Quantitative Evaluation of Environmental Loading Induced Displacement Products for Correcting GNSS Time Series in CMONOC

Mass redistribution within the Earth system deforms the surface elastically. Loading theory allows us to predict loading induced displacement anywhere on the Earth’s surface using environmental loading models, e.g., Global Land Data Assimilation System. In addition, different publicly available loading products are available. However, there are differences among those products and the differences among the combinations of loading models cannot be ignored when precisions of better than 1 cm are required. Many scholars have applied these loading corrections to Global Navigation Satellite System (GNSS) time series from mainland China without considering or discussing the differences between the available models. Evaluating the effects of different loading products over this region is of paramount importance for accurately removing the loading signal. In this study, we investigate the performance of these different publicly available loading products on the scatter of GNSS time series from the Crustal Movement Observation Network of China. We concentrate on five different continental water storage loading models, six different non-tidal atmospheric loading models, and five different non-tidal oceanic loading models. We also investigate all the different combinations of loading products. The results show that the difference in RMS reduction can reach 20% in the vertical component depending on the loading correction applied. We then discuss the performance of different loading combinations and their effects on the noise characteristics of GNSS height time series and horizontal velocities. The results show that the loading products from NASA may be the best choice for corrections in mainland China. This conclusion could serve as an important reference for loading products users in this region.

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Estimating trends in atmospheric water vapor and temperature time series over Germany

Atmospheric Measurement Techniques ◽

10.5194/amt-10-3117-2017 ◽

2017 ◽

Vol 10 (9) ◽

pp. 3117-3132 ◽

Cited By ~ 14

Author(s):

Fadwa Alshawaf ◽

Kyriakos Balidakis ◽

Galina Dick ◽

Stefan Heise ◽

Jens Wickert

Keyword(s):

Time Series ◽

Water Vapor ◽

Time Windows ◽

Temporal Trends ◽

Precipitable Water ◽

Satellite System ◽

Reanalysis Data ◽

Mean Value ◽

Global Navigation Satellite ◽

Gnss Time Series

Abstract. Ground-based GNSS (Global Navigation Satellite System) has efficiently been used since the 1990s as a meteorological observing system. Recently scientists have used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) data and meteorological measurements. We aim to evaluate climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. PWV time series were obtained by three methods: (1) estimated from ground-based GNSS observations using the method of precise point positioning, (2) inferred from ERA-Interim reanalysis data, and (3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods: the first applies least squares to deseasonalized time series and the second uses the Theil–Sen estimator. The trends estimated at 113 GNSS sites, with 10 to 19 years temporal coverage, vary between −1.5 and 2.3 mm decade−1 with standard deviations below 0.25 mm decade−1. These results were validated by estimating the trends from ERA-Interim data over the same time windows, which show similar values. These values of the trend depend on the length and the variations of the time series. Therefore, to give a mean value of the PWV trend over Germany, we estimated the trends using ERA-Interim spanning from 1991 to 2016 (26 years) at 227 synoptic stations over Germany. The ERA-Interim data show positive PWV trends of 0.33 ± 0.06 mm decade−1 with standard errors below 0.03 mm decade−1. The increment in PWV varies between 4.5 and 6.5 % per degree Celsius rise in temperature, which is comparable to the theoretical rate of the Clausius–Clapeyron equation.

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How small can ground movements be to be detectable with GNSS?

