Analysis of computational performance and adaptative time step for numerical weather prediction models

Marcos Vinicius Bueno de Morais

Abstract


In this work, it will evaluate the use of a Linux server to execute a numerical weather forecasting model. The evaluation will be both in the use of cores for the parallel simulation, through the efficiency and speedup indexes, as well as a quantitative analysis for the use of adaptive time step. The adaptive time step is that the ∆t varies for each time step, based on the stability conditions of the model, through a tolerance level with respect to the truncation error used in the equations. This simulation will be compared with other two simulations, with time steps of 15 seconds and 30 seconds, both considered fixed and within CFL conditions. The simulations were done for the Metropolitan Area of São Paulo, Brazil, because of the observational data available to compare with the output. The results show that the optimal execution point of the model is when it is used 7 cores, less than half of the total available (24 cores). However, the use of the adaptive time step does not present better results in relation to the statistical indexes, but it is recommended for numerical predictions that need a faster result.

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