Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory
Part 1 A new approach is developed to reconstruct a three-dimensional incompressible flow from noisy data in an open domain using a two-scalar (toroidal and poloidal) spectral representation. The results are presented in two parts: theory (first part) and application (second part). In Part I, this app...
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ftnavalpschool:oai:calhoun.nps.edu:10945/36158 2024-06-09T07:49:45+00:00 Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory Ivanov, Leonid M. Korzhova, Tatiana P. Margolina, Tatiana Melnichenko, Oleg V. Chu, Peter C. Oceanography 2003 application/pdf https://hdl.handle.net/10945/36158 unknown Chu, P.C., L.M. Ivanov, T.P. Korzhova, T.M. Margolina, and O.M. Melnichenko, 2003: Analysis of sparse and noisy ocean current data using flow decomposition (paper download). Part 1: Theory. Journal of Atmospheric and Oceanic Technology, American Meteorological Society, 20 (4), 478-491. https://hdl.handle.net/10945/36158 This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. Article 2003 ftnavalpschool 2024-05-15T00:45:41Z Part 1 A new approach is developed to reconstruct a three-dimensional incompressible flow from noisy data in an open domain using a two-scalar (toroidal and poloidal) spectral representation. The results are presented in two parts: theory (first part) and application (second part). In Part I, this approach includes (a) a boundary extension method to determine normal and tangential velocities at an open boundary, (b) establishment of homogeneous open boundary conditions for the two potentials with a spatially varying coefficient k, (c) spectral expansion of k, (d) calculation of basis functions for each of the scalar potentials, and (e) determination of coefficients in the spectral decomposition of both velocity and k using linear or nonlinear regressions. The basis functions are the eigenfunctions of the Laplacian operator with homogeneous mixed boundary conditions and depend upon the spatially varying parameter k at the open boundary. A cost function used for poor data statistics is introduced to determine the optimal number of basis functions. An optimization scheme with iteration and regularization is proposed to obtain unique and stable solutions. In Part II, the capability of the method is demonstrated through reconstructing a 2D wind-driven circulation in a rotating channel, a baroclinic circulation in the eastern Black Sea, and a large-scale surface circulation in the Southern Ocean. This research was sponsored by the Office of Naval Research, Naval Oceanographic Office, and the Naval Postgraduate School. Leonid Ivanov, Tatyana Korzhova, Tatyana Margolina, and Oleg Melnichenko thank U.S. Civilian Research and Development Foundation for sup- port received through Award UG-2079. Article in Journal/Newspaper Southern Ocean Naval Postgraduate School: Calhoun Southern Ocean |
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Open Polar |
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Naval Postgraduate School: Calhoun |
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ftnavalpschool |
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description |
Part 1 A new approach is developed to reconstruct a three-dimensional incompressible flow from noisy data in an open domain using a two-scalar (toroidal and poloidal) spectral representation. The results are presented in two parts: theory (first part) and application (second part). In Part I, this approach includes (a) a boundary extension method to determine normal and tangential velocities at an open boundary, (b) establishment of homogeneous open boundary conditions for the two potentials with a spatially varying coefficient k, (c) spectral expansion of k, (d) calculation of basis functions for each of the scalar potentials, and (e) determination of coefficients in the spectral decomposition of both velocity and k using linear or nonlinear regressions. The basis functions are the eigenfunctions of the Laplacian operator with homogeneous mixed boundary conditions and depend upon the spatially varying parameter k at the open boundary. A cost function used for poor data statistics is introduced to determine the optimal number of basis functions. An optimization scheme with iteration and regularization is proposed to obtain unique and stable solutions. In Part II, the capability of the method is demonstrated through reconstructing a 2D wind-driven circulation in a rotating channel, a baroclinic circulation in the eastern Black Sea, and a large-scale surface circulation in the Southern Ocean. This research was sponsored by the Office of Naval Research, Naval Oceanographic Office, and the Naval Postgraduate School. Leonid Ivanov, Tatyana Korzhova, Tatyana Margolina, and Oleg Melnichenko thank U.S. Civilian Research and Development Foundation for sup- port received through Award UG-2079. |
author2 |
Oceanography |
format |
Article in Journal/Newspaper |
author |
Ivanov, Leonid M. Korzhova, Tatiana P. Margolina, Tatiana Melnichenko, Oleg V. Chu, Peter C. |
spellingShingle |
Ivanov, Leonid M. Korzhova, Tatiana P. Margolina, Tatiana Melnichenko, Oleg V. Chu, Peter C. Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory |
author_facet |
Ivanov, Leonid M. Korzhova, Tatiana P. Margolina, Tatiana Melnichenko, Oleg V. Chu, Peter C. |
author_sort |
Ivanov, Leonid M. |
title |
Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory |
title_short |
Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory |
title_full |
Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory |
title_fullStr |
Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory |
title_full_unstemmed |
Analysis of sparse and noisy ocean current data using flow decomposition Part 1: Theory |
title_sort |
analysis of sparse and noisy ocean current data using flow decomposition part 1: theory |
publishDate |
2003 |
url |
https://hdl.handle.net/10945/36158 |
geographic |
Southern Ocean |
geographic_facet |
Southern Ocean |
genre |
Southern Ocean |
genre_facet |
Southern Ocean |
op_relation |
Chu, P.C., L.M. Ivanov, T.P. Korzhova, T.M. Margolina, and O.M. Melnichenko, 2003: Analysis of sparse and noisy ocean current data using flow decomposition (paper download). Part 1: Theory. Journal of Atmospheric and Oceanic Technology, American Meteorological Society, 20 (4), 478-491. https://hdl.handle.net/10945/36158 |
op_rights |
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. |
_version_ |
1801382548457127936 |