Research Of High-performance Parallel Computing For Numerical Models In Meteorologic Prediction

The development of atmosphere science, especially the numerical meteorologic forecasting model, and the parallel computing are closed linked. To meet the practical requirements for distributed-memory parallel computing of numerical forecasting models, we study on the parallel characteristics of spectral element and finite difference methods. On this basis, we develop fast and parallel computations for three meteorologic models, including 2-D shallow water equations, the new generation multi-scale weather forecasting model and the ocean general circulation model. The main work is summarized as follows:(1) We analyze the situation of the parallel computing technology and it's influence on numerical forecasting models, and point out that the numerical models now are in serious demand for efficient parallel algorithms. We also review parallel computing model, parallel programming model and the software engineering for numerical applications.(2) On spectral element method and parallel computing of 2-D spectral element shallow water modeli) We put forward a hybrid-local-basis theorem, and give two kinds of local basis schemes fitting for both the Chebyshev polynomials and the Legendre case. With these spectral element schemes, we can get elemental matrix with specific sparse pattern, without sacrificing precision. In addition, the famous C?continuity can be hold by these schemes.ii) The parallel computing of spectral element methods by element-by-element strategy is analyzed deeply, and we design a high-performance spectral element parallel software package named PSES. Numerical tests show that the high-order (>7) spectral element methods can performance efficiently on the relatively slow-network PC clusters, and parallel efficiency with eight nodes is more than 60% with normal elemental scale (32*32 elements).iii) For the semi-implicit spectral element method on the 2-D shallow water equations, we give a parallel mass-matrix-diagonal preconditioned CG method with the element-by-element strategy and develop the corresponding parallel software package. We also get high efficiency on PC clusters.(3) On parallel computing of the third generation Ocean General Circulation Model from LASG/IAPi) We present an optimization model by multi-overlapping-boundary for parallel explicit integration with finite difference discretization, and point out that the gap between speed of network and CPU makes it a practical technique. We compare the parallel characteristics of spectral element and finite difference from the point of view of communications, communication-to-computation ratio and scalability.ii) We organize the parallel computing of'the third generation ocean general circulation model from the Chinese Institute of Atmosphere Physics (LASG/IAP), and we also apply several parallel optimization strategies including multi-overlapping-boundary. The parallelism is implemented both on distributed memory and shared memory parallel computers, based on the spitting of latitude zones. This parallel ocean general circulation model is the first one in China.(4) On the efficient method for the dynamical core of the new generation multi-scale forecasting modeli) We present a new multi-level sparse approximate inverse preconditnioner for the complicated 3-D helmholtz equations in the new generation weather forecasting model. As a result, the new sparse approximate inverse preconditioned GCR and GMRES algorithms are given and successfully applied in the dynamical core. Numerical tests show that the new algorithms perform very efficiently, and can greatly improve the efficiency of numerical model.