Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0)

Abstract. This paper presents the development of a stochastic particle method to simulate advection in regional-scale models with a particle-resolving aerosol representation. The new method is based on finite-volume discretizations with the flux terms interpreted as probabilities of particle transport between grid cells. We analyze the method in 1D and show that the stochastic particle sampling during transport injects energy at high spatial frequencies, which can be partially compensated for with the choice of a dissipative odd-order finite-volume scheme. We then apply the stochastic third- and fifth-order advection algorithms with monotonic limiters in WRF-PartMC, using idealized and realistic wind fields in 2D and 3D. In all cases we observe the expected convergence rates of the stochastic particle method to the finite-volume solution as the number of computational particles is increased. This work enables the use of particle-based aerosol models on the regional scale.

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Publication Details

Journal
Geoscientific model development
Published
2024-11-27
DOI
https://doi.org/10.5194/gmd-17-8399-2024
Citations
2
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.57

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article

Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0)

Matthew West, Jeffrey H. Curtis, Nicole Riemer
2 citations
Geoscientific model development
Atmospheric aerosols and clouds
0.57
article

Explicit stochastic advection algorithms for the regional-scale particle-resolved atmospheric aerosol model WRF-PartMC (v1.0)

Matthew West, Jeffrey H. Curtis, Nicole Riemer
article en
2 citations

Abstract

Abstract. This paper presents the development of a stochastic particle method to simulate advection in regional-scale models with a particle-resolving aerosol representation. The new method is based on finite-volume discretizations with the flux terms interpreted as probabilities of particle transport between grid cells. We analyze the method in 1D and show that the stochastic particle sampling during transport injects energy at high spatial frequencies, which can be partially compensated for with the choice of a dissipative odd-order finite-volume scheme. We then apply the stochastic third- and fifth-order advection algorithms with monotonic limiters in WRF-PartMC, using idealized and realistic wind fields in 2D and 3D. In all cases we observe the expected convergence rates of the stochastic particle method to the finite-volume solution as the number of computational particles is increased. This work enables the use of particle-based aerosol models on the regional scale.

Geoscientific model developmentVol. 17(22)
University of Illinois Urbana-Champaign (US), Urbana University (US)
National Science Foundation, U.S. Department of Energy, University of Illinois at Urbana-Champaign, Office of Advanced Cyberinfrastructure
Affordable and clean energy
Openalex Percentile: Top 32%
Atmospheric aerosols and clouds
0.57
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