Coastal sea level measurements using a single geodetic GPS receiver

This paper presents a method to derive local sea level variations using data from a single geodetic-quality Global Navigation Satellite System (GNSS) receiver using GPS (Global Positioning System) signals. This method is based on multipath theory for specular reflections and the use of Signal-to-Noise Ratio (SNR) data. The technique could be valuable for altimeter calibration and validation. Data from two test sites, a dedicated GPS tide gauge at the Onsala Space Observatory (OSO) in Sweden and the Friday Harbor GPS site of the EarthScope Plate Boundary Observatory (PBO) in USA, are analyzed. The sea level results are compared to independently observed sea level data from nearby and in situ tide gauges. For OSO, the Root-Mean-Square (RMS) agreement is better than 5 cm, while it is in the order of 10 cm for Friday Harbor. The correlation coefficients are better than 0.97 for both sites. For OSO, the SNR-based results are also compared with results from a geodetic analysis of GPS data of a two receivers/antennae tide gauge installation. The SNR-based analysis results in a slightly worse RMS agreement with respect to the independent tide gauge data than the geodetic analysis (4.8 cm and 4.0 cm, respectively). However, it provides results even for rough sea surface conditions when the two receivers/antennae installation no longer records the necessary data for a geodetic analysis.     

Integrating Non-Tidal Sea Level data from altimetry and tide gauges for coastal sea level prediction

The main objective of this paper is to integrate Non-Tidal Sea Level (NSL) from the joint TOPEX, Jason-1 and Jason-2 satellite altimetry with tide gauge data at the west and north coast of the United Kingdom for coastal sea level prediction. The temporal correlation coefficient between altimetric NSLs and tide gauge data reaches a maximum higher than 90% for each gauge. The results show that the multivariate regression approach can efficiently integrate the two types of data in the coastal waters of the area. The Multivariate Regression Model is established by integrating the along-track NSL from the joint TOPEX/Jason-1/Jason-2 altimeters with that from eleven tide gauges. The model results give a maximum hindcast skill of 0.95, which means maximum 95% of NSL variance can be explained by the model. The minimum Root Mean Square Error (RMSe) between altimetric observations and model predictions is 4.99 cm in the area. The validation of the model using Envisat satellite altimetric data gives a maximum temporal correlation coefficient of 0.96 and a minimum RMSe of 4.39 cm between altimetric observations and model predictions, respectively. The model is furthermore used to predict high frequency NSL variation (i.e., every 15 min) during a storm surge event at an independent tide gauge station at the Northeast of the UK (Aberdeen).     

The impact on tsunami detection from space using GNSS-reflectometry when combining GPS with GLONASS and Galileo

The devastating Sumatra tsunami in 2004 demonstrated the need for a tsunami early warning system in the Indian Ocean. Such a system has been installed within the German-Indonesian Tsunami Early Warning System (GITEWS) project. Tsunamis are a global phenomenon and for global observations satellites are predestined. Within the GITEWS project a feasibility study on a future tsunami detection system from space has therefore been carried out. The Global Navigation Satellite System Reflectometry (GNSS-R) is an innovative way of using GNSS signals for remote sensing. It uses ocean reflected GNSS signals for sea surface altimetry. With a dedicated Low Earth Orbit (LEO) constellation of satellites equipped with GNSS-R receivers, densely spaced sea surface height measurements could be established to detect tsunamis. Some general considerations on the geometry between LEO and GNSS are made in this simulation study. It exemplary analyzes the detection performance of a GNSS-R constellation at 900 km altitude and 60° inclination angle when applied to the Sumatra tsunami as it occurred in 2004. GPS is assumed as signal source and the combination with GLONASS and Galileo signals is investigated. It can be demonstrated, that the combination of GPS and Galileo is advantageous for constellations with few satellites while the combination with GLONASS is preferable for constellations with many satellites. If all three GNSS are combined, the best detection performance can be expected for all scenarios considered. In this case an 18 satellite constellation will detect the Sumatra tsunami within 17 min with certainty, while it takes 53 min if only GPS is considered.     

