Assessment of length-of-day and universal time predictions based on the results of the Second Earth Orientation Parameters Prediction Comparison Campaign
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Título: | Assessment of length-of-day and universal time predictions based on the results of the Second Earth Orientation Parameters Prediction Comparison Campaign |
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Autor/es: | Śliwińska-Bronowicz, Justyna | Kur, Tomasz | Wińska, Małgorzata | Dobslaw, Henryk | Nastula, Jolanta | Partyka, Aleksander | Belda, Santiago | Bizouard, Christian | Boggs, Dale | Bruni, Sara | Chen, Lue | Chin, Mike | Dhar, Sujata | Dill, Robert | Ferrandiz, Jose M. | Gou, Junyang | Gross, Richard | Guessoum, Sonia | Han, Songtao | Heinkelmann, Robert | Irrgang, Christopher | Shahvandi, Mostafa Kiani | Li, Jia | Ligas, Marcin | Liu, Lintao | Lu, Weitao | Mayer, Volker | Michalczak, Maciej | Modiri, Sadegh | Otten, Michiel | Ratcliff, Todd | Raut, Shrishail | Saynisch-Wagner, Jan | Schartner, Matthias | Schoenemann, Erik | Schuh, Harald | Soja, Benedikt | Su, Xiaoqing | Thaller, Daniela | Thomas, Maik | Wang, Guocheng | Wu, Yuanwei | Xu, Xueqing | Yang, Xinyu | Zhao, Xin | Zhou, Zhijin |
Grupo/s de investigación o GITE: | Geodesia Espacial y Dinámica Espacial |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Matemática Aplicada |
Palabras clave: | Earth Orientation Parameters (EOP) | Length-of-day (LOD) | UT1–UTC | Prediction |
Fecha de publicación: | 20-mar-2024 |
Editor: | Springer Nature |
Cita bibliográfica: | Journal of Geodesy. 2024, 98:22. https://doi.org/10.1007/s00190-024-01824-7 |
Resumen: | Predicting Earth Orientation Parameters (EOP) is crucial for precise positioning and navigation both on the Earth’s surface and in space. In recent years, many approaches have been developed to forecast EOP, incorporating observed EOP as well as information on the effective angular momentum (EAM) derived from numerical models of the atmosphere, oceans, and land-surface dynamics. The Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) aimed to comprehensively evaluate EOP forecasts from many international participants and identify the most promising prediction methodologies. This paper presents the validation results of predictions for universal time and length-of-day variations submitted during the 2nd EOP PCC, providing an assessment of their accuracy and reliability. We conduct a detailed evaluation of all valid forecasts using the IERS 14 C04 solution provided by the International Earth Rotation and Reference Systems Service (IERS) as a reference and mean absolute error as the quality measure. Our analysis demonstrates that approaches based on machine learning or the combination of least squares and autoregression, with the use of EAM information as an additional input, provide the highest prediction accuracy for both investigated parameters. Utilizing precise EAM data and forecasts emerges as a pivotal factor in enhancing forecasting accuracy. Although several methods show some potential to outperform the IERS forecasts, the current standard predictions disseminated by IERS are highly reliable and can be fully recommended for operational purposes. |
Patrocinador/es: | This study was funded by the National Science Centre, Poland under the OPUS call in the Weave programme, Grant number 2021/43/I/ST10/01738. H. Dobslaw is supported by the project DISCLOSE, funded by the German Research Foundation (DO 1311/6-1). The work of D. Boggs, M. Chin, R. Gross, and T. Ratcliff described in this paper was performed at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. S. Belda was partially supported by Generalitat Valenciana (SEJIGENT/2021/001) and the European Union—NextGenerationEU (ZAMBRANO 21-04). J. M. Ferrandiz was partially supported by Spanish Project PID2020-119383 GB-I00 funded by Ministerio de Ciencia e Innovación (MCIN/AEI/10.13039/501100011033/) and PROMETEO/2021/030 funded by Generalitat Valenciana. |
URI: | http://hdl.handle.net/10045/141855 |
ISSN: | 0949-7714 (Print) | 1432-1394 (Online) |
DOI: | 10.1007/s00190-024-01824-7 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © The Author(s) 2024. Open Access This 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/. |
Revisión científica: | si |
Versión del editor: | https://doi.org/10.1007/s00190-024-01824-7 |
Aparece en las colecciones: | INV - GEDE - Artículos de Revistas |
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