Is regional air quality model diversity representative of uncertainty for ozone simulation?

Vautard, Robert; Loon, M. van; Schaap, Martijn; Bergström, R. W.; Bessagnet, Bertrand; Brandt, Jørgen; Builtjes, P. J. H.; Christensen, J. H.; Cuvelier, Cornelis; Graff, A.; Jonson, Jan Eiof; Krol, Maarten; Langner, Joakim; Roberts, P.T.; Rouïl, Laurence; Stern, R.; Tarrasón, L.; Thunis, Philippe; Vignati, E.; White, L.; Wind, Peter

doi:10.1029/2006gl027610

Cited by 33 publications

(21 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…When combined with observational data, this allows identification of model weaknesses and a clearer assessment of model reliability. Additionally, ensemble mean results are often found to compare better with observations than those of any one model [e.g., Vautard et al, 2006]. In this chapter we draw on valuable conclusions from previous model intercomparisons, in particular ACCENT/PHOTOCOMP [Dentener et al, 2006], AEROCOM [Textor et al, 2006], TRANSCOM [Law et al, 2008], and RETRO which provide additional insight into the strengths and weaknesses of current models.…”

Section: Role Of Coordinated Model Studiesmentioning

confidence: 92%

Emission inventories and projections

Streets¹,

Aardenne²

2010

Air Pollution Studies

View full text Add to dashboard Cite

Section: Role Of Coordinated Model Studiesmentioning

confidence: 92%

Emission inventories and projections

Streets¹,

Aardenne²

2010

Air Pollution Studies

View full text Add to dashboard Cite

“…Kalnay, 2002) are to (i) improve the forecast by ensemble averaging, (ii) to provide an indication of the reliability of the forecast, and (iii) to provide a quantitative basis for probabilistic forecasting. The spread of predictions in a collection of models can also be used as a measure of the model uncertainty (Vautard et al, 2006). The comparison of the predictions of model ensemble and those of the individual models can also give valuable insight on model performance, e.g.…”

Section: Model Ensemblesmentioning

confidence: 99%

A review of operational, regional-scale, chemical weather forecasting models in Europe

et al. 2012

Self Cite

View full text Add to dashboard Cite

Abstract. Numerical models that combine weather forecasting and atmospheric chemistry are here referred to as chemical weather forecasting models. Eighteen operational chemical weather forecasting models on regional and continental scales in Europe are described and compared in this article. Topics discussed in this article include how weather forecasting and atmospheric chemistry models are integrated into chemical weather forecasting systems, how physical processes are incorporated into the models through parameterization schemes, how the model architecture affects the predicted variables, and how air chemistry and aerosol processes are formulated. In addition, we discuss sensitivity analysis and evaluation of the models, user operational requirements, such as model availability and documentation, and output availability and dissemination. In this manner, this article allows for the evaluation of the relative strengths and weaknesses of the various modelling systems and modelling approaches. Finally, this article highlights the most prominent gaps of knowledge for chemical weather forecasting models and suggests potential priorities for future research Published by Copernicus Publications on behalf of the European Geosciences Union. J. Kukkonen et al.: A review of operational, regional-scale, chemical weather forecasting models in Europedirections, for the following selected focus areas: emission inventories, the integration of numerical weather prediction and atmospheric chemical transport models, boundary conditions and nesting of models, data assimilation of the various chemical species, improved understanding and parameterization of physical processes, better evaluation of models against data and the construction of model ensembles.

show abstract

“…All relevant processes are parameterized in such a way that the computational demands are modest enabling hour-by-hour calculations over extended periods of several years within acceptable CPU time of several days. Scientific studies have been performed to address secondary inorganic aerosol (Schaap et al, 2004a;Erisman and Schaap, 2004), black carbon (Schaap et al, 2004b;Schaap and Denier van der Gon, 2007), sea salt (Manders et al, 2009a(Manders et al, , 2010, particulate matter (PM) (Manders et al, 2009b), and ozone (Vautard et al, 2006;Schaap et al, 2008). The model has participated frequently in international model comparisons aimed at ozone (Van Loon et al, 2007;Hass et al, 2003), PM Stern et al, 2008) and source-receptor matrices (Thunis and Cuvelier, 2008).…”

Section: Lotos-euros Model Descriptionmentioning

confidence: 99%

Modeling the distribution of ammonia across Europe including bi-directional surface–atmosphere exchange

Kruit

Schaap

Sauter³

et al. 2012

Biogeosciences

Self Cite

116

101

View full text Add to dashboard Cite

Abstract.A large shortcoming of current chemistry transport models (CTM) for simulating the fate of ammonia in the atmosphere is the lack of a description of the bi-directional surface-atmosphere exchange. In this paper, results of an update of the surface-atmosphere exchange module DEPAC, i.e. DEPosition of Acidifying Compounds, in the chemistry transport model LOTOS-EUROS are discussed. It is shown that with the new description, which includes bi-directional surface-atmosphere exchange, the modeled ammonia concentrations increase almost everywhere, in particular in agricultural source areas. The reason is that by using a compensation point the ammonia lifetime and transport distance is increased. As a consequence, deposition of ammonia and ammonium decreases in agricultural source areas, while it increases in large nature areas and remote regions especially in southern Scandinavia. The inclusion of a compensation point for water reduces the dry deposition over sea and allows reproducing the observed marine background concentrations at coastal locations to a better extent. A comparison with measurements shows that the model results better represent the measured ammonia concentrations. The concentrations in nature areas are slightly overestimated, while the concentrations in agricultural source areas are still underestimated. Although the introduction of the compensation point improves the model performance, the modeling of ammonia remains challenging. Important aspects are emission patterns in space and time as well as a proper approach to deal with the high concentration gradients in relation to model resolution. In short, the inclusion of a bi-directional surface-atmosphere exchange is a significant step forward for modeling ammonia.

show abstract

Is regional air quality model diversity representative of uncertainty for ozone simulation?

Cited by 33 publications

References 25 publications

Emission inventories and projections

Emission inventories and projections

A review of operational, regional-scale, chemical weather forecasting models in Europe

Modeling the distribution of ammonia across Europe including bi-directional surface–atmosphere exchange

Contact Info

Product

Resources

About