Evaluation and improvement of coastal GNSS reflectometry sea level variations from existing GNSS stations in Taiwan

Global sea level rise due to an increasingly warmer climate has begun to induce hazards, adversely affecting the lives and properties of people residing in low-lying coastal regions and islands. Therefore, it is important to monitor and understand variations in coastal sea level covering offshore regions. Signal-to-noise ratio (SNR) data of Global Navigation Satellite System (GNSS) have been successfully used to robustly derive sea level heights (SLHs). In Taiwan, there are a number of continuously operating GNSS stations, not originally installed for sea level monitoring. They were established in harbors or near coastal regions for monitoring land motion. This study utilizes existing SNR data from three GNSS stations (Kaohsiung, Suao, and TaiCOAST) in Taiwan to compute SLHs with two methods, namely, Lomb–Scargle Periodogram (LSP)-only, and LSP aided with tidal harmonic analysis developed in this study. The results of both methods are compared with co-located or nearby tide gauge records. Due to the poor quality of SNR data, the worst accuracy of SLHs derived from traditional LSP-only method exceeds 1?m at the TaiCOAST station. With our procedure, the standard deviations (STDs) of difference between GNSS-derived SLHs and tide gauge records in Kaohsiung and Suao stations decreased to 10?cm and the results show excellent agreement with tide gauge derived relative sea level records, with STD of differences of 7?cm and correlation coefficient of 0.96. In addition, the absolute GNSS-R sea level trend in Kaohsiung during 2006–2011 agrees well with that derived from satellite altimetry. We conclude that the coastal GNSS stations in Taiwan have the potential of monitoring absolute coastal sea level change accurately when our proposed methodology is used.     

Analysis of coastal altimetry in the Mexican Caribbean

A reprocessing of sea-level anomalies (SLA) resulting from X-TRACK coastal altimetry was carried out for the ENVISAT (2002–2010) and TOPEX/POSEIDON-Jason (1992–2019) satellite missions in the coastal area of the Mexican Caribbean. This consisted of applying a tidal correction to coastal altimetry sea level observations. Harmonic analysis of five coastal tide gauge records was performed to estimate the most important tidal components of the area, resulting on M2, N2, O1, S2, K1, MF, and MM. The tidal signal was reconstructed with the seven tidal components using the TPXO9 model. The SLA signals corrected with the seven tidal components were validated with in situ data from coastal tide gauges. The validation showed that the TPXO9 tidal barotropic model (1/30° grid) used to reconstruct the tidal signal with the seven representative tidal components performed better than the FES2012 global model (1/16° grid) that uses 33 tidal components. The reprocessed SLAs showed clear seasonality with significant signals at 4, 6, and 12 months, with the annual signal being the dominant one. In the Mexican Caribbean coastal zone, oceanographic processes with different scales (from coastal to mesoscale) converge, showing their complexity in the different SLA signals observed. The aim of this work is to contribute to the analysis of coastal altimetry data and understanding the sea level variations in the Mexican Caribbean. This work is the first step in the implementation of methodologies that take advantage of coastal satellite altimetry in the Caribbean Sea.     

Estimates of vertical land motion along the southwestern coasts of Turkey from coastal altimetry and tide gauge data

The differences between coastal altimetry and sea level time series of tide gauges in between March 1993 and December 2009 are used to estimate the rates of vertical land motion at three tide gauge locations along the southwestern coasts of Turkey. The CTOH/LEGOS along-track coastal altimetry retrieves altimetric sea level anomalies closer to the coast than the standard along-track altimetry products. However, the use of altimetry very close to the coast is not found to improve the results. On the contrary, the gridded and interpolated AVISO merged product exhibits the best agreement with tide gauge data as it provides the smoothest variability both in space and time compared with along track altimetry data. The Antalya gauge to the south (in the Mediterranean Sea) and the Mentes/Izmir gauge to the west (in the Aegean Sea) both show subsidence while the Bodrum tide gauge to the south (in the Aegean Sea) shows no significant vertical land motion. The results are compared and assessed with three independent geophysical vertical land motion estimates like from GPS. The GIA effect in the region is negligible. The VLM estimates from altimetry and tide gauge data are in good agreement both with GPS derived vertical velocity estimates and those inferred from geological and archaeological investigations.     

