Regional weather downscaling using ensemble Kalman filter with singular vector

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Publication Details

Author list: Payakkarak S., Sukawat D., Humphries U.

Publisher: Pushpa

Publication year: 2015

Journal: Far East Journal of Mathematical Sciences (0972-0871)

Volume number: 97

Issue number: 3

Start page: 347

End page: 376

Number of pages: 30

ISSN: 0972-0871

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929572208&doi=10.17654%2fFJMSJun2015_347_376&partnerID=40&md5=ad20d0a3f7c3bd160d160b5da69b7acb

Languages: English-Great Britain (EN-GB)

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Abstract

A modified ensemble Kalman filter (modified EnKF) is developed by using singular vector to generate the ensemble members instead of random generation as in the original EnKF. To test the performance of the modified EnKF, the outputs from weather downscaling by a shallow water model for wind speeds associated with two cold surges that reach Thailand are adjusted by the original EnKF and the modified EnKF. Result shows that the modified EnKF provides more realistic wind speed than the original EnKF. ฉ 2015 Pushpa Publishing House, Allahabad, India.

Keywords

Ensemble Kalman filter, Singular vector