Determination of the chemical equator from GEOS-Chem model simulation: a focus on the tropical western Pacific region
Bibliographic record
Abstract
The tropical western Pacific (TWP) plays an important role in global stratosphere–troposphere exchange and is an active region of the interhemispheric transport (IHT). Common indicators for transport between the hemispheres like the tropical rain belt are too broad or lack precision in the TWP. In this paper, we provide a method to determine the atmospheric chemical equator (CE), which is a boundary for air mass transport between the two hemispheres in the tropics. This method used the model output from an artificial passive tracer simulated by the chemical transport model GEOS-Chem in the troposphere. We investigated the movement of the CE in the tropics, which indicates the migration of atmospheric circulation systems and air mass origins. Our results show the CE on different timescales, suggesting that the different features of the IHT in different regions are highly related to the variation in the circulation systems. We compared the CE with the tropical wind fields, indicating that the region of IHT does not coincide with the convergence of the 10 m wind fields in the tropical land sectors and the TWP region. We compared the CE with the atmospheric composition such as satellite data of CH 4 and model simulation of sulfur hexafluoride (SF 6 ). The results show that the CE and north–south gradient of CH 4 in the Indian Ocean in January are well consistent with each other, which indicates the CE has good potential to estimate the IHT inferred by observations. We discussed the vertical extent and the meridional extent of the IHT. We find that the vertical structure above 2 km has a slight northern tilt in the Northern Hemisphere (NH) winter season and a southern tilt in the NH summer, meaning the seasonality of the migration of the CE at the lower altitude is larger than that at the higher altitude. The meridional extent of the CE indicates a narrow transition zone where IHT happens throughout the year. We find that the meridional extent above South America is larger compared to other regions. The distribution of the land–sea contrast plays an important role in the meridional extent of IHT. We focus on the TWP region and further compared the tropical rain belt with the CE. There is a broad region of high precipitation occurring in the TWP region, and it is difficult to determine the IHT by the rain belt. In the NH winter, the CE is not consistent with the tropical rain belt in the TWP but is confined to the southern branch of the peak of the rain belt. For the other seasons, both indicators of IHT agree.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".