Modeling the impact of sub-grid scale emission variability on upper-air concentration

Galmarini, Stefano; Vinuesa, J.-F.; Martilli, Alberto

doi:10.5194/acp-8-141-2008

Cited by 19 publications

(14 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Future steps are to implement this parameterization in an inverse modeling system and to assess, using pseudo-data experiments, to what degree biases in retrieved fluxes due to representation errors can be avoided. A further refinement of the method will be to treat the subgrid variance as a tracer itself, allowing for advection of subgrid variance within the coarse transport models similar to the study by Galmarini et al (2008), with the difference that the focus is not on microscale, but rather on mesoscale variability. This would probably allow to better describing the representation error over the ocean near the coasts, which with the current linear (local) model cannot be described.…”

Section: Discussionmentioning

confidence: 99%

High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

et al. 2010

View full text Add to dashboard Cite

Abstract. Satellite retrievals for column CO 2 with better spatial and temporal sampling are expected to improve the current surface flux estimates of CO 2 via inverse techniques. However, the spatial scale mismatch between remotely sensed CO 2 and current generation inverse models can induce representation errors, which can cause systematic biases in flux estimates. This study is focused on estimating these representation errors associated with utilization of satellite measurements in global models with a horizontal resolution of about 1 degree or less. For this we used simulated CO 2 from the high resolution modeling framework WRF-VPRM, which links CO 2 fluxes from a diagnostic biosphere model to a weather forecasting model at 10×10 km 2 horizontal resolution. Sub-grid variability of column averaged CO 2 , i.e. the variability not resolved by global models, reached up to 1.2 ppm with a median value of 0.4 ppm. Statistical analysis of the simulation results indicate that orography plays an important role. Using sub-grid variability of orography and CO 2 fluxes as well as resolved mixing ratio of CO 2 , a linear model can be formulated that could explain about 50% of the spatial patterns in the systematic (bias or correlated error) component of representation error in column and near-surface CO 2 during day-and night-times. These findings give hints for a parameterization of representation error which would allow for the representation error to taken into account in inverse models or data assimilation systems.

show abstract

Section: Discussionmentioning

confidence: 99%

High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

et al. 2010

View full text Add to dashboard Cite

show abstract

“…Cook et al [61] discuss the development of local scale emissions for hybrid modeling to simulate air quality near roadways. Other hybrid modeling approaches are discussed in [62][63][64]. The application of hybrid modeling to predict the local-scale air quality impacts of airport emissions is discussed in [65,66].…”

Section: Hybrid Modelingmentioning

confidence: 99%

Sub-Grid Scale Plume Modeling

2011

View full text Add to dashboard Cite

Multi-pollutant chemical transport models (CTMs) are being routinely used to predict the impacts of emission controls on the concentrations and deposition of primary and secondary pollutants. While these models have a fairly comprehensive treatment of the governing atmospheric processes, they are unable to correctly represent processes that occur at very fine scales, such as the near-source transport and chemistry of emissions from elevated point sources, because of their relatively coarse horizontal resolution. Several different approaches have been used to address this limitation, such as using fine grids, adaptive grids, hybrid modeling, or an embedded sub-grid scale plume model, i.e., plumein-grid (PinG) modeling. In this paper, we first discuss the relative merits of these various approaches used to resolve sub-grid scale effects in grid models, and then focus on PinG modeling which has been very effective in addressing the problems listed above. We start with a history and review of PinG modeling from its initial applications for ozone modeling in the Urban Airshed Model (UAM) in the early 1980s using a relatively simple plume model, to more sophisticated and state-of-the-science plume models, that include a full treatment of gas-phase, aerosol, and cloud chemistry, embedded in contemporary models such as CMAQ, CAMx, and WRF-Chem. We present examples of some typical results from PinG modeling for a variety of applications, discuss the implications of PinG on model predictions of source attribution, and discuss possible future developments and applications for PinG modeling. OPEN ACCESSAtmosphere 2011, 2 390

show abstract

“…Large-scale atmospheric models do not directly solve Eq. (1) but an "average" form of these equations, where average can be interpreted either in a statistical sense as an ensemble mean or a Reynolds average, or as a grid average over a large computational cell (Galmarini et al, 2008). In the latter case, one can defined a grid-average for any variable ϕ as:…”

Section: General Formulation Of Large-scale Models In the Presence Ofmentioning

confidence: 99%

Review of effective emissions modeling and computation

2011

View full text Add to dashboard Cite

Abstract. An important issue in the evaluation of the environmental impact of emissions from concentrated sources such as transport modes, is to understand how processes occurring at the scales of exhaust plumes can influence the physical and chemical state of the atmosphere at regional and global scales. Indeed, three-dimensional global circulation models or chemistry transport models generally assume that emissions are instantaneously diluted into large-scale grid boxes, which may lead, for example, to overpredict the efficiency of NO x to produce ozone. In recent times, various methods have been developed to incorporate parameterizations of plume processes into global models that are based e.g. on correcting the original emission indexes or on introducing "subgrid" reaction rates in the models. This paper provides a review of the techniques proposed so far in the literature to account for local conversion of emissions in the plume, as well as the implementation of these techniques into atmospheric codes.

show abstract

Modeling the impact of sub-grid scale emission variability on upper-air concentration

Cited by 19 publications

References 35 publications

High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

Sub-Grid Scale Plume Modeling

Review of effective emissions modeling and computation

Contact Info

Product

Resources

About

Modeling the impact of sub-grid scale emission variability on upper-air concentration

Cited by 19 publications

References 35 publications

High resolution modeling of CO&lt;sub&gt;2&lt;/sub&gt; over Europe: implications for representation errors of satellite retrievals

High resolution modeling of CO&lt;sub&gt;2&lt;/sub&gt; over Europe: implications for representation errors of satellite retrievals

Sub-Grid Scale Plume Modeling

Review of effective emissions modeling and computation

Contact Info

Product

Resources

About

High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals

High resolution modeling of CO<sub>2</sub> over Europe: implications for representation errors of satellite retrievals