Using Polynomial Regression in Designing the Time Filters for the Leapfrog Time-Stepping Scheme

A general framework is presented based on the least squares polynomial regression to design time filters for the leapfrog time-stepping scheme with required amplitude and phase properties. The well-known Robert–Asselin filter and its modification, the Robert–Asselin–Williams filter, are obtained usi...

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Veröffentlicht in:Monthly weather review 2017-05, Vol.145 (5), p.1779-1795
Hauptverfasser: Yazgi, Daniel, Mohebalhojeh, Ali R., Ghader, Sarmad
Format: Artikel
Sprache:eng
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Zusammenfassung:A general framework is presented based on the least squares polynomial regression to design time filters for the leapfrog time-stepping scheme with required amplitude and phase properties. The well-known Robert–Asselin filter and its modification, the Robert–Asselin–Williams filter, are obtained using the zeroth-degree and first-degree polynomial regression, respectively. It is shown that using the second-degree polynomial regression, one can achieve seventh-order amplitude accuracy with only four time levels. In addition, the designed filter exhibits promising results when used with a semi-implicit time-stepping scheme.
ISSN:0027-0644
1520-0493
DOI:10.1175/MWR-D-16-0380.1