[en] The maximum cross-correlation (MCC) method reconstructs the surface advective velocity fields from the displacements of spatial patterns in pairs of sequential satellite (normally infrared) images. However, the performance of the conventional MCC method is not always satisfactory. One of the main reasons for this is the fact that the method can correctly estimate only the velocity component parallel to the gradient of the property depicted in the images, while any small displacement perpendicular to the gradient (i.e., directed along the isolines) essentially maps the spatial pattern onto itself and therefore can not be detected using the conventional MCC technique. In the present work we propose a modification of the MCC method that allows circumventing this basic deficiency and improving the performance of the MCC technique. In this approach, the "cross-isoline'' components of the velocity field are obtained as in the conventional MCC scheme; however, the "along-isoline'' components derived from the MCC are disregarded as unreliable. Instead, the "true'' along-isoline components are then reconstructed from the given cross-isoline velocity field based on the continuity requirement and on the condition of no normal flow at solid boundaries. This inverse problem is solved by constructing the two-dimensional stream function in the curvilinear coordinate frame associated with the image isolines. The method is illustrated using AVHRR images from the southwestern Atlantic Ocean and the Black Sea. The results are compared with some direct drifter and current meter measurements and geostrophic estimates.
Research Center/Unit :
MARE - Centre Interfacultaire de Recherches en Océanologie - ULiège
Disciplines :
Physical, chemical, mathematical & earth Sciences: Multidisciplinary, general & others
Author, co-author :
Zavialov, Peter O.; Shirshov Institute of Oceanology (Moscow)
Grigorieva, Julia V.; Shirshov Institute of Oceanology (Moscow)
Moller, Osmar O.; University of Rio Grande (Brazil)
Kostianoy, Andrey G.; Shirshov Institute of Oceanology (Moscow)
Grégoire, Marilaure ; Université de Liège - ULiège > Département des sciences et gestion de l'environnement > Océanologie
Language :
English
Title :
Continuity preserving modified maximum cross-correlation technique
Publication date :
2002
Journal title :
Journal of Geophysical Research. Oceans
ISSN :
2169-9275
eISSN :
2169-9291
Publisher :
Amer Geophysical Union, Washington, United States - Washington
Afanasyev, Ya. D., A. G. Kostianoy, A. G. Zatsepin, and P.-M. Poulain, Analysis of velocity field in the Eastern Black Sea from satellite data during the "Black Sea - 99" experiment, J. Geophys. Res., 107, 3098, doi:10.1029/2000JC000578, 2002.
Borzelli, G., G. Manzella, S. Marullo, and R. Santoleri, Observations of coastal filaments in the Adriatic Sea, J. Mar. Syst., 20, 187-203, 1999.
Davis, R. E., Drifter observations of coastal surface currents during CODE: The method and descriptive view, J. Geophys. Res., 90, 4741-4755, 1985.
Domingues, C. M., C. A. Goncalves, R. D. Ghisolfi, and C. A. E. Garcia, Advective surface velocities derived from sequential infrared images in the Southwestern Atlantic ocean, Remote Sens. Environ., 73, 218-226, 2000.
Emery, W. J., A. C. Thomas, M. J. Collins, W. R. Crawford, and D. L. Mackas, An objective method for computing advective surface velocities from sequential infrared satellite images, J. Geophys. Res., 91, 12,865-12,878, 1986.
Garcia, C. A. E., and I. S. Robinson, Sea surface velocities in shallow seas extracted from sequential Coastal Zone Color Scanner satellite data, J. Geophys. Res., 94, 12,681-12,691, 1989.
Kamachi, M., Advective surface velocities derived from sequential images for rotational flow field: Limitations and applications of maximum cross correlation method with rotational registration, J. Geophys. Res., 94, 18,227-18,233, 1989.
Kelly, K. A., The influence of wind and topography on sea surface temperature patterns in the Northern California slope, J. Geophys. Res., 90, 11,783-11,798, 1985.
Kelly, K. A., An inverse model for near-surface velocity from infrared images, j. Phys. Oceanogr., 19, 1845-1864, 1989.
