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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Main Authors: Parés Sierra, Alejandro autor 13912, Flores Morales, Ana Laura autora, Gómez Valdivia, Felipe Doctor autor 13911
Format: Texto biblioteca
Language:eng
Subjects:Corrientes oceánicas, Análisis estadístico,
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spelling 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
institution ECOSUR
collection Koha
country México
countrycode MX
component Bibliográfico
access En linea
databasecode cat-ecosur
tag biblioteca
region America del Norte
libraryname Sistema de Información Bibliotecario de ECOSUR (SIBE)
language eng
topic Corrientes oceánicas
Análisis estadístico
Corrientes oceánicas
Análisis estadístico
spellingShingle 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.
format Texto
topic_facet 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
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