An improved sea level retrieval method using the differential evolution of GNSS SNR data

This paper presents an improved new method with differential evolution and the cubic spline approach is proposed to retrieve sea level height based on GNSS SNR observations from a single geodetic receiver. Considering the B-spline function is unstable at the beginning or end, and the feature that B-spline functions do not pass through nodes may introduce errors. Thus, the cubic spline is applied to the retrieval process and accounts for a continuous and smooth in sea level retrieval time series. Besides, the biases caused by tropospheric delay and dynamic sea level are considered and corrected. Testing data from two stations with different tidal range and the final solution agrees well with measurements from co-located tide gauges, reaching the RMSE of 3.67 cm at Friday Harbor, Washington, and 1.36 cm at Onsala, Sweden. Comparison of the nonlinear least squares, this method leads to a clear increase in precision of the sea level retrievals within 50%. Additionally, referring to the result of Purnell et al. (2020) and the IAG inter-comparison campaign, the results of this paper show more potential.     

Multi- GNSS reflectometry performance evaluation for coastal sea level monitoring: A case study in Antarctic Peninsula

Antarctica is a continent that crucial for studying climate change and its progression across time, as well as analyzing and forecasting local and global change. In this environment, due to the challenges caused by sea-level rise, storm surges, and tsunamis, sustainability is a critical concern, particularly for coastal regions. As a result, the long-term observations that will be conducted in Antarctica are critical for monitoring the adverse impacts of climate change. In recent years, many monitoring approaches, both space, and ground-based are performed to monitor sea/ice level trends in space-based scientific investigations conducted in and around the region. In the study, based on one year of observations from the Palmer GNSS Station, the GNSS Reflectometry technique was used to measure the sea level on the Antarctic Peninsula (PALM). GNSS Station observations were analyzed with a Lomb-Scargle periodogram to monitor sea-level changes, and results were validated with data from a co-located tide gauge (TG). The results show that the correlation between GNSS-R sea-level changes and tidal sea-level changes is found as 0.91.     

Using altimetry and seafloor pressure data to estimate vertical deformation offshore: Vanuatu case study

Measuring ground deformation underwater is essential for understanding Earth processes at many scales. One important example is subduction zones, which can generate devastating earthquakes and tsunamis, and where the most important deformation signal related to plate locking is usually offshore. We present an improved method for making offshore vertical deformation measurements, that involve combining tide gauge and altimetry data. We present data from two offshore sites located on either side of the plate interface at the New Hebrides subduction zone, where the Australian plate subducts beneath the North Fiji basin. These two sites have been equipped with pressure gauges since 1999, to extend an on-land GPS network across the plate interface. The pressure series measured at both sites show that Wusi Bank, located on the over-riding plate, subsides by 11 ± 4 mm/yr with respect to Sabine Bank, which is located on the down-going plate. By combining water depths derived from the on-bottom pressure data with sea surface heights derived from altimetry data, we determine variations of seafloor heights in a global reference frame. Using altimetry data from TOPEX/Poseidon, Jason-1, Jason-2 and Envisat missions, we find that the vertical motion at Sabine Bank is close to zero and that Wusi Bank subsides by at least 3 mm/yr and probably at most 11 mm/yr.     

Azimuth selection for sea level measurements using geodetic GPS receivers

Based on analysis of Global Positioning System (GPS) multipath signals recorded by a geodetic GPS receiver, GPS Reflectometry (GPS-R) has demonstrated unique advantages in relation to sea level monitoring. Founded on multipath reflectometry theory, sea level changes can be measured by GPS-R through spectral analysis of recorded signal-to-noise ratio data. However, prior to estimating multipath parameters, it is necessary to define azimuth and elevation angle mask to ensure the reflecting zones are on water. Here, a method is presented to address azimuth selection, a topic currently under active development in the field of GPS-R. Data from three test sites: the Kachemak Bay GPS site PBAY in Alaska (USA), Friday Harbor GPS site SC02 in the San Juan Islands (USA), and Brest Harbor GPS site BRST in Brest (France) are analyzed. These sites are located in different multipath environments, from a rural coastal area to a busy harbor, and they experience different tidal ranges. Estimates by the GPS tide gauges at azimuths selected by the presented method are compared with measurements from physical tide gauges and acceptable correspondence found for all three sites.     

