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Record W3035344058 · doi:10.5194/gmd-14-495-2021

A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54

2021· article· en· W3035344058 on OpenAlexfundno aff
Tamara Emmerichs, Astrid Kerkweg, H. G. Ouwersloot, Silvano Fares, Ivan Mammarella, Domenico Taraborrelli

Bibliographic record

VenueGeoscientific model development · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersEnvironment and Climate Change CanadaInstituto Nacional de Pesquisas da AmazôniaFinanciadora de Estudos e ProjetosMax-Planck-GesellschaftEuropean CommissionMinistério da Ciência, Tecnologia e InovaçãoFundação de Amparo à Pesquisa do Estado do AmazonasBundesministerium für Bildung und ForschungHelsingin YliopistoU.S. Environmental Protection Agency
KeywordsTrace gasTroposphereAtmospheric sciencesTropospheric ozoneEnvironmental scienceDeposition (geology)Atmospheric chemistryAtmosphere (unit)Sink (geography)Boundary layerPlanetary boundary layerOzoneMeteorologyClimatologyGeologyTurbulenceGeographyPhysics

Abstract

fetched live from OpenAlex

Abstract. Dry deposition to vegetation is a major sink of ground-level ozone and is responsible for about 20 % of the total tropospheric ozone loss. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for the global tropospheric ozone budget and might account for the mismatch with observations. The model used in this study, the Modular Earth Submodel System version 2 (MESSy2) linked to the fifth-generation European Centre Hamburg general circulation model (ECHAM5) as an atmospheric circulation model (EMAC), is no exception. Like many global models, EMAC employs a “resistance in series” scheme with the major surface deposition via plant stomata which is hardly sensitive to meteorology, depending only on solar radiation. Unlike many global models, however, EMAC uses a simplified high resistance for non-stomatal deposition which makes this pathway negligible in the model. However, several studies have shown this process to be comparable in magnitude to the stomatal uptake, especially during the night over moist surfaces. Hence, we present here a revised dry deposition in EMAC including meteorological adjustment factors for stomatal closure and an explicit cuticular pathway. These modifications for the three stomatal stress functions have been included in the newly developed MESSy VERTEX submodel, i.e. a process model describing the vertical exchange in the atmospheric boundary layer, which will be evaluated for the first time here. The scheme is limited by a small number of different surface types and generalized parameters. The MESSy submodel describing the dry deposition of trace gases and aerosols (DDEP) has been revised accordingly. The comparison of the simulation results with measurement data at four sites shows that the new scheme enables a more realistic representation of dry deposition. However, the representation is strongly limited by the local meteorology. In total, the changes increase the dry deposition velocity of ozone up to a factor of 2 globally, whereby the highest impact arises from the inclusion of cuticular uptake, especially over moist surfaces. This corresponds to a 6 % increase of global annual dry deposition loss of ozone resulting globally in a slight decrease of ground-level ozone but a regional decrease of up to 25 %. The change of ozone dry deposition is also reasoned by the altered loss of ozone precursors. Thus, the revision of the process parameterization as documented here has, among others, the potential to significantly reduce the overestimation of tropospheric ozone in global models.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.004

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 head0.024
GPT teacher head0.222
Teacher spread0.198 · 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 source (direct Gemma or distilled Codex), 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

Citations41
Published2021
Admission routes1
Has abstractyes

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