10.5194/egusphere-egu21-1999 ◽

2021 ◽

Author(s):

Roland Hohensinn ◽

Pia Ruttner ◽

Benedikt Soja ◽

Markus Rothacher

Keyword(s):

Time Series ◽

Time Series Data ◽

Sampling Rate ◽

Satellite System ◽

Series Data ◽

Ground Movements ◽

Trajectory Model ◽

Noise Characteristics ◽

Movement Parameters ◽

Gnss Time Series

High-precision GNSS (Global Navigation Satellite System) positioning can reach an accuracy at the millimeter level, and by collecting these data over years, very small ground movements can be resolved. These data can be used to study geodynamics, like continental drifts, tidal- and non-tidal loading effects, or earthquakes, for example. Here we focus on the sensitivity of GNSS for resolving these different types of movements. We derive minimal detectable displacements for linear drift rates, annual- and semiannual periodic motions, and offsets &#8211; these are main parameters of the so-called standard linear trajectory model for GNSS station motions. For our analysis, our data comes from several hundreds of permanent GNSS stations across Europe&#8211; the GNSS stations&#8217; coordinates are obtained at a daily sampling rate, with almost 25 years of data available for some stations. Based on cleaned residual GNSS time series we calibrate a &#8220;power-law plus white noise&#8221; stochastic model for each station. Together with the functional trajectory model we compute the formal errors of the movement parameters based on a least-squares adjustment. Based on these errors we then introduce the statistics to derive minimum detectable displacements for the movement parameters.Our analysis shows that the minimum detectable trends can be as low as few tenth of millimeters per year. The minimum detectable amplitudes at the annual and semiannual periods are at the millimeter level or lower, and the detectable offset is few millimeters on average, too. As expected, the minimum detectable displacements depend strongly on the length of the datasets and on the noise characteristics. Another important parameter is the number of discontinuities and offsets for each station &#8211; it impacts the minimum detectable trend. We conclude that such an analysis can be very useful for sensitivity studies in climate change monitoring. Furthermore, the methodology cannot only be applied in the field of GNSS time series analysis, but also to any other time series data in geosciences.

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Modeling and Analysis of BDS-2 and BDS-3 Combined Precise Time and Frequency Transfer Considering Stochastic Models of Inter-System Bias

Remote Sensing ◽

10.3390/rs13040793 ◽

2021 ◽

Vol 13 (4) ◽

pp. 793

Author(s):

Guoqiang Jiao ◽

Shuli Song ◽

Qinming Chen ◽

Chao Huang ◽

Ke Su ◽

...

Keyword(s):

Stochastic Models ◽

Satellite System ◽

Modeling And Analysis ◽

System Bias ◽

Frequency Transfer ◽

Global Navigation ◽

The Difference ◽

The Stability ◽

Global Navigation Satellite ◽

Precise Time

BeiDou global navigation satellite system (BDS) began to provide positioning, navigation, and timing (PNT) services to global users officially on 31 July, 2020. BDS constellations consist of regional (BDS-2) and global navigation satellites (BDS-3). Due to the difference of modulations and characteristics for the BDS-2 and BDS-3 default civil service signals (B1I/B3I) and the increase of new signals (B1C/B2a) for BDS-3, a systemically bias exists in the receiver-end when receiving and processing BDS-2 and BDS-3 signals, which leads to the inter-system bias (ISB) between BDS-2 and BDS-3 on the receiver side. To fully utilize BDS, the BDS-2 and BDS-3 combined precise time and frequency transfer are investigated considering the effect of the ISB. Four kinds of ISB stochastic models are presented, which are ignoring ISB (ISBNO), estimating ISB as random constant (ISBCV), random walk process (ISBRW), and white noise process (ISBWN). The results demonstrate that the datum of receiver clock offsets can be unified and the ISB deduced datum confusion can be avoided by estimating the ISB. The ISBCV and ISBRW models are superior to ISBWN. For the BDS-2 and BDS-3 combined precise time and frequency transfer using ISBNO, ISBCV, ISBRW, and ISBWN, the stability of clock differences of old signals can be enhanced by 20.18%, 23.89%, 23.96%, and 11.46% over BDS-2-only, respectively. For new signals, the enhancements are −50.77%, 20.22%, 17.53%, and −3.69%, respectively. Moreover, ISBCV and ISBRW models have the better frequency transfer stability. Consequently, we recommended the optimal ISBCV or suboptimal ISBRW model for BDS-2 and BDS-3 combined precise time and frequency transfer when processing the old as well as the new signals.