Estimating sea level rise around Australia using a new approach to account for low frequency climate signals

Regional sea level studies help to identify the vulnerable areas to the sea level rise. This study investigates the impact of climate modes on sea level variations and trends around Australia using altimetry data, climate indices, and sea level records from tide gauge stations. Here, we show that the sea level variations are negatively correlated with climate indices to the north and west of Australia. The spectral analyses of the climate indices and tide gauge data suggest that a low frequency signal with a period of 11 years emerges during the mid 1980s. Since the 25-year length of the satellite altimetry record is yet too short to detect low frequency signals, their effect on the estimation of regional sea level trend is unknown. Therefore, we estimate the sea level trend with consideration of this signal and using a two-step method. All signals with periods shorter than 7.5 years are first removed from sea level time series and then the trend is estimated using the parametric model that includes the 11-year signal. The skill of the parametric model in explaining the variations in sea level anomaly validates the presence of the 11-year signal detected in the spectrograms of the tide gauge data and climate indices. The average sea level trend for the study area is estimated as 3.85 ± 0.15 mm/year.     

The X-TRACK/ALES multi-mission processing system: New advances in altimetry towards the coast

In the context of the ESA Climate Change Initiative project, a new coastal sea level altimetry product has been developed in order to support advances in coastal sea level variability studies. Measurements from Jason-1,2&3 missions have been retracked with the Adaptive Leading Edge Subwaveform (ALES) Retracker and then ingested in the X-TRACK software with the best possible set of altimetry corrections. These two coastal altimetry processing approaches, previously successfully validated and applied to coastal sea level research, are combined here for the first time in order to derive a 16-year-long (June 2002 to May 2018), high-resolution (20-Hz), along-track sea level dataset in six regions: Northeast Atlantic, Mediterranean Sea, West Africa, North Indian Ocean, Southeast Asia and Australia. The study demonstrates that this new coastal sea level product called X-TRACK/ALES is able to extend the spatial coverage of sea level altimetry data ~3.5 km in the land direction, when compared to the X-TRACK 1-Hz dataset. We also observe a large improvement in coastal sea level data availability from Jason-1 to Jason-3, with data at 3.6 km, 1.9 km and 0.9 km to the coast on average, for Jason-1, Jason-2 and Jason-3, respectively. When combining measurements from Jason-1 to Jason-3, we reach a distance of 1.2–4 km to the coast. When compared to tide gauge data, the accuracy of the new altimetry near-shore sea level estimations also improves. In terms of correlations with a large set of independent tide gauge observations selected in the six regions, we obtain an average value of 0.77. We also show that it is now possible to derive from the X-TRACK/ALES product an estimation of the ocean current variability up to 5 km to the coast. This new altimetry dataset, freely available, will provide a valuable contribution of altimetry in coastal marine research community.     

An Integer Precise Point Positioning technique for sea surface observations using a GPS buoy

GPS data dedicated to sea surface observation are usually processed using differential techniques. Unfortunately, the precision of resulting kinematic positions is baseline-length dependent. So, high precision sea surface observations using differential GPS techniques are limited to coasts, lakes, and rivers. Recent improvements in GPS satellite products (orbits, clocks, and phase biases) make phase ambiguity fixing at the zero difference level achievable and opens up the observation of the sea surface without geographical constraints. This paper recalls the concept of the Integer Precise Point Positioning technique and discusses the precision of GPS buoy positioning. A sequential version of the GINS software has been implemented to achieve single epoch GPS positioning. We used 1 Hz data from a two week GPS campaign conducted in the Kerguelen Islands. A GPS buoy has been moored close to a radar gauge and 90 m away from a permanent GPS station. This infrastructure offers the opportunity to compare both kinematic Integer Precise Point Positioning and classical differential GPS positioning techniques to in situ radar gauge data. We found that Precise Point Positioning results are not significantly biased with respect to radar gauge data and that horizontal time series are consistent with differential processing at the sub-centimetre precision level. Nevertheless, standard deviations of height time series with respect to radar gauge data are typically [4–5] cm. The dominant driver for noise at this level is attributed to errors in tropospheric estimates which propagate into position solutions.     

