The accuracy of numerical weather prediction is essentially dependent on the spatial resolution of the atmospheric model used for this purpose and on the complexity and accuracy of the involved subgrid-scale parameterizations (i.e., the parameterizations of processes whose typical scale is smaller than the spatial step). A possibility of application of models with higher spatial resolution and more precise parameterizations is determined by the available computer technique and by the presence of high-performing codes. Some trial versions of the atmospheric spectral model with increased spatial resolution have been developed with the purpose to improve the quality of numerical weather prediction. The corresponding code was optimized and parallelized using the MPI technology. The code uses one-dimensional decompositions over latitude in the physical space and over spectral numbers in the spectral space. The developed parallel versions of the spectral model (in different configurations) were tested and the speed-up of the code was estimated as a function of the number of processors for various computing platforms. Different methods of inter-processor data exchange were examined and their efficiency was estimated. This work was supported by the Russian Foundation for Basic Research (porojects 04-05-64530a and 05-05-64575a). The paper was prepared on the basis of the authors' report at the International Conference on Parallel Computing Technologies (PaVT-2007; http://agora.guru.ru/pavt2007).

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