Springtime transitions of NO<sub>2</sub>, CO, and O<sub>3</sub> over North America: Model evaluation and analysis
Bibliographic record
Abstract
Surface observations from AIRNow and Southeastern Aerosol Research and Characterization Study networks, aircraft observations from the Measurement of Ozone and Water Vapor by Airbus In‐Service Aircraft program, ozonesondes, and remote sensing measurements from Global Ozone Mapping Experiment, Total Ozone Mapping Spectrometer (TOMS), and Stratospheric Aerosol and Gas Experiment (SAGE) II for February–May 2000 over North America are used to characterize the springtime transitions of O3 and its precursors. These measurements provide a comprehensive data set to evaluate the performance of the 3‐D Regional Chemical Transport Model (REAM). The model is then applied to analyze the key factors affecting the springtime transitions of trace gas concentrations and export. The global GEOS‐CHEM model is used to provide chemical initial and boundary conditions. Generally, the model results are in good agreement with the observations in the troposphere except for a low bias of upper tropospheric O3; the bias decreases toward the summer and lower latitudes. The rate of observed surface O3 increase in spring is simulated well by REAM. It is overestimated by GEOS‐CHEM over the eastern United States. A key factor driving the model difference is daytime mixing depth. A shallow boundary layer in REAM leads to more efficient removal of radicals and hence slower activation of photochemistry in spring, when the primary radical source is relatively small. Comparison of top‐down estimates of fossil fuel NOx emissions between REAM and GEOS‐CHEM shows model dependence. The associated uncertainty is up to 20% on a monthly basis. Averaging over a season reduces this uncertainty. While tropospheric column NO2 decreases over the continent, it increases over the western North Atlantic due to lightning NOx production. Consequently, the REAM model simulates significant increases of tropospheric O3 over the region as indicated by column data derived from TOMS‐SAGE II. Lightning impact is also evident in model‐simulated NOx exports.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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".