Spatial regression and multiscale approximations for sequential data assimilation in ocean models

Journal of Geophysical Research: Oceans

Volumn 104, Issue C4, 1999, Pages 7991-8014

  Chin, Toshio M ^a   Mariano, Arthur J ^a   Chassignet, Eric P ^a  

^a UNIVERSITY OF MIAMI   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ASSIMILATION; KALMAN FILTER; MODELING; PHYSICAL OCEANOGRAPHY;

EID: 0033560571     PISSN: None     EISSN: 21699291     Source Type: Journal    
DOI: 10.1029/1998jc900075     Document Type: Article

References (39)

1. Anderson, B. D. O., and J. B. Moore, Optimal Filtering, Prentice-Hall, Englewood Cliffs, N. J., 1979.
2. Bennett, A. F., Inverse Methods in Physical Oceanography, Cambridge Univ. Press, New York, 1992.
3. Bennett, A. F., and W. P. Budgell, Ocean data assimilation and the Kalman filter: Spatial regularity, J. Phys. Oceanogr., 17, 1583-1601, 1987.
4. Besag, J., Spatial interaction and the statistical analysis of lattice systems, J. R. Stat. Soc. Ser. B, 36, 192-236, 1974.
5. Bleck, R., and E. Chassignet, Simulating the oceanic circulation with isopycnic-coordinate models, in The Oceans: Physical-Chemical Dynamics and Human Impact, edited by S. K. Majumbar and W. E. Miller, pp. 17-39, Pa. Acad. of Sci., Easton, 1994.
6. Bleck, R., C. Rooth, D. Hu, and L. T. Smith, Ventilation and mode water formation in a wind- and thermohaline-driven isopycnic coordinate model of the North Atlantic, J. Phys. Oceanogr., 22, 1486-1505, 1992.
7. Bleck, R., S. Dean, M. O'Keefe, and A. Sawdey, A comparison of data-parallel and message-passing versions of the Miami Isopycnic Coordinate Ocean Model (MICOM), Parallel Comput., 21, 1695-1720, 1995.
8. Cane, M. A., A. Kaplan, R. N. Miller, B. Tang, E. C. Hackert, and A. J. Busalacchi, Mapping tropical Pacific sea level: Data assimilation via a reduced state space Kalman filter, J. Geophys. Res., 101, 22,599-22,617, 1996.
9. Chassignet, E. P., D. B. Olson, and D. B. Boudra, Motion and evolution of oceanic rings in a numerical model and in observations, J. Geophys. Res., 95, 22,121-22,140, 1990.
10. Chassignet, E. P., W. R. Holland, and A. Capotondi, Impact of the altimeter orbit on the reproduction of oceanic rings: Application to a regional model of the Gulf Stream, Oceanol. Acta, 15, 479-490, 1992.
11. Chin, T. M., W. C. Karl, and A. S. Willsky, Sequential filtering for multi-frame visual reconstruction, Signal Process., 28, 311-333, 1992.
12. Chin, T. M., W. C. Karl, and A. S. Willsky, Probabilistic and sequential computation of optical flow using temporal coherence, IEEE Trans. Image Process., 3, 773-788, 1994.
13. Chin, T. M., W. C. Karl, and A. S. Willsky, A distributed and iterative method for square root filtering in space-time estimation, Automatica, 31, 67-82, 1995.
14. Cohn, S. E., Dynamics of short-term univariate forecast error covariances, Mon. Weather Rev., 121, 3123-3149, 1993.
15. Cohn, S. E., and D. F. Parrish, The behavior of forecast error covariances for a Kalman filter in two dimensions, Mon. Weather Rev., 119, 1757-1785, 1991.
16. Daley, R., Atmospheric Data Analysis, Cambridge Univ. Press, New York, 1991.
17. Daubechies, I., Ten Lectures on Wavelets, Soc. for Ind. and Appl. Math., Philadelphia, Pa., 1992.
18. Dee, D. P., Simplification of the Kalman filter for meteorological data assimilation, Q. J. R. Meteorol. Soc., 117, 365-384, 1991.
19. Evensen, G., Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res., 99, 10,143-10,162, 1994.
20. Fukumori, I., and P. Malanotte-Rizzoli, An approximate Kalman filter for ocean data assimilation: An example with an idealized Gulf Stream model, J. Geophys. Res., 100, 6777-6793, 1995.
21. Geman, S., and D. Geman, Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, IEEE Trans. Pattern Anal. Mach. Intel., PAMI-6, 721-741, 1984.
22. Ghil, M., and P. Malanotte-Rizzoli, Data assimilation in meteorology and oceanography, Adv. Geophys., 33, 141-266, 1991.
23. Ghil, M., S. Cohn, J. Travantzis, K. Bube, and E. Issacson, Application of estimation theory to numerical weather prediction, in Dynamic Meteorology: Data Assimilation Methods, edited by L. Bengtsson, M. Ghil, and E. Kallen, pp. 139-284. Springer-Verlag, New York, 1981.
24. Habibi, A., Two-dimensional Bayesian estimate of images, Proc. IEEE, 60, 878-883, 1972.
25. Jiang, S., and M. Ghil, Dynamical properties of error statistics in a shallow-water model, J. Phys. Oceanogr., 23, 2541-2566, 1993.
26. Kindermann, R., and J. L. Snell, Markov Random Fields and Their Applications, Am. Math. Soc., Providence, R. I., 1980.
27. Lewis, F. L., Optimal Estimation, John Wiley, New York, 1986.
28. Mariano, A. J., and O. Brown, Efficient objective analysis of dynamically heterogeneous and nonstationary fields via the parameter matrix, Deep Sea Res., Part A, 39, 1255-1271, 1992.
29. Menemenlis, D., and C. Wunsch, Linearization of an oceanic general circulation model for data assimilation and climate studies, J. Atmos. Oceanic Technol., 14, 1420-1443, 1997.
30. Miller, R. N., Toward the application of the Kalman filter to regional open ocean modeling, J. Phys. Oceanogr., 16, 72-86, 1986.
31. Miller, R. N., and M. A. Cane, A Kalman filter analysis of sea level height in the tropical Pacific, J. Phys. Oceanogr., 19, 773-790, 1989.
32. Miller, R. N., M. S. Ghil, and F. Gauthiez, Advanced data assimilation in strongly nonlinear dynamical systems, J. Atmos. Sci., 51, 1037-1056, 1994.
33. Parrish, D. F., and S. E. Cohn, A Kalman filter for a two-dimensional shallow-water model: Formulation and preliminary experiments, Tech. Rep. Off. Note 304, Natl. Cent. for Environ. Predict., Washington, D. C., 1985.
34. Pham, D. T., J. Verron, and M. C. Roubaud, A singular evolutive extended Kalman filter for data assimilation in oceanography, J. Mar. Syst., 16, 323-340, 1998.
35. Sasaki, Y., Some basic formalism in numerical variational analysis, Mon. Weather Rev., 98, 875-883, 1970.
36. Talagrand, O., Assimilation of observations, an introduction, J. Meteorol. Soc. Jpn., 75, 191-209, 1997.
37. Thacker, W. C., and R. B. Long, Fitting dynamics to data, J. Geophys. Res., 93, 1227-1240, 1988.
38. Wilks, D. S., Statistical Methods in the Atmospheric Sciences, Academic, San Diego, Calif., 1995.
39. Wunsch, C., The Ocean Circulation Inverse Problem, Cambridge Univ. Press, New York, 1996.