Preprints
https://doi.org/10.5194/egusphere-2026-2532
https://doi.org/10.5194/egusphere-2026-2532
22 Jun 2026
 | 22 Jun 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

A computationally efficient TVD-FFSL hybrid tracer transport scheme on spherical centroidal voronoi tessellations in iAMAS (v2.6.3)

Gudongze Li, Chun Zhao, Yinhua Xia, Li Dong, Yibo Xue, Xiao-Xiao Zhang, Jun Gu, Jiawang Feng, and Zihan Xia

Abstract. Tracer transport is a critical computational bottleneck in high-resolution atmospheric chemistry models, where tens to hundreds of species are advected. The iAMAS model (v2.6.3) on spherical centroidal Voronoi tessellations (SCVTs) currently employs a scheme (2H1FCT) that performs two steps of third-order transport followed by one step of flux-corrected transport (FCT), in which the FCT correction step dominates computational cost. This study develops TVD-FFSL, a computationally efficient hybrid tracer transport scheme. Horizontally, a total variation diminishing (TVD) flux operator with the KOREN limiter is employed. Vertically, a flux-form semi-Lagrangian (FFSL) operator based on piecewise parabolic method reconstruction handles cells with CFL > 1unconditionally. Together with a second-order TVD Runge-Kutta time integration, the scheme ensures monotonicity without a separate FCT step. Idealized 2D tests demonstrate that TVD-FFSL achieves robust shape preservation. Although its errors are slightly higher than 2H1FCT, superior convergence rates render the accuracy gap negligible at finer resolutions (∆x ≤ 30 km). Realistic 3D dust simulations on a 16–60 km variable-resolution grid confirm its long-term stability and accuracy comparable to 2H1FCT. Performance benchmarks show that TVD-FFSL achieves over 2× speedup in standalone transport tests and exceeds 3.75× speedup in long-term atmospheric dust simulations, significantly reducing the computational overhead of numerous tracer transport. The design principles of TVD-FFSL could be transferable to other unstructured meshes, offering a pathway toward accelerating high-resolution atmospheric chemistry simulations.

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Gudongze Li, Chun Zhao, Yinhua Xia, Li Dong, Yibo Xue, Xiao-Xiao Zhang, Jun Gu, Jiawang Feng, and Zihan Xia

Status: open (until 17 Aug 2026)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CEC1: 'Comment on egusphere-2026-2532', Juan Antonio Añel, 27 Jun 2026 reply
    • AC1: 'Reply on CEC1: Compliance with Code and Data Policy', Gudongze Li, 27 Jun 2026 reply
    • AC2: 'Reply on CEC1: Compliance with Code and Data Policy', Gudongze Li, 27 Jun 2026 reply
      • CEC3: 'Reply on AC2', Juan Antonio Añel, 27 Jun 2026 reply
  • CEC2: 'Comment on egusphere-2026-2532', Juan Antonio Añel, 27 Jun 2026 reply
Gudongze Li, Chun Zhao, Yinhua Xia, Li Dong, Yibo Xue, Xiao-Xiao Zhang, Jun Gu, Jiawang Feng, and Zihan Xia
Gudongze Li, Chun Zhao, Yinhua Xia, Li Dong, Yibo Xue, Xiao-Xiao Zhang, Jun Gu, Jiawang Feng, and Zihan Xia
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Latest update: 27 Jun 2026
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Short summary
Simulating how chemical species are advected by air flow is essential for air quality and climate research, but becomes prohibitively slow when hundreds of species are tracked at high resolution. We developed a new transport method that removes the most costly step in current approaches. Tests show it matches existing accuracy while achieving nearly 4-fold computational speedup. The design is transferable to other models, offering a pathway toward faster high-resolution atmospheric simulations.
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