Инд. авторы: Platov G., Klimova E.
Заглавие: The results of numerical simulation of the lena river runoff with the assimilation of satellite data: summer 2008
Библ. ссылка: Platov G., Klimova E. The results of numerical simulation of the lena river runoff with the assimilation of satellite data: summer 2008 // Bulletin of the Novosibirsk Computing Center. Series: Numerical Modeling in Atmosphere, Ocean, and Environment Studies. - 2014. - Vol.14. - P.55-72. - ISSN 1680-6999.
Внешние системы: РИНЦ: 25467846;
Реферат: eng: The paper discusses the results of preliminary experiments to test the quality of the data assimilation procedure based on the use of ensemble Kalman filter applied to the basin of the Laptev Sea in the vicinity of the Lena Delta. As perturbation we used the river runoff closure, and as the true values -- the surface salinity, taken from a reference experiment with the included river inflow. The comparison of two numerical experiments with assimilation of simulated salinity data and without assimilation shows that the proposed assimilation procedure is able to restore adequately the salinity field.
Издано: 2014
Физ. характеристика: с.55-72
Цитирование: 1. Agoshkov V.I., Ipatova V.M., Zalesnyi V.B., et al. Problems of variational assimilation of observational data for ocean general circulation models and methods for their solution // Izv. Atmospheric and Oceanic Physics. \--- 2010. \--- Vol.~46, \No~6. \--- P.~677--712. doi:10.1134/S0001433810060034. 2. Blumberg A.F., Mellor G.L. A description of a three-dimensional coastal ocean circulation model // Three-Dimensional Coastal Ocean Models, 4 of Coastal and Estuarine Series / American Geophysical Union, Washington, D.C. \--- 1987. \--- P.~1--16. 3. Chant R.J., Glenn S.M., Hunter E., et al. Bulge formation of a Buoyant river outflow // J. Geophys. Res. \--- 2008. \--- Vol.~113. doi:10.1029/2007JC004100. 4. Cherniawsky J., Holloway G. On western boundary current separation in an upper ocean general circulation model of the North Pacific // J. Geophys. Res. \--- 1993. \--- Vol.~98. \--- P.~22843--22853. 5. Choi B.J., Wilkin J.L. The effect of wind on the dispersal of the Hudson river plume // J. Phys. Oceanogr. \--- 2007. \--- Vol.~37, \No~7. \--- P.~1878--1897. doi:10.1175/JPO3081.1. 6. Evensen G. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics // J. Geophys. Res. \--- 1994. \--- Vol.~99(C5). \--- P.~10143--10162. 7. Evensen G. The ensemble Kalman filter: theoretical formulation and practical implementation // Ocean Dynamics. \--- 2003. \--- Vol.~53. \--- P.~343--367. 8. Evensen G. Data Assimilation. The Ensemble Kalman Filter. \--- Berlin, Heideberg: Spriger, 2009. 9. Golubeva E.N., Platov G.A. On improving the simulation of Atlantic water circulation in the Arctic Ocean // J. Geophys. Res. \--- 2007. \--- Vol.~112. \--- doi:10.1029/2006JC003734. 10. Golubeva E.N., Platov G.A. Numerical modeling of the Arctic Ocean ice system response to variations in the atmospheric circulation from 1948 to 2007 // Izv. Atmospheric and Oceanic Physics. \--- 2009. \--- Vol.~45, \No~1. \--- P.~137--151. 11. Handbook on Automatic Control Theory / A.A. Krasovsky, ed. \--- Moscow: Nauka, 1987 (In Russian). 12. Hickey B.M., Pietrafesa L.J., Jay D.A., Boicourt W.C. The Columbia river plume study: subtidal variability in the velocity and salinity fields // J. Geophys. Res. \--- 1998. \--- Vol.~103, \No~C5. \--- P.~10339--10368. 13. Houtekamer P.L., Mitchell H.L. Data assimilation using an ensemble Kalman filter technique // Mon. Wea. Rev. \--- 1998. \--- Vol.~126. \--- P.~796--811. 14. Houtekamer P.L., Mitchell H.L. A sequential ensemble Kalman filter for atmospheric data assimilation // Mon. Wea. Rev. \--- 2001. \--- Vol.