Tide Gauge Research Articles

Variability Assessment of Global Extreme Coastal Sea Levels Using Altimetry Data

This study assesses the variability of coastal extreme sea levels globally by utilizing nearly three decades of along-track, multi-mission satellite altimetry data. An altimetry-based global coastal database of the non-tidal residual sea level component has been produced. The climate variability of extremes is modeled through a parametric, non-stationary statistical model. This model captures intra-annual, inter-annual and long-term variations in non-tidal residual return levels. Comparisons with tide gauge data demonstrate the ability of altimetry data to capture the variability of coastal extreme sea levels. Our findings reveal a greater complexity in the monthly variability patterns of non-tidal residual extremes in tropical latitudes, often exhibiting multiple storm periods, contrasting with coasts in extratropical latitudes, which are mostly controlled by a winter–summer pattern. This study also highlights the significant influence of established climate circulation patterns on sea level extremes. The positive phase of the Arctic Oscillation pattern leads to increases of over 25% in non-tidal residual return levels in Northwestern Europe with respect to a neutral phase. Furthermore, return levels in the western coast of Central America could be 50% higher during El Niño compared to La Niña. Our results show a robust increasing trend in non-tidal residual return levels along most global coastlines. A comparative analysis shows that variations during the 1995–2020 period were primarily driven by intra-annual variations.

The Verification of Sea Level Anomaly (SLA) Versus Tide Gauge for Geoid Modelling

The increasing long-term sea level rise is of particular interest and needs a significant investment in coastal protection procedures. The coastal sea level has been verified with tide gauges and well maintained with reliable accuracy of data since a few centuries ago. Satellite altimeter has been used for sea level study and increasingly for operational purposes. However, the precision of altimetry data in coastal areas is frequently eliminated by the geographically correlated orbit errors, which induce a regional inhomogeneous mission bias. This study presents an effort to verify sea level anomaly based on altimetry data with tide gauge stations as an early procedure to provide a good sea level anomaly data for mean sea surface, gravity anomaly, and geoid determination over Malaysian seas. The altimetry data is validated by comparing the sea level anomaly with ground truth data (tidal data) near the coastal area. A total of nine selected areas were chosen to represent the ground truth data. The findings found that the altimetry data over the South China Sea (Pulau Tioman, Geting, Cendering, Bintulu, and Kota Kinabalu) provided a good pattern, high correlation, and a minimum root mean square error (RMSE) value after the verification with tidal sea level anomaly data. However, it clearly shows that Tawau station over the Celebes Sea provides a poor pattern, poor correlation, and a high RMSE value with tidal sea level anomaly data. In conclusion, further enhancements are expected from the refined processing and filtering of altimetry data for the sea level study in the coastal zone.

Observed Spatiotemporal Variability in the Annual Sea Level Cycle Along the Global Coast

AbstractChanges in the seasonal sea level cycle can modulate the flooding risk along coastlines. Here, we use harmonic analysis to quantify changes in the amplitude and phase of the annual component of the sea level cycle at 798 tide gauge locations along the global coastline where long records are available. We identify coastal hotspots by applying clustering methods revealing coherent regions with similar patterns of variability in the annual sea level cycle. Results show that for most tide gauges the annual amplitude reached its maximum after 1970 and its peak typically occurs during the fall season of the respective hemisphere. Many tide gauges exhibit non‐stationarity in the annual cycle in terms of amplitude and/or phase. For example, at 226 tide gauges we find significant trends in the amplitude (either increasing or decreasing) for the time period after 1970; while several sites (50 in total), mostly in the Mediterranean and around Pacific islands, experienced phase changes leading to shifts in the timing of the peak of the annual cycle by more than a month over their entire record. Our results highlight the importance of accounting for potential non‐stationarity in seasonal mean sea level cycles along coastlines.

