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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/gmd-2020-352
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-352
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 05 Nov 2020

Submitted as: model description paper | 05 Nov 2020

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This preprint is currently under review for the journal GMD.

A new Lagrangian in-time particle simulation module (Itpas v1) for atmospheric particle dispersion

Matthias Faust1, Ralf Wolke1, Steffen Münch2, Roger Funk2, and Kerstin Schepanski1 Matthias Faust et al.
  • 1Leibniz Institute for Tropospheric Research (TROPOS), Permoserstr. 15, 04318, Leipzig, Germany
  • 2Leibniz Centre for Agricultural Landscape Research (ZALF), Eberswalder Str. 84, 15374, Müncheberg, Germany

Abstract. Trajectory models are intuitive tools for airflow studies. But in general, they are limited to non-turbulent, i.e. laminar flow conditions. Therefore, trajectory models are not particularly suitable for investigating airflow within the turbulent atmospheric boundary layer. To overcome this, a common approach is handling the turbulent uncertainty as a random deviation from a mean path in order to create a statistic of possible solutions which envelops the mean path. This is well known as Lagrangian particle dispersion model (LPDM). However, the decisive factor is the representation of turbulence in the model, for which widely used models such as FLEXPART and HYSPLIT use an approximation. A conceivable improvement can be using a turbulence parameterisation approach based on the turbulent kinetic energy (TKE) on high temporal resolution. Here, we elaborated this approach and developed the LPDM Itpas, which is online coupled to the German Weather Service's mesoscale weather forecast model COSMO. It allows for benefiting from the prognostically calculated TKE as well as from the high-frequent wind information. We exemplary demonstrate the model's applicability for a case study on agricultural particle emission in Eastern Germany. The results obtained are discussed with regard to the model's ability to describe particle transport within a turbulent boundary layer. Ultimately, the simulations performed suggest that the newly introduced method based on prognostic TKE sufficiently represents the particle transport.

Matthias Faust et al.

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Status: open (until 31 Dec 2020)
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Matthias Faust et al.

Data sets

In-time particle simulation (Itpas) - sample data Matthias Faust https://doi.org/10.5281/zenodo.3965683

Model code and software

In-time particle simulation (Itpas) module in the framework of the COSMO-Model Matthias Faust https://doi.org/10.5281/zenodo.3932248

mttfst/dust-bubble: randomised test input Matthias Faust https://doi.org/10.5281/zenodo.3975563

mttfst/trajectory-plot: Trajectory-Plot - Paper Version Matthias Faust https://doi.org/10.5281/zenodo.4062147

mttfst/trajectory-cross-section: paper version, prep for sample data Matthias Faust https://doi.org/10.5281/zenodo.3975529

Matthias Faust et al.

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Latest update: 01 Dec 2020
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Short summary
Trajectory dispersion models are powerful and intuitive tools for tracing air pollution through the atmosphere. But the turbulent nature of the atmospheric boundary layer makes it challenging to provide accurate predictions near the surface. To overcome this, we propose an approach using wind and turbulence information at high temporal resolution. Finally, we demonstrate the strength of our approach in a case study on dust emissions from agriculture.
Trajectory dispersion models are powerful and intuitive tools for tracing air pollution through...
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