925 resultados para Concertos (Harpsichord ensemble with string orchestra)


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The background error covariance matrix, B, is often used in variational data assimilation for numerical weather prediction as a static and hence poor approximation to the fully dynamic forecast error covariance matrix, Pf. In this paper the concept of an Ensemble Reduced Rank Kalman Filter (EnRRKF) is outlined. In the EnRRKF the forecast error statistics in a subspace defined by an ensemble of states forecast by the dynamic model are found. These statistics are merged in a formal way with the static statistics, which apply in the remainder of the space. The combined statistics may then be used in a variational data assimilation setting. It is hoped that the nonlinear error growth of small-scale weather systems will be accurately captured by the EnRRKF, to produce accurate analyses and ultimately improved forecasts of extreme events.

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Also attributed to Cannabich in the Breitkopf ms. cat. of 1767.

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Photocopy of the ms. original in the Stiftsbibliothek, Seitenstetten, Austria. 30-36 cm.

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Originally for horn and string orchestra.

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"Edition Eulenburg, no. 268".

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Cover title.

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Cover title.

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Originally for violin and string orchestra; acc. arr. for piano.

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Mode of access: Internet.

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For violin and piano; acc. originally for string orchestra.

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Mode of access: Internet.