Simulation of the Mediterranean tsunami generated by the Mw 6.0 event offshore Bejaia (Algeria) on 18 March 2021

SUMMARY On 18 March 2021 an earthquake of magnitude Mw = 6.0 occurred offshore the Algerian coasts and generated a tsunami with offshore amplitudes smaller than a few millimetres crossing the western Mediterranean Sea. The objective of this study is threefold: first, to determine whether seismic sources calculated in the context of tsunami early warning are relevant; secondly, to determine whether tsunami simulations are able to reproduce tide-gauge observations and thirdly, to define the sensitivity of simulations to the grid resolutions and tsunami parameters. In the Mediterranean Sea, a very small number of available coastal tide gauges recorded the tsunami. Among them, a few French tide gauge stations recorded water waves with amplitudes smaller than a few centimetres and with periods ranging from 5 to 20 min associated to harbour or bay resonances. Numerical simulations of the tsunami are performed by the operational code Taitoko for seven different source fault models. Three of them allow for a rapid source detection and characterization in the framework of tsunami warning at CENALT (Centre National d'Alerte aux Tsunamis, France). The integrated code Taitoko uses a system of multiple nested grids. Standard Boussinesq equations are solved in the Mediterranean grid, whereas non-linear shallow water equations are solved in coastal and harbour grids with 25 and 5 m resolutions, respectively. Whatever the fault model, the observed time-series of water heights are reproduced satisfactorily both in phase and amplitude by the model at Nice and Monaco but poorly at Port Mahon (Minorca) and Toulon.

Verification of tidal trends in Cananeia (SP) and Santos (SP)

Recent studies indicate an imminent global rise in mean sea level. However, comprehending variations in tidal patterns is imperative before analyzing the scenario of extreme events, typically associated with the combination of high tides and intense meteorological influences. This study presents local trends in sea level, amplitude, and phase of the two main tidal components in Cananeia (SP) and Santos (SP), utilizing tide gauge data from records of sufficient length to avoid the need for nodal correction in the tide components. Using more up-to-date tide gauge data allowed the investigation of observed trends. Long-term tidal data series revealed an upward trend in mean level of approximately 4,324 mm/year in Cananeia and 0,538 mm/year in Santos. Both locations were affected by human activities along their estuaries, with Santos experiencing significant variations in the amplitude and phase values of the tidal constituents annually.

Altimeter Calibrations in the Preliminary Four Years’ Operation of Wanshan Calibration Site

In order to accomplish the calibration and validation (Cal/Val) of altimeters, the Wanshan calibration site (WSCS) has been used as a calibration site for satellite altimeters since its completion in August 2019. In this paper, we introduced the WSCS and the dedicated equipment including permanent GNSS reference stations (PGSs), acoustic tide gauges (ATGs), and dedicated GNSS buoys (DGB), etc. placed on Zhi’wan, Wai’ling’ding, Dan’gan, and Miao’Wan islands of the WSCS. The PGSs data of Zhi’wan and Wai’ling’ding islands were processed and analyzed using the GAMIT/GLOBK (Version 10.7) and Hector (Version 1.9) software to define the datum for Cal/Val of altimeters in WSCS. The DGB was used to transfer the datum from the PGSs to the ATGs of Zhi’wan, Wai’ling’ding, and Dan’gan islands. Separately, the tidal and mean sea surface (MSS) corrections are needed in the Cal/Val of altimeters. We evaluated the global/regional tide models of FES2014, HAMTIDE12, DTU16, NAO99jb, GOT4.10, and EOT20 using the three in situ tide gauge data of WSCS and Hong Kong tide gauge data (No. B329) derived from the Global Sea Level Observing System. The HAMTIDE12 tide model was chosen to be the most accurate one to maintain the tidal difference between the locations of the ATGs and the altimeter footprints. To establish the sea surface connections between the ATGs and the altimeter footprints, a GPS towing body and a highly accurate ship-based SSH measurement system (HASMS) were used to measure the sea surface of this area in 2018 and 2022, respectively. The global/regional mean sea surface (MSS) models of DTU 2021, EGM 2008 (mean dynamic topography minus by CLS_MDT_2018), and CLS2015 were accurately evaluated using the in situ measured data and HY-2A altimeter, and the CLS2015 MSS model was used for Cal/Val of altimeters in WSCS. The data collected by the equipment of WSCS, related auxiliary models mentioned above, and the sea level data of the hydrological station placed on Dan’gan island were used to accomplish the Cal/Val of HY-2B, HY-2C, Jason-3, and Sentinel-3A (S3A) altimeters. The bias of HY-2B (Pass No. 375) was −16.7 ± 45.2 mm, with a drift of 0.5 mm/year. The HY-2C biases were −18.9 ± 48.0 mm with drifts of 0.0 mm/year and −5.6 ± 49.3 mm with −0.3 mm/year drifts for Pass No. 170 and 185, respectively. The Jason-3 bias was −4.1 ± 78.7 mm for Pass No. 153 and −25.8 ± 85.5 mm for Pass No. 012 after it has changed its orbits since April 2022, respectively. The biases of S3A were determined to be −16.5 ± 46.3 mm with a drift of −0.6 mm/year and −9.8 ± 30.1 mm with a drift of 0.5 mm/year for Pass No. 260 and 309, respectively. The calibration results show that the WSCS can commercialize the satellite altimeter calibration. We also discussed the calibration potential for a wide swath satellite altimeter of WSCS.