GNSS-R open-loop difference phase altimetry: Results from a bridge experiment

The paper explores a method to obtain accurate lake surface heights using measurements of the Global Navigation Satellite System (GNSS) carrier phase reflected from the lake surface. The method is referred to as Global Navigation Satellite System-Reflection (GNSS-R) open-loop difference phase altimetry method. It consists of two key technologies: one is the open-loop tracking method to track the GNSS-R signals, where the direct GNSS signal’s frequency is used as a reference frequency to obtain the carrier phases of the GNSS-R signals; the other key technology is time difference phase altimetry method to invert the lake surface heights using two or more carrier phases of GNSS-R signals received simultaneously. A validation experiment is carried out on the SANYING bridge over GUANTING lake using a GNSS-R receiver developed by the Center for Space Science and Applied Research (CSSAR), processing the data with GNSS-R open-loop difference phase altimetry method. The lake surface height results are consistent with the height results of GPS dual-frequency differential positioning altimetry. The results show that we can achieve centimeter level height in one minute average, by using 11 minutes carrier phase data of three GNSS-R signals received simultaneously.     

机载GNSS海洋反射信号的建模与仿真

由于全球导航卫星系统反射(GNSS-R)机载试验耗费大和重复性差,需研制GNSS-R信号模拟器,但没有相应的反射信号模型。提出了一种基于数据拟合的机载GNSS海洋反射信号建模方法。首先,对复杂的GNSS海面反射信号进行近似简化。然后利用ZV模型生成的时延相关功率曲线,通过最小二乘拟合和非线性拟合,建立了多条等时延间隔的海洋反射信号功率衰减模型,从而得到机载GNSS海洋反射信号的时延、功率、多普勒频率参数。最后,对多条反射信号的合路信号进行相关的仿真验证。验证的结果表明模拟的14条反射信号的相关功率曲线与ZV模型理论曲线的相关系数优于0.99,能够有效地用于GNSS海洋反射信号的生成。该方法可根据海面风场、浪高、波高等海面信息,模拟不同海况的海洋反射信号,为GNSS-R信号模拟器的研制奠定基础。     

Sensing snow height and surface temperature variations in Greenland from GPS reflected signals

The in situ measurements of snow surface temperature (SST) and snow height (SH) are very difficult with high costs, particularly in Greenland Ice Sheet (GrIS). Since the snow depth variations coupling with surface temperature are related to GPS multipath, it is possible to estimate the snow depth and surface air temperature variations by incorporating GPS-Reflectometry (GPS-R). In this paper, the reflected signals from ground GPS receivers are used to sense the SST and SH variations based on the thermophysical behavior and variations of snow layer from April to June 2010 at SMM1 site and from March to December 2010 at MARG site in Greenland. The results show that the mean daily changes in the ionospheric geometrical-free linear combination (GPS-L4) of dual-frequency GPS signals are related to daily SST and SH variations. The nonparametric bootstrapping model in direct (forward) and inverse models are developed and applied to estimate the SST and SH variations. The mean biases of SST and SH estimates are 0.18 °C and 0.23 m at SMM1 site, respectively, and 3.8 °C and 0.13 m at MARG site, respectively.     

