The renewed interest in lunar exploration and the development of future lunar communication and navigation services highlight the need for a precise, stable, and interoperable geodetic and timing infrastructure on the Moon. NovaMoon, proposed as a scientific and navigation payload for ESA's Argonaut lander, is designed as a lunar-based local differential, geodetic, and timing station supporting both operational needs in the Moon's south polar region and a broad range of scientific investigations. The payload integrates a lunar laser retroreflector, a Very Long Baseline Interferometry transmitter, a receiver for navigation signals compatible with LunaNet standards, high-stability atomic clocks, and direct-to-Earth radio links – making it the first lunar station to co-locate multiple ranging, tracking, and timing techniques. NovaMoon will enable sub-metre to decimetre positioning, provide local differential corrections for lunar users, and ensure an accurate and stable realisation of position and time. Preliminary simulation studies show that this multi-technique dataset improves the lunar reference frame, orientation and ephemerides, and estimates of interior parameters like tidal response and core properties. NovaMoon will also provide the first long-duration physical realisation of a lunar time reference. Beyond its primary goals, it supports improved cartography, precise surface geolocation, and higher-resolution topography, contributing to safer landings and operations. It also enables new tests of fundamental physics, including constraints on relativity and possible deviations from classical gravity.

The Earth’s rotation phase, expressed as UT1-UTC, is the most crucial geodetic parameter that can only be precisely measured using Very Long Baseline Interferometry (VLBI), although with considerable latency. Reliable predictions of UT1-UTC are essential for real-time positioning and navigation, and thus several approaches have been developed to forecast this Earth Orientation Parameter (EOP). These methods depend on different versions of post-processed International Earth Rotation and Reference Systems Service (IERS) products and incorporate effective angular momentum (EAM) as additional information to predict for different forecasting horizons. This study investigates the impact of the additional VLBI observations from the International VLBI Service for Geodesy and Astrometry (IVS), which occur at irregular epochs, unlike IERS products at regular epochs. First, a new 10-day forecast model using IERS and EAM data is introduced, and is further modified to incorporate the IVS data. The prediction framework combines a local linear trend estimator with a non-linear recurrent architecture, Coupled Oscillatory Recurrent Neural Network (coRNN). Our model achieves an MAE of 0.02 ms and 0.26 ms at 1st and 10th prediction days, respectively, with IERS observations as input. Further, the modified hybrid model also demonstrates the ability to handle temporal irregularity in the input sequence. While the inclusion of additional IVS epochs leads to a small reduction in prediction accuracy, this decrease is equivalent to the root-mean-square difference between the IERS and IVS series. Overall, the results indicate that UT1-UTC prediction performance depends more on the quality of additional observations than on their quantity.

Geodetic very long baseline interferometry (VLBI) is affected by stochastic fluctuations in atmospheric water vapor, which degrade delay measurements and limit the precision of derived geodetic parameters. The high quality and data rate of modern VLBI observations allow us to analyze high-rate residuals on two baselines (ONSA13NE–WETTZ13S, 920 km; MACGO12M–WESTFORD, 3138 km) to quantify turbulence-induced variations. Using power spectral density analysis and debiased Whittle maximum likelihood estimation, we estimate two turbulence parameters from 31 VGOS sessions: the cutoff frequency λ (linked to the outer scale of turbulence) and the variance σ ^2 (reflecting turbulence intensity). Both parameters exhibit clear seasonal patterns consistent with atmospheric dynamics: higher λ in winter indicates stable stratification with smaller eddies, while lower λ in summer reflects buoyancy-driven convection with larger turbulent structures. Cross-validation using co-located Onsala telescopes yields correlations exceeding 0.82 for σ ^2 and 0.62 for λ . These results provide a first step toward refining stochastic VLBI models and open perspectives for climatological applications through comparisons with satellite-derived atmospheric data.

The Wetterstein Millimeter Telescope (WMT) is a planned broadband (1.2-120 GHz) radio telescope to be established near the Environmental Research Station Schneefernerhaus (UFS) on Germany's highest mountain, the Zugspitze. Developed by a consortium of German research institutes and partners, the WMT is conceived as a multidisciplinary research infrastructure supporting radio astronomy, geodetic VLBI, satellite communications, space situational awareness, and technology development. The telescope is designed to operate within international VLBI networks, including the European VLBI Network, the Global mm-VLBI Array, and future ngVLA and SKA-VLBI observations. This contribution summarizes recent progress in the WMT project, including the evolution of the antenna design, and highlights the potential of the WMT to support future astronomical and geodetic VLBI.