Slip distribution of the 2024 Noto Peninsula earthquake (MJMA 7.6) estimated from tsunami waveforms and GNSS data

AbstractThe 1 January 2024 Noto-Hanto (Noto Peninsula) earthquake (MJMA 7.6) generated strong ground motion, large crustal deformation and tsunamis that caused significant damage in the region. Around Noto Peninsula, both offshore submarine and partially inland active faults have been identified by previous projects: Ministry of Land, Infrastructure, Transport and Tourism (MLIT) and Japan Sea Earthquake and Tsunami Research Project (JSPJ). We inverted the tsunami waveforms recorded on 6 wave gauges and 12 tide gauges around Sea of Japan and the GNSS data recorded at 53 stations in Noto Peninsula to estimate the slip amount and seismic moment on each of active faults. The results show that the 2024 coseismic slips were 3.5 m, 3.2 m, and 3.2 m on subfaults NT4, NT5 and NT6 of the JSPJ model, located on the northern coast of Noto Peninsula and dipping toward southeast. A smaller slip, 1.0 m, estimated on NT8 on the southwestern end of the 2024 rupture, may be attributed to its previous rupture during the 2007 Noto earthquake. The total length of these four faults is ~ 100 km, and the seismic moment is 1.90 × 1020 Nm (Mw = 7.5). Almost no slip was estimated on the northeastern subfaults NT2 and NT3, which dip northwestward, opposite to NT4–NT5–NT6, and western subfault NT8. Aftershocks including the MJMA 6.1 event occurred in the NT2–NT3 region, but they are smaller than the potential magnitude (Mw 7.1) those faults can release in a tsunamigenic earthquake. Similar features are also found for the MLIT model; the 2024 slip was only on F43 along the northern coast of Noto Peninsula, and northeastern F42 did not rupture, leaving potential for future event. Graphical Abstract

A deep-learning model for rapid spatiotemporal prediction of coastal water levels

With the increasing impact of climate change and relative sea level rise, low-lying coastal communities face growing risks from recurrent nuisance flooding and storm tides. Thus, timely and reliable predictions of coastal water levels are critical to resilience in vulnerable coastal areas. Over the past decade, there has been increasing interest in utilizing machine learning (ML) based models for emulation and prediction of coastal water levels. However, flood advisory systems still rely on running computationally demanding hydrodynamic models. To alleviate the computational burden, these physics-based models are either run at small scales with high resolution or at large scales with low resolution. While ML-based models are very fast, they face challenges in terms of ensuring reliability and ability to capture any surge levels. In this paper, we develop a deep neural network for spatiotemporal prediction of water levels in coastal areas of the Chesapeake Bay in the U.S. Our model relies on data from numerical weather prediction models as the atmospheric input and astronomical tide levels, while its outputs are time series of predicted water levels at several tide gauge locations across the Chesapeake Bay. We utilized a CNN-LSTM setting as the architecture of the model. The CNN part extracts the features from a sequence of gridded wind fields and fuses its output to several independent LSTM units. The LSTM units concatenate the atmospheric features with respective astronomical tide levels and produce water level time series. The novel contribution of the present work is in spatiotemporality and in prioritization of the physical relationships in the model to maintain a high analogy to hydrodynamic modeling, either in the network architecture or in the selection of predictors and predictands. The results show that this setting yields a strong performance in predicting coastal water levels that cause flooding from minor to major levels. We also show that the model stands up successfully to the rigorous comparison with a high-fidelity ADCIRC model, yielding mean RMSE and correlation coefficient of 14.3 cm and 0.94, respectively, in two extreme cases, versus 12.30 cm and 0.96 for the ADCIRC model. The results highlight the practical feasibility of employing fast yet inexpensive data-driven models for resilient coastal management.

