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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-2020-344
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2020-344
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: model description paper 31 Oct 2020

Submitted as: model description paper | 31 Oct 2020

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This preprint is currently under review for the journal GMD.

JlBox v1.0: A Julia based mixed-phase atmospheric chemistry box-model

Langwen Huang1,2 and David Topping2 Langwen Huang and David Topping
  • 1Department of Mathematics, ETH Zurich, Switzerland
  • 2Department of Earth and Environmental Science,The University of Manchester, UK

Abstract. As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing community mechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. Julia is a relatively new programming language that promises computational performance close to that of Fortran, for example, without sacrificing flexibility offered by languages such as Python. With this in mind, in this paper we present and demonstrate the initial development of a high-performance community mixed phase atmospheric 0D box-model, JlBox, written in Julia.

In JlBox v1.0 we provide the option to simulate the chemical kinetics of a gas phase whilst also providing a fully coupled gasparticle model with dynamic partitioning to a fully moving sectional size distribution, in the first instance. JlBox is built around chemical mechanism files, using existing informatics software to provide parameters required for mixed phase simulations. In this study we use mechanisms from a subset and the complete Master Chemical Mechanism (MCM). Exploiting the ability to perform automatic differentiation of Jacobian matrices within Julia, we profile the use of sparse linear solvers and preconditioners, whilst also using a range of stiff solvers included within the expanding ODE solver suite the Julia environment provides, including the development of an adjoint model. Case studies range from a single volatile organic compound [VOC] with 305 equations to a full complexity MCM mixed phase simulation with 47544 variables. Comparison with an existing mixed phase model shows significant improvements in performance and potential for developments in a number of areas.

Langwen Huang and David Topping

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Langwen Huang and David Topping

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Latest update: 01 Dec 2020
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Short summary
As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows, designing communitymechanistic models requires an ability to capture increasing chemical, physical and therefore numerical complexity. As the landscape of computing software and hardware evolves, it is important to profile the usefulness of emerging platforms in tackling this complexity. With this in mind we present JlBox, written in Julia.
As our knowledge and understanding of atmospheric aerosol particle evolution and impact grows,...
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