Earth rotation parameter estimation from LLR

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  • DLR-Institut für Satellitengeodäsie und Inertialsensorik
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Details

OriginalspracheEnglisch
Seiten (von - bis)2383-2398
Seitenumfang16
FachzeitschriftAdvances in Space Research
Jahrgang70
Ausgabenummer8
Frühes Online-Datum22 Juli 2022
PublikationsstatusVeröffentlicht - 15 Okt. 2022

Abstract

LLR measures the distance between observatories on Earth and retro-reflectors on Moon since 1969. In this paper, we estimate the Earth Rotation Parameters (ERP; terrestrial pole offsets, xp and yp, and Earth rotation phase, ΔUT) using LLR data. We estimate the values of ΔUT, and the pole offsets separately. For the pole offsets, we estimate the values of xp and yp together and separately. Overall, the uncertainties of ERP from the new LLR data (after 2000.0) have significantly improved, staying less than 20 μs for ΔUT, less than 2.5 mas for xp, and less than 3 mas for yp for nights selected from subsets of the LLR time series which have 10 and 15 normal points obtained per night. Furthermore, we add the non-tidal loading effect provided by the IMLS, as observation level corrections of the LLR observatories in the analysis. This effect causes deformations of the Earth surface up to the centimetre level. Its addition in the Institute of Geodesy (IfE) LLR model, leads to a marginal improvement in the uncertainties (3-σ values) of about 1% for both, ΔUT and the pole offsets.

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Earth rotation parameter estimation from LLR. / Singh, Vishwa Vijay; Biskupek, Liliane; Müller, Jürgen et al.
in: Advances in Space Research, Jahrgang 70, Nr. 8, 15.10.2022, S. 2383-2398.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Singh VV, Biskupek L, Müller J, Zhang M. Earth rotation parameter estimation from LLR. Advances in Space Research. 2022 Okt 15;70(8):2383-2398. Epub 2022 Jul 22. doi: 10.1016/j.asr.2022.07.038
Singh, Vishwa Vijay ; Biskupek, Liliane ; Müller, Jürgen et al. / Earth rotation parameter estimation from LLR. in: Advances in Space Research. 2022 ; Jahrgang 70, Nr. 8. S. 2383-2398.
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title = "Earth rotation parameter estimation from LLR",
abstract = "LLR measures the distance between observatories on Earth and retro-reflectors on Moon since 1969. In this paper, we estimate the Earth Rotation Parameters (ERP; terrestrial pole offsets, xp and yp, and Earth rotation phase, ΔUT) using LLR data. We estimate the values of ΔUT, and the pole offsets separately. For the pole offsets, we estimate the values of xp and yp together and separately. Overall, the uncertainties of ERP from the new LLR data (after 2000.0) have significantly improved, staying less than 20 μs for ΔUT, less than 2.5 mas for xp, and less than 3 mas for yp for nights selected from subsets of the LLR time series which have 10 and 15 normal points obtained per night. Furthermore, we add the non-tidal loading effect provided by the IMLS, as observation level corrections of the LLR observatories in the analysis. This effect causes deformations of the Earth surface up to the centimetre level. Its addition in the Institute of Geodesy (IfE) LLR model, leads to a marginal improvement in the uncertainties (3-σ values) of about 1% for both, ΔUT and the pole offsets.",
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note = "Funding information: Current LLR data are collected, archived, and distributed under the auspices of the International Laser Ranging Service (ILRS) (Pearlman et al. 2019). We acknowledge with thanks that the processed LLR data, since 1969, has been obtained under the efforts of the personnel at the Observatoire de la C{\^o}te d'Azur in France, the LURE Observatory in Maui, Hawaii, the McDonald Observatory in Texas, the Apache Point Observatory in New Mexico, the Matera Laser Ranging observatory in Italy, and the Wettzell Laser Ranging System in Germany. This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy EXC 2123 QuantumFrontiers, Project-ID 390837967. We would additionally like to thank Franz Hofmann for his contributions to LUNAR.",
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Download

TY - JOUR

T1 - Earth rotation parameter estimation from LLR

AU - Singh, Vishwa Vijay

AU - Biskupek, Liliane

AU - Müller, Jürgen

AU - Zhang, Mingyue

N1 - Funding information: Current LLR data are collected, archived, and distributed under the auspices of the International Laser Ranging Service (ILRS) (Pearlman et al. 2019). We acknowledge with thanks that the processed LLR data, since 1969, has been obtained under the efforts of the personnel at the Observatoire de la Côte d'Azur in France, the LURE Observatory in Maui, Hawaii, the McDonald Observatory in Texas, the Apache Point Observatory in New Mexico, the Matera Laser Ranging observatory in Italy, and the Wettzell Laser Ranging System in Germany. This research was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany's Excellence Strategy EXC 2123 QuantumFrontiers, Project-ID 390837967. We would additionally like to thank Franz Hofmann for his contributions to LUNAR.

PY - 2022/10/15

Y1 - 2022/10/15

N2 - LLR measures the distance between observatories on Earth and retro-reflectors on Moon since 1969. In this paper, we estimate the Earth Rotation Parameters (ERP; terrestrial pole offsets, xp and yp, and Earth rotation phase, ΔUT) using LLR data. We estimate the values of ΔUT, and the pole offsets separately. For the pole offsets, we estimate the values of xp and yp together and separately. Overall, the uncertainties of ERP from the new LLR data (after 2000.0) have significantly improved, staying less than 20 μs for ΔUT, less than 2.5 mas for xp, and less than 3 mas for yp for nights selected from subsets of the LLR time series which have 10 and 15 normal points obtained per night. Furthermore, we add the non-tidal loading effect provided by the IMLS, as observation level corrections of the LLR observatories in the analysis. This effect causes deformations of the Earth surface up to the centimetre level. Its addition in the Institute of Geodesy (IfE) LLR model, leads to a marginal improvement in the uncertainties (3-σ values) of about 1% for both, ΔUT and the pole offsets.

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