Inferring Global Ocean Mass Increase From Tide Gauges Network With Climate Models

AbstractOcean mass increase contributes to global sea level rise, and plays an important role in understanding climate change. Here, we develop a data assimilation approach that enables the inference of ocean mass increase from global tide gauge network. This approach incorporates outputs from climate models and sea level fingerprints caused by water mass changes over land areas. The results suggest a trend of 2.15 ± 0.72 mm/yr for ocean mass increase over the period 1993–2022, which closes the global sea level budget with estimates of thermosteric sea level rise. Furthermore, the inferred ocean mass increase offers an insight into the causes of sea level rise since 1950. These findings emphasize the significance of climate models, in addition to simulating sea level changes, they contribute to understanding causes of sea level rise over the past decades.

The Impact of Serial Cyclone Clustering on Extremely High Sea Levels in the Baltic Sea

AbstractIn the Baltic Sea, sea level variations are often very pronounced. During the winter season, storm surges caused by strong extratropical cyclones (ETCs) can have major societal impacts on coastal cities. In this study, using reanalysis‐based cyclone tracks and in‐situ tide gauge records, we show that serial cyclone clustering (SCC) leads to higher sea levels in the Baltic Sea than situations where only one ETC passes the tide gauge. Consequently, almost half of extreme sea level events in the Baltic Sea are associated with cyclone clustering periods. For example, in Helsinki, 45% of the extreme sea level events coincided with SCC periods of three or more ETCs, while only 6% of the events coincided with a single ETC. Our study represents a significant advance in the understanding of the factors influencing sea level variations in the Baltic Sea.

Modern digital hydrography and the new international hydrographic organisation bathymetric survey standards

The current state of the International Hydrographic organization bathymetric survey Standards S44 (6.1.0) is examined in this study. The introduction of the S44 survey Standards fourth edition in 1998 heralded the beginning of a new era of modern digital hydrography based on the concept of the survey orders resulting from implementation of the Global Navigation Satellite Systems of positioning and hydrographic information systems. The fundamental changes between the 4th and 6th editions of the Standards for Hydrographic Surveys (S-44) are described. The differences between the 5th and 6th editions of the Standards for Hydrographic Surveys (S-44) are evaluated. Particular attention is paid to the conceptual evolution of such definitions as “bathymetric model” and “ features detection”. The main new S44 (6.1.0) survey Standards paradigm became the concept of “bathymetric coverage” and the rejection of the “ full sea floor coverage” concept which was introduced in the previous 5th edition. Introducing the “bathymetric coverage” and “ feature search” notions in the 6th S44 (2022) survey Standards provides the possibility to avoid the implementation of such previously important hydrographic definition as “line spacing”. It is especially emphasized that the introduction and combined application of such definitions as “bathymetric coverage”, “ feature detection” and “ feature search” necessitate the usage in the 6th S44 (2022) survey Standards of the new special tool named “specification matrix”. This tool is important for hydrographic survey drafting taking into consideration the various stakeholder requirements as well as providing a short hydrographic survey description. The introduction of gridding concept in hydrography provided in the S44 (6.1.0) survey Standards for the first time is also mentioned. Critical comments on the interpretation of gridding methods provided in the annex D which are not considered as the part of the Standards are presented. Some recommendations concerning general quality control requirements and survey posteriori quality control provided in the annex C and B are also commented on. It should be especially emphasized that three last editions of S44 Standards use the “standard deviation” term without specifying its confidence level for position uncertainty (Total Horizontal Uncertainty — THU) calculation. The position uncertainty (2D) quantities are stated as “standard deviation” multiplied by coefficient 2.45. The “standard deviation” term needs additional explanation and clarification; it should not be confused with the widely used term «position standard deviation =distance root mean squared». It is also pointed out the insufficient study of the 3D hydrographic technology provisions presented in the 6th S44 survey Standards edition associated with the alternative method of sea level correction determination based on the precise ellipsoid (geodetic) heights measurements of the tide gauges benchmarks and chart datum using GNSS observations. The necessity of inclusion of the requirements for survey posteriori quality control as the result of survey data post-processing, using statistical comparison of check lines crossing the regular lines, is substantiated. Finally, the urgency of developing new Russian hydrographic standards and specifications based on IHO S44 (6.1.0) on the basis of modern technology is emphasized.

