The North American Mercury Model Intercomparison Study (NAMMIS): Study description and model‐to‐model comparisons
Bibliographic record
Abstract
An atmospheric mercury model intercomparison study has been conducted to compare three regional‐scale atmospheric mercury models, CMAQ, REMSAD, and TEAM, in a tightly constrained testing environment with a focus on North America. Each of these models used the same horizontal modeling grid, pollutant emission information, modeled meteorology, and boundary conditions to the greatest extent practical. Three global‐scale atmospheric mercury models were applied to define three separate initial condition and boundary condition (IC/BC) data sets for elemental mercury, reactive gaseous mercury, and particulate mercury air concentrations for use by the regional‐scale models. The monthly average boundary concentrations of some mercury species simulated by the global models were found to vary by more than a factor of 10, especially at high altitudes. CMAQ, REMSAD, and TEAM were each applied three times, once for each IC/BC data set, to simulate atmospheric mercury transport and deposition during 2001. This paper describes the study design and shows qualitative model‐to‐model comparisons of simulation results on an annual basis. The air concentration patterns for mercury simulated by the regional‐scale models showed significant differences even when the same IC/BC data set was used. Simulated wet deposition of mercury was strongly influenced by the shared precipitation data, but differences of over 50% were still apparent. Simulated dry deposition of mercury was found to vary between the regional‐scale models by nearly a factor of 10 in some locations. Further analysis is underway to perform statistical comparisons of simulated and observed mercury wet deposition using weekly and annual sample integration periods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".