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.     

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.     

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.     

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.     

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).     

Monitoring coastal sea level using reflected GNSS signals

A continuous monitoring of coastal sea level changes is important for human society since it is predicted that up to 332 million people in coastal and low-lying areas will be directly affected by flooding from sea level rise by the end of the 21st century. The traditional way to observe sea level is using tide gauges that give measurements relative to the Earth’s crust. However, in order to improve the understanding of the sea level change processes it is necessary to separate the measurements into land surface height changes and sea surface height changes. These measurements should then be relative to a global reference frame. This can be done with satellite techniques, and thus a GNSS-based tide gauge is proposed. The GNSS-based tide gauge makes use of both GNSS signals that are directly received and GNSS signals that are reflected from the sea surface. An experimental installation at the Onsala Space Observatory (OSO) shows that the reflected GNSS signals have only about 3 dB less signal-to-noise-ratio than the directly received GNSS signals. Furthermore, a comparison of local sea level observations from the GNSS-based tide gauge with two stilling well gauges, located approximately 18 and 33 km away from OSO, gives a pairwise root-mean-square agreement on the order of 4 cm. This indicates that the GNSS-based tide gauge gives valuable results for sea level monitoring.     

The challenges in long-term altimetry calibration for addressing the problem of global sea level change

Long-term change of the global sea level resulting from climate change has become an issue of great societal interest. The advent of the technology of satellite altimetry has modernized the study of sea level on both global and regional scales. In combination with in situ observations of the ocean density and space observations of Earth’s gravity variations, satellite altimetry has become an essential component of a global observing system for monitoring and understanding sea level change. The challenge of making sea level measurements with sufficient accuracy to discern long-term trends and allow the patterns of natural variability to be distinguished from those linked to anthropogenic forcing rests largely on the long-term efforts of altimeter calibration and validation. The issues of long-term calibration for the various components of the altimeter measurement system are reviewed in the paper. The topics include radar altimetry, the effects of tropospheric water vapor, orbit determination, gravity field, tide gauges, and the terrestrial reference frame. The necessity for maintaining a complete calibration effort and the challenges of sustaining it into the future are discussed.     

A comparison of seasonal variations of sea level in the southern Baltic Sea from altimetry and tide gauge data

In this paper, seasonal sea level variations have been determined at five locations in the Baltic Sea from satellite altimetry for the period 1993–2015. The results were compared to tide gauge water level data. Annual and semi-annual amplitudes have been investigated for both sea level anomalies and tide gauge water level. It was found that the two independent observations of sea level variations along the Polish coast are in good agreement both in terms of their annual and semi-annual amplitudes and their annual and semi-annual phases. The annual cycles in the sea level variations measured by altimetry and tide gauge reach maximum values at approximately the same month (November/December).Moreover, this article shows the differences between the annual and semi-annual amplitudes and phases in the sea level anomalies and water level data within the same time frame. The difference in the annual amplitudes between the satellite altimetry and the tide gauge results is between 0.33?cm and 1.53?cm. The maximum differences in the annual cycle of the sea level changes were found at the Swinoujscie station. The correlations between the original series and the calculated curves were determined, and the relationship between the amplitudes and the phases were investigated. The correlation between the annual variations observed from the two independent observation techniques is 0.92.To analyse the dynamics of the change in sea level, the linear trend was estimated from the satellite altimetry and tide gauge time series both in the original time series of the data and in the time series in which seasonal variations were removed. In addition, we calculated the estimated errors of regression and how many years’ worth of data are needed to obtain an accuracy of 0.1?mm per year. The estimated errors of regression showed that to get an accuracy of 0.1?mm per year, we need 100?years of data.     

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.     

Coastal sea level changes in Europe from GPS,tide gauge,satellite altimetry and GRACE, 1993–2011

Sea level changes are threatening the human living environments, particularly along the European Coasts with highly dense population. In this paper, coastal sea level changes in western and southern Europe are investigated for the period 1993–2011 using Global Positioning System (GPS), Tide Gauge (TG), Satellite Altimetry (SA), Gravity Recovery and Climate Experiment (GRACE) and geophysical models. The mean secular trend is 2.26 ± 0.52 mm/y from satellite altimetry, 2.43 ± 0.61 mm/y from TG+GPS and 1.99 ± 0.67 mm/y from GRACE mass plus steric components, which have a remarkably good agreement. For the seasonal variations, annual amplitudes of satellite altimetry and TG+GPS results are almost similar, while GRACE Mass+Steric results are a little smaller. The annual phases agree remarkably well for three independent techniques. The annual cycle is mainly driven by the steric contributions, while the annual phases of non-steric (mass component) sea level changes are almost a half year later than the steric sea level changes.     