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Performance Assessment of GNSS-R Polarimetric Observations for Sea Level Monitoring

10.5194/egusphere-egu21-12709 ◽

2021 ◽

Author(s):

Mahmoud Rajabi ◽

Mstafa Hoseini ◽

Hossein Nahavandchi ◽

Maximilian Semmling ◽

Markus Ramatschi ◽

...

Keyword(s):

Time Series ◽

Circular Polarization ◽

Sea Level ◽

Tide Gauge ◽

Satellite System ◽

Sea Surface ◽

Analysis Tool ◽

Lower Accuracy ◽

Coastal Sea ◽

Global Navigation Satellite

Determination and monitoring of the mean sea level especially in the coastal areas are essential, environmentally, and as a vertical datum. Ground-based Global Navigation Satellite System Reflectometry (GNSS-R) is an innovative way which is becoming a reliable alternative for coastal sea-level altimetry. Comparing to traditional tide gauges, GNSS-R can offer different parameters of sea surface, one of which is the sea level. The measurements derived from this technique can cover wider areas of the sea surface in contrast to point-wise observations of a tide gauge. &#160;We use long-term ground-based GNSS-R observations to estimate sea level. The dataset includes one-year data from January to December 2016. The data was collected by a coastal GNSS-R experiment at the Onsala space observatory in Sweden. The experiment utilizes three antennas with different polarization designs and orientations. The setup has one up-looking, and two sea-looking antennas at about 3 meters above the sea surface level. The up-looking antenna is Right-Handed Circular Polarization (RHCP). The sea-looking antennas with RHCP and Left-Handed Circular Polarization (LHCP) are used for capturing sea reflected Global Positioning System (GPS) signals. A dedicated reflectometry receiver (GORS type) provides In-phase and Quadrature (I/Q) correlation sums for each antenna based on the captured interferometric signal. The generated time series of I/Q samples from different satellites are analyzed using the Least Squares Harmonic Estimation (LSHE) method. This method is a multivariate analysis tool which can flexibly retrieve the frequencies of a time series regardless of possible gaps or unevenly spaced sampling. The interferometric frequency, which is related to the reflection geometry and sea level, is obtained by LSHE with a temporal resolution of 15&#160;minutes. The sea level is calculated based on this frequency in six modes from the three antennas in GPS L1 and L2 signals.Our investigation shows that the sea-looking antennas perform better compared to the up-looking antenna. The highest accuracy is achieved using the sea-looking LHCP antenna and GPS L1 signal. The annual Root Mean Square Error (RMSE) of 15-min GNSS-R water level time series compared to tide gauge observations is 3.7 (L1) and 5.2 (L2) cm for sea-looking LHCP, 5.8 (L1) and 9.1 (L2) cm for sea-looking RHCP, 6.2 (L1) and 8.5 (L2) cm for up-looking RHCP. It is worth noting that the GPS IIR block satellites show lower accuracy due to the lack of L2C code. Therefore, the L2 observations from this block are eliminated.

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GNSS Multipath Detection Using Continuous Time-Series C/N0

Sensors ◽

10.3390/s20144059 ◽

2020 ◽

Vol 20 (14) ◽

pp. 4059

Author(s):

Nobuaki Kubo ◽

Kaito Kobayashi ◽

Rei Furukawa

Keyword(s):

