Improved UT1 predictions through low-latency VLBI observations

The quality of predictions of Earth orientation parameters (EOPs) in general, and of Universal Time (UT1) in particular, depends strongly on the time delay between the last observation available and the first prediction. Since 30 September 2007 (MJD 54373), the latency of UT1 results from a subset of single baseline VLBI observations running once per week (Mondays) has been decreased from 2 to 3 days to about 8 h. This was achieved by transmitting the raw VLBI data of 1-h duration from the observing sites in Tsukuba (Japan), Wettzell (Germany) and Ny-Ålesund (Norway) to the correlator of the Max-Planck-Institute for Radio Astronomy and the German Federal Agency of Cartography and Geodesy at Bonn, Germany, by high-speed Internet connections (e-Transfer). The reduced latency of the observations has improved the accuracy of the combined International Earth Rotation and Reference Systems Service (IERS) Rapid Service/Prediction Center (RS/PC) UT1-UTC solution by roughly 50% on the days when the data are available. Because this combination is an input to the UT1-UTC prediction process, the improved latency is also responsible for a roughly 21% improvement in the accuracy of short-term IERS RS/PC UT1-UTC predictions on the days where the data are available.     

Ultra-rapid earth rotation determination with VLBI during CONT11 and CONT14

We present earth rotation results from the ultra-rapid operations during the continuous VLBI campaigns CONT11 and CONT14. The baseline Onsala–Tsukuba, i.e., using two out of the 13 and 17 stations contributing to CONT11 and CONT14, respectively, was used to derive UT1-UTC in ultra-rapid mode during the ongoing campaigns. The latency between a new observation and a new UT1-UTC result was less than 10 min for more than 95% of the observations. The accuracy of the derived ultra-rapid UT1-UTC results is approximately a factor of three worse than results from optimized one-baseline sessions and/or complete analysis of large VLBI networks. This is, however, due to that the one-baseline picked from the CONT campaigns is not optimized for earth rotation determination. Our results prove that the 24/7 operation mode planned for VGOS, the next-generation VLBI system, is possible already today. However, further improvements in data connectivity of stations and correlators as well in the automated analysis are necessary to realize the ambitious VGOS plans.     

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.     

Possible improvement of Earth orientation forecast using autocovariance prediction procedures

 Autocovariance prediction has been applied to attempt to improve polar motion and UT1-UTC predictions. The predicted polar motion is the sum of the least-squares extrapolation model based on the Chandler circle, annual and semiannual ellipses, and a bias fit to the past 3 years of observations and the autocovariance prediction of these extrapolation residuals computed after subtraction of this model from pole coordinate data. This prediction method has been applied also to the UT1-UTC data, from which all known predictable effects were removed, but the prediction error has not been reduced with respect to the error of the current prediction model. However, the results show the possibility of decreasing polar motion prediction errors by about 50 for different prediction lengths from 50 to 200 days with respect to the errors of the current prediction model. Because of irregular variations in polar motion and UT1-UTC, the accuracy of the autocovariance prediction does depend on the epoch of the prediction. To explain irregular variations in x, y pole coordinate data, time-variable spectra of the equatorial components of the effective atmospheric angular momentum, determined by the National Center for Environmental Prediction, were computed. These time-variable spectra maxima for oscillations with periods of 100–140 days, which occurred in 1985, 1988, and 1990 could be responsible for excitation of the irregular short-period variations in pole coordinate data. Additionally, time-variable coherence between geodetic and atmospheric excitation function was computed, and the coherence maxima coincide also with the greatest irregular variations in polar motion extrapolation residuals. Received: 22 October 1996 / Accepted: 16 September 1997     

The International VLBI Service for Geodesy and Astrometry (IVS): current capabilities and future prospects

