summer Monsoon Under Global Warming from 1.5° to 5°C

2021· article· en· W3184098272 on OpenAlexfundaboutno aff
Zhibo Li, Ying Sun, Tim Li, Wen Chen, Yihui Ding

Bibliographic record

VenueJournal of Climate · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsnot available
FundersNational Natural Science Foundation of ChinaGovernment of CanadaNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsClimatologyEnvironmental scienceForcing (mathematics)PrecipitationMonsoonAdvectionAnticycloneAtmospheric sciencesPrecipitable waterSouth asiaClimate changeGeologyGeographyMeteorologyOceanography

Abstract

fetched live from OpenAlex

Abstract The South Asian summer monsoon (SASM) is one of the most crucial climate components in boreal summer. The future potential changes in the SASM have great importance for climate change adaption and policy setting in this populous region. To understand the SASM changes and its link with the global warming of 1.5°C to 5°C above the preindustrial level, we investigate the changes in the SASM circulation and precipitation based on a large-ensemble simulation conducted with Canadian Earth System Model version 2 (CanESM2). With the global mean surface temperature (GMST) increase, the large-ensemble mean of SASM circulation is projected to weaken almost linearly while the precipitation and precipitable water to enhance quasi-linearly. A double anticyclone along the tropical Indian Ocean is a major anomalous circulation pattern for each additional degree of warming and is responsible for the weakening of the lower-level westerlies. The decreased upper-level land-sea thermal contrast (TCupper) is the main thermal driver for the weakening of the SASM circulation while the lower-level thermal contrast contributes little. The non-linearly decreased TCupper is mainly related to the temperature response to the increased CO2 forcing and convection induced latent heat release in the tropics. The increase in the SASM precipitation is mainly due to the quasi-linearly increased positive contribution of the thermodynamic component, while the dynamic component has a negative impact. Both horizontal moisture advection and moisture convergence contribute to the precipitation increase, and moisture convergence plays a dominant role. These results provide new insight that the SASM changes can be roughly scaled by the GMST 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 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)0.000
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 score0.351
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.294
Teacher spread0.259 · 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

Citations16
Published2021
Admission routes2
Has abstractyes

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