Changes in Sea Level along the South China Sea Coast Based on the Homogenized Tide Gauge Data

To estimate the changes in the annual mean sea level (MSL) and extreme sea levels (ESLs), the largest collection of tide gauge records from 10 tidal stations along the northern coast of the South China Sea (SCS) were analyzed in this study. Here, all the tide gauge records had been homogenized by a two-step process involving the detection of inhomogeneities, that is, breakpoints caused by non-climatic changes and the application of the adjustment. The study’s conclusions, based on the homogenized tide gauge records, can be summarized as follows: The instrument change and station relocation are the main causes for the identified inhomogeneities. From 1989 to 2018, the sea level along the SCS was at an average rate of 4.0 mm per year, as measured by the homogenized tide gauges. The ESLs from the nine tidal stations rose notably with interannual fluctuations, except for the XSA station. Additionally, the ESLs exhibited substantial decadal variations. The ESLs rose along the northern coast of the SCS and were accelerated at most stations throughout the whole study period, especially after the 1980s. There were significant positive correlations between the ESL and the annual MSL at most tide gauges. The MSL’s changes, especially long-term changes, play an important role in the change in ESLs.

Island-based GNSS-IR network for tsunami detecting and warning

Deep-sea tsunami detection relies on Deep-ocean Assessment and Reporting of Tsunamis (DART), GNSS buoys, and cabled Ocean-Bottom Pressure (OBP) gauges, which are very expensive and difficult to maintain, and often suffer from vandalism or negligent damage. Here, we exploit the potential of establishing a less expensive and more robust island-based geodetic network for tsunami detecting, source reconstruction and warning. The network locates at the coastline of islands and uses a new technique: GNSS Interferometric Reflectometry (GNSS-IR). GNSS-IR retrieves sea levels from combination of the direct and reflected signals from the sea surface sent by satellites. To test the feasibility and efficiency of such a new geodetic network, we use the South China Sea region as an example, and compare its performance in reconciling the variable slip distribution on the Manila megathrust with the previously designed deep-sea monitoring system, i.e., DARTs and planned cable-based OBP gauges. We find that the newly designed GNSS-IR network could work equally well as the cabled OBP network in detecting tsunamis if the stations are built in strategically chosen locations. Combining GNSS-IR with a Kalman filter approach, we demonstrate that carefully situated coastal GNSS stations at global remote deep-ocean islands could function similarly to conventional tide gauges but with advantages of simultaneously measuring relative sea-level and land-height changes, meanwhile suffering lower risk from damaging sea-level events and potential vandalism.