Very Long Baseline Interferometry (VLBI) plays a unique and fundamental role in the maintenance of the global (terrestrial and celestial) reference frames, which are required for precise positioning in many research areas such as the understanding and monitoring of global changes, and for space missions. The International VLBI Service for Geodesy and Astrometry (IVS) coordinates the global VLBI components and resources on an international basis. The service is tasked by the International Association of Geodesy (IAG) and International Astronomical Union (IAU) to provide products for the realization of the Celestial Reference Frame (CRF) through the positions of quasars, to deliver products for the maintenance of the terrestrial reference frame (TRF), such as station positions and their changes with time, and to generate products describing the rotation and orientation of the Earth. In particular, VLBI uniquely provides direct observations of nutation parameters and of the time difference UT1-UTC. This paper summarizes the evolution and current status of the IVS. It points out the activities to improve further on the product quality to meet future service requirements.     

Recent Improvements to IERS Bulletin A Combination and Prediction

Driven by a need for increased accuracy in real-time Earth orientation parameters (EOPs), the Bulletin A (Rapid Servce and Predictions) of the International Earth Rotation Service (IERS) has recently made several major changes to its combination and prediction procedures. Changes to the process ob combining multi-technique results include creation of a daily Bulletin A updata, inclusion of several new data sets, and use of polar motion rantes for the latest epoch. Notably, the contributions from GPS observations have grown steadily in significance, both for polar motion and Universal Time (UT1). The prediction procedure has, in turn, benefited from these changes as well as improvements to the polar motion prediction model. As a result, demanding real-time applications, such as for satellite orbit extrapolations should observe a major improvement in the accuracy of our real-time EOP products. All results, together with supporting and diagnostic information, are available at the website http://maia.usno.navy.mil. The maximum EOP errors (root-mean-squared sense) that a real-time user would experience using the latest available update of Bulletin A are currently estimated to be ∼0.9 milliarcseconds (mas) for polar motion and ∼0.15 milliseconds (ms) for UT1-UTC. The data latency (the lag since the most recent observations) for EOP predictions need not exceed ∼41 hours for users who avail themselves of the daily updates. Over the past four years, the accuracy for real-time applications has improved by nearly a factor of 4 in polar motion and a factor of 10 in UT1. This is primarily due to the large reduction in data latency, which in turn is mostly possible due to the Rapid product delivery of the International GPS Service (IGS) (see Mireault et al, 1999). ? 2001 John Wiley & Sons, Inc.     

Is there utility in rigorous combinations of VLBI and GPS Earth orientation parameters?

Combinations of station coordinates and velocities from independent space-geodetic techniques have long been the standard method to realize robust global terrestrial reference frames (TRFs). In principle, the particular strengths of one observing method can compensate for weaknesses in others if the combination is properly constructed, suitable weights are found, and accurate co-location ties are available. More recently, the methodology has been extended to combine time-series of results at the normal equation level. This allows Earth orientation parameters (EOPs) to be included and aligned in a fully consistent way with the TRF. While the utility of such multi-technique combinations is generally recognized for the reference frame, the benefits for the EOPs are yet to be quantitatively assessed. In this contribution, which is a sequel to a recent paper on co-location ties (Ray and Altamimi in J Geod 79(4–5): 189–195, 2005), we have studied test combinations of very long baseline interferometry (VLBI) and Global Positioning System (GPS) time-series solutions to evaluate the effects on combined EOP measurements compared with geophysical excitations. One expects any effect to be small, considering that GPS dominates the polar motion estimates due to its relatively dense and uniform global network coverage, high precision, continuous daily sampling, and homogeneity, while VLBI alone observes UT1-UTC. Presently, although clearly desirable, we see no practical method to rigorously include the GPS estimates of length-of-day variations due to significant time-varying biases. Nevertheless, our results, which are the first of this type, indicate that more accurate polar motion from GPS contributes to improved UT1-UTC results from VLBI. The situation with combined polar motion is more complex. The VLBI data contribute directly only very slightly, if at all, with an impact that is probably affected by the weakness of the current VLBI networks (small size and sparseness) and the quality of local ties relating the VLBI and GPS frames. Instead, the VLBI polar motion information is used primarily in rotationally aligning the VLBI and GPS frames, thereby reducing the dependence on co-location tie information. Further research is needed to determine an optimal VLBI-GPS combination strategy that yields the highest quality EOP estimates. Improved local ties (including internal systematic effects within the techniques) will be critically important in such an effort.     

