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Comment on egusphere-2024-1713
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This commentary responds to a preprint on FLEXPART version 11, evaluating the Lagrangian particle dispersion model's claimed improvements in accuracy and efficiency for atmospheric transport studies including microplastic and radionuclide tracking.
Abstract. Numerical methods and simulation codes are essential for the advancement of our understanding of complex atmospheric processes. As technology and computer hardware continue to evolve, the development of sophisticated code is vital for accurate and efficient simulations. In this paper, we present the recent advancements made in FLEXPART, a Lagrangian particle dispersion model, which has been used in a wide range of atmospheric transport studies over the past three decades, extending from tracing radionuclides from the Fukushima nuclear disaster, to inverse modelling of greenhouse gases, and to the study of atmospheric moisture cycles. This version of FLEXPART includes notable improvements in accuracy and computational efficiency. 1) By leveraging the native vertical coordinates of European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) instead of interpolating to terrain-following coordinates, we achieved an improvement in trajectory accuracy, leading to a ∼ 8−10 % reduction in conservation errors for semi-conserved quantities like potential vorticity. 2) The shape of aerosol particles is now accounted for in the gravitational settling and dry deposition calculation, increasing the simulation accuracy for non-spherical aerosol particles such as microplastic fibers. 3) Wet deposition has been improved by the introduction of a new below-cloud scheme, a new cloud identification scheme, and by improving the interpolation of precipitation. 4) Functionality from a separate version of FLEXPART, the FLEXPART-CTM model, is implemented, which includes linear chemical reactions. Additionally, the incorporation of Open Multi-Processing parallelisation makes the model better suited for handling large input data. Furthermore, we introduced novel methods for the input and output of particle properties and distributions. Users now have the option to run FLEXPART with more flexible particle input data, providing greater adaptability for specific research scenarios (e. g., effective backward simulations corresponding to satellite retrievals). Finally, a new user manual and restructuring of the source code into modules will serve as a basis for further development.
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Comment on egusphere-2024-1713
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This study presents updates to the FLEXPART Lagrangian particle dispersion model, improving accuracy and computational efficiency for simulating atmospheric transport of trace substances including radionuclides, greenhouse gases, and airborne microplastics. The enhancements respond to community review and expand the model's applicability across a wider range of atmospheric transport scenarios.
Review of “FLEXPART version 11: Improved accuracy, efficiency, and flexibility”
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This review evaluates FLEXPART version 11, a Lagrangian particle dispersion model, describing improvements in accuracy, efficiency, and flexibility for atmospheric transport simulations including tracking radionuclides, microplastics, and other airborne particles.
FLEXPART version 11: Improved accuracy, efficiency, and flexibility
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This paper describes FLEXPART version 11, an updated Lagrangian particle dispersion model with improved accuracy and flexibility, designed for tracking atmospheric transport of substances including microplastics, radionuclides, and air pollutants. New features include enhanced wet deposition schemes and improved boundary layer parameterization.
Comment on egusphere-2024-1713
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Researchers present recent advancements in the FLEXPART atmospheric particle dispersion model, developing updated numerical methods and simulation code capabilities to enable more accurate and computationally efficient simulations of complex atmospheric transport processes.
Reply on CEC1
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This paper presents recent advancements in FLEXPART, a Lagrangian particle dispersion model used for atmospheric transport simulations, with improvements in accuracy, computational efficiency, and support for applications ranging from nuclear radionuclide tracking to greenhouse gas inverse modeling. The work responds to community feedback and expands the model's capabilities for studying complex atmospheric transport phenomena.
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