Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 5
Articles | Volume 14, issue 5
https://doi.org/10.5194/gmd-14-2289-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-2289-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 5
Development and technical paper
 | 
03 May 2021
Development and technical paper |  | 03 May 2021

Extending legacy climate models by adaptive mesh refinement for single-component tracer transport: a case study with ECHAM6-HAMMOZ (ECHAM6.3-HAM2.3-MOZ1.0)

Yumeng Chen, Konrad Simon, and Jörn Behrens

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Cited articles

Becker, R. and Rannacher, R.: An optimal control approach to a posteriori error estimation in finite element methods, Acta Numer., 10, 1–102, 2001. a
Behrens, J.: An adaptive semi-Lagrangian advection scheme and its parallelization, Mon. Weather Rev., 124, 2386–2395, 1996. a
Behrens, J.: Data Structures for Computational Efficiency, Springer Berlin Heidelberg, Berlin, Heidelberg, 49–69, https://doi.org/10.1007/3-540-33383-5_4, 2006a. a
Behrens, J.: Adaptive atmospheric modeling: key techniques in grid generation, data structures, and numerical operations with applications, vol. 207, Lecture Notes in Computational Science and Engineering, Springer-Verlag Berlin Heidelberg, 2006b. a
Behrens, J., Dethloff, K., Hiller, W., and Rinke, A.: Evolution of Small-Scale Filaments in an Adaptive Advection Model for Idealized Tracer Transport, Mon. Weather Rev., 128, 2976–2982, 2000. a, b
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Mesh adaptivity can reduce overall model error by only refining meshes in specific areas where it us necessary in the runtime. Here we suggest a way to integrate mesh adaptivity into an existing Earth system model, ECHAM6, without having to redesign the implementation from scratch. We show that while the additional computational effort is manageable, the error can be reduced compared to a low-resolution standard model using an idealized test and relatively realistic dust transport tests.
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