基于VLBI与BDS联合解算ERP的算法研究

利用PANDA软件解算2016年第61~91天的MGEX(Multi-GNSS Experiment)服务站的北斗数据,获得地球自转参数(ERP)。利用VieVS2.2软件处理了同时段的甚长基线干涉测量(VLBI)数据。采用基于IERS 08C04序列的定权方法对BDS和VLBI的解算结果进行加权平均,得到综合的ERP值。结果表明,与IERS比较,极移在X方向差值的RMS为0.249 mas,Y方向差值的RMS为0.296 mas,UT1-UTC差值的RMS为0.053 ms.利用BDS与VLBI数据对ERP参数进行联合解算,弥补了BDS解算结果不稳定和VLBI观测不连续的缺陷,使解算结果的稳定性和可靠性均有所提高。      

Use of atmospheric angular momentum forecasts for UT1 predictions: analyses over CONT08

Real-time orbit determination and interplanetary navigation require accurate predictions of the orientation of the Earth in the celestial reference frame and in particular that for Universal Time UT1. Much of the UT1 variations over periods ranging from hours to a couple of years are due to the global atmospheric circulation. Therefore, the axial atmospheric angular momentum (AAM) forecast series may be used as a proxy index to predict UT1. Our approach taking advantage of this fact is based on an adaptive procedure. It involves incorporating integrations of AAM estimates into UT1 series. The procedure runs on a routine basis using AAM forecasts that are based on the two meteorological series, from the US National Centers for Environmental Prediction and the Japan Meteorological Agency. It is pertinent to test the prediction method for the period that includes the special CONT08 campaign over which we expect a significant improvement in UT1 accuracy. The studies we carried out were aimed both to compare atmospheric forecasts and analyses, as well as to compare the skills of the UT1 forecasts based on the method with atmospheric forecasts and that using current statistical processes, as applied to the C04 Earth orientation parameters series derived by the International Earth rotation and Reference Systems service (IERS). Here we neglect the oceanic sub-diurnal and diurnal variations, as these signals are expected to be smaller than the UT1-equivalent of 100 μs, when averaged over a few days. The prediction performances for a 2-day forecast are similar, but at a forecast horizon of a week, the AAM-based forecast is roughly twice as skillful as the statistically based one.     

A Global Terrestrial Reference Frame from simulated VLBI and SLR data in view of GGOS

In this study, we assess the impact of two combination strategies, namely local ties (LT) and global ties (GT), on the datum realization of Global Terrestrial Reference Frames in view of the Global Geodetic Observing System requiring 1 mm-accuracy. Simulated Very Long Baseline Interferometry (VLBI) and Satellite Laser Ranging (SLR) data over a 7 year time span was used. The LT results show that the geodetic datum can be best transferred if the precision of the LT is at least 1 mm. Investigating different numbers of LT, the lack of co-located sites on the southern hemisphere is evidenced by differences of 9 mm in translation and rotation compared to the solution using all available LT. For the GT, the combination applying all Earth rotation parameters (ERP), such as pole coordinates and UT1-UTC, indicates that the rotation around the Z axis cannot be adequately transferred from VLBI to SLR within the combination. Applying exclusively the pole coordinates as GT, we show that the datum can be transferred with mm-accuracy within the combination. Furthermore, adding artificial stations in Tahiti and Nigeria to the current VLBI network results in an improvement in station positions by 13 and 12%, respectively, and in ERP by 17 and 11%, respectively. Extending to every day VLBI observations leads to 65% better ERP estimates compared to usual twice-weekly VLBI observations.     

