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Record W4200270660 · doi:10.1002/essoar.10508160.1

Three Modes of Cloud-Boundary Layer Coupling over the Southern Ocean: Performance of Conventional and Mass-flux PBL Schemes

2021· preprint· en· W4200270660 on OpenAlexaff
Xiao‐Ming Hu, Greg M. McFarquhar, Wei Wu, Ming Xue

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicClimate variability and models
Canadian institutionsImpact
Fundersnot available
KeywordsMesoscale meteorologyCloud computingFlux (metallurgy)Coupling (piping)Boundary layerBoundary (topology)MeteorologyPlanetary boundary layerPhysicsComputer scienceEngineeringMaterials scienceMathematicsOperating systemTurbulenceMechanical engineering

Abstract

fetched live from OpenAlex

While the continental planetary boundary layer (PBL) structure and model capability to simulate it are relatively well understood, its structure and the ability of models to simulate it over the Southern Ocean (SO), especially in the presence of clouds, are less known. In this study, in situ soundings and remote sensing data collected from ships during two field campaigns over the SO, the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean (MARCUS) and the Clouds Aerosols Precipitation Radiation and atmospheric Composition over the Southern Ocean (CAPRICORN) campaigns, and WRF simulations with different PBL schemes are examined to study the boundary layer structure over the SO, focusing particularly on the coupling status between the surface-based boundary layer and the single cloud layer above. Ten single cloud layer cases, including Dec. 1, 2017, Mar. 21-22, 2018, Mar. 23, 2018, Jan. 10, 2018 detected during MARCUS, and Feb. 17-18, 2018 detected during CAPRICORN, are examined. The cloud-boundary layer coupling over the SO for these cases can be classified into three modes: Coupled cloud-boundary layer in the presence of weak surface positive flux; Decoupled cloud-boundary layer in the presence of surface negative flux, with a very shallow surface-based PBL; and Decoupled cloud-boundary layer in the presence of single-layer high clouds and stronger surface positive flux, with thicker surface-based PBL. WRF simulations were conducted for these selected cases using different PBL schemes, including the Yonsei University (YSU) scheme with and without extra mixing and entrainment induced by cloud-top cooling (referred to as YSUtopdown when the cloud-top cooling treatment is included), the Mellor–Yamada Nakanishi and Niino (MYNN) scheme, and the MYNN scheme with the eddy-diffusivity (ED) local closure and mass flux (MF) nonlocal approach (referred to as MYNN-EDMF). For cases with the different cloud-boundary layer coupling modes, different PBL schemes provided the best consistency with observations. The MYNN-EDMF scheme is more consistent with observations than the conventional PBL schemes for the type 3 coupling mode because of the different vertical extent of local mixing and nonlocal mass flux in presence of sufficient surface flux. The YSUtopdown scheme has more consistency with observations than the YSU scheme for the type 1 coupling mode to simulate higher cloud-topped boundary layer. For the type 2 coupling mode, the different PBL schemes perform similarly.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.028
GPT teacher head0.246
Teacher spread0.218 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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