~129. \--- P.~123--137. 15. Houtekamer P.L., Mitchell H.L., Pellerin G., et al. Atmospheric data assimilation with an ensemble Kalman filter: results with real observations // Mon. Wea. Rev. \--- 2005. \--- Vol.~133. \--- P.~604--620. 16. Hunke E.C., Dukowicz J.K. An elastic-viscous-plastic model for ice dynamics // J. Phys. Oceanography. \--- 1997. \--- Vol.~27, \No~9. \--- P.~1849--1867. 17. Jazwinski A.H. Stochastic Processes and Filtering Theory. \--- New York: Academic Press, 1970. 18. Kalnay E. Atmospheric Modeling, Data Assimilation and Predictability. \-- Cambridge Univ. Press, 2002, 377 pp. 19. Kilanova N.V., Klimova E.G. Numerical experiments on model error estimation in a problem of a passive pollution concentration data assimilation // Computational Technologies. \--- 2006. \--- Vol.~11, \No~5. \--- P.~32--40. 20. Klimova E.G., Kilanova N.V. Numerical experiments on estimation of methane emission based on the data assimilation system for passive impurity in the atmosphere of the Northern hemisphere // Atmospheric and Oceanic Optics. \--- 2006. \--- Vol.~19, \No~11. \--- P.~863--866. 21. Klimova E.G. A data assimilation technique based on the $\pi$-algorithm // Russian Meteorology and Hydrology. \--- 2008. \--- Vol.~33, \No~3. \--- P.~143--150. doi:10.3103/S1068373908030023. 22. Klimova E.G. Data assimilation technique based on the ensemble $\pi$-algorithm // Russian Meteorology and Hydrology. \--- 2008. \--- Vol.~33, \No~9. \--- P.~570--576. doi:10.3103/S1068373908090045. 23. Marchuk G.I., Sarkisian A.S. Mathematical Modeling of Ocean Circulation. \--- Moscow: Nauka, 1988 (In Russian). 24. Nadiga B.T., Casper W.R., Jones P.W. Ensemble-based global ocean data assimilation // Ocean Modelling. \---2003. \--- Vol.~72. \--- P.~210--230. doi:10.1016/j.ocemod.2013.09.002. 25. Nazarenko L., Holloway G., Tausnev N. Dynamics of transport of ``Atlantic signature" in the Arctic Ocean // J. Geophys. Res. \--- 1998. \--- Vol.~103. \--- P.~31003--31015. 26. Platov G.A. Numerical modeling of the Arctic Ocean deepwater formation: Part II. Results of regional and global experiments // Izv. Atmospheric and Oceanic Physics. \--- 2011. \--- Vol.~47, \No~3. \--- P.~377--392. 27. Proshutinsky A., Aksenov Y., Clement Kinney J., et al. Recent advances in Arctic ocean studies employing models from the Arctic Ocean Model Intercomparison Project // Oceanography. \--- 2011. \--- Vol.~24, \No~3. \--- P.~102--113. 28. Resnyansky Ju.D., Zelen'ko A.A. Development of models and methods of analysis of observation data for monitoring and predicting large-scale processes in the ocean // Proc. ``80th Anniversary of Hydrometcentre of Russia".\--- Moscow: Triada Ltd., 2010. \--- P.~350--375. 29. Reynolds R.W., Smith T.M., Liu C., Chelton D.B., Casey K.S., Schlax M.G. Daily high-resolution-blended analysis for sea surface temperature // J. Climate. \---2007. \--- Vol.~20. \--- P.~5473--5496. doi:10.1175/2007JCLI1824.1. 30. Scientific program of the Russian Federation participation in the International Polar Year (2007/2008).\--- Moscow, 2006.\--- \url{http://www.ipyrus.aari.ru/scientific_program.html}. 31. Weaver A.T., Deltel C., Machu E., et al. A multivariate balance operator for variational ocean data assimilation // Q.J.R. Meteorol. Soc. \--- 2005. \--- Vol.~131, \No~613. \--- P.~3605--3625. doi:10.1256/qj.05.119. 32. Yaglom A.M. Correlation Theory of Stationary Random Functions. \--- Leningrad: Gidrometeoizdat, 1981. 33. Yin Y., Alves O., Oke P.R. An ensemble ocean data assimilation system for seasonal prediction // Mon. Wea. Rev. \--- 2011. \--- Vol.~139. \--- P.~786--808. doi:10.1175/2010MWR3419.1.