Impacts of Urban Expansion on the Diurnal Variations of Summer Monsoon Precipitation Over the South China Coast
Bibliographic record
Abstract
Abstract This study investigates the possible relationship between changes in monsoonal (May–June) rainfall diurnal variations over the south China coast and urban surface processes using hourly rain gage data during 1981–2014 and semi‐idealized numerical simulations. The continuous landward penetration of regional climatic rainband observed prior to urbanization is blocked by the city. The morning precipitation initiated at the coast “jumps” to the downstream area of city in the late afternoon, causing a 2 hr delay of the rainfall peak time. Simulations clearly reproduce this change by turning off/on the urban land use, and demonstrate a direct connection between the change of rainfall diurnal variations with a magnitude‐enhancing but slower‐penetrating sea breeze as well as the thermodynamic conditions modified by the city. Individual impacts of sensible heating, evapotranspiration, and friction from urban surface are examined using various sensitivity experiments. Urban sensible heat is found to act as the energy source to enhance the sea breeze and induce the asymmetric low‐level urban inflow that blocks the penetration of sea breeze and changes the rainfall location. Evapotranspiration and latent heat flux suppressed by the impervious urban surface causes a drier boundary layer and lower CAPE over the city. The “jumping” of the climatic rainband may result from the competing interaction of the dynamic and thermodynamic factors. Urban friction has little impact on the daytime rainfall, but could slow down seaward wind speed and enhance coastal convergence in the early morning if no strong urban heat island is present.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".