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 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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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. |
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ISSN: | 0027-0644 1520-0493 |
DOI: | 10.1175/MWR-D-16-0380.1 |