Large-eddy simulation and stochastic modeling of Lagrangian particles for footprint determination in the stable boundary layer

Glazunov, Andrey; Rannik, Üllar; Stepanenko, Victor; Lykosov, V. N.; Auvinen, Mikko; Vesala, Timo; Mammarella, Ivan

doi:10.5194/gmd-9-2925-2016

Cited by 29 publications

(17 citation statements)

References 57 publications

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“…It should also be noted that a targeted refinement in the z direction, while using coarser horizontal resolution in effort to generate thin subvolumes that approximate planes, does not remedy the situation because the mean flow gradients around the sensor site are significant in all directions. Such finite planes or one-cell-high grid layers are conventionally used as targets when Lagrangian-particle-based methods are utilized to evaluate footprints under heterogeneous conditions with undisturbed sensor sites (e.g., Steinfeld et al, 2008;Hellsten et al, 2015;Glazunov et al, 2016). Unfortunately, at the required level of target volume discretization, the excessive number of individual f i,j,k contributions causes the postprocessing to become highly tedious.…”

Section: Coordinate Rotation Via Far-field Correctionmentioning

confidence: 99%

“…The deterministic velocity components are directly obtained from the LES solution, while the random components are evaluated according to Weil et al (2004). Although LS modeling approaches that are less computationally expensive exist (Glazunov et al, 2016), warranting further investigation on their applicability to urban problems, the presented high-resolution urban flow problem is assumed to require the highest level of description also from the LS model; the interaction between the atmospheric wind and the cascade of multistoried buildings and street canyons gives rise to strongly anisotropic turbulence structures, which are not reliably amendable to parametrization.…”

Section: Numerical Modeling Frameworkmentioning

confidence: 99%

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Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

et al. 2017

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Abstract. Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddycovariance (EC) flux measurements in urban studies. This work introduces a computational methodology that enables the generation of detailed footprints in arbitrarily complex urban flux measurements sites. The methodology is based on conducting high-resolution large-eddy simulation (LES) and Lagrangian stochastic (LS) particle analysis on a model that features a detailed topographic description of a real urban environment. The approach utilizes an arbitrarily sized target volume set around the sensor in the LES domain, to collect a dataset of LS particles which are seeded from the potential source area of the measurement and captured at the sensor site. The urban footprint is generated from this dataset through a piecewise postprocessing procedure, which divides the footprint evaluation into multiple independent processes that each yield an intermediate result. These results are ultimately selectively combined to produce the final footprint. The strategy reduces the computational cost of the LES-LS simulation and incorporates techniques to account for the complications that arise when the EC sensor is mounted on a building instead of a conventional flux tower. The presented computational framework also introduces a result assessment strategy which utilizes the obtained urban footprint together with a detailed land cover type dataset to estimate the potential error that may arise if analytically derived footprint models were employed instead. The methodology is demonstrated with a case study that concentrates on generating the footprint for a building-mounted EC measurement station in downtown Helsinki, Finland, under the neutrally stratified atmospheric boundary layer.

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Section: Coordinate Rotation Via Far-field Correctionmentioning

confidence: 99%

Section: Numerical Modeling Frameworkmentioning

confidence: 99%

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

et al. 2017

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“…Increased local knowledge and general understanding of the relevant processes (e.g. Glazunov et al, 2016) can then help the forecasters to improve air quality predictions based on NWP models, as suggested by Steyn et al (2013).…”

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confidence: 99%

Sensitivity of local air quality to the interplay between small- and large-scale circulations: a large-eddy simulation study

Wolf¹,

Esau²,

Reuder

2017

Atmos. Chem. Phys.

