Earth Rotation Parameters Prediction and Climate Change Indicators in It

• Autorzy: Xu Xueqing , Zhou Yonghong , Xu Cancan

Identyfikatory

DOI

10.2478/arsa-2022-0023

• Konferencja: Proceedings of the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) Workshop, online, February 15-16, 2022
• Języki publikacji: EN

Abstrakty

EN

As one of the participants in the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC), we submitted two data files. One is 365 days’ predictions into the future for Earth orientation parameters (EOP) (the position parameters Px and Py, the time parameters UT1-UTC and length of day changes ΔLOD), processed by the traditional least-square and autoregressive (LS + AR) model. Another is 90 days’ predictions by the combined least-square and convolution method (LS + Convolution), with effective angular momentum (EAM) from Earth System Modelling GeoForschungsZentrum in Potsdam (ESMGFZ). Results showed that the LS + Convolution method performed better than the LS + AR model in short-term EOP predictions within 10 days, while the traditional LS + AR model presented higher accuracy in medium-term predictions over 10-90 days. Furthermore, based on the climate change information in Earth’s rotation (mainly in the interannual variations of LOD), the climate change indicators are investigated with ΔLOD observations and long-term predictions. After two intermediate La Nina events were detected in the climate-related ΔLOD observations during the period of 2020-2022, another stronger La Nina phenomenon is indicated in the climate-related ΔLOD long-term predictions.

Słowa kluczowe

EN

EOP prediction; effective angular momentum; interannual ΔLOD; climate change indicators

• Wydawca: Centrum Badań Kosmicznych PAN ; De Gruyter
• Czasopismo: Artificial Satellites : Journal of Planetary Geodesy
• Rocznik: 2022
• Tom: Vol. 57, Special Issue 1
• Strony: 262--273
• Opis fizyczny: Bibliogr. 32 poz., tab., wykr.

Twórcy

autor

Xu Xueqing

• Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, China
• Key Laboratory of Planetary Sciences, Chinese Academy of Sciences, Shanghai, China
• School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing, China

autor

Zhou Yonghong

• Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, China
• Key Laboratory of Planetary Sciences, Chinese Academy of Sciences, Shanghai, China
• School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing, China

autor

Xu Cancan

• Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai, China
• School of Astronomy and Space Science, University of Chinese Academy of Sciences, Beijing, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).