Summertime impact of convective transport and lightning NO <sub>x</sub> production over North America: modeling dependence on meteorological simulations
Bibliographic record
Abstract
Abstract. Global-scale chemical transport model simulations indicate lightning NOx dominates upper tropospheric O3 production above Eastern North America during summertime but vary in their estimates. To improve our understanding, a regional-scale model (REAM) with higher resolution is applied. To examine the uncertainties in modeling the impact of convective transport and lightning NOx production on upper tropospheric chemical tracer distributions, REAM simulations of chemical tracers are driven by two meteorological models, WRF and MM5, with different cumulus convective parameterizations. The model simulations are evaluated using INTEX-A aircraft measurements and satellite measurements of NO2 columns and cloud top pressure, and we find that mid and upper tropospheric trace gas concentrations are affected strongly by convection and lightning NOx production. WRF with the KF-eta convection scheme simulates larger convective updraft mass fluxes below 150 hPa than MM5 with the Grell scheme. The inclusion of the entrainment and detrainment processes leads to more outflow in the mid troposphere in WRF than MM5. The ratio of C2H6/C3H8 is found to be a sensitive parameter to convective outflow; the simulation by WRF-REAM is in closer agreement with INTEX-A measurements than MM5-REAM, implying that convective mass fluxes by WRF are more realistic. WRF also simulates lower cloud top heights (10–12 km) than MM5 (up to 16 km), and hence smaller amounts of estimated (intra-cloud) lightning NOx and lower emission altitudes. WRF simulated cloud top heights are in better agreement with GOES satellite measurements than MM5. Simulated lightning NOx production difference (due primarily to cloud top height difference) is mostly above 12 km. At 8–12 km, the models simulate a contribution of 60–75% of NOx and up to 20 ppbv of O3 from lightning, although the decrease of lightning NOx effect from the Southeast to Northeast and eastern Canada is overestimated. The model differences and biases found in this study reflect some major uncertainties of upper tropospheric NOx and O3 simulations driven by those in meteorological simulations and lightning parameterizations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".