Data-Parallel Numerical Methods in a Weather Forecast Model

The results presented in this paper are part of a research project to investigate the possibilities to apply massively parallel architectures for numerical weather forecasting. Within numerical weather forecasting several numerical techniques are used to solve the model equations. This paper compare...

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Bibliographic Details
Main Authors: Lex Wolters, Gerard Cats, Nils Gustafsson, Tomas Wilhelmsson
Other Authors: The Pennsylvania State University CiteSeerX Archives
Format: Text
Language:English
Published: 1994
Subjects:
Online Access:http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.30.6013
Description
Summary:The results presented in this paper are part of a research project to investigate the possibilities to apply massively parallel architectures for numerical weather forecasting. Within numerical weather forecasting several numerical techniques are used to solve the model equations. This paper compares the performance of implementations on a MasPar system of two techniques, finite difference and spectral, that are adopted in the numerical weather forecasting model HIRLAM. The operational HIRLAM model is based on finite difference methods, while the spectral model is still in a research phase. Also the differences in relative performance of these methods on the MasPar and vector architectures will be discussed. 1 Introduction The HIRLAM (HIgh Resolution Limited Area Modeling) forecasting system has been developed within a common research project among the weather services of Denmark, Finland, Iceland, Ireland, the Netherlands, Norway, and Sweden [12, 6]. The application of this f.