Time Series ◽

Continuous Time ◽

Urban Areas ◽

Satellite System ◽

Line Of Sight ◽

Static Tests ◽

Gnss Receivers ◽

Multipath Detection ◽

Global Navigation Satellite ◽

Multipath Errors

The reduction of multipath errors is a significant challenge in the Global Navigation Satellite System (GNSS), especially when receiving non-line-of-sight (NLOS) signals. However, selecting line-of-sight (LOS) satellites correctly is still a difficult task in dense urban areas, even with the latest GNSS receivers. This study demonstrates a new method of utilization of C/N0 of the GNSS to detect NLOS signals. The elevation-dependent threshold of the C/N0 setting may be effective in mitigating multipath errors. However, the C/N0 fluctuation affected by NLOS signals is quite large. If the C/N0 is over the threshold, the satellite is used for positioning even if it is still affected by the NLOS signal, which causes the positioning error to jump easily. To overcome this issue, we focused on the value of continuous time-series C/N0 for a certain period. If the C/N0 of the satellite was less than the determined threshold, the satellite was not used for positioning for a certain period, even if the C/N0 recovered over the threshold. Three static tests were conducted at challenging locations near high-rise buildings in Tokyo. The results proved that our method could substantially mitigate multipath errors in differential GNSS by appropriately removing the NLOS signals. Therefore, the performance of real-time kinematic GNSS was significantly improved.

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Testing Multi-Frequency Low-Cost GNSS Receivers for Geodetic Monitoring Purposes

Sensors ◽

10.3390/s20164375 ◽

2020 ◽

Vol 20 (16) ◽

pp. 4375

Author(s):

Veton Hamza ◽

Bojan Stopar ◽

Tomaž Ambrožič ◽

Goran Turk ◽

Oskar Sterle

Keyword(s):

Low Cost ◽

Base Point ◽

Satellite System ◽

Gnss Receivers ◽

The Difference ◽

Short Baselines ◽

Height Component ◽

Global Navigation Satellite ◽

High Level ◽

Positional Precision

Global Navigation Satellite System (GNSS) technology is widely used for geodetic monitoring purposes. However, in cases where a higher risk of receiver damage is expected, geodetic GNSS receivers may be considered too expensive to be used. As an alternative, low-cost GNSS receivers that are cheap, light, and prove to be of adequate quality over short baselines, are considered. The main goal of this research is to evaluate the positional precision of a multi-frequency low-cost instrument, namely, ZED-F9P with u-blox ANN-MB-00 antenna, and to investigate its potential for displacement detection. We determined the positional precision within static survey, and the displacement detection within dynamic survey. In both cases, two baselines were set, with the same rover point equipped with a low-cost GNSS instrument. The base point of the first baseline was observed with a geodetic GNSS instrument, whereas the second baseline was observed with a low-cost GNSS instrument. The results from static survey for both baselines showed comparable results for horizontal components; the precision was on a level of 2 mm or better. For the height component, the results show a better performance of low-cost instruments. This may be a consequence of unknown antenna calibration parameters for low-cost GNSS antenna, while statistically significant coordinates of rover points were obtained from both baselines. The difference was again more significant in the height component. For the displacement detection, a device was used that imposes controlled movements with sub-millimeter accuracy. Results, obtained on a basis of 30-min sessions, show that low-cost GNSS instruments can detect displacements from 10 mm upwards with a high level of reliability. On the other hand, low-cost instruments performed slightly worse as far as accuracy is concerned.

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VISUAL ANALYSIS OF RECURRENCE OF TIME SERIES OF THE COORDINATES ENU IN THE GPS STATIONS

Boletim de Ciências Geodésicas ◽

10.1590/s1982-21702018000400029 ◽

2018 ◽

Vol 24 (4) ◽

pp. 470-484

Author(s):

Alfonso Tierra ◽

Rubén León ◽

Alexis Tinoco-S ◽

Carolina Cañizares ◽

Marco Amores ◽

...

Keyword(s):

