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A new hybrid method to improve the ultra-short-term prediction of LOD

Accurate, short-term predictions of Earth orientation parameters (EOP) are needed for many real-time applications including precise tracking and navigation of interplanetary spacecraft, climate forecasting, and disaster prevention. Out of the EOP, the LOD (length of day), which represents the change...

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Autores principales: Modiri, Sadegh, Belda, Santiago, Hoseini, Mostafa, Heinkelmann, Robert, Ferrándiz, José M., Schuh, Harald
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004433/
https://www.ncbi.nlm.nih.gov/pubmed/32109976
http://dx.doi.org/10.1007/s00190-020-01354-y
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author Modiri, Sadegh
Belda, Santiago
Hoseini, Mostafa
Heinkelmann, Robert
Ferrándiz, José M.
Schuh, Harald
author_facet Modiri, Sadegh
Belda, Santiago
Hoseini, Mostafa
Heinkelmann, Robert
Ferrándiz, José M.
Schuh, Harald
author_sort Modiri, Sadegh
collection PubMed
description Accurate, short-term predictions of Earth orientation parameters (EOP) are needed for many real-time applications including precise tracking and navigation of interplanetary spacecraft, climate forecasting, and disaster prevention. Out of the EOP, the LOD (length of day), which represents the changes in the Earth’s rotation rate, is the most challenging to predict since it is largely affected by the torques associated with changes in atmospheric circulation. In this study, the combination of Copula-based analysis and singular spectrum analysis (SSA) method is introduced to improve the accuracy of the forecasted LOD. The procedure operates as follows: First, we derive the dependence structure between LOD and the Z component of the effective angular momentum (EAM) arising from atmospheric, hydrologic, and oceanic origins (AAM + HAM + OAM). Based on the fitted theoretical Copula, we then simulate LOD from the Z component of EAM data. Next, the difference between LOD time series and its Copula-based estimation is modeled using SSA. Multiple sets of short-term LOD prediction have been done based on the IERS 05 C04 time series to assess the capability of our hybrid model. The results illustrate that the proposed method can efficiently predict LOD.
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spelling pubmed-70044332020-02-25 A new hybrid method to improve the ultra-short-term prediction of LOD Modiri, Sadegh Belda, Santiago Hoseini, Mostafa Heinkelmann, Robert Ferrándiz, José M. Schuh, Harald J Geod Original Article Accurate, short-term predictions of Earth orientation parameters (EOP) are needed for many real-time applications including precise tracking and navigation of interplanetary spacecraft, climate forecasting, and disaster prevention. Out of the EOP, the LOD (length of day), which represents the changes in the Earth’s rotation rate, is the most challenging to predict since it is largely affected by the torques associated with changes in atmospheric circulation. In this study, the combination of Copula-based analysis and singular spectrum analysis (SSA) method is introduced to improve the accuracy of the forecasted LOD. The procedure operates as follows: First, we derive the dependence structure between LOD and the Z component of the effective angular momentum (EAM) arising from atmospheric, hydrologic, and oceanic origins (AAM + HAM + OAM). Based on the fitted theoretical Copula, we then simulate LOD from the Z component of EAM data. Next, the difference between LOD time series and its Copula-based estimation is modeled using SSA. Multiple sets of short-term LOD prediction have been done based on the IERS 05 C04 time series to assess the capability of our hybrid model. The results illustrate that the proposed method can efficiently predict LOD. Springer Berlin Heidelberg 2020-02-05 2020 /pmc/articles/PMC7004433/ /pubmed/32109976 http://dx.doi.org/10.1007/s00190-020-01354-y Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Article
Modiri, Sadegh
Belda, Santiago
Hoseini, Mostafa
Heinkelmann, Robert
Ferrándiz, José M.
Schuh, Harald
A new hybrid method to improve the ultra-short-term prediction of LOD
title A new hybrid method to improve the ultra-short-term prediction of LOD
title_full A new hybrid method to improve the ultra-short-term prediction of LOD
title_fullStr A new hybrid method to improve the ultra-short-term prediction of LOD
title_full_unstemmed A new hybrid method to improve the ultra-short-term prediction of LOD
title_short A new hybrid method to improve the ultra-short-term prediction of LOD
title_sort new hybrid method to improve the ultra-short-term prediction of lod
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7004433/
https://www.ncbi.nlm.nih.gov/pubmed/32109976
http://dx.doi.org/10.1007/s00190-020-01354-y
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