Very Long Baseline Interferometry (VLBI) is a truly global scientific effort that demands rigorous coordination among a network of telescopes distributed worldwide. Central to this collaboration is the generation and distribution of a synchronized observation plan, a task typically called scheduling. Given a network of telescopes, a catalog of celestial sources, and a constrained time window, the goal of scheduling is to find an optimal sequence of observations to achieve the best possible scientific outcomes.The complexity of this task arises from the virtually infinite number of potential schedules, making it practically impossible to find the most perfect solution. Instead, the objective is to generate a schedule that balances quality with practical constraints. Additionally, numerous optimization criteria must be considered, such as maximizing the number of observations for increased redundancy, ensuring a well-distributed coverage in azimuth and elevation angles to mitigate atmospheric effects, and achieving a balanced distribution of observations across the network and sources to enhance the parameter estimation process. Unfortunately, many of these criteria are in direct conflict with each other, further complicating the optimization process.However, the importance of optimized scheduling cannot be overstated, as it directly determines the data available for analysis and, consequently, the quality of the scientific results. In recent years, significant progress has been made in VLBI scheduling algorithms. State-of-the-art practices involve generating hundreds of potential schedules for each experiment and using simulations to evaluate and select the optimal one. Nowadays, developing advanced scheduling algorithms requires a multifaceted approach, encompassing the creation of logical observation sequences, the generation of high-quality simulations, and the application of cutting-edge analysis and parameter estimation techniques. Additionally, new observing scenarios emerging from upcoming satellite missions, e.g. Genesis, combined with the more interdisciplinary application of VLBI resources, are fundamentally changing scheduling optimization objectives.In this lecture, I will give a brief introduction to VLBI scheduling, highlighting its unique and exciting challenges. I will discuss recent advancements in scheduling algorithms and their impact on VLBI science. Furthermore, I will provide insights into future challenges and opportunities.

Simulation studies are an essential tool in space geodesy. They support the optimization of ground and space networks, the exploration of innovative concepts, and the advancement of technological developments. Beyond measurement noise, realistic simulations must incorporate various error sources, including atmospheric effects, clock drift, and technology-related issues. For many space geodetic techniques, accurate simulations of tropospheric effects, particularly incorporating spatio-temporal correlations, are essential in this context. Traditionally, high-quality tropospheric simulations popular in the Very Long Baseline Interferometry (VLBI) technology rely on Kolmogorov turbulence theory combined with the frozen flow assumption. These simulations are parameterized using the refractive index structure constant (Cn), alongside auxiliary parameters like wind velocity and troposphere height. Although Cn values can be derived from Global Navigation Satellite System (GNSS) observations, most existing studies assume a generalized average troposphere, largely independent of specific locations or seasonal variations. Only a few incorporate location-based conditions, often through a simplistic latitude-based interpolation. Furthermore, reliance on GNSS data limits the ability to test potential network extensions when such observations are not available. This work enhances tropospheric simulations by introducing a global, three-dimensional (latitude, longitude, time) Cn model. The model is trained using zenith wet delay (ZWD) estimates from 21,000 globally distributed GNSS stations (2000–2023) and leverages meteorological data from the ERA5 reanalysis, including specific humidity across 11 pressure levels (1000 to 300 hPa) and wind velocity as features. Utilizing the XGBoost algorithm, the model supports short-term prediction scenarios with HRES weather forecasts and provides model uncertainty through an ensemble strategy. The proposed model is able to effectively capture the spatio-temporal patterns in the input data and provides high accuracy, allowing for enhanced simulations of space geodetic observations operating at radio frequencies such as VLBI and GNSS. Additionally, global monthly average estimates on a 0.25° x 0.25° latitude, longitude grid can be derived, offering a practical solution with sufficient accuracy for most simulation studies.

