Parallel computing of GRAPES 3D-variational data assimilation system

  • Authors:
  • Xiaoqian Zhu;Weimin Zhang;Junqiang Song

  • Affiliations:
  • National Laboratory for Parallel and Distributed Processing, Changsha, Hunan, China;National Laboratory for Parallel and Distributed Processing, Changsha, Hunan, China;National Laboratory for Parallel and Distributed Processing, Changsha, Hunan, China

  • Venue:
  • PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
  • Year:
  • 2007

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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.