GPS-based sea level measurements to help the characterization of land contamination in coastal areas

The Corsica site has been established in 1996 to perform altimeter calibration on TOPEX/Poseidon and then on its successors Jason-1 and Jason-2. The first chosen location was under the #85 ground track that overflight the Senetosa Cape. In 2005, it was decided to develop another location close to Ajaccio, to be able to perform the calibration of Envisat and in a next future of SARAL/AltiKa that will flight over the same ground tracks. Equipped with various instruments (tide gauges, permanent GPS, GPS buoy, weather station…) the Corsica calibration site is able to quantify the altimeter Sea Surface Height bias but also to give an input on the origin of this bias (range, corrections, orbits, …). Due to the size of Corsica (not a tiny island), the altimeter measurement system (range and corrections) can be contaminated by land. The aim of this paper is to evaluate this land contamination by using GPS measurements from a fixed receiver on land and from another receiver onboard a life buoy. Concerning the altimeter land contamination, we have quantify that this effect can reach 8 mm/km and then affects the Sea Surface Height bias values already published in the framework of the Corsica calibration site by 5–8 mm for TOPEX and Jason missions. On the other hand, the radiometer measurements (wet troposphere correction) are also sensitive to land and we have been able to quantify the level of improvement of a dedicated coastal algorithm that reconciles our results with those coming from other calibration sites. Finally, we have also shown that the standard deviation of the GPS buoy sea level measurements is highly correlated (∼87%) with the Significant Wave Height derived from the altimeters and can be used to validate such parameter.     

Atmospheric correction of satellite altimetry observations and sea-level variability in the NE Atlantic

Satellite altimetry provides continuous and spatially regular measurements of the height of the sea surface. Sea level responds to density changes of the water, to mass changes, due to addition or reduction of water mass, and to changes in the atmosphere above it. The present study examines the influence of atmospheric effects on sea-level variability in the North-East Atlantic. The association between the height of the sea surface and the North Atlantic Oscillation (NAO) is investigated by considering different sets of altimetry measurements for which the atmospheric effects have been handled differently. Altimetry data not corrected for atmospheric effects are strongly anti-correlated with the state of the NAO, reflecting the hydrostatic response of sea-level to the NAO pressure dipole. The application of an atmospheric correction to satellite altimetry observations in the NE Atlantic decreases variability of the height time series by more than 70% and reduces the amplitude of the seasonal cycle by ∼5 cm. Altimetry data for which atmospheric effects are removed via an inverse barometer correction show a non-negligible correlation with the NAO index at some locations suggesting further indirect non-hydrostatic influences of the state of the NAO on sea level variability.     

Vertical crustal motion derived from satellite altimetry and tide gauges,and comparisons with DORIS measurements

A somewhat unorthodox method for determining vertical crustal motion at a tide-gauge location is to difference the sea level time series with an equivalent time series determined from satellite altimetry. To the extent that both instruments measure an identical ocean signal, the difference will be dominated by vertical land motion at the gauge. We revisit this technique by analyzing sea level signals at 28 tide gauges that are colocated with DORIS geodetic stations. Comparisons of altimeter-gauge vertical rates with DORIS rates yield a median difference of 1.8 mm yr⁻¹ and a weighted root-mean-square difference of 2.7 mm yr⁻¹. The latter suggests that our uncertainty estimates, which are primarily based on an assumed AR(1) noise process in all time series, underestimates the true errors. Several sources of additional error are discussed, including possible scale errors in the terrestrial reference frame to which altimeter-gauge rates are mostly insensitive. One of our stations, Malè, Maldives, which has been the subject of some uninformed arguments about sea-level rise, is found to have almost no vertical motion, and thus is vulnerable to rising sea levels.     

Remote sensing using GNSS signals: Current status and future directions

The refracted, reflected and scattered signals of global navigation satellite systems (GNSS) have been successfully used to remotely sense the Earth’s surface and atmosphere. It has demonstrated its potential to sense the atmosphere and ionosphere, ocean, land surfaces (including soil moisture) and the cryosphere. These new measurements, although in need of refinement and further validation in many cases, can be used to complement existing techniques and sensors, e.g., radiosonde, ionosonde, radar altimetry and synthetic aperture radar (SAR). This paper presents the current status and new developments of remote sensing using GNSS signals as well as its future directions and applications. Some notable emerging applications include monitoring sea ice, dangerous sea states, ocean eddy and storm surges. With the further improvement of the next generation multi-frequency GNSS systems and receivers and new space-based instruments utilizing GNSS reflections and refractions, new scientific applications of GNSS are expected in various environment remote sensing fields in the near future.