Temporal variations of atmospheric carbon dioxide in the southernmost part of Japan
Bibliographic record
Abstract
We present analysis of the temporal variation of atmospheric CO2 in the subtropical region of East Asia, obtained aboard a ferry between Ishigaki Island and Hateruma Island, Japan for the period June 1993–April 2005. The annual mean CO2 concentration increases from 360.1 ppmv in 1994 to 378.4 ppmv in 2004, showing an average growth rate of 1.8 ppmv yr-1. The growth rate shows interannual variations with high values duringENSOevents. The average seasonal CO2 cycle reaches the maximum in early April and the minimum in mid-September, with a peak-to-peak amplitude of 8.5 ppmv. Numerical simulations using a three-dimensional atmospheric transport model show interannual variations of the CO2 growth rate similar to the observation, but the amplitude of the seasonal cycle is larger, with maximum concentration appearing earlier than the observation by 1 month. Low CO2 values observed during the spring of 1998 are likely associated with the 1997/1998 ENSO event. A backward trajectory analysis suggests that they were due to changes in atmospheric transport whereby maritime air masses from the Pacific Ocean dominated over polluted air masses from the Asian Continent. Extreme values (either high or low) of CO2 are also occasionally observed. A comparison of backward trajectories of air parcels with CO2 concentration fields calculated using the atmospheric transport model shows that these unusual CO2 concentrations result from the transport of air affected not only by anthropogenic CO2 emissions but also by terrestrial biospheric activities mainly in China.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".