Numerical Simulation of Storm Surge Inundation in Estuarine Area Considering Multiple Influencing Factors

With global climate change, the risk of extreme storms and storm surges in estuarine areas is increasing; thus, storm surge inundation research and prediction have become important issues to ensure sustainable development in estuarine areas. The Jitimen estuary in Guangdong Province, China, was chosen as our study area. In this study, a numerical model for simulating storm surge inundation in small regions based on unstructured triangular grids was established, and the model accuracy was validated. The typhoon characteristics in the study area were statistically analyzed based on historical data. Three experimental schemes, involving factors influencing storm surge inundation, such as typhoon landfall location, intensity, and direction, were used to evaluate the differences in the numerical results. The results showed that when the typhoon landfall direction remained unchanged and the highest tide levels at the Sanzao tide gauge station were similar, the differences between the numerical results for the typhoon landfall location and typhoon intensity schemes were less than 5%, and the inundation characteristics were similar. However, when the typhoon location and intensity were unchanged and the highest tide levels at the Sanzao tide gauge station were similar, the numerical results for the typhoon landfall direction scheme significantly differed; this result was caused by the difference in the duration of the high tide level (exceeding 3 m); these results indicated that the topographic characteristics and the typhoon landing direction had a greater impact on storm surge inundation. The results from this study can aid in the prediction of storm surge inundation information for the Jitimen estuary area when the typhoon landing direction and the maximum tide level are known.

Tropical Atmospheric Intraseasonal Oscillations Leading to Sea Level Extremes in Coastal Indonesia during Recent Decades

Abstract Coastal flooding induced by sea surface High EXtreme (HEX) events is an increasing risk to human society and infrastructure as both urban growth in coastal areas and anthropogenic sea level rise continue, especially for island nations like Indonesia. This paper investigates the role of atmospheric IntraSeasonal Oscillations (ISOs), which are dominated by the Madden-Julian Oscillation (MJO), in forcing HEXs on the coasts of Indonesia bordering the Indian Ocean. We use satellite altimetry data from 1993-2021 and tide gauge observations to detect HEXs, and modeling experiments using both the Regional Ocean Modeling System and a Bayesian dynamic linear model to understand the forcing and processes. We find that HEXs exhibit strong seasonality, with most events occurring during boreal winter (December-February) and spring (March-May) that are dominated by seasonal-to-decadal and intraseasonal variability respectively. In 32% of the 56 HEX events detected, the amplitude of ISO-induced sea level anomalies (SLAs) exceeds that of seasonal-to-decadal SLAs. Surface wind stress associated with atmospheric ISOs is the major forcing for intraseasonal SLAs, and both the remote westerly wind stress from the Indian Ocean equator and northwesterly longshore wind stress at the Indonesian coasts play important roles in driving the HEXs. The MJO is the dominant cause of ISO-dominated HEXs and its impact shows strong seasonal differences. Spring MJOs are associated with stronger convective anomalies over the eastern Indian Ocean equator that drive stronger zonal winds across the equatorial basin that lead to more HEX events compared to winter MJOs when the convection is shifted southward.

Loop Current Eddies as a Possible Cause of the Rapid Sea Level Rise in the Gulf of Mexico

AbstractThe Gulf of Mexico (GOM), with its densely populated coastline, is one of the world's most vulnerable regions to climate change and sea level (SL) rise. Over the last three decades, various works have been conducted to assess coastal SL trends around the basin using tide gauge stations, separately from studies dealing with regional dynamical processes. Using altimetry, Argo, and eddy atlas products over the period from January 1993 to December 2020, we have analyzed the regional SL variations in the area to define their characteristics and explore their possible dynamical causes. We observe a mean GIA‐corrected SL rise rate of 4.81 ± 0.85 mm yr−1, which is 25% higher than that of the adjacent Caribbean Sea and 44% higher than that of the global ocean. This result highlights the singular SL evolution in the GOM over the 28‐year study period. Over 2010–2020, the SL trend in the GOM has even accelerated, along with a strong warming of the upper‐layer (0.58 ± 0.17°C), which explains ∼60% of the SL rise rate through the thermosteric effect. Finally, the heat input estimates emphasize the role of the Loop Current eddies as a major contributor to the recent acceleration of SL rise due to upper‐layer warming.

