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A class of finite-volume models for atmospheric flows across scales

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conference contribution
posted on 2018-06-07, 09:02 authored by Joanna SzmelterJoanna Szmelter, Mike Gillard, Piotr K. Smolarkiewicz, Christian Kühnlein
The paper examines recent advancements in the class of Nonoscillatory Forward-in-Time (NFT) schemes that exploit the implicit LES (ILES) properties of Multidimensional Positive Definite Advection Transport Algorithm (MPDATA). The reported developments address both global and limited area models spanning a range of atmospheric flows, from the hydrostatic regime at planetary scale, down to mesoscale and microscale where flows are inherently nonhydrostatic. All models operate on fully unstructured (and hybrid) meshes and utilize a median dual mesh finite volume discretisation. High performance computations for global flows employ a bespoke hybrid MPI-OpenMP approach and utilise the ATLAS library. Simulations across scales—from a global baroclinic instability epitomising evolution of weather systems down to stratified orographic flows rich in turbulent phenomena due to gravity-wave breaking in dispersive media, verify the computational advancements and demonstrate the efficacy of ILES both in regularizing large scale flows at the scale of the mesh resolution and taking a role of a subgrid-scale turbulence model in simulation of turbulent flows in the LES regime.


This work was supported by the funding received from the European Research Council under the European Union’s Seventh Framework Programme (FP7/2012/ERC Grant agreement no. 320375), and from the ESCAPE project; ESCAPE is funded by the European Commission under the Horizon 2020 Programme - grant agreement 671627.



  • Mechanical, Electrical and Manufacturing Engineering

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SZMELTER, J. ...et al., 2018. A class of finite-volume models for atmospheric flows across scales. Presented at AIAA AVIATION 2018, Atlanta, Georgia, 25-29 June.


© American Institute of Aeronautics and Astronautics (AIAA)


  • AM (Accepted Manuscript)

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This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

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This is a conference paper published by the AIAA, the definitive published version can be found here: https://doi.org/10.2514/6.2018-3497

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AIAA; 2018-3497


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Atlanta, Gorgia

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