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Инд. авторы: Klimova E.
Заглавие: A suboptimal data assimilation algorithm based on the ensemble Kalman filter
Библ. ссылка: Klimova E. A suboptimal data assimilation algorithm based on the ensemble Kalman filter // Quarterly Journal of the Royal Meteorological Society. - 2012. - Vol.138. - Iss. 669. - P.2079-2085. - ISSN 0035-9009. - EISSN 1477-870X.
Внешние системы: DOI: 10.1002/qj.1941; РИНЦ: 20482023; РИНЦ: 22093848; SCOPUS: 2-s2.0-84871632990; WoS: 000314503700010;
Реферат: eng: A suboptimal algorithm for data assimilation based on the ensemble Kalman filter (EnKF) is proposed. An advantage of the algorithm is that it does not require an additional calculation of the ensemble of perturbations that correspond to the analysis-error covariance matrix because it is calculated automatically with this algorithm. The operation count of the algorithm is close to that of the local ensemble transform Kalman filter (LETKF), but its formulae are different from those of the LETKF. © 2012 Royal Meteorological Society.
Ключевые слова: Extended Kalman filter; Covariance matrix;
Издано: 2012
Физ. характеристика: с.2079-2085
Цитирование:
1. Bellman R. 1960. Introduction to Matrix Analysis. McGraw-Hill: New York, NY.
2. Burgers G, van Leeuwen PJ, Evensen G. 1998. Analysis scheme in the ensemble Kalman filter. Mon. Weath. Rev. 126: 1719-1724.
3. Evensen G. 1994. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J. Geophys. Res. 99: 10143-10162.
4. Evensen G. 2003. The ensemble Kalman filter: theoretical formulation and practical implementation. Ocean Dyn. 53: 343-367.
5. Evensen G. 2007. Data Assimilation. The Ensemble Kalman Filter. Springer-Verlag: Berlin.
6. Ghil M, Malanotte-Rizzolli P. 1991. Data assimilation in meteorology and oceanography. Adv. Geophys. 33: 141-266.
7. Greybush SH, Kalnay E, Miyoshi T, Ide K. 2011. Balance and ensemble Kalman filter localization techniques. Mon. Weath. Rev. 139: 511-522.
8. Houtekamer PL, Mitchell HL. 1998. Data assimilation using an ensemble Kalman Filter Technique. Mon. Weath. Rev. 126: 796-811.
9. Houtekamer PL, Mitchell HL. 2001. A sequential ensemble Kalman filter for atmospheric data assimilation. Mon. Weath. Rev. 129: 123-137.
10. Houtekamer PL, Mitchell HL. 2005. Ensemble Kalman Filtering. Quarterly Journal of the Royal Meteorological Society. 131: 1-23.
11. Hunt BR, Kostelich EJ, Szunyogh I. 2007. Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter. Physica D 230: 112-126.
12. Jazwinski AH. 1970. Stochastic Processes and Filtering Theory. Academic Press: New York, NY.
13. Kalnay E. 2002. Atmospheric Modeling, Data Assimilation and Predictability. Cambridge University Press: Cambridge.
14. Klimova EG. 2008a. A data assimilation technique based on the π-algorithm. Russian Meteorol. Hydrol. 33(3): 143-150.
15. Klimova EG. 2008b. Data assimilation technique based on the ensemble π-algorithm. Russian Meteorol. Hydrol. 33(9): 570-576.
16. Krasovskii AA, Beloglazov IN, Chigin GP. 1979. Theory of Correlation-Extreme Navigation Systems. Nauka: Moscow. [In Russian].
17. Lorenc AC. 2003. The potential of the ensemble Kalman filter for NWP-a comparison with 4Dvar. Q.J.R. Meteorol. Soc. 129: 3183-3203.
18. Marchuk GI. 1987. Methods of Computational Mathematics. Springer: New York, NY.
19. Sakov P, Oke PR. 2008. A deterministic formulation of the ensemble square root filters. Tellus. 60A: 361-371.
20. Szunyogh I, Kostelich EJ, Gyarmati G, Kalnay E, Hunt BR, Ott E, Satterfield E, Yorke JA. 2008. A local ensemble transform Kalman filter data assimilation system for the NCEP global model. Tellus 60A: 113-130.
21. Whitaker JS, Hamill TM. 2002. Ensemble data assimilation without perturbed observations. Mon. Weath. Rev. 130: 1913-1924.
22. Tippett MK, Anderson JL, Bishop CH, Hamill TM, Whitaker JS. 2003. Ensemble square root filters. Mon. Weath. Rev. 131: 1485-1490.
23. Yaglom AM. 1987. Correlation Theory of Stationary and Random Functions. Springer: New York, NY.