Abstract
An advection-diffusion-chemistry module of a large-scale air pollution model is split into two parts: (a) advection-diffusion part and (b) chemistry part. A simple sequential splitting is used. This means that at each time-step first the advection-diffusion part is treated and after that the chemical part is handled. A discretization technique based on central differences followed by Crank-Nicolson time-stepping is used in the advection-diffusion part. The non-linear chemical reactions are treated by the robust Backward Euler Formula. The performance of the combined numerical method (splitting procedure + numerical algorithms used in the advection-diffusion part and in the chemical part) is studied in connection with six test-problems. We are interested in both the accuracy of the results and the efficiency of the parallel computations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Alexandrov, V., et al.: Parallel runs of a large air pollution model on a grid of Sun computers. Mathematics and Computers in Simulation 65, 557–577 (2004)
Anderson, E., et al.: LAPACK: Users’ Guide. SIAM, Philadelphia (1992)
Crowley, W.P.: Numerical advection experiments. Monthly Weather Review 96, 1–11 (1968)
Demmel, J.W., et al.: A supernodal approach to sparse partial pivoting. SIAM Journal of Matrix Analysis and Applications 20, 720–755 (1999)
Demmel, J.W., Gilbert, J.R., Li, X.S.: An asynchronous parallel supernodal algorithm for sparse Gaussian elimination. SIAM Journal of Matrix Analysis and Applications 20, 915–952 (1999)
Duff, I.S., Erisman, A.M., Reid, J.K.: Direct Methods for Sparse Matrices. Oxford University Press, Oxford-London (1986)
Golub, G.H., Ortega, J.M.: Scientific Computing and Differential Equations. Academic Press, Boston-San Diego-New York-London-Sydney-Tokyo-Toronto (1992)
Golub, G.H., Van Loan, C.F.: Matrix Computations, Maryland. Johns Hopkins University Press, Baltimore (1983)
Hov, Ø., et al.: Comparison of numerical techniques for use in air pollution models with non-linear chemical reaction. Atmospheric Environment 23, 967–983 (1988)
Molenkampf, C.R.: Accuracy of finite-difference methods applied to the advection equation. Journal of Applied Meteorology 7, 160–167 (1968)
Strikwerda, J.C.: Finite difference schemes and partial differential equations. Second Edition. SIAM, Philadelphia (2004)
Zlatev, Z.: Computational methods for general sparse matrices. Kluwer Academic Publishers, Dordrecht-Boston-London (1991)
Zlatev, Z.: Computer Treatment of Large Air Pollution Models. In: Environmental Science and Technology Science, vol. 2, Kluwer Academic Publishers, Dordrecht-Boston-London (1995)
Zlatev, Z., Dimov, I.: Computational and Environmental Challenges in Environmental Modelling. In: Studies in Computational Mathematics, Amsterdam-Boston-Heidelberg-London-New York-Oxford-Paris-San Diego-San Francisco-Singapore-Sydney-Tokyo, vol. 13, Elsevier, Amsterdam (2006)
Danish Centre for Scientific Computing at the Technical University of Denmark, Sun High Performance Computing Systems (2002), http://www.hpc.dtu.dk
Open MP tools (1999), http://www.openmp.org
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Faragó, I., Georgiev, K., Zlatev, Z. (2008). Parallelization of Advection-Diffusion-Chemistry Modules. In: Lirkov, I., Margenov, S., Waśniewski, J. (eds) Large-Scale Scientific Computing. LSSC 2007. Lecture Notes in Computer Science, vol 4818. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78827-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-540-78827-0_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78825-6
Online ISBN: 978-3-540-78827-0
eBook Packages: Computer ScienceComputer Science (R0)