The geodetic and astrometric very long baseline interferometry (VLBI) community is in the process of upgrading its existing infrastructure with the VLBI Global Observing System (VGOS). The primary objective of VGOS is to substantially boost the number of scans per hour for enhanced parameter estimation. However, the current observing strategy results in fewer scans than anticipated. During 2022, six 24-h VGOS Research and Development (R&D) sessions were conducted to demonstrate a proof-of-concept aimed at addressing this shortcoming. The new observation strategy centers around a signal-to-noise (SNR)-based scheduling approach combined with eliminating existing overhead times in existing VGOS sessions. Two SNR-based scheduling approaches were tested during these sessions: one utilizing inter-/extrapolation of existing S/X source flux density models and another based on a newly derived source flux density catalog at VGOS frequencies. Both approaches proved effective, leading to a 2.3-fold increase in the number of scheduled scans per station and a 2.6-fold increase in the number of observations per station while maintaining a high observation success rate of approximately 90 % to 95 %. Consequently, both strategies succeeded in the main objective of these sessions by successfully increasing the number of scans per hour. The strategies described in this work can be easily applied to operational VGOS observations. Besides outlining and discussing the observation strategy, we further provide insight into the resulting signal-to-noise ratios, and discuss the impact on the precision of the estimated geodetic parameters. Monte Carlo simulations predicted a roughly 50 % increase in geodetic precision compared to operational VGOS sessions. The analysis confirmed that the formal errors in estimated station coordinates were reduced by 40 % to 50 %. In addition, Earth orientation parameters showed significant improvement, with a 40 % to 50 % reduction in formal errors.

Irregularities in the Earth’s rotation speed are quantified by the difference between Universal Time (UT1) and Coordinated Universal Time (UTC). This important observable is expressed as UT1−UTC and only estimated through Very Long Baseline Interferometry (VLBI). Typically, 1 h sessions, known as Intensives, are conducted daily between two to three stations, with the primary goal of determining UT1−UTC with a short latency. With the proposed plan of India having its own VLBI Global Observing System (VGOS) telescope, it is necessary to identify the optimal location for it and the ways it can help the International VLBI Service for Geodesy and Astrometry (IVS) to improve the precision of UT1−UTC estimates. This study investigates the change in the precision of different existing baseline solutions when a third station from India is added either in tagalong or in regular mode. Additionally, it identifies a new two-station intensive baseline including one Indian station, which could be part of future intensive sessions. Extensive simulations were conducted using VieSched++ software, varying the VGOS telescope’s location in India on a regular 5 × 5 degree grid to test potential locations. The study reveals that adding an Indian telescope as a regular third station only improves the precision of UT1−UTC in certain cases. In particular, when the initial baselines already have a good geometry compared to the new baselines with the Indian station, no improvement can be expected. In contrast, using tagalong mode is always beneficial due to the increased number of observations. For example, adding an Indian station in regular mode to the KOKEE12M-WETTZ13S and European-ISHIOKA baselines does not improve the UT1−UTC precision. On the other hand, an Indian station added in tagalong mode with the MACGO12M-WETTZ13S baseline improves the UT1−UTC precision by a factor of 0.5. The study further highlights that UT1−UTC precision depends on baseline length, baseline geometry, and common sky coverage. Moreover, it is shown that an Indian station paired with U.S. stations, except KOKEE12M, results in a high precision of UT1−UTC, comparable with current VGOS intensive sessions. Overall, in both strategies, the study concludes that the optimal location for a VGOS telescope in India for UT1−UTC estimation is in the northeastern part of the country.

