Abstract
The three-dimensional variational assimilation (3D-Var) is the most commonly used technique currently to generate an analysis that provides better consistent initial conditions for numerical weather prediction (NWP). The Global and Regional Assimilation Prediction System (GRAPES) is a new generation NWP system in China, in which 3D-Var is one of the main components and plays an important role in direct assimilation for non-conventional observations. In this study, the principal theory and serial implementation of GRAPES 3D-Var are introduced firstly, and the details of distributed parallel computing algorithm of GRAPES 3D-Var are discussed, including data partitioning strategies, data communication strategies and stagger parallelization strategies. At last, some parallel experimental results on 16-CPU cluster platform are put forward, and the numerical simulations of the parallelization show that the parallel strategies can be combined to achieve considerable load balancing and good performance.
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Zhu, X., Zhang, W., Song, J. (2008). Parallel Computing of GRAPES 3D-Variational Data Assimilation System. In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2007. Lecture Notes in Computer Science, vol 4967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68111-3_47
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DOI: https://doi.org/10.1007/978-3-540-68111-3_47
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-68105-2
Online ISBN: 978-3-540-68111-3
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