Combination of modeled short-term angular momentum function forecasts from atmosphere, ocean, and hydrology with 90-day EOP predictions

Angular momentum forecasts for up to 10 days into the future, modeled from predicted states of the atmosphere, ocean and continental hydrosphere, are combined with the operational IERS EOP prediction bulletin A to reduce the prediction error in the very first day and to improve the subsequent 90-day prediction by exploitation of the revised initial state and trend information. EAM functions derived from ECMWF short-range forecasts and corresponding LSDM and OMCT simulations can account for high-frequency mass variations within the geophysical fluids for up to 7 days into the future primarily limited by the accuracy of the forecasted atmospheric wind fields. Including these wide-band stochastic signals into the first days of the 90-day statistical IERS predictions reduces the mean absolute prediction error even for predictions beyond day 10, especially for polar motion, where the presently used prediction approach does not include geophysical fluids data directly. In a hindcast experiment using 1 year of daily predictions from May 2011 till July 2012, the mean prediction error in polar motion, compared to bulletin A, is reduced by 32, 12, and 3 % for prediction days 10, 30, and 90, respectively. In average, the prediction error for medium-range forecasts (30–90 days) is reduced by 1.3–1.7 mas. Even for UT1-UTC, where AAM forecasts are already included in IERS bulletin A, we obtain slight improvements of up to 5 % (up to 0.5 ms) after day 10 due to the additional consideration of oceanic angular momentum forecasts. The improved 90-day predictions can be generated operationally on a daily basis directly after the publication of the related IERS bulletin A product finals2000A.daily.     

Assessment of periodic sub-diurnal Earth rotation variations at tidal frequencies through transformation of VLBI normal equation systems

We present an empirical model for periodic variations of diurnal and sub-diurnal Earth rotation parameters (ERPs) that was derived based on the transformation of normal equation (NEQ) systems of Very Long Baseline Interferometry (VLBI) observing sessions. NEQ systems that contain highly resolved polar motion and UT1-TAI with a temporal resolution of 15 min were generated and then transformed to the coefficients of the tidal ERP model to be solved for. To investigate the quality of this model, comparisons with empirical models from the Global Positioning System (GPS), another VLBI model and the model adopted by the conventions of the International Earth Rotation and Reference Systems Service (IERS) were performed. The absolute coefficients of these models agree almost completely within 7.5 μ as in polar motion and 0.5 μs in UT1-TAI. Several bigger differences exist, which are discussed in this paper. To be able to compare the model estimates with results of the continuous VLBI campaigns, where signals with periods of 8 and 6 h were detected, terms in the ter- and quarter-diurnal band were included in the tidal ERP model. Unfortunately, almost no common features with the results of continuous VLBI campaigns or ERP predictions in these tidal bands can be seen.     

VGOS超宽带观测的首次UT1测量数据处理及分析

在国际甚长基线干涉测量（very long baseline interferometry, VLBI）大地测量与天体测量服务组织协调下,首次利用隶属于VLBI全球观测系统（VLBI global observing system, VGOS）的美国Kokee和德国Wettzell观测站及并置的传统VLBI观测站开展了世界时（universal time, UT1）联合测量试验,观测数据在上海VLBI中心进行了干涉处理。结果表明,VGOS超宽带观测系统的UT1测量精度约为7 μs,并置基线的传统S/X双频系统测量精度约为14 μs,VGOS系统的UT1解算结果优于S/X系统。通过试验建立了从相关处理、相关后处理到UT1参数解算的完整数据处理流程,验证了上海VLBI相关处理机的VGOS数据处理能力,为承担国内和国际VGOS观测数据的相关处理任务奠定了基础。     

