An efficient Markovian algorithm for the analysis of ocean currents
We propose a method for analyzing ocean currents using a statistical approach. The proposed technique is useful for analyzing global velocity fields and producing indices to describe the probable trajectories and destinations of particles embedded in such fields. Short-term Lagrangian integration of the velocities was used to generate transition matrices that define the system locally. A reshuffling algorithm, based on standard Markov Chain theory, was implemented to mix and synthesize the information involved in the global analysis. Iterative methods were then used to solve the resulting large and sparse linear systems. The method efficiently used local information (short-term Lagrangian integration) to infer global characteristics of the system. Two case studies were presented to emphasize the merits of the described scheme: one using modeled data from the Gulf of California, and another from the Gulf of Mexico.
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KOHA-OAI-ECOSUR:588292024-03-11T15:27:13ZAn efficient Markovian algorithm for the analysis of ocean currents Parés Sierra, Alejandro autor 13912 Flores Morales, Ana Laura autora Gómez Valdivia, Felipe Doctor autor 13911 textengWe propose a method for analyzing ocean currents using a statistical approach. The proposed technique is useful for analyzing global velocity fields and producing indices to describe the probable trajectories and destinations of particles embedded in such fields. Short-term Lagrangian integration of the velocities was used to generate transition matrices that define the system locally. A reshuffling algorithm, based on standard Markov Chain theory, was implemented to mix and synthesize the information involved in the global analysis. Iterative methods were then used to solve the resulting large and sparse linear systems. The method efficiently used local information (short-term Lagrangian integration) to infer global characteristics of the system. Two case studies were presented to emphasize the merits of the described scheme: one using modeled data from the Gulf of California, and another from the Gulf of Mexico.We propose a method for analyzing ocean currents using a statistical approach. The proposed technique is useful for analyzing global velocity fields and producing indices to describe the probable trajectories and destinations of particles embedded in such fields. Short-term Lagrangian integration of the velocities was used to generate transition matrices that define the system locally. A reshuffling algorithm, based on standard Markov Chain theory, was implemented to mix and synthesize the information involved in the global analysis. Iterative methods were then used to solve the resulting large and sparse linear systems. The method efficiently used local information (short-term Lagrangian integration) to infer global characteristics of the system. Two case studies were presented to emphasize the merits of the described scheme: one using modeled data from the Gulf of California, and another from the Gulf of Mexico.Corrientes oceánicasAnálisis estadísticoEnvironmental Modelling & SoftwareDisponible para usuarios de ECOSUR con su clave de acceso |
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Corrientes oceánicas Análisis estadístico Corrientes oceánicas Análisis estadístico |
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Corrientes oceánicas Análisis estadístico Corrientes oceánicas Análisis estadístico Parés Sierra, Alejandro autor 13912 Flores Morales, Ana Laura autora Gómez Valdivia, Felipe Doctor autor 13911 An efficient Markovian algorithm for the analysis of ocean currents |
description |
We propose a method for analyzing ocean currents using a statistical approach. The proposed technique is useful for analyzing global velocity fields and producing indices to describe the probable trajectories and destinations of particles embedded in such fields. Short-term Lagrangian integration of the velocities was used to generate transition matrices that define the system locally. A reshuffling algorithm, based on standard Markov Chain theory, was implemented to mix and synthesize the information involved in the global analysis. Iterative methods were then used to solve the resulting large and sparse linear systems. The method efficiently used local information (short-term Lagrangian integration) to infer global characteristics of the system. Two case studies were presented to emphasize the merits of the described scheme: one using modeled data from the Gulf of California, and another from the Gulf of Mexico. |
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Texto |
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Corrientes oceánicas Análisis estadístico |
author |
Parés Sierra, Alejandro autor 13912 Flores Morales, Ana Laura autora Gómez Valdivia, Felipe Doctor autor 13911 |
author_facet |
Parés Sierra, Alejandro autor 13912 Flores Morales, Ana Laura autora Gómez Valdivia, Felipe Doctor autor 13911 |
author_sort |
Parés Sierra, Alejandro autor 13912 |
title |
An efficient Markovian algorithm for the analysis of ocean currents |
title_short |
An efficient Markovian algorithm for the analysis of ocean currents |
title_full |
An efficient Markovian algorithm for the analysis of ocean currents |
title_fullStr |
An efficient Markovian algorithm for the analysis of ocean currents |
title_full_unstemmed |
An efficient Markovian algorithm for the analysis of ocean currents |
title_sort |
efficient markovian algorithm for the analysis of ocean currents |
work_keys_str_mv |
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1794791848464613376 |