Aims. We computed a celestial reference frame (CRF) from Very Long Baseline Interferometry (VLBI) Global Observing System (VGOS) data after five years of regular observations carried out under the umbrella of the International VLBI Service for Geodesy and Astrometry. In this paper we evaluate its strengths and weaknesses, document the source selection and scheduling strategies for the individual sessions, and investigate the effect of using this new VGOS CRF in the analysis of individual geodetic VLBI sessions where the radio source positions are fixed to their a priori coordinates. Methods. We estimated the VIE2023-VG CRF in a global adjustment of 155 multi-baseline 24-hour VGOS sessions until 2024.0. We carried out several comparisons with the third version of the International Celestial Reference Frame (ICRF3) adopted by the International Astronomical Union in 2018, and with VIE2023sx CRF which includes VLBI S/X data until 2024.0. Furthermore, we studied the effect of more frequent estimations of tropospheric parameters (30,10, and 5 min for zenith wet delay) on the estimated CRF in the current VGOS network. We evaluated the VIE2023-VG CRF in the geodetic analysis of VGOS sessions by computing the baseline lengths and station positions and statistics on the Earth orientation parameters estimated in the single-session analysis where the source positions were fixed to either the VIE2023-VG CRF or to ICRF3-SX. Results. The current VIE2023-VG CRF is built with 1.39 million VGOS group delays and includes 418 radio sources, where 172 sources (41%) are introduced in only four research and development sessions alone. We show that the VIE2023-VG CRF has excellent source position precision. The median formal error from the least-squares adjustment is 30 mu as for right ascension (scaled by cosine of declination) and 47 mu as for declination. In terms of systematic distortions versus ICRF3-SX, the largest terms in the vector spherical harmonics up to the degree and order two, reach in absolute values around 60 mu as, caused by correlations between the individual terms. Because of the lack of observations in the southern hemisphere, a constraint for a zero slope in declination difference with respect to ICRF3-SX is imposed in the global adjustment. Therefore, VGOS should prioritize the development of southern stations in order to limit the need for such constraints on the frame. Further we show that fixing the a priori CRF to VIE2023-VG CRF instead of the ICRF3-SX in the single-session analysis improves the weighted root mean square of the baseline length by up to 3 mm, especially for the extremely long baselines (>12 000 km), with a weighted mean difference between the baseline length time series up to 2 mm. Therefore, in order to meet the ambitious goal of 1 mm accuracy for a terrestrial reference frame set by the Global Geodetic Observing System, the development of a VGOS-only CRF is required for use in the geodetic analysis of the new generation VGOS data.

Geodetic applications depend on the precise transformation between terrestrial and celestial reference frames, which are tied by the Earth Orientation Parameters (EOP). Very Long Baseline Interferometry (VLBI) is the only space geodetic technique capable of observing the complete set of EOP, which includes polar motion, UT1-UTC, and celestial pole offsets. Over the past three to four years, India has been planning the establishment of a VLBI Global Observing System (VGOS) telescope. Thus, identifying the optimal location for these antennas is critical for enhancing the precision of EOP estimation. The International VLBI Service for Geodesy and Astrometry (IVS) conducts its VLBI observing program in two formats: 24-hr sessions and 1-hr sessions. While 24-hr sessions typically involve a global network of stations and measure the full set of EOP, the 1-hr sessions, called Intensive sessions, focus on determining UT1-UTC with a short latency and generally involve two to three stations.This study uses VieSched++ software to simulate the optimal position of VGOS telescopes in the Indian subcontinent separately for both 24-hr and 1-hr sessions. For the 24-hr sessions, 14 potential VLBI stations, co-located with GPS stations, are selected and simulated in addition to three different reference networks. Additionally, the study assesses the significance of using station-specific tropospheric turbulence parameters and wind speed in finding the optimal position. For 1-hr sessions, simulations were conducted by varying the VGOS telescope’s location in India on a regular 5 × 5 degree grid. It investigates the change in the precision of different baseline solutions when a third station from India is added in both regular mode and tag-along mode. Furthermore, it also identifies a new baseline, which includes one Indian station and one other station, that could be part of future Intensive sessions. Our findings show that the southern and north-eastern regions of India are optimal for improving EOP precision from 24-hr and 1-hr VGOS observing sessions, respectively. The findings also highlight that while a station may be geometrically advantageous for 24-hr sessions, the location might not be favorable if the tropospheric turbulence value is too high.

This work presents a global, three-dimensional (latitude–longitude–time) model of the refractive index structure constant ( C_n ), enabling the spatiotemporally correlated simulation of tropospheric delays for space geodetic observations at radio frequencies. The model is based on an ensemble of 100 XGBoost models trained on 21 years of observations from 18,500 GNSS stations, using meteorological variables from ERA5 as features. It effectively captures high-frequency spatial and temporal variations, achieving a mean absolute error of 0.52 m^-1/3 . To simplify the use of the model, monthly average C_n values are computed on a regular 2.5× 2.5 degree grid, which are sufficiently accurate for most simulation studies. Besides, the model provides a Monte Carlo-based measure for the prediction uncertainty based on the XGBoost ensemble spread, which is revealed to be primarily driven by feature augmentation using ensemble spread information from ERA5. The model is validated both independently on 2500 GNSS stations over 3 years and externally through very long baseline interferometry simulations. The results demonstrate a significant improvement over current state-of-the-art simulation approaches.

