The impacts of source structure on geodetic parameters demonstrated by the radio source 3C371

Closure quantities measured by very long baseline interferometry (VLBI) observations are independent of instrumental and propagation instabilities and antenna gain factors, but are sensitive to source structure. A new method is proposed to calculate a structure index based on the median values of closure quantities rather than the brightness distribution of a source. The results are comparable to structure indices based on imaging observations at other epochs and demonstrate the flexibility of deriving structure indices from exactly the same observations as used for geodetic analysis and without imaging analysis. A three-component model for the structure of source 3C371 is developed by model-fitting closure phases. It provides a real case of tracing how the structure effect identified by closure phases in the same observations as the delay observables affects the geodetic analysis, and investigating which geodetic parameters are corrupted to what extent by the structure effect. Using the resulting structure correction based on the three-component model of source 3C371, two solutions, with and without correcting the structure effect, are made. With corrections, the overall rms of this source is reduced by 1 ps, and the impacts of the structure effect introduced by this single source are up to 1.4 mm on station positions and up to 4.4 microarcseconds on Earth orientation parameters. This study is considered as a starting point for handling the source structure effect on geodetic VLBI from geodetic sessions themselves.Comment: 5 figures, 15 pages, accepted by Journal of Geodesy at 19 Dec., 201

Deep ensemble geophysics-informed neural networks for the prediction of celestial pole offsets

Celestial Pole Offsets (CPO), denoted by dX and dY, describe the differences in the observed position of the pole in the celestial frame with respect to a certain precession-nutation model. Precession and nutation components are part of the transformation matrix between terrestrial and celestial systems. Therefore, various applications in geodetic science such as high-precision spacecraft navigation require information regrading precession and nutation. For this purpose, CPO can be added to the precession-nutation model to precisely describe the motion of the celestial pole. However, as Very Long Baseline Interferometry (VLBI) – currently the only technique providing CPO – requires long data processing times resulting in several weeks of latency, predictions of CPO become necessary. Here we present a new methodology named Deep Ensemble Geophysics-Informed Neural Networks (DEGINNs) to provide accurate CPO predictions. The methodology has three main elements: (1) deep ensemble learning to provide the prediction uncertainty; (2) broad-band Liouville equation as a geophysical constraint connecting the rotational dynamics of CPO to the atmospheric and oceanic Effective Angular Momentum functions (EAM); and (3) coupled oscillatory recurrent neural networks to model the sequential characteristics of CPO time series, also capable of handling irregularly-sampled time series. To test the methodology, we use the newest version of the final CPO time series of International Earth Rotation and Reference Systems Service (IERS), namely IERS 20 C04. We focus on a forecasting horizon of 90 days, the practical forecasting horizon needed in space-geodetic applications. Furthermore, for validation purposes we generate an independent global VLBI solution for CPO since 1984 up to the end of 2022 and analyze the series. We draw the following conclusions. First, the prediction performance of DEGINNs demonstrates up to 25% and 33% improvement respectively for dX and dY, with respect to the rapid data provided by IERS. Second, predictions made with the help of EAM are more accurate compared to those without EAM, thus providing a clue to the role of atmosphere and ocean on the excitation of CPO. Finally, free core nutation period shows temporal variations with a dominant periodicity of around one year, partially excited by EAM.Santiago Belda was partially supported by Generalitat Valenciana (SEJIGENT/2021/001), the European Union—NextGenerationEU (ZAMBRANO 21-04) and Ministerio de Ciencia e Innovación (MCIN/AEI/10.13039/501100011033/). Maria Karbon was supported by PROMETEO/2021/030 funded by Generalitat Valenciana

An Improved Empirical Harmonic Model of the Celestial Intermediate Pole Offsets from a Global VLBI Solution

Very Long Baseline Interferometry (VLBI) is the only space geodetic technique capable of measuring all the Earth orientation parameters (EOP) accurately and simultaneously. Modeling the Earth's rotational motion in space within the stringent consistency goals of the Global Geodetic Observing System (GGOS) makes VLBI observations essential for constraining the rotation theories. However, the inaccuracy of early VLBI data and the outdated products could cause non-compliance with these goals. In this paper, we perform a global VLBI analysis of sessions with different processing settings to determine a new set of empirical corrections to the precession offsets and rates, and to the amplitudes of a wide set of terms included in the IAU 2006/2000A precession-nutation theory. We discuss the results in terms of consistency, systematic errors, and physics of the Earth. We find that the largest improvements w.r.t. the values from IAU 2006/2000A precession-nutation theory are associated with the longest periods (e.g., 18.6-yr nutation). A statistical analysis of the residuals shows that the provided corrections attain an error reduction at the level of 15 μas. Additionally, including a Free Core Nutation (FCN) model into a priori Celestial Pole Offsets (CPOs) provides the lowest Weighted Root Mean Square (WRMS) of residuals. We show that the CPO estimates are quite insensitive to TRF choice, but slightly sensitive to the a priori EOP and the inclusion of different VLBI sessions. Finally, the remaining residuals reveal two apparent retrograde signals with periods of nearly 2069 and 1034 days.This work was funded and realized in the framework of the project AYA2016-79775-P (AEI/FEDER, UE) and APOSTD/2026/079

