Evaluation and improvements of two community models in simulating dry deposition velocities for peroxyacetyl nitrate (PAN) over a coniferous forest
Bibliographic record
Abstract
Dry deposition velocities (Vd) for peroxyacetyl nitrate (PAN) calculated using two community dry deposition models with different treatments of both stomatal and nonstomatal uptakes were evaluated using measurements of PAN eddy covariance fluxes over a Loblolly pine forest in July 2003. The observed daytime maximum of Vd(PAN) was ∼1.0 cm s−1on average, while the estimates by the WRF‐Chem dry deposition module (WDDM) and the Noah land surface model coupled with a photosynthesis‐based Gas Exchange Model (Noah‐GEM) were only 0.2 cm s−1 and 0.6 cm s−1, respectively. The observations also showed considerable PAN deposition at night with typical Vd values of 0.2–0.6 cm s−1, while the estimated values from both models were less than 0.1 cm s−1. Noah‐GEM modeled more realistic stomatal resistance (Rs) than WDDM, as compared with observations of water vapor exchange fluxes. The poor performance of WDDM for stomatal uptake is mainly due to its lack of dependence on leaf area index. Thermal decomposition was found to be relatively unimportant for measured PAN fluxes as shown by the lack of a relationship between measured total surface conductance and temperature. Thus, a large part of the underprediction in Vd from both models should be caused by the underestimation of nonstomatal uptake, in particular, the cuticle uptake. Sensitivity tests on both stomatal and nonstomatal resistances terms were conducted and some recommendations were provided.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".