Kelly, K. A., and P. T. Strub, Comparison of velocity estimates from Advanced Very High Resolution Radiometer in the coastal transition zone, J. Geophys. Res., 97, 9653-9668, 1992.
La Violette, P. E., The advection of submesoscale thermal features in the Alboran Sea Gyre, J. Phys. Oceanogr., 14, 450-505, 1984.
Leese, J. A., C. S. Novak, and B. B. Clarke, An automated technique for obtaining cloud motion from geosynchronous satellite data using cross correlation, J. Appl. Meteorol., 10, 110-132, 1971.
Levy, G., and R. A. Brown, A simple objective analysis scheme for scatterometer data, J. Geophys. Res., 91, 5153-5158, 1986.
Motyzhev, S. V., A. G. Zatsepin, C. Fayos, A. G. Kostianoy, N. A. Maximenko, S. G. Poyarkov, D. M. Soloviev, and S. V. Stanichny, New phase of drifter experiment in the Black sea, Global Drifting Buoy Observations - 2000, in A DBCP Implementation Strategy, DBCP Tech. Doc. Ser. 16, WMO, Geneva, 2000.
Ninnis, R. M., W. J. Emery, and M. J. Collins, Automated extraction of pack ice motion from AVHRR imagery, J. Geophys. Res., 91, 10,725-10,734, 1986.
Stow, D. A., Numerical derivation of a hydrodynamic surface flow field from time sequential remotely sensed data, Remote Sens. Environ., 23, 1-22, 1987.
Svejkovsky, J., Sea surface flow estimation from Advanced Very High Resolution Radiometer and Coastal Zone Color Scanner imagery, J. Geophys. Res., 93, 6735-6743, 1988.
Sybrandy, A. L., and P. P. Niiler, WOCE/TOGA Lagrangian Drifter Construction Manual, Scripps Inst. of Oceanogr., La Jolla, Calif., 1991.
Tokmakian, R. T., P. T. Strub, and J. McClean-Padman, Evaluation of the maximum cross-correlation method of estimating sea surface velocities from sequential satellite images, J. Atmos. Oceanic Technol., 7, 852-865, 1990.
Van Woert, M., The subtropical front: Satellite observations during FRONTS 80, J. Geophys. Res., 87, 9523-9536, 1982.
Vastano, A. C., and R. O. Reid, Sea surface topography estimation with infrared satellite imagery, J. Atmos. Technol., 2, 393-400, 1985.
Vigan, X., C. Provost, R. Bleck, and F. Courtier, Sea surface velocities from sea surface temperature image sequences, 1, Method and validation using primitive equation model output, J. Geophys. Res., 105, 19,499-19,514, 2000a.
Vigan, X., C. Provost, and G. Podesta, Sea surface velocities from sea surface temperature image sequences, 2, Application to the Brazil-Malvinas Confluence area, J. Geophys. Res., 105, 19,515-19,534, 2000b.
Wunsch, C., Can a tracer field be inverted for velocity?, J. Phys. Oceanogr:, 15, 1521-1531, 1985.
Zavialov, P. O., R. D. Ghisolfi, and C. A. E. Garcia, An inverse model for seasonal circulation over the Southern Brazilian shelf: Near-surface velocity from the heat budget, J. Phys. Oceanogr., 28, 545-562, 1998.
Zavialov, P. O., I. Wainer, and J. M. Absy, Sea surface temperature variability off southern Brazil and Uruguay as revealed from historical data since 1854, J. Geophys. Res., 104, 21,021-21,032, 1999.
Zavialov, P. O., S. M. F. Gianesella-Galvão, F. M. Pimenta, G. P. Castelão, and S. M. Abdoullaev, Diurnal variability on the continental shelf of Southern Brazil, Cont. Shelf Res., 20, 15-35, 2000.
Zavialov, P. O., O. O. Möller Jr., and E. Campos, First direct measurements of currents on the shelf of Southern Brazil, Cont. Shelf Res., 22, 1975-1986, 2002.