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For the current ITRS, the origin is assumed to be aligned to the long-term Earth’s CM. In parallel, the geopotential models assume that on average the Earth’s CM is at the center of the geodetic network (i.e., zero values for degree-1 geopotential coefficients). Thus, the importance of an accurate geocenter motion cannot be overstated. Not accounting properly for the geocenter motion affects both satellite altimetry, precise orbit determination and satellite-derived estimates of the change in regional mean sea level. Because of climate change, and the need to both measure the change in the ice sheets and understand their impact on sea level and global fluid mass redistribution, we must explore strategies to better observe and model these subtle variations in the Earth’s geocenter. All space geodetic techniques rely on the availability of a precise and stable terrestrial reference frame such as ITRF2014 and ITRF2020 (see section Present status of the terrestrial reference frame realization; Altamimi et al. 2016). The stability over time of such a frame may inevitably impact all kind of geophysical interpretations that are deduced from geodetic observations. It was shown that it is not possible to ensure consistency between the ITRF2008 origin and the mean CM at a level better than 0.5 mm/year (Wu et al. 2011). These inconsistencies remain in ITRF2014 and cannot be properly explained by geophysical models (Riddell et al. 2017). Moreover, CM motions are today more than ever difficult to estimate with precision and stability, because they are also impacted by climate change. It has been shown that the global ice sheet melting may induce today an accelerated CM motion, possibly up to \(\sim\)1 mm/year with respect to the CF, towards south pole along the Earth’s rotational axis (e.g., Métivier et al. 2010, 2011, 2020). An error of a few tenths of mm/year in the frame origin stability estimation is well known to have a large impact on the orbit calculations of satellites and in the water mass redistribution on the surface (see Table 2). Nowadays uncertainty in the long-term trends in the geocenter motion of ±0.3 mm/year leads to uncertainties in the Antarctica mass change of 18 Gt/year (Wu et al. 2012; Blazquez et al. 2018). Direct local observations and space geodetic techniques including gravimetry, radar and laser altimetry, optical and synthetic aperture radar imagery and GNSS, have provided clear evidence for large changes in the world’s glaciers and ice sheets, in response to present climate change (e.g., Shepherd et al. 2018, 2020; Millan et al. 2022; Fox-Kemper et al. 2022). However, despite the extensive literature on the subject, the ice mass balances over the different ice sheets and smaller glacier regions are associated with large uncertainties (e.g., Cazenave et al. 2018; Métivier et al. 2010; Khan et al. 2015). In particular, the question of possible local accelerations of ice mass loss in Greenland is still open (e.g., Velicogna and Wahr 2013; Velicogna et al. 2014, 2020).

These ideas are ignoring some plainly obvious facts of logic that blows these theories to smithereans. This article and scientists are really promoting speculation fairy tales that cannot have any logic to them if one does not ignore some obvious facts that contradict these "far out theories" only found in their imaginations. Observed ground movements at the Earth surface are manifold and related to a whole set of processes. Common and essential to all these movements are detection and monitoring to execute and develop risk assessment strategies. Natural hazards, such as earthquakes, volcanic hazards or landslides may be preceded by small displacements of the Earth’s surface. Dense networks of GNSS stations in Japan, the western United States, and South America have been installed to monitor these surface displacements, related to the seismic cycle. In particular, pre-earthquake surface deformation can be related to the stress and the state of stress in the lithosphere. Surface displacements from increasing stress in the lithosphere may have small amplitudes. Therefore, a very stable and precise reference frame is required to be able to interpret these observations as reliable prediction tools for the onset of hazards versus errors in the techniques themselves. Top of atmosphere radiation budget and Earth energy imbalance and the Very Long Baseline Interferometry (VLBI) technique, which normal operation is to record signals from quasars. VLBI in its current application is a purely geometric technique, thus, it has no connection to the Earth’s gravity field (including the CM of the Earth). VLBI can currently be connected to the satellite techniques only via the station network and the local ties, and is not able to contribute to the geocenter determination. However, numerical simulations demonstrated that geodetic VLBI is able to observe geocenter motion using observations of Galileo satellites (Klopotek et al. 2020), suggesting that the GENESIS mission will enable a VLBI-contribution to the estimation of geocenter motion. The OHU can be estimated with an accuracy of a few tenths of W m \(On shorter timescales, GNSS stations also record Earth’s elastic response to surface mass redistribution within the climatic system (mainly continental water storage, atmosphere and ocean). Dense networks of permanent GNSS stations can now be used to derive soil and snow water content at seasonal timescales, but has also provided evidence for extreme droughts, especially in California (see, e.g., Argus et al. 2014; Fu et al. 2015; Jiang et al. 2022). GNSS time series from dense networks can be used to refine the information provided by space gravimetry missions (GRACE and GRACE-FO) at longer spatial wavelengths (see section Long-wavelength gravity field). Amplitude and spatial extent of surface water mass variations can be inferred from both vertical and horizontal deformation measurements. In particular, horizontal displacements help to refine the determination of the location and the spatial extent of the load. This elastic Earth’s response to surface loads has to be separated from a longer-term deformation, which can only be obtained with a more accurate and stable reference frame as proposed by the GENESIS project. The TRF is the realization of the TRS and is