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Record W2165163954 · doi:10.1002/2014gl059651

Coupling dry deposition to vegetation phenology in the Community Earth System Model: Implications for the simulation of surface O<sub>3</sub>

2014· article· en· W2165163954 on OpenAlexaff
M. Val Martin, Colette L. Heald, S. R. Arnold

Bibliographic record

VenueGeophysical Research Letters · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsDeposition (geology)Environmental scienceVegetation (pathology)Atmospheric sciencesOzonePhenologyAtmospheric modelSeasonalityClimatologyLeaf area indexMeteorologyEcologyGeologyGeography

Abstract

fetched live from OpenAlex

Dry deposition is an important removal process controlling surface ozone. We examine the representation of this ozone loss mechanism in the Community Earth System Model. We first correct the dry deposition parameterization by coupling the leaf and stomatal vegetation resistances to the leaf area index, an omission which has adversely impacted over a decade of ozone simulations using both the Model for Ozone and Related chemical Tracers (MOZART) and Community Atmospheric Model‐Chem (CAM‐Chem) global models. We show that this correction increases O 3 dry deposition velocities over vegetated regions and improves the simulated seasonality in this loss process. This enhanced removal reduces the previously reported bias in summertime surface O 3 simulated over eastern U.S. and Europe. We further optimize the parameterization by scaling down the stomatal resistance used in the Community Land Model to observed values. This in turn further improves the simulation of dry deposition velocity of O 3 , particularly over broadleaf forested regions. The summertime surface O 3 bias is reduced from 30 ppb to 14 ppb over eastern U.S. and 13 ppb to 5 ppb over Europe from the standard to the optimized scheme, respectively. O 3 deposition processes must therefore be accurately coupled to vegetation phenology within 3‐D atmospheric models, as a first step toward improving surface O 3 and simulating O 3 responses to future and past vegetation changes.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.303
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations157
Published2014
Admission routes1
Has abstractyes

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