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Record W3036095670 · doi:10.5194/acp-21-3255-2021

Convective uplift of pollution from the Sichuan Basin into the Asian monsoon anticyclone during the StratoClim aircraft campaign

2021· article· en· W3036095670 on OpenAlexaff
Keun-Ok Lee, Brice Barret, É. Le Flochmoën, Pierre Tulet, Silvia Bucci, Marc von Hobe, Corinna Kloss, Bernard Legras, Maud Leriche, Bastien Sauvage, F. Ravegnani, A. Ulanovsky

Bibliographic record

VenueAtmospheric chemistry and physics · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Environment Research CouncilFP7 Ideas: European Research CouncilEuropean Centre for Medium-Range Weather ForecastsBundesministerium für Bildung und ForschungIndo-French Centre for the Promotion of Advanced ResearchAgence Nationale de la RechercheEuropean Commission
KeywordsAnticycloneMonsoonTroposphereEast Asian MonsoonStratosphereConvectionClimatologyEnvironmental scienceTropopauseAtmospheric sciencesDeep convectionGeologyMeteorologyGeography

Abstract

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Abstract. The StratoClim airborne campaign took place in Nepal from 27 July to 10 August 2017 to document the physical and chemical properties of the South Asian upper troposphere–lower stratosphere (UTLS) during the Asian summer monsoon (ASM). In the present paper, simulations with the Meso-NH cloud-chemistry model at a horizontal resolution of 15 km are performed over the Asian region to characterize the impact of monsoon deep convection on the composition of Asian monsoon anticyclone (AMA) and on the formation of the Asian tropopause aerosol layer (ATAL) during the StratoClim campaign. StratoClim took place during a break phase of the monsoon with intense convective activity over South China and Sichuan. Comparisons between brightness temperatures (BTs) at 10.8 µm observed by satellite sensors and simulated by Meso-NH highlight the ability of the model to correctly reproduce the life cycle of deep convective clouds. A comparison between CO and O3 concentrations from Meso-NH and airborne observations (StratoClim and IAGOS (In-service Aircraft for a Global Observing System)) demonstrates that the model captures most of the observed variabilities. Nevertheless, for both gases, the model tends to overestimate the concentrations and misses some thin CO plumes related to local convective events probably because the resolution is too coarse, but the convective uplift of pollution is very well captured by the model. We have therefore focused on the impact of Sichuan convection on the AMA composition. A dedicated sensitivity simulation showed that the 7 August convective event brought large amounts of CO deep into the AMA and even across the 380 K isentropic level located at 17.8 km. This Sichuan contribution enhanced the CO concentration by ∼15 % to reach more than 180 ppbv over a large area around 15 km height. It is noteworthy that Meso-NH captures the impact of the diluted Sichuan plume on the CO concentration during a StratoClim flight south of Kathmandu, highlighting its ability to reproduce the transport pathway of Sichuan pollution. According to the model, primary organic aerosol and black carbon particles originating from Sichuan are transported following the same pathway as CO. The large particles are heavily scavenged within the precipitating part of the convective clouds but remain the most important contributor to the particle mass in the AMA. Over the whole AMA region, the 7 August convective event resulted in a 0.5 % increase in CO concentration over the 10–20 km range that lasted about 2 d. The impact of pollution uplift from three regions (India, China, and Sichuan) averaged over the first 10 d of August has also been evaluated with sensitivity simulations. Even during this monsoon break phase, the results confirm the predominant role of India relative to China with respective contributions of 11 % and 7 % to CO concentration in the 10–15 km layer. Moreover, during this period a large part (35 %) of the Chinese contribution comes from the Sichuan Basin alone.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.211

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 communication0.0010.000
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 head0.005
GPT teacher head0.186
Teacher spread0.181 · 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 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

Citations10
Published2021
Admission routes1
Has abstractyes

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