Time Series ◽

Continuous Monitoring ◽

Visual Analysis ◽

Finite Impulse Response ◽

Satellite System ◽

Nearest Neighbours ◽

Low Pass ◽

Global Navigation Satellite ◽

Low Pass Filters ◽

Content Information

Abstract The time series content information about the dynamic behavior of the system under study. This behavior could be complex, irregular and no lineal. For this reason, it is necessary to study new models that can solve this dynamic more satisfactorily. In this work a visual analysis of recurrence from time series of the coordinate’s variation ENU (East, North, Up) will be made. This analysis was obtained from nine continuous monitoring stations GPS (Global Navigation Satellite System); the intention is to study their behavior, they belong to the Equatorian GPS Network that materializes the reference system SIRGAS - ECUADOR. The presence of noise in the observations was reduced using digital low pass filters with Finite Impulse Response (FIR). For these series, the time delay was determined using the average mutual information, and for the minimum embedding dimension the False Nearest Neighbours (FNN) method was used; the purpose is to obtain the recurrent maps of each coordinates. The results of visual analysis show a strong tendency, especially in the East and North coordinates, while the Up coordinates indicate discontinued, symmetric and periodic behavior.

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Analysis and Comparison of GPS Precipitable Water Estimates between Two Nearby Stations on Tahiti Island

Sensors ◽

10.3390/s19245578 ◽

2019 ◽

Vol 19 (24) ◽

pp. 5578

Author(s):

Fangzhao Zhang ◽

Jean-Pierre Barriot ◽

Guochang Xu ◽

Marania Hopuare

Keyword(s):

Mapping Function ◽

Precipitable Water ◽

Satellite System ◽

Tropospheric Delay ◽

Horizontal Distance ◽

International Gnss Service ◽

Weighted Mean Temperature ◽

The Difference ◽

Global Navigation Satellite ◽

The Impact

Since Bevis first proposed Global Positioning System (GPS) meteorology in 1992, the precipitable water (PW) estimates retrieved from Global Navigation Satellite System (GNSS) networks with high accuracy have been widely used in many meteorological applications. The proper estimation of GNSS PW can be affected by the GNSS processing strategy as well as the local geographical properties of GNSS sites. To better understand the impact of these factors, we compare PW estimates from two nearby permanent GPS stations (THTI and FAA1) in the tropical Tahiti Island, a basalt shield volcano located in the South Pacific, with a mean slope of 8% and a diameter of 30 km. The altitude difference between the two stations is 86.14 m, and their horizontal distance difference is 2.56 km. In this paper, Bernese GNSS Software Version 5.2 with precise point positioning (PPP) and Vienna mapping function 1 (VMF1) was applied to estimate the zenith tropospheric delay (ZTD), which was compared with the International GNSS Service (IGS) Final products. The meteorological parameters sourced from the European Center for Medium-Range Weather Forecasts (ECMWF) and the local weighted mean temperature ( T m ) model were used to estimate the GPS PW for three years (May 2016 to April 2019). The results show that the differences of PW between two nearby GPS stations is nearly a constant with value 1.73 mm. In our case, this difference is mainly driven by insolation differences, the difference in altitude and the wind being only second factors.

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Two decades of satellite observations of AOD over mainland China using ATSR-2, AATSR and MODIS/Terra: data set evaluation and large-scale patterns

Atmospheric Chemistry and Physics ◽

10.5194/acp-18-1573-2018 ◽

2018 ◽

Vol 18 (3) ◽

pp. 1573-1592 ◽

Cited By ~ 48

Author(s):

Gerrit de Leeuw ◽

Larisa Sogacheva ◽

Edith Rodriguez ◽

Konstantinos Kourtidis ◽

Aristeidis K. Georgoulias ◽

...

Keyword(s):