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Abstract. Street-level urban air pollution is a challenging concern for modern urban societies. Pollution dispersion models assume that the concentrations decrease monotonically with raising wind speed. This convenient assumption breaks down when applied to flows with local recirculations such as those found in topographically complex coastal areas. This study looks at a practically important and sufficiently common case of air pollution in a coastal valley city. Here, the observed concentrations are determined by the interaction between large-scale topographically forced and local-scale breeze-like recirculations.Analysis of a long observational dataset in Bergen, Norway, revealed that the most extreme cases of recurring wintertime air pollution episodes were accompanied by increased large-scale wind speeds above the valley. Contrary to the theoretical assumption and intuitive expectations, the maximum NO 2 concentrations were not found for the lowest 10 m ERA-Interim wind speeds but in situations with wind speeds of 3 m s −1 . To explain this phenomenon, we investigated empirical relationships between the large-scale forcing and the local wind and air quality parameters. We conducted 16 large-eddy simulation (LES) experiments with the Parallelised Large-Eddy Simulation Model (PALM) for atmospheric and oceanic flows. The LES accounted for the realistic relief and coastal configuration as well as for the large-scale forcing and local surface condition heterogeneity in Bergen. They revealed that emerging local breeze-like circulations strongly enhance the urban ventilation and dispersion of the air pollutants in situations with weak largescale winds. Slightly stronger large-scale winds, however, can counteract these local recirculations, leading to enhanced surface air stagnation.Furthermore, this study looks at the concrete impact of the relative configuration of warmer water bodies in the city and the major transport corridor. We found that a relatively small local water body acted as a barrier for the horizontal transport of air pollutants from the largest street in the valley and along the valley bottom, transporting them vertically instead and hence diluting them. We found that the stable stratification accumulates the street-level pollution from the transport corridor in shallow air pockets near the surface. The polluted air pockets are transported by the local recirculations to other less polluted areas with only slow dilution. This combination of relatively long distance and complex transport paths together with weak dispersion is not sufficiently resolved in classical air pollution models. The findings have important implications for the air quality predictions over urban areas. Any prediction not resolving these, or similar local dynamic features, might not be able to correctly simulate the dispersion of pollutants in cities.

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“…The individual sectional footprints are typically evaluated from subsets that contain an insufficient number of particle data entries needed to obtain a converged footprint distribution. (Hellsten et al, 2015) showed that, in an urbanlike environment, ∼ 10 6 particle hits are required to attain an adequately converged footprint distribution while ∼ 10 5 particle entries is sufficient to reveal the characteristic shape of the near-field distribution. In the piecewise postprocessing approach, the sectional footprint contributions may be constructed from an arbitrarily small dataset, but since the methodology substantially benefits from the ability to inspect and compare individual f i,j,k distributions, it is desirable to work with subsets s i,j,k containing more than 10 5 entries.…”

Section: Piecewise Postprocessing Methodology For Constructing the Fomentioning

confidence: 99%

Section: Coordinate Rotation Via Far-field Correctionmentioning

confidence: 99%

Code availability information improved

Auvinen¹

2017

Preprint

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Conventional footprint models cannot account for the heterogeneity of the urban landscape imposing a pronounced uncertainty on the spatial interpretation of eddycovariance (EC) flux measurements in urban studies. This work introduces a computational methodology that enables the generation of detailed footprints in arbitrarily complex urban flux measurements sites. The methodology is based on conducting high-resolution large-eddy simulation (LES) and Lagrangian stochastic (LS) particle analysis on a model that features a detailed topographic description of a real urban environment. The approach utilizes an arbitrarily sized target volume set around the sensor in the LES domain, to collect a dataset of LS particles which are seeded from the potential source area of the measurement and captured at the sensor site. The urban footprint is generated from this dataset through a piecewise postprocessing procedure, which divides the footprint evaluation into multiple independent processes that each yield an intermediate result. These results are ultimately selectively combined to produce the final footprint. The strategy reduces the computational cost of the LES-LS simulation and incorporates techniques to account for the complications that arise when the EC sensor is mounted on a building instead of a conventional flux tower. The presented computational framework also introduces a result assessment strategy which utilizes the obtained urban footprint together with a detailed land cover type dataset to estimate the potential error that may arise if analytically derived footprint models were employed instead. The methodology is demonstrated with a case study that concentrates on generating the footprint for a building-mounted EC measurement station in downtown Helsinki, Finland, under the neutrally stratified atmospheric boundary layer.

show abstract

Large-eddy simulation and stochastic modeling of Lagrangian particles for footprint determination in the stable boundary layer

Cited by 29 publications

References 57 publications

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

Numerical framework for the computation of urban flux footprints employing large-eddy simulation and Lagrangian stochastic modeling

Sensitivity of local air quality to the interplay between small- and large-scale circulations: a large-eddy simulation study

Code availability information improved

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