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Spectral Representation of Time and Physical Parameters in Numerical Weather Prediction
KTH, School of Electrical Engineering and Computer Science (EECS), Fusion Plasma Physics.ORCID iD: 0000-0003-0160-4060
KTH, School of Electrical Engineering and Computer Science (EECS), Fusion Plasma Physics.ORCID iD: 0000-0001-6379-1880
2018 (English)In: Understanding of Atmospheric Systems with Efficient Numerical Methods for Observation and Prediction, IntechOpen , 2018Chapter in book (Refereed)
Abstract [en]

Numerical weather prediction (NWP) is a difficult task in chaotic dynamical regimes because of the strong sensitivity to initial conditions and physical parameters. As a result, high numerical accuracy is usually necessary. In this chapter, an accurate and efficient alternative to the traditional time stepping solution methods is presented; the time-spectral method. The generalized weighted residual method (GWRM) solves systems of nonlinear ODEs and PDEs using a spectral representation of time. Not being subject to CFL-like criteria, the GWRM typically employs time intervals two orders of magnitude larger than those of time-stepping methods. As an example, efficient solution of the chaotic Lorenz 1984 equations is demonstrated. The results indicate that the method has strong potential for NWP. Furthermore, employing spectral representations of physical parameters and initial values, families of solutions are obtained in a single computation. Thus, the GWRM is conveniently used for studies of system parameter dependency and initial condition error growth in NWP.

Place, publisher, year, edition, pages
IntechOpen , 2018.
Keywords [en]
NWP time-spectral chaotic error analysis initial condition
National Category
Natural Sciences
Research subject
Physics
Identifiers
URN: urn:nbn:se:kth:diva-240836DOI: 10.5772/intechopen.80351OAI: oai:DiVA.org:kth-240836DiVA, id: diva2:1274975
Note

QC 20190121

Available from: 2019-01-04 Created: 2019-01-04 Last updated: 2019-01-21Bibliographically approved

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CiteExportLink to record
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  • Other locale
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