Time Series ◽

European Space Agency ◽

Mainland China ◽

Satellite Observations ◽

Data Sets ◽

Data Set ◽

Modis Aod ◽

The Difference ◽

Along Track ◽

Aerosol Properties

Abstract. The retrieval of aerosol properties from satellite observations provides their spatial distribution over a wide area in cloud-free conditions. As such, they complement ground-based measurements by providing information over sparsely instrumented areas, albeit that significant differences may exist in both the type of information obtained and the temporal information from satellite and ground-based observations. In this paper, information from different types of satellite-based instruments is used to provide a 3-D climatology of aerosol properties over mainland China, i.e., vertical profiles of extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a lidar flying aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the column-integrated extinction (aerosol optical depth – AOD) available from three radiometers: the European Space Agency (ESA)'s Along-Track Scanning Radiometer version 2 (ATSR-2), Advanced Along-Track Scanning Radiometer (AATSR) (together referred to as ATSR) and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Terra satellite, together spanning the period 1995–2015. AOD data are retrieved from ATSR using the ATSR dual view (ADV) v2.31 algorithm, while for MODIS Collection 6 (C6) the AOD data set is used that was obtained from merging the AODs obtained from the dark target (DT) and deep blue (DB) algorithms, further referred to as the DTDB merged AOD product. These data sets are validated and differences are compared using Aerosol Robotic Network (AERONET) version 2 L2.0 AOD data as reference. The results show that, over China, ATSR slightly underestimates the AOD and MODIS slightly overestimates the AOD. Consequently, ATSR AOD is overall lower than that from MODIS, and the difference increases with increasing AOD. The comparison also shows that neither of the ATSR and MODIS AOD data sets is better than the other one everywhere. However, ATSR ADV has limitations over bright surfaces which the MODIS DB was designed for. To allow for comparison of MODIS C6 results with previous analyses where MODIS Collection 5.1 (C5.1) data were used, also the difference between the C6 and C5.1 merged DTDB data sets from MODIS/Terra over China is briefly discussed. The AOD data sets show strong seasonal differences and the seasonal features vary with latitude and longitude across China. Two-decadal AOD time series, averaged over all of mainland China, are presented and briefly discussed. Using the 17 years of ATSR data as the basis and MODIS/Terra to follow the temporal evolution in recent years when the environmental satellite Envisat was lost requires a comparison of the data sets for the overlapping period to show their complementarity. ATSR precedes the MODIS time series between 1995 and 2000 and shows a distinct increase in the AOD over this period. The two data series show similar variations during the overlapping period between 2000 and 2011, with minima and maxima in the same years. MODIS extends this time series beyond the end of the Envisat period in 2012, showing decreasing AOD.

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IWV retrieval from ship-borne GNSS receiver in the framework of the MAP-IO project

10.5194/ems2021-172 ◽

2021 ◽

Author(s):

Pierre Bosser ◽

Joël Van Ballen ◽

Olivier Bousquet

Keyword(s):

Marine Biology ◽

Weather Prediction ◽

Vertical Component ◽

Satellite System ◽

Sea Surface Height ◽

Sea Surface ◽

Gnss Receiver ◽

Height Determination ◽

Global Navigation Satellite ◽

Height Model

In the framework of the research project &#8220;Marion Dufresne Atmospheric Program &#8211; Indian Ocean&#8221; (MAP-IO), which is aiming at collecting long-term atmospheric and marine biology observations in the under-instrumented Indian and Austral Oceans, a Global Navigation Satellite System (GNSS) receiver was installed on the research vessel (RV) Marion Dufresne in October 2020 to describe, and monitor, global moisture changes in these areas. GNSS raw data are recorded continuously and used to retrieve integrated water vapor contents (IWV) along the RV route.After a data quality check that confirmed that a wise choice of location of the GNSS antenna on the RV is crucial to avoid mask, signal reflection and interference from other instruments that may degrade IWV retrieval, a first assessment of the GNSS analysis performances was carried out by comparing the vertical component of the estimated positions to sea surface height model. The differences are on the order of 20 to 30 cm; they are consistent with both the error budget for sea surface height determination using GNSS and the sea surface height model formal errors.An evaluation of GNSS-derived IWV was conducted using IWV estimates from the ECMWF fifth ReAnalysis (ERA5) and ground-based GNSS reference stations located nearby the tracks of RV Marion Dufresne. Preliminary analyses show encouraging results with a mean root mean square error of ~2-3&#160;kg&#160;m-2 between ERA5 and GNSS-derived IWV. The use of ultra-rapid GNSS orbit and clock product was also investigated to assess the performance of near real-time GNSS-derived IWV estimation for numerical weather prediction purposes.

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