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.     

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.     

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.     

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.     

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.     

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 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.     

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.     

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.     

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.     

Influence of time variable geopotential models on precise orbits of altimetry satellites,global and regional mean sea level trends

During the last decade a significant progress has been reached in the investigation of the gravity field of the Earth. Besides static, also time variable geopotential models have been recently created. In this paper we investigate the impact of the recent time variable geopotential models on altimetry satellite orbits and such altimetry products based on these orbits, as global and regional mean sea level trends. We show that the modeling of time variable gravity improves the orbit solutions, at least for the GRACE period where time variable gravity is sufficiently accurately observed by this mission. Our analysis includes six geopotential models jointly developed by GFZ German Research Centre for Geosciences and Space Geodesy Research Group (CNES/GRGS) Toulouse: the stationary model EIGEN-GL04S, a stationary version of EIGEN-6S (EIGEN-6S_stat), a corrected version of EIGEN-6S and three enhanced versions of EIGEN-6S called EIGEN-6S2, EIGEN-6S2A and EIGEN-6S2B. By “stationary” we mean “containing periodic parameters such as annual and semi-annual variations, but no secular (drift) terms”. We computed precise orbits for the radar altimetry satellites ERS-1, ERS-2, TOPEX/Poseidon, and Envisat over 20 years between 1991 and 2011. The orbit, single-mission and multi-mission altimetry crossover analyses show that the time variable models EIGEN-6S_corrected, EIGEN-6S2 and its two precursors EIGEN-6S2A/B perform notably better than the stationary models for the GRACE period from 2003 onwards. Thus, using EIGEN-6S2 and EIGEN-6S2A/B we have got 3.6% smaller root mean square fits of satellite laser ranging observations for Envisat, as when using EIGEN-GL04S. However, for the pre-GRACE period 1991–2003, the stationary geopotential models EIGEN-GL04S and EIGEN-6S_stat as well as EIGEN-6S2 having no drift terms for degree 3–50 at this time interval perform superior compared to EIGEN-6S_correct and EIGEN-6S2A/B which contain drifts for this period. We found, that the time variable geopotential models have a low (0.1–0.2 mm/yr) impact on our results for the global mean sea level trend. However, we found strong East/West differences up to 3 mm/yr in the regional mean sea level trends when using orbits of all four satellites based on time variable and stationary geopotential models. We show that these differences are related to the relative drifts of the centers-of-origin between the orbit solutions based on the time variable and stationary geopotential models. From the results of our detailed study, we conclude that the final version of the time variable gravity field model EIGEN-6S2 performs best for the four satellites tested. This model provides the most reliable and mission-consistent sea level estimates for the whole time period from 1992 to 2010. This model is of maximum spherical harmonic degree and order 260 and contains time series for drifts as well as annual and semiannual variations of the spherical harmonic coefficients for degree 2–50.     

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.     

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 solar cycle variation of plasma parameters in equatorial and mid latitudinal areas during 2005–2010

Based on the ISL data detected by DEMETER satellite, the solar cycle variation in electron density (Ne) and electron temperature (Te) were studied separately in local daytime 10:30 and nighttime 22:30 during 2005–2010 in the 23rd/24th solar cycles. The semi-annual, annual periods and decreasing trend with the descending solar activity were clearly revealed in Ne. At middle and high latitudes, there exhibited phase shift and even reversed annual variation over Southern and Northern hemisphere, and the annual variation amplitudes were asymmetrical at both hemispheres in local daytime. In local nighttime, the annual variations of Ne at south and north hemispheres were symmetrical at same latitudes, but the annual variation amplitudes at different latitudes differed largely, showing obviously zonal features. As for Te, the phase shift in annual variations was not as apparent as Ne with the increase of latitudes at Southern and Northern hemisphere in local daytime. While in local nighttime the reversed annual variations of Te were shown at low latitudinal areas, not at high latitudes as those in Ne. The correlation study on Ne and Te illustrated that, in local daytime, Ne and Te showed strong negative correlation at equator and low latitudes, but during the solar minimum years the correlation between Ne and Te changed to be positive at 25–30° latitudes in March 2009. The correlation coefficient R between Ne and Te also showed semi-annual periodical variations during 2005–2010. While in local nighttime, Ne and Te exhibited relatively weak positive correlation with R being about 0.6 at low latitudes, however no correlation beyond latitudes of 25° was obtained.     

Large-scale circulation of atomic oxygen in the upper mesosphere and lower thermosphere

The variability of the atomic oxygen green line airglow at 557.7 nm, originating from the O(¹S) level, has a long history of observation. Only recently, global observations of the oxygen airglow, interpreted with the help of global circulation models have provided some understanding. Satellite observations of winds and temperatures clearly demonstrate the dynamical influence of tides on the daily variations. Both annual and semi-annual components of the variation have been identified as occurring over the course of the year. From the large-scale circulation of the atmosphere one expects downwelling in the winter at high latitudes, causing enhanced atomic oxygen and enhanced airglow while the opposite is expected in summer. In the present investigation a search is made for this large-scale signature using data from the WIND Imaging Interferometer on the Upper Atmosphere Research Satellite, model results from the Thermosphere–Ionosphere–Mesosphere-Electrodynamics-Global Circulation Model, and earlier published results. A well-defined semi-annual variation of emission rate is found in the tropics, apparently the result of the semi-annual variation of the diurnal tide. Annual and semi-annual patterns are found at mid-latitudes, in satellite and model data, while ground-based observations detect only an annual variation, with a maximum in the autumn. At still higher latitudes the fall peak persists, but with a deep depletion of atomic oxygen in the springtime; this appears to be the signature of the large-scale circulation.     

Detection of surface temperature anomaly of the Sea of Marmara

Monitoring sea surface temperature (SST) over a long-term and detecting the anomalies highly contribute to understanding the prevailing water quality of the sea. Earth observation satellite images are the key data sources that offer the long-term SST detection in a cost and time effective way. Since the Sea of Marmara in Türkiye is surrounded by the highly populated provinces, the water quality of the sea has gained importance for scientific and public communities over the years. This article emphasizes on the significance of detecting SST trend and corresponding anomalies of the Sea of Marmara over the past 32 years. To address the SST variations of the Sea of Marmara in time, a comprehensive set of both field and satellite data regarding SSTs were obtained within the context of this study. The SST trend and its anomalies between the years 1990 and 2021 were detected by applying Seasonal-Trend decomposition procedure based on LOESS (STL) method to NOAA OISST V2 data. On the other hand, spatial SST distribution was detected with Landsat-8, Sentinel-3 and NOAA OISST V2 satellite data. SST results were verified with the in-situ data within the scope of accuracy assessment. The results showed that SST time-series data performed an increasing trend and had anomalies mostly during the spring months in the recent years.     

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.     

武昌低电离层LF观测的季节变化

通过分析武昌低电离层LF观测数据,得到了中低纬度低电离层电子密度剖面的季节变化特征及其与太阳天顶角周年变化的关系,给出LF相位周年振荡幅度的年际变化曲线．