The VLBI Global Observing System (VGOS) was created to meet the ambitious requirements set by the Global Geodetic Observing System (GGOS). Its primary objective is achieving millimeter-level precision while maintaining continuous 24/7 observations. Currently, both aims remain unfulfilled. Simultaneously, new requirements, such as the development of a dedicated VGOS Celestial Reference Frame (CRF), have emerged. Thus, a reevaluation of our current VGOS observational framework is necessary to reach the VGOS goals. This study addresses three pivotal challenges within VGOS: attaining millimeter precision, providing observations for a CRF, and achieving uninterrupted 24/7 observations. Each of these topics demand a readjustment of our current observation scheduling methodology. Based on insight from VGOS R&D sessions, this work discusses potential approaches to meet the requisite precision through shorter, signal-to-noise-driven observations. Additionally, it explores the combination of this methodology with source-based scheduling to facilitate the creation of essential observations for establishing a dedicated VGOS CRF. Finally, it addresses the issue of reaching 24/7 observations, currently limited by data transfer and correlation capacities. To overcome this, a potential solution involves a significant reduction in the recorded data volume per session by temporarily thinning out the schedule. Thus, it comes with a trade-off in precision. This concept might be seen as a paradigm shift in VLBI observations, traditionally striving for the highest precision possible, which we believe is worth being discussed. Based on observation statistics and Monte-Carlo simulations, we will elaborate on the expected impact of this approach.

Global ionospheric mapping is essential for ionospheric research. However, conventional approaches often struggle to accurately capture small-scale ionospheric variations. This study proposes a deep ensemble method based on neural networks (NNs) that generates high-accuracy global vertical total electron content (VTEC) maps along with corresponding uncertainty estimates. To develop the machine learning model, we first determined the VTEC time series based on the carrier-to-code leveling method using multi-GNSS observations from global IGS stations. These VTEC time series were then used to train daily NNs, which subsequently generated global ionospheric maps (GIMs) for improved usability and accessibility. During our experiment covering the year 2023, the NNs achieved an average mean absolute error of 1.76 TEC Units (TECU) at 52 global test stations. Compared to IGS combined GIMs and two other representative GIMs from IGS analysis centers, the VTEC time series extracted from NN-GIMs showed better consistency with Jason-3 VTEC, achieving an average root mean squared error of 4.09 TECU after removing daily biases. Furthermore, NN-GIMs achieved the best baseline length repeatability in K-band Very Long Baseline Interferometry analysis. In single-frequency precise point positioning (SF-PPP) tests, NN-GIMs improved positioning accuracy by 11%, 9%, and 24% in the east, north, and up components compared to IGS combined GIMs. Additionally, the deep ensemble-based uncertainty quantification proved beneficial for weighting GNSS observations in SF-PPP, enhancing the positioning accuracy in low-latitude regions by approximately 14% compared to the elevation-based weighting scheme.

In this simulation study, we investigate the potential performance of VLBI Intensives using the AuScope 12-metre VLBI network. This continental Australian network consisting of three stations, has recently been fully upgraded with VGOS receivers and has the capacity for observing the first southern hemisphere VGOS Intensive series. This Intensive series can be conducted entirely in-house, from the scheduling through to the correlation and post-processing. We determine such a VGOS Intensive series could achieve a median performance, with respect to the estimation of UT1-UTC, of 9.74 μ s for mean formal error and 17.95 μ s for repeatabiliy, which is comparable to existing inter-continental S/X Intensive series. Additionally, we investigate the effects of varying observation duration and session duration on the accuracy of the UT1-UTC estimate from this network. The ideal location for a 4th station on continental Australia is also evaluated under the context of optimising UT1-UTC performance, with north-eastern Tasmania providing the greatest increase to UT1-UTC accuracy. Finally, we investigate the effect of adding the Warkworth 12-metre into the network, which provides an efficient increase to UT1-UTC performance and would be an ideal addition pending a future VGOS upgrade for the station.

We have assessed accuracy of estimates of Earth orientation parameters (EOP) determined from several very long baseline interferometry (VLBI) observing programs that ran concurrently at different networks. We consider that the root mean square of differences in EOP estimates derived from concurrent observations is a reliable measure of accuracy. We confirmed that formal errors based on the assumption that the noise in observables is uncorrelated are close to useless. We found no evidence that advanced scheduling strategies with special considerations regarding the ability to better solve for atmospheric path in zenith direction applied for 1-hr single-baseline sessions have any measurable impact on the accuracy of EOP estimates. From this, we conclude that there is a certain limit in our ability to solve for the atmospheric path delay using microwave observations themselves and a scheduling strategy is not the factor that impairs accuracy of EOP determination. We determined that EOP errors vary with season, being smaller in winter and greater in summer. We found that the EOP errors are scaled with an increase in duration of an observing session as a broken power law with the power of -0.3 at durations longer than 2-4 hours, which we explain as manifestation of the presence of correlations in the atmospheric noise.