3D Traveling Ionospheric Disturbances During the 2022 Hunga Tonga–Hunga Ha’apai Eruption Using GNSS TEC

AbstractThe dual frequency Global Navigation Satellite System (GNSS) observations could determine the total electron content (TEC) in the ionosphere. In this study, GNSS TEC was applied to detect traveling ionospheric disturbances (TIDs) after the eruption of Hunga Tonga–Hunga Ha’apai (HTHH) on 15 January 2022. The eruption caused two types of tsunamis, first is tsunami generated by atmospheric wave (meteo‐tsunami) and second is caused by eruption induces water displacement or tsunami classic. At the same time with former tsunami, the atmospheric wave (shock and lamb waves) also caused TIDs at a speed of approximately ∼0.3 km/s. We found moderate correlation between this TIDs amplitude and the tsunami wave height model from tide gauge stations in New Zealand (0.64) and Australia (0.65). Further we attempted to reveal 3D structure of the TIDs in New Zealand, South Australia, and Philippines using 3D tomography. The tomography was set up > 1,170 blocks, as large as 1.0° (east–west)  × 1.0° (north–south) × 100 km (vertical), up to 600 km altitude over selected regions. Tomogram shows beautiful concentric directivity of the first TIDs generated by atmospheric wave (AW).

Performance evaluation of different reflected signal extraction methods on GNSS-R derived sea level heights

In order to obtain reliable GNSS-R derived sea level heights (SLHs), it is crucial to extract accurate reflected signals from signal-to-noise ratio (SNR) data. In this study, Quadratic Fitting, Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), and Singular Spectrum Analysis (SSA) are adopted for extracting the reflected signals from SNR data, which are then analyzed with Lomb Scargle Periodogram (LSP) assisted with tidal harmonic analysis for GNSS-R SLHs. Three continuous GNSS stations including Onsala in Sweden, Friday Harbor in the United States, and Brest in France with tidal ranges of approximately 1 m, 3 m, and 7 m, respectively, were used in the study. The derived SLHs were evaluated against the nearby or co-located tide gauge records. The results reveal that the three proposed algorithms effectively cope with the multi-peaks spectrum problems when using the conventional Quadratic Fitting without a priori reflected height constraint, and SSA can provide the solutions with fewer outliers among the proposed methods with the RMSEs of 6.7 cm, 13.4 cm and 39.6 cm at Onsala, Friday Harbor, and Brest stations, respectively. Without implementing tidal harmonic analysis, SSA is the method capable of acquiring reliable SLHs among the stations, as evidenced by comparing with co-located gauge records, particularly at the Brest station. In summary, SSA not only distinguishes signals across different frequencies, but also orders the signal components according to their eigenvalues, demonstrating the potential to extract the reflected signals from SNR and enhance the stability and accuracy of GNSS-R applications.

Comparative analysis of PCS and ICA on trend estimation of sea-level change from tide gauge observations

Comparative analysis of PCS and ICA on trend estimation of sea-level change from tide gauge observations

The potential recording of North Ionian Gyre’s reversals as a decadal signal in sea level during the instrumental period

In recent decades, the north Ionian Sea, central Mediterranean Sea, has witnessed shifts in surface current circulation from cyclonic to anticyclonic and vice versa at the quasi-decadal scale, a phenomenon termed the North Ionian Gyre (NIG) reversal. This process impacts parameters such as sea level by altering thermohaline properties and redistributing water masses at the sub-basin scale. Previous studies have shown that during anticyclonic (cyclonic) phases, the Ionian sea-level trend is falling (rising), the opposite of what is observed in other Mediterranean sub-basins. Assuming that sea level records reversals, this study employed signal decomposition to analyze satellite altimetry data and tide gauge observations across the region, some dating back to the 1900s. A distinct quasi-decadal periodicity emerges as the second dominant oscillatory mode from all independent observations, aligning its peaks and troughs (i.e., changes in sea-level trend) with known NIG reversals and associated changes in the state of North Ionian vorticity. Furthermore, this mode from altimetry data clearly depicts the spatial variability of sea level attributed to the opposite NIG states. This periodicity appears coherent among different sub-basins within the domain, especially in the eastern Mediterranean, with a shared generalized out of phase and weakening occurred from the 1930s to the 1950s. This study presents a century-scale reconstruction of NIG reversals, contributing to the understanding of this phenomenon prior to 1987 using direct observations from sea-level data.