多尺度ARMA残差修正模型震前电离层TEC异常探测

为提高电离层总电子含量（total electronic content，TEC）扰动探测参考背景值的预测精度，提出了多尺度自回归移动平均（autoregressive moving average，ARMA）残差修正模型。通过对比该方法、ARMA模型、四分位距法（inter quartile range，IQR）及滑动时窗法对TEC背景值的预测精度，结果显示修正模型预测的TEC背景值平均相对精度为89.78%，分别比ARMA模型、IQR及滑动时窗法高5.18%、1.41%和1.42%，且预测值的残差绝对值小于等于3.0 TECU的百分比为91.67%，明显优于其他3种方法，说明修正模型探测震前TEC异常是可行的。利用该方法探测2013-04-20芦山县Mw7.0级地震震前电离层TEC扰动情况，验证了该方法的有效性。实验结果表明，震前第9天和第13天电离层明显的正异常和震前第1~4天明显的负异常极可能是孕育地震引起的，且正异常主要出现在08:00-10:00 UT，而负异常主要集中在0:00-14:00 UT。     

The impact of celestial pole offset modelling on VLBI UT1 intensive results

Very Long Baseline Interferometry (VLBI) Intensive sessions are scheduled to provide operational Universal Time (UT1) determinations with low latency. UT1 estimates obtained from these observations heavily depend on the model of the celestial pole motion used during data processing. However, even the most accurate precession- nutation model, IAU 2000/2006, is not accurate enough to realize the full potential of VLBI observations. To achieve the highest possible accuracy in UT1 estimates, a celestial pole offset (CPO), which is the difference between the actual and modelled precession-nutation angles, should be applied. Three CPO models are currently available for users. In this paper, these models have been tested and the differences between UT1 estimates obtained with those models are investigated. It has been shown that neglecting CPO modelling during VLBI UT1 Intensive processing causes systematic errors in UT1 series of up to 20 μas. It has been also found that using different CPO models causes the differences in UT1 estimates reaching 10 μas. Obtained results are applicable to the satellite data processing as well.     

The impact of errors in polar motion and nutation on UT1 determinations from VLBI Intensive observations

The earth’s phase of rotation, expressed as Universal Time UT1, is the most variable component of the earth’s rotation. Continuous monitoring of this quantity is realised through daily single-baseline VLBI observations which are interleaved with VLBI network observations. The accuracy of these single-baseline observations is established mainly through statistically determined standard deviations of the adjustment process although the results of these measurements are prone to systematic errors. The two major effects are caused by inaccuracies in the polar motion and nutation angles introduced as a priori values which propagate into the UT1 results. In this paper, we analyse the transfer of these components into UT1 depending on the two VLBI baselines being used for short duration UT1 monitoring. We develop transfer functions of the errors in polar motion and nutation into the UT1 estimates. Maximum values reach 30 [μs per milliarcsecond] which is quite large considering that observations of nutation offsets w.r.t. the state-of-the-art nutation model show deviations of as much as one milliarcsecond.     

Stochastic modeling of length of day and universal time

We propose a general stochastic model for the UT1/LOD system and derive the corresponding Kalman filter model. This stochastic model consists of an arbitrary sum of continous time autoregressive moving average (ARMA) processes, each chosen to characterize a different frequency band. The transition matrix which corresponds to the overall system and the time-dependent process noise covariance matrix are derived.Based on the general formulation, several models for UT1 were derived from spectral analysis of the Space 92 UT1 series (Gross,1993). Using Space 92 as the reference series, the candidate models were compared based on their ability to predict UT1 and LOD up to 30 days in the absence of data. These candidate models were compared with the JPL operational Kalman Earth Orientation Filter (KEOF) which assumes a random walk model for LOD (Morabito et al.,1987). The results of the comparison revealed that autoregressive modeling the 40–50 day oscillation in the LOD reduces the LOD prediction error by 10prediction.     