In 2021, the International Earth Rotation and Reference Systems Service (IERS) established a working group tasked with conducting the Second Earth Orientation Parameters Prediction Comparison Campaign (2nd EOP PCC) to assess the current accuracy of EOP forecasts. From September 2021 to December 2022, EOP predictions submitted by participants from various institutes worldwide were systematically collected and evaluated. This article summarizes the campaign's outcomes, concentrating on the forecasts of the dX, dY, and dψ, dε components of celestial pole offsets (CPO). After detailing the campaign participants and the methodologies employed, we conduct an in-depth analysis of the collected forecasts. We examine the discrepancies between observed and predicted CPO values and analyze their statistical characteristics such as mean, standard deviation, and range. To evaluate CPO forecasts, we computed the mean absolute error (MAE) using the IERS EOP 14 C04 solution as the reference dataset. We then compared the results obtained with forecasts provided by the IERS. The main goal of this study was to show the influence of different methods used on predictions accuracy. Depending on the evaluated prediction approach, the MAE values computed for day 10 of forecast were between 0.03 and 0.16 mas for dX, between 0.03 and 0.12 mas for dY, between 0.07 and 0.91 mas for dψ, and between 0.04 and 0.41 mas for dε. For day 30 of prediction, the corresponding MAE values ranged between 0.03 and 0.12 for dX, and between 0.03 and 0.14 mas for dY. This research shows that machine learning algorithms are the most promising approach in CPO forecasting and provide the highest prediction accuracy (0.06 mas for dX and 0.08 mas for dY for day 10 of prediction). Graphical abstract

Global Navigation Satellite Systems (GNSS), such as the American Global Positioning System (GPS) and the European Galileo system, are capable of monitoring tropospheric properties. An important parameter describing the tropospheric impact on GNSS is zenith wet delay (ZWD), which is highly correlated to the amount of water vapour in the troposphere and thus interesting for atmospheric and climate research. This work demonstrates how GNSS observations help to sense the atmosphere and its dynamics by using a newly developed machine learning-based ZWD model. The model provides ZWD globally for the years 2010 to 2023 with a positive trend in the Northern Hemisphere and a negative trend in the Southern Hemisphere. Furthermore, the global average ZWD anomaly follows alternating trends, strongly correlated with the El Nino Southern Oscillation (ENSO) index, increasing up to a correlation coefficient of 0.74 when introducing a time lag of two months.

The complete set of five Earth Orientation Parameters (EOP) can only be estimated accurately using geodetic Very Long Baseline Interferometry (VLBI). Their precision and accuracy depends on network geometry and station-dependent properties. Atmospheric turbulence poses one of the largest error sources for geodetic VLBI, impacting the precision of EOP. Thus, it becomes imperative to consider this factor while choosing the optimal locations for geodetic VLBI. The magnitude of tropospheric turbulence is approximated through the refractive index structure constant, C_n^2 . In this study, we simulate the optimal locations for geodetic VLBI in India, considering individual tropospheric turbulence parameters per telescope location. The study identifies 14 potential VLBI stations, co-located with GPS stations and homogeneously distributed all over India, and computes the C_n values from zenith wet delay variances over 24 h obtained from GPS data. These locations are simulated in addition to three different reference networks, which show the current and future VLBI Global Observing System (VGOS) networks. Multiple schedules have been generated and simulated for each configuration using VieSched++, and the precision of EOP is compared when constant and station-specific tropospheric turbulence parameters are used. The study shows that, for the investigated networks, southern stations are optimal for polar motion and celestial pole offsets estimation, whereas an eastern station is optimal for UT1−UTC estimation. Furthermore, the study highlights that for reference networks with fewer stations, utilizing station-specific C_n values significantly influences the determination of optimal locations. It further demonstrates how station-specific C_n values impact the positioning of VGOS telescopes in each network for each EOP differently. The findings show that higher C_n values generally lead to a degradation in EOP precision. Geometrically, a station might be at a good location, but if the C_n value is too high, that location is not favorable.