<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Real-time prediction of Earth Orientation Parameters is necessary for many advanced geodetic and astronomical tasks including positioning and navigation on Earth and in space. Earth Rotation Parameters (ERP) are a subset of EOP, consisting of coordinates of the Earth’s pole (PMx, PMy) and UT1-UTC (or Length of Day – LOD). This paper presents the ultra-short-term (up to 15 days into the future) and short-term (up to 30 days into the future) ERP prediction using geostatistical method of ordinary kriging and autoregressive integrated moving average (ARIMA) model. This contribution uses rapid GNSS products EOP 14 12h from IGS, CODE and GFZ and also IERS final products – IERS EOP 14 C04 12h (IAU2000A). The results indicate that the accuracy of ARIMA prediction for each ERP is better for ultra-short prediction. The maximum differences between methods for first few days of 15-day predictions are around 0.32 mas (PMx), 0.23 mas (PMy) and 0.004 ms (LOD) in favour of ARIMA model. The maximum differences of Mean Absolute Prediction Errors (MAPEs) on the last few days of 30-day predictions are 1.91 mas (PMx), 0.30 mas (PMy) and 0.026 ms (LOD) with advantage to kriging method. For all ERPs the differences of MAPEs for time series from various analysis centres are not significant and vary up to maximum value of around 0.05 mas (PMx), 0.04 mas (PMy) and 0.005 ms (LOD).</p>
</abstract>

Real-time prediction of Earth Orientation Parameters is necessary for many advanced geodetic and astronomical tasks including positioning and navigation on Earth and in space. Earth Rotation Parameters (ERP) are a subset of EOP, consisting of coordinates of the Earth’s pole (PMx, PMy) and UT1-UTC (or Length of Day – LOD). This paper presents the ultra-short-term (up to 15 days into the future) and short-term (up to 30 days into the future) ERP prediction using geostatistical method of ordinary kriging and autoregressive integrated moving average (ARIMA) model. This contribution uses rapid GNSS products EOP 14 12h from IGS, CODE and GFZ and also IERS final products – IERS EOP 14 C04 12h (IAU2000A). The results indicate that the accuracy of ARIMA prediction for each ERP is better for ultra-short prediction. The maximum differences between methods for first few days of 15-day predictions are around 0.32 mas (PMx), 0.23 mas (PMy) and 0.004 ms (LOD) in favour of ARIMA model. The maximum differences of Mean Absolute Prediction Errors (MAPEs) on the last few days of 30-day predictions are 1.91 mas (PMx), 0.30 mas (PMy) and 0.026 ms (LOD) with advantage to kriging method. For all ERPs the differences of MAPEs for time series from various analysis centres are not significant and vary up to maximum value of around 0.05 mas (PMx), 0.04 mas (PMy) and 0.005 ms (LOD).

Prediction of Earth Rotation Parameters with the Use of Rapid Products from IGS, Code and GFZ Data Centres Using Arima and Kriging – A Comparison

Department of Integrated Geodesy and Cartography, Faculty of Geo-Data Science, Geodesy, and Environmental Engineering

Artificial Satellites

This work is licensed under the Creative Commons Attribution 4.0 International License.

Real-time prediction of Earth Orientation Parameters is necessary for many advanced geodetic and astronomical tasks including positioning and navigation on...

Prediction of Earth Rotation Parameters with the Use of Rapid Products from IGS, Code and GFZ Data Centres Using Arima and Kriging – A Comparison

Data publikacji: 05 sty 2023

Zakres stron: 274 - 289

Otrzymano: 18 lip 2022

Przyjęty: 06 paź 2022

DOI: https://doi.org/10.2478/arsa-2022-0024

Słowa kluczowe
ARIMA, kriging, polar motion, length of day, Earth Rotation Parameters

© 2022 Maciej Michalczak et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Prediction of Earth Rotation Parameters with the Use of Rapid Products from IGS, Code and GFZ Data Centres Using Arima and Kriging – A Comparison

Data publikacji: 05 sty 2023

Zakres stron: 274 - 289

Otrzymano: 18 lip 2022

Przyjęty: 06 paź 2022

DOI: https://doi.org/10.2478/arsa-2022-0024

Słowa kluczoweARIMA, kriging, polar motion, length of day, Earth Rotation Parameters

© 2022 Maciej Michalczak et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
ARIMA, kriging, polar motion, length of day, Earth Rotation Parameters