Name
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. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-68111-3_47 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
Keywords | Field | DocType |
parallelization show,data assimilation system,numerical weather prediction,parallel computing algorithm,stagger parallelization strategy,new generation nwp system,parallel strategy,direct assimilation,numerical simulation,data communication strategy,parallel experimental result,load balance,initial condition,three dimensional,parallel computing,parallel computer | Assimilation (phonology),Load balancing (computing),Computer science,Parallel computing,Theoretical computer science,Data assimilation,Data partitioning,Numerical weather prediction,Prediction system | Conference |
Volume | Issue | ISSN |
4967 LNCS | null | 16113349 |
ISBN | Citations | PageRank |
3-540-68105-1 | 0 | 0.34 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaoqian Zhu | 1 | 86 | 16.92 |
| Weimin Zhang | 2 | 72 | 21.91 |
| Junqiang Song | 3 | 185 | 26.86 |