Impact of the terrestrial reference frame on the determination of the celestial reference frame

Currently three up-to-date Terrestrial Reference Frames (TRF) are available, the ITRF2014 from IGN, the DTRF2014 from DGFI-TUM, and JTRF2014 from JPL. All use the identical input data of space-geodetic station positions and Earth orientation parameters, but the concept of combining these data is fundamentally different. The IGN approach is based on the combination of technique solutions, while the DGFI is combining the normal equation systems. Both yield in reference epoch coordinates and velocities for a global set of stations. JPL uses a Kalman filter approach, realizing a TRF through weekly time series of geocentric coordinates. As the determination of the CRF is not independent of the TRF and vice versa, the choice of the TRF might impact on the CRF. Within this work we assess this effect.We find that the estimated Earth orientation parameter (EOP) from DTRF2014 agree best with those from ITRF2014, the EOP resulting from JTRF2014 show besides clear yearly signals also some artifacts linked to certain stations. The estimated source position time series however, agree with each other better than ±1μas. When fixing EOP and station positions we can see the maximal effect of the TRF on the CRF. Here large systematics in position as well as proper motion arise. In case of ITRF2008 they can be linked to the missing data after 2008. By allowing the EOP and stations to participate in the adjustment, the agreement increases, however, systematics remain. Keywords: Reference frames, CRF, TRF, DTRF2014, JTRF2014, ITRF201

Deep ensemble geophysics-informed neural networks for the prediction of celestial pole offsets

Celestial Pole Offsets (CPO), denoted by dX and dY, describe the differences in the observed position of the pole in the celestial frame with respect to a certain precession-nutation model. Precession and nutation components are part of the transformation matrix between terrestrial and celestial systems. Therefore, various applications in geodetic science such as high-precision spacecraft navigation require information regrading precession and nutation. For this purpose, CPO can be added to the precession-nutation model to precisely describe the motion of the celestial pole. However, as Very Long Baseline Interferometry (VLBI)—currently the only technique providing CPO—requires long data processing times resulting in several weeks of latency, predictions of CPO become necessary. Here we present a new methodology named Deep Ensemble Geophysics-Informed Neural Networks (DEGINNs) to provide accurate CPO predictions. The methodology has three main elements: (1) deep ensemble learning to provide the prediction uncertainty; (2) broad-band Liouville equation as a geophysical constraint connecting the rotational dynamics of CPO to the atmospheric and oceanic Effective Angular Momentum (EAM) functions and (3) coupled oscillatory recurrent neural networks to model the sequential characteristics of CPO time-series, also capable of handling irregularly sampled time-series. To test the methodology, we use the newest version of the final CPO time-series of International Earth Rotation and Reference Systems Service (IERS), namely IERS 20 C04. We focus on a forecasting horizon of 90 days, the practical forecasting horizon needed in space-geodetic applications. Furthermore, for validation purposes we generate an independent global VLBI solution for CPO since 1984 up to the end of 2022 and analyse the series. We draw the following conclusions. First, the prediction performance of DEGINNs demonstrates up to 25 and 33 percent improvement, respectively, for dX and dY, with respect to the rapid data provided by IERS. Secondly, predictions made with the help of EAM are more accurate compared to those without EAM, thus providing a clue to the role of atmosphere and ocean on the excitation of CPO. Finally, free core nutation period shows temporal variations with a dominant periodicity of around one year, partially excited by EAM.ISSN:0956-540XISSN:1365-246

Earth orientation parameters from VLBI determined with a Kalman filter

This paper introduces the reader to our Kalman filter developed for geodetic VLBI (very long baseline interferometry) data analysis. The focus lies on the EOP (Earth Orientation Parameter) determination based on the Continuous VLBI Campaign 2014 (CONT14) data, but also earlier CONT campaigns are analyzed. For validation and comparison purposes we use EOP determined with the classical LSM (least squares method) estimated from the same VLBI data set as the Kalman solution with a daily resolution. To gain higher resolved EOP from LSM we run solutions which yield hourly estimates for polar motion and dUT1 = Universal Time (UT1) – Coordinated Universal Time (UTC). As an external validation data set we use a GPS (Global Positioning System) solution providing hourly polar motion results. Further, we describe our approach for determining the noise driving the Kalman filter. It has to be chosen carefully, since it can lead to a significant degradation of the results. We illustrate this issue in context with the de-correlation of polar motion and nutation. Finally, we find that the agreement with respect to GPS can be improved by up to 50% using our filter compared to the LSM approach, reaching a similar precision than the GPS solution. Especially the power of erroneous high-frequency signals can be reduced dramatically, opening up new possibilities for high-frequency EOP studies and investigations of the models involved in VLBI data analysis. We prove that the Kalman filter is more than on par with the classical least squares method and that it is a valuable alternative, especially on the advent of the VLBI2010 Global Observing System and within the GGOS frame work

Improving the modeling of the atmospheric delay in the data analysis of the Intensive VLBI sessions and the impact on the UT1 estimates

The very long baseline interferometry (VLBI) Intensive sessions are typically 1-h and single-baseline VLBI sessions, specifically designed to yield low-latency estimates of UT1-UTC. In this work, we investigate what accuracy is obtained from these sessions and how it can be improved. In particular, we study the modeling of the troposphere in the data analysis. The impact of including external information on the zenith wet delays (ZWD) and tropospheric gradients from GPS or numerical weather prediction models is studied. Additionally, we test estimating tropospheric gradients in the data analysis, which is normally not done. To evaluate the results, we compared the UT1-UTC values from the Intensives to those from simultaneous 24-h VLBI session. Furthermore, we calculated length of day (LOD) estimates using the UT1-UTC values from consecutive Intensives and compared these to the LOD estimated by GPS. We find that there is not much benefit in using external ZWD; however, including external information on the gradients improves the agreement with the reference data. If gradients are estimated in the data analysis, and appropriate constraints are applied, the WRMS difference w.r.t. UT1-UTC from 24-h sessions is reduced by 5% and the WRMS difference w.r.t. the LOD from GPS by up to 12%. The best agreement between Intensives and the reference time series is obtained when using both external gradients from GPS and additionally estimating gradients in the data analysis

GABA(B) receptor-mediated stimulation of adenylyl cyclase activity in membranes of rat olfactory bulb

1. Previous studies have shown that GABA(B) receptors facilitate cyclic AMP formation in brain slices likely through an indirect mechanism involving intracellular second messengers. In the present study, we have investigated whether a positive coupling of GABA(B) receptors to adenylyl cyclase could be detected in a cell-free preparation of rat olfactory bulb, a brain region where other G(i)/G(o)-coupled neurotransmitter receptors have been found to stimulate the cyclase activity. 2. The GABA(B) receptor agonist (−)-baclofen significantly increased basal adenylyl cyclase activity in membranes of the granule cell and external plexiform layers, but not in the olfactory nerve-glomerular layer. The adenylyl cyclase stimulation was therefore examined in granule cell layer membranes. 3. The (−)-baclofen stimulation (pD(2)=4.53) was mimicked by 3-aminopropylphosphinic acid (pD(2)=4.60) and GABA (pD(2)=3.56), but not by (+)-baclofen, 3-aminopropylphosphonic acid, muscimol and isoguvacine. The stimulatory effect was counteracted by the GABA(B) receptor antagonists CGP 35348 (pA(2)=4.31), CGP 55845 A (pA(2)=7.0) and 2-hydroxysaclofen (pK(i)=4.22). Phaclofen (1 mM) was inactive. 4. The (−)-baclofen stimulation was not affected by quinacrine, indomethacin, nordihydroguaiaretic acid and staurosporine, but was completely prevented by pertussis toxin and significantly reduced by the α subunit of transducin, a βγ scavenger. The βγ subunits of transducin stimulated the cyclase activity and this effect was not additive with that produced by (−)-baclofen. 5. In the external plexiform and granule cell layers, but not in the olfactory nerve-glomerular layer, (−)-baclofen enhanced the adenylyl cyclase stimulation elicited by the neuropeptide pituitary adenylate cyclase activating polypeptide (PACAP) 38. 6. Conversely, the adenylyl cyclase activity stimulated by either forskolin or Ca(2+)/calmodulin-(Ca(2+)/CaM) was inhibited by (−)-baclofen in all the olfactory bulb layers examined. 7. These data demonstrate that in specific layers of rat olfactory bulb activation of GABA(B) receptors enhances basal and neurotransmitter-stimulated adenylyl cyclase activities by a mechanism involving βγ subunits of G(i)/G(o). This positive coupling is associated with a widespread inhibitory effect on forskolin- and Ca(2+)/CaM-stimulated cyclic AMP formation