currently provided by precisely determined coordinates and velocities of physical points on the Earth’s surface. The main physical and mathematical properties of a TRS (at the definition and conventions level) or of the TRF (at the realization level) include each its origin, scale, orientation, and their time evolution. The center of mass (CM) of the Earth System, or geocenter, as the realized origin of the TRF on long-term scales, needs to be accurately determined including its temporal motion (e.g., Petit and Luzum 2010). The temporal variations of the geocenter represent a component of mass change (at spherical harmonic degree one) that is not directly observable from a mass-change mission such as GRACE-FO (Wu et al. 2012). While the degree one component of mass change can be derived from a combination of GRACE data with ocean model output (e.g., Swenson et al. 2008; Sun et al. 2016, 2017) or space geodetic techniques such as GNSS, SLR (e.g., Fritsche et al. 2009; Glaser et al. 2015), a high-quality TRF solution furnished by space geodesy that allows a matching with the temporal resolution of the GRACE-FO data would be highly desired (see section Long-wavelength gravity field for more details). GNSS-based determinations of the geocenter motion suffer from orbit modeling deficiencies due to an inherent coupling of the GNSS orbit dynamic parameters: the GNSS geocenter Z-component is strongly correlated with the parameterization of the Solar Radiation Pressure (SRP) (Meindl et al. 2013). With only limited a priori knowledge about the non-conservative forces acting on GNSS satellites, we must incorporate additional empirical orbit parameters into the solution, i.e., Empirical CODE Orbit Model or Jet Propulsion Laboratory GSPM. The errors in the orbit model, as well as the correlations between the estimated parameters (Rebischung et al. 2014), introduce spurious orbit-related signals in the GNSS-based geocenter motion estimates (Meindl et al. 2013; Rodriguez-Solano et al. 2014). The consistency between GNSS-based and SLR-based geocenter motion estimates can be improved by using satellite macromodels (Zajdel et al. 2021). Another way to improve the GNSS-based geocenter motion is the combined multi-GNSS processing (Scaramuzza et al. 2018) or the inclusion of Galileo satellites on an eccentric plane (Zajdel et al. 2021). The GENESIS mission will improve our ability to simultaneously identify the systematic errors and to consequently improve the ITRF accuracy and stability, particularly the origin and the scale that are the most critical parameters for scientific applications. GENESIS will leverage the crucial existing ground-based co-location network, allowing the development of future-proof terrestrial reference frames. Improvements in the ITRF geocenter and scale

A well written summary for the definition of space-time. I like the history and the introduction of how space-time works, but the focus on a reconciled quantum mechanical model to explain gravity seems like a math problem. A more logical approach might be to consider the 'Big Bang' theory from a pre-existing fabric of space-time without any real matter, as a proposed one dimensional determinant, its inception starts with the unfolding perspective of this dimensional determinant for space-time fabric towards existence. The sequence is somewhat understood from an expansion from our one dimensional space-time into a two dimensional space-time fabric, and then into a three dimensional space-time fabric, and so on. The expectation is that ordinary matter creation took place within a pre-existing dark energy medium of space-time. Indeed, the existence of matter would be an intrusion upon this pre-existing universal medium of space-time which maintains a zero sum difference that is the balance of our cosmological continuum. The ITRF long-term origin is defined by SLR, the most accurate satellite technique in sensing the Earth’s CM. The ITRF long-term scale, however, is defined by an average of the SLR and VLBI intrinsic scales. The consistency of these scales still needs to be improved, since both techniques are subject to systematic errors and other technical limitations, such as time and range biases for SLR, antenna deformation for VLBI, etc. The GENESIS mission will help to solve these inconsistencies. The ITRF orientation and its time evolution are defined to be the same for the successive ITRF realizations. Relativity means it is possible to travel into the future. We don't even need a time machine, exactly. We need to either travel at speeds close to the speed of light, or spend time in an intense gravitational field. In relativity, these two acts are essentially equivalent. Either way, you will experience a relatively short amount of subjective time, while decades or centuries pass in the rest of the Universe. If you want to see what happens hundreds of years from now, this is how to do it. As mentioned before, we expect that GENESIS will improve the determination of the reference frame. Such a stable ITRF should drastically reduce the frame dependency of ice mass balance estimations. Geodynamics, geophysics, natural hazards While time travel is fundamental to Doctor Who, the show never tries to ground the Tardis' abilities in anything resembling real-world physics. It would be odd to complain about this: Doctor Who has a fairy-tale quality and doesn't aspire to be realistic science fiction.It isn't even possible to send a message into the past, says Adlam. "The retrocausality is very specifically hidden by the way it's implemented." The GENESIS proposal is dedicated to improving and homogenizing time and space references on Earth and, more specifically, to realizing the Terrestrial Reference System (TRS) with an accuracy of 1 mm and a long-term stability of 0.1 mm/year. These numbers are relevant for many scientific and societal endeavors for which a precise realization of the TRS and the knowledge of the Earth’s kinematic parameters are crucial. So physical objects being 4D spatially-extended, as @jimdodds put it "fluctuations of density," reflects the fact that what the CERN LHC high-energy physics experiments actually measure is 4D electromagnetic energy density pressure concentrations. Just as AI pattern recognition famously aided in the discovery of the Higgs boson by recognizing collision pattern energy densities.