Impact of seasonal station motions on VLBI UT1 intensives results

UT1 estimates obtained from the very long baseline interferometry (VLBI) Intensives data depend on the station displacement model used during processing. In particular, because of seasonal variations, the instantaneous station position during the specific intensive session differs from the position predicted by the linear model generally used. This can cause systematic errors in UT1 Intensives results. In this paper, we first investigated the seasonal signal in the station displacements for the 5 VLBI antennas participating in UT1 Intensives observing programs, along with the 8 collocated GPS stations. It was found that a significant annual term is present in the time series for most stations, and its amplitude can reach 8 mm in the height component, and 2 mm in horizontal components. However, the annual signals found in the displacements of the collocated VLBI and GPS stations at some sites differ substantially in amplitude and phase. The semiannual harmonics are relatively small and unstable, and for most stations no prevailing signal was found in the corresponding frequency band. Then two UT1 Intensives series were computed with and without including the seasonal term found in the previous step in the station movement model. Comparison of these series has shown that neglecting the seasonal station position variations can cause a systematic error in UT1 estimates, which can exceed 1  $\upmu $ s, depending on the observing program.     

Asymmetric tropospheric delays from numerical weather models for UT1 determination from VLBI Intensive sessions on the baseline Wettzell–Tsukuba

One-baseline 1-h Very Long Baseline Interferometry (VLBI) Intensive sessions are carried out every day to determine Universal Time (UT1). Azimuthal asymmetry of tropospheric delays around the stations is usually ignored and not estimated because of the small number of observations. In this study we use external information about the asymmetry for the Intensive sessions between Tsukuba (Japan) and Wettzell (Germany), which are carried out on Saturdays and Sundays (1) from direct ray-tracing for each observation at Tsukuba and (2) in the form of linear horizontal north and east gradients every 6 h at both stations. The change of the UT1 estimates is at the 10 μs level with maximum differences of up to 50 μs, which is clearly above the formal uncertainties of the UT1 estimates (between 5 and 20 μs). Spectral analysis reveals that delays from direct ray-tracing for the station Tsukuba add significant power at short periods (1–2 weeks) w.r.t. the state-of-the-art approach, and comparisons with length-of-day (LOD) estimates from Global Positioning System (GPS) indicate that these ray-traced delays slightly improve the UT1 estimates from Intensive sessions.     

Prediction of UT1–UTC,LOD and AAM χ<Subscript>3</Subscript> by combination of least-squares and multivariate stochastic methods

This article presents the application of a multivariate prediction technique for predicting universal time (UT1–UTC), length of day (LOD) and the axial component of atmospheric angular momentum (AAM χ ₃). The multivariate predictions of LOD and UT1–UTC are generated by means of the combination of (1) least-squares (LS) extrapolation of models for annual, semiannual, 18.6-year, 9.3-year oscillations and for the linear trend, and (2) multivariate autoregressive (MAR) stochastic prediction of LS residuals (LS + MAR). The MAR technique enables the use of the AAM χ ₃ time-series as the explanatory variable for the computation of LOD or UT1–UTC predictions. In order to evaluate the performance of this approach, two other prediction schemes are also applied: (1) LS extrapolation, (2) combination of LS extrapolation and univariate autoregressive (AR) prediction of LS residuals (LS + AR). The multivariate predictions of AAM χ ₃ data, however, are computed as a combination of the extrapolation of the LS model for annual and semiannual oscillations and the LS + MAR. The AAM χ ₃ predictions are also compared with LS extrapolation and LS + AR prediction. It is shown that the predictions of LOD and UT1–UTC based on LS + MAR taking into account the axial component of AAM are more accurate than the predictions of LOD and UT1–UTC based on LS extrapolation or on LS + AR. In particular, the UT1–UTC predictions based on LS + MAR during El Niño/La Niña events exhibit considerably smaller prediction errors than those calculated by means of LS or LS + AR. The AAM χ ₃ time-series is predicted using LS + MAR with higher accuracy than applying LS extrapolation itself in the case of medium-term predictions (up to 100 days in the future). However, the predictions of AAM χ ₃ reveal the best accuracy for LS + AR.