A point-wise least squares spectral analysis (LSSA) of the Caspian Sea level fluctuations,using TOPEX/Poseidon and Jason-1 observations

The Caspian Sea has displayed considerable fluctuations in its water level during the past century. Knowledge of such fluctuation is vital for understanding the local hydrological cycles, climate of the region, and construction activities within the sea and along its shorelines. This study established a point-wise satellite altimetry approach to monitor the fluctuations of the Caspian Sea using a complete dataset of TOPEX/Poseidon for the period 1993 to the middle of 2002, and its follow-on Jason-1 for the period 2002 to August 2009. Therefore, 280 virtual time-series were constructed to monitor the fluctuations. The least squares spectral analysis (LSSA) method is, then employed to find the most significant frequencies of the time-series, while the statistical method of principle component analysis (PCA) is applied to extract the dominant variability of level variations. The study also used the observations of TOPEX/Poseidon and Jason-1 over the Volga River along with 5 years of Volga’s water discharge to study its influence on the Caspian Sea level changes. The LSSA results indicate that the lunar semidiurnal (M2) and the Sun semidiurnal (S2) frequencies are the main tidal frequencies of the Caspian Sea with the mean amplitude of 4.2 and 2.8 cm, respectively. A statistically significant long-term frequency (12.5-years period) is also found from altimetry and tide gauge observations. A phase lag, related to the inter-annual frequencies of the Volga River was detected from the point-wise time-series showing level propagation from the northwest to the southeast of the sea. The cross-correlation between the power spectrum of Volga and that of the northern-most, middle, and southern-most points within the Caspian Sea were respectively 0.63, 0.51 and 0.4 of zero-lag correlation, corroborating the influence of the Volga River. The result of PCA also shows that different parts of the Caspian Sea exhibit different amplitudes of level variations, indicating that the point-wise approach, when employing all available satellite measurements could be a suitable method for a preliminary monitoring of this inland water resource as it gives accurate local fluctuations.     

基于半无码的P(Y)码自相关GNSS-R海面测高方法

针对传统GPS C/A码延迟测高方法测高精度低和互相关测高方法时延波形信噪比低的问题,研究了基于半无码的P（Y）码自相关海面测高方法。首先,通过理论测高精度模型,对比分析了C/A码和P（Y）码的测高精度;然后,描述了L1、L2双频反射信号基于半无码的P（Y）码自相关处理架构,并论述了测高模型和L1、L2双频电离层时延误差修正方法;最后,利用模拟的L1、L2反射信号对比分析了基于半无码的P（Y）码自相关、C/A码自相关以及信号互相关方法的海面测高精度。结果表明:相比于C/A码自相关和信号互相关测高精度,基于半无码的P（Y）码自相关的测高精度分别提高了3.97倍和1.47倍。      

基于QZSS L1信号的岸基GNSS-R码延迟海面测高

为了探究GNSS L1波段中信号不同调制方式的GNSS-R码相位延迟海面的测高性能，开展了双天线岸基GNSS-R海面测高实验，收集了采样率为40 MHz的原始中频数据。利用自主开发的GNSS-R测高软件接收机和反演软件对实验数据进行了处理分析，同时获得了基于QZSS L1C/A码和L1C码的GNSS-R海面测高结果，并分别与岸基同步观测的雷达高度计的测高值进行对比，以对反演结果进行精度评定。实验结果表明:基于QZSS L1C/A码和L1C码的海面测高精度最优可达0.63 m和0.4 m，L1C码的延迟GNSS-R测高精度明显高于L1C/A码。此外，GNSS-R测高精度会随着卫星高度角的增加而有所增加。      

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.     

Preliminary gravity recovery from CryoSat-2 data in the Baffin Bay

A number of geophysical phenomenons in the open ocean are still unresolved by conventional altimetry, but could be resolved through the potential improvements offered by Synthetic Aperture Radar (SAR), also called Delay-Doppler, altimetry. The SAR altimeter offers the following benefits with respect to conventional satellite altimetry: factor of 20 improvements in the along-track resolution, the along-track footprint length which does not vary with wave height (sea state), and improved precision in sea surface height measurements or sea surface slope measurements.     

Minimum time span of TOPEX/Poseidon,Jason-1 and Jason-2 global altimeter data to detect a significant trend and acceleration in sea level change

The present study aims to estimate a minimum time span of the global mean sea level time series (from TOPEX/Poseidon, Jason-1 and Jason-2 satellite altimetry) which is sufficient to detect a statistically meaningful trend in global sea level variation. In addition, the objective of this paper is also to seek a minimum time span required to detect a significant acceleration in sea level change.     

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.     

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.