Kehm, A., Hellmers, H., Bloßfeld, M., Dill, R., Angermann, D., Seitz, F., Hugentobler, U., Dobslaw, H., Thomas, M., Thaller, D., Böhm, J., Schönemann, E., Mayer, V., Springer, T., Otten, M., Bruni, S., & Enderle, W. (2023). Combination strategy for consistent final, rapid and predicted Earth rotation parameters. Journal of Geodesy, 97(1). https://doi.org/10.1007/s00190-022-01695-w
The accurate knowledge of the Earth’s orientation and rotation in space is essential for a broad variety of scientific and societal applications. Among others, these include global positioning, near-Earth and deep-space navigation, the realisation of precise reference and time systems as well as studies of geodynamics and global change phenomena. In this paper, we present a refined strategy for processing and combining Very Long Baseline Interferometry (VLBI), Satellite Laser Ranging (SLR), Global Navigation Satellite Systems (GNSS), and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) observations at the normal equation level and formulate recommendations for a consistent processing of the space-geodetic input data. Based on the developed strategy, we determine final and rapid Earth rotation parameter (ERP) solutions with low latency that also serve as the basis for a subsequent prediction of ERPs involving effective angular momentum data. Realising final ERPs on an accuracy level comparable to the final ERP benchmark solutions IERS 14C04 and JPL COMB2018, our strategy allows to enhance the consistency between final, rapid and predicted ERPs in terms of RMS differences by up to 50% compared to existing solutions. The findings of the study thus support the ambitious goals of the Global Geodetic Observing System (GGOS) in providing highly accurate and consistent time series of geodetic parameters for science and applications.
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Project title:
Unabhängige Bestimmung von Erdorientierungsparametern: 4000xxxxxx/17/D/SR (Europäische Weltraumorganisation ESA)
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Research Areas